Engineering Service Systems in the Digital Age [1st ed.] 978-3-658-26202-0;978-3-658-26203-7

Table of contents :
Front Matter ....Pages I-XIX
Introduction: Objective of this Research (Benedikt S. Höckmayr)....Pages 3-20
Research Background: Grounding of the Research (Benedikt S. Höckmayr)....Pages 21-41
Research Method: Consuming and Producing Knowledge (Benedikt S. Höckmayr)....Pages 43-55
Knowledge Creation: Advancing Design Knowledge (Benedikt S. Höckmayr)....Pages 57-211
Discussion: Shaping a Body of Design Knowledge (Benedikt S. Höckmayr)....Pages 213-238
Conclusion: Reflections on the Research (Benedikt S. Höckmayr)....Pages 241-261
Back Matter ....Pages 263-314

Citation preview

Benedikt S. Höckmayr

Engineering Service Systems in the Digital Age

Markt- und Unternehmensentwicklung Markets and Organisations Series editor Arnold Picot, München, Germany Ralf Reichwald, Leipzig, Germany Egon Franck, Zürich, Switzerland Kathrin M. Möslein, Erlangen-Nürnberg, Germany

Change of institutions, technology and competition drives the interplay of markets and organisations. The scientific series ‘Markets and Organisations’ addresses a magnitude of related questions, presents theoretic and empirical findings and discusses related concepts and models.

Edited by Professor Dr. Dres. h. c. Arnold Picot Ludwig-Maximilians-Universität München, Deutschland Professor Dr. Egon Franck Universität Zürich, Schweiz

Professor Dr. Professor h. c. Dr. h. c. Ralf Reichwald HHL Leipzig Graduate School of Management Leipzig, Deutschland Professorin Dr. Kathrin M. Möslein Friedrich-Alexander-Universität Erlangen-Nürnberg & HHL Leipzig, Deutschland

More information about this series at http://www.springer.com/series/12561

Benedikt S. Höckmayr

Engineering Service Systems in the Digital Age With a foreword by Prof. Dr. Kathrin M. Möslein

Benedikt S. Höckmayr Schrobenhausen, Germany Dissertation Friedrich-Alexander-Universität Erlangen-Nürnberg, 2018

Markt- und Unternehmensentwicklung Markets and Organisations ISBN 978-3-658-26202-0 ISBN 978-3-658-26203-7  (eBook) https://doi.org/10.1007/978-3-658-26203-7 Springer Gabler © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Gabler imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany

Foreword

What’s new about digital innovation is a question academics are increasingly paying attention to. Understanding underlying premises, extracting common themes and getting to know which emerging research areas will gain importance in the future are central to manifold research disciplines. The multifaceted nature of the phenomenon leads to the convergence of hitherto bounded schools of thought, thus opening up the opportunity of combining a broad variety of different worldviews and research approaches. In a similar vein, businesses ask themselves what buzz words such as Big Data, Internet of Things, Cyber Physical Systems, Industry 4.0, Smart Factory, and Digital Transformation mean to them. Visions emerge and leave all kinds of firms with the uncertainty of where to pigeon themselves in a range from being hesitant via embracing a pragmatic view to risking too much. Other organizations might know where to go to and which novel business models might emerge, but do not necessarily possess the armamentarium to tread the right path. Dr. Benedikt S. Höckmayr’s work invites the reader on an exciting journey: It builds on the paradigm of design science research in order to solve this real organizational problem via gathering an scientific understanding of underlying premises and providing knowledge for the prospective design of artifacts that are attuned to the nature of innovating in the digital age. Artifacts in which valuable design knowledge is ingrained are built in order to support the engineering of digitally enabled service systems. However, and even more important, in the worldview of Dr. Benedikt S. Höckmayr, it is the abstracted knowledge on how to build and use these artifacts that constitutes a promising key for future success. This book is a much-needed step towards a more elaborate understanding on what digital innovation is all about. It clearly delivers significant advancement in knowledge on how to engineer service systems in the digital age. It acknowledges the generative nature of innovation in a digitally permeated world through the lens of service systems as complex configuration of tangible and intangible resources. The work appeals by its theoretical reach and empirical scope, as well as the argumentative brilliance by which

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Foreword

findings are presented. The thesis has been accepted as a doctoral dissertation in 2018 by the School of Business and Economics at the Friedrich-Alexander University Erlangen-Nuremberg (FAU). The book deserves broad dissemination in both the research community and in management practice. It is especially recommended to innovation managers interested in bringing a service-oriented lens on novel digitally enabled value creation opportunities to their organizations. Prof. Dr. Kathrin M. Möslein

Preface

This book is the result of my scientific work in recent years, but it also reflects a considerable part of how I developed as a person on this journey. The challenges and successes, but also the intensive interaction with people from the inner as well as extended circle of family, friends, and peers throughout this time have contributed to coalescing my personality and talents in a direction which I assume makes me appear as a person that is aware of his social responsibility and open to both new developments and, even more important, new people. I could not have made this journey without what my parents, my brother and my entire family gave me. Their warmth and security have provided me with the foundation to master my way confidently and on my own feet. I am glad to have you. Apart from all personal successes you are the most important element in life to me. In addition, I also want to shed light on the people I had the pleasure to deal with in my working environment. Colleagues became friends with whom I shared many great experiences. Supervisors became mentors from whose knowledge and guidance I learned a lot. I am convinced that these people will also play a significant role in my future life, be it explicitly through funny and deep shared experiences or implicitly on the basis of our common mindset. I am proud of what I have achieved. However, I am also aware that the result would have been different if I had not experienced the diverse inspiration of interesting and great people. Thank you! Dr. Benedikt S. Höckmayr

Overview of Contents

I

Introduction: Objective of this Research .....................................................1

1

The Relevance of Engineering Novel Service Systems in the Digital Age................ 3

2

Research Objective: Toward a Body of Design Knowledge........................................ 6

3

Purpose and Scope of the Dissertation......................................................................... 11

II Research Background: Grounding of the Research ................................ 21 1

The Notion of Innovation in Service Systems and Service Systems Engineering . 23

2

The Concepts of Generativity and Resource Density as Lenses on Digitality ....... 27

3

The Role of Extant Design Knowledge ........................................................................ 35

III Research Method: Consuming and Producing Knowledge .................. 43 1

The Paradigm of Design Science Research .................................................................. 45

2

The Roles of Knowledge and Knowledge Bases......................................................... 46

3

The Nexus of Artifacts and Design Theories as Knowledge Contribution ............ 48

4

The Research Design and Intended Contributions .................................................... 50

IV Knowledge Creation: Advancing Design Knowledge ........................... 57 1

Study 1: Bringing Order to Design Knowledge – A Taxonomy ............................... 59

2

Study 2: Gathering Design Knowledge – Generative Mechanisms ......................... 94

3

Study 3: Ingraining Design Knowledge – A Method ............................................... 126

4

Study 4: Preserving and Communicating Design Knowledge – A Digital Tool.. 162

V Discussion: Shaping a Body of Design Knowledge ............................. 213 1

Synthetizing Accumulated Knowledge Contributions ........................................... 215

2

Specifying an Emergent Design Theory .................................................................... 217

3

Maturing Toward a Consistent Body of Design Knowledge.................................. 235

4

Contribution and Conclusion ...................................................................................... 238

X

Overview of Contents

VI Conclusion: Reflections on the Research ................................................ 241 1

Overview of Work ........................................................................................................ 243

2

Theoretical Contributions ............................................................................................ 246

3

Practical Contributions ................................................................................................ 250

4

Limitations and Avenues for Future Research ......................................................... 255

5

Final Considerations .................................................................................................... 261

References ............................................................................................................ 263 Annexes................................................................................................................. 299

Table of Contents

I

Introduction: Objective of this Research .....................................................1

1

The Relevance of Engineering Novel Service Systems in the Digital Age................ 3

2

Research Objective: Toward a Body of Design Knowledge........................................ 6

3

Purpose and Scope of the Dissertation......................................................................... 11

II Research Background: Grounding of the Research ................................ 21 1

The Notion of Innovation in Service Systems and Service Systems Engineering . 23 1.1 The Facets of Innovation in Service Systems ....................................................................23 1.2 The Interplay of Service Systems in the Digital Age .......................................................24 1.3 The Engineering of Service Systems ..................................................................................25

2

The Concepts of Generativity and Resource Density as Lenses on Digitality ....... 27 2.1 The Facets of Digitally Enabled Innovation .....................................................................27 2.2 The Nature of Digital Technology .....................................................................................28 2.3 The Prevalence of Generativity ..........................................................................................29 2.4 The Idea of Resource Density .............................................................................................32

3

The Role of Extant Design Knowledge ........................................................................ 35 3.1 The Systematic Development of Service Systems............................................................36 3.2 The Premises Concomitant with Digitally Enabled Service Innovation ......................38 3.3 The Intersection of Research Streams in IS and Service Research .................................40

III Research Method: Consuming and Producing Knowledge .................. 43 1

The Paradigm of Design Science Research .................................................................. 45

2

The Roles of Knowledge and Knowledge Bases......................................................... 46

3

The Nexus of Artifacts and Design Theories as Knowledge Contribution ............ 48

4

The Research Design and Intended Contributions .................................................... 50

XII

Table of Contents

IV Knowledge Creation: Advancing Design Knowledge ........................... 57 1

Study 1: Bringing Order to Design Knowledge – A Taxonomy .............................. 59 1.1 Purpose and Scope .............................................................................................................. 60 1.2 Background .......................................................................................................................... 62 1.2.1 Characterization and Positioning of Design Knowledge............................................ 63 1.2.2 Digitally Enabled Generativity and Digital Technology ........................................... 64 1.3 Research Method ................................................................................................................. 65 1.3.1 Systematic Literature Review..................................................................................... 66 1.3.2 Taxonomy Development ............................................................................................. 69 1.4 Results ................................................................................................................................... 75 1.4.1 Literature Analysis ..................................................................................................... 76 1.4.2 Resulting Taxonomy .................................................................................................. 76 1.5 Discussion ............................................................................................................................. 86 1.6 Contribution and Conclusion ............................................................................................ 92

2

Study 2: Gathering Design Knowledge – Generative Mechanisms ........................ 94 2.1 Purpose and Scope .............................................................................................................. 95 2.2 Background .......................................................................................................................... 97 2.2.1 Generativity and Generative Mechanisms ................................................................. 97 2.2.2 Resource Density and Dematerialization Mechanisms.............................................. 98 2.3 Research Method ............................................................................................................... 100 2.3.1 Research Objective.................................................................................................... 101 2.3.2 Research Design ....................................................................................................... 101 2.3.3 Data Collection ......................................................................................................... 102 2.3.4 Data Analysis ........................................................................................................... 105 2.3.5 Data Interpretation................................................................................................... 105 2.4 Results ................................................................................................................................. 110 2.4.1 Invention .................................................................................................................. 111 2.4.2 Improvement............................................................................................................. 113 2.4.3 Exaptation ................................................................................................................ 116 2.5 Discussion ........................................................................................................................... 122 2.6 Contribution and Conclusion .......................................................................................... 124

Table of Contents

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XIII

Study 3: Ingraining Design Knowledge – A Method ............................................... 126 3.1 Purpose and Scope .............................................................................................................127 3.2 Background .........................................................................................................................129 3.2.1 Digitally Enabled Innovation – A Systems Perspective ...........................................129 3.2.2 Digitally Enabled Innovation – An Activity Perspective .........................................130 3.3 Research Method ................................................................................................................132 3.4 Artifact Development ........................................................................................................132 3.4.1 Requirements Elicitation...........................................................................................133 3.4.2 Initial Design of the Method – Building Blocks and Meta-Model ............................137 3.4.3 Assembly of the Method – Development Activities and Interrelations ....................138 3.5 Artifact Evaluation .............................................................................................................143 3.5.1 Artificial Evaluation of the Artifact ..........................................................................144 3.5.2 Naturalistic Evaluation of the Artifact .....................................................................147 3.6 Discussion............................................................................................................................158 3.7 Contribution and Conclusion ...........................................................................................159

4

Study 4: Preserving and Communicating Design Knowledge – A Digital Tool.. 162 4.1 Purpose and Scope .............................................................................................................163 4.2 Background .........................................................................................................................165 4.2.1 Understanding Digitally Enabled Generativity in Service Systems ........................165 4.2.2 Engineering Digitally Enabled Generativity in Service Systems .............................167 4.3 Research Method ................................................................................................................168 4.4 Artifact Development and Evaluation ............................................................................170 4.4.1 Identify Problem and Eval1.......................................................................................171 4.4.2 Design and Eval2 ......................................................................................................176 4.4.3 Construct and Eval3 .................................................................................................183 4.4.4 Use and Eval4 ...........................................................................................................189 4.5 Artifact Description............................................................................................................194 4.6 Discussion............................................................................................................................208 4.7 Contribution and Conclusion ...........................................................................................211

XIV

Table of Contents

V Discussion: Shaping a Body of Design Knowledge ............................. 213 1 2

Synthetizing Accumulated Knowledge Contributions ........................................... 215 Specifying an Emergent Design Theory .................................................................... 217 2.1 Purpose and Scope ............................................................................................................ 221 2.2 Constructs ........................................................................................................................... 222 2.3 Principles of Form and Function ..................................................................................... 223 2.4 Artifact Mutability ............................................................................................................. 227 2.5 Testable Propositions ........................................................................................................ 228 2.6 Justificatory Knowledge ................................................................................................... 229 2.7 Principles of Implementation........................................................................................... 230 2.8 Expository Instantiation ................................................................................................... 234

3

Maturing Toward a Consistent Body of Design Knowledge ................................. 235

4

Contribution and Conclusion ..................................................................................... 238

VI Conclusion: Reflections on the Research ................................................ 241 1

Overview of Work ........................................................................................................ 243

2

Theoretical Contributions ............................................................................................ 246

3

Practical Contributions ................................................................................................ 250 3.1 Industrial applications ...................................................................................................... 250 3.2 Industrial Standardization ............................................................................................... 252 3.3 Living Labs ......................................................................................................................... 253

4

Limitations and Avenues for Future Research ......................................................... 255

5

Final Considerations .................................................................................................... 261

References ............................................................................................................ 263 Annexes................................................................................................................. 299 Annex A: Knowledge Contributions Ingrained in Research ............................................... 301 Annex B: Interview Guideline for Multiple Case Study ...................................................... 302 Annex C: Insights on the Development of TRIGGER........................................................... 306 Annex D: Insights on the Development of the DiDesigner ................................................. 313

List of Figures

Figure 1. Scope of the Dissertation............................................................................................ 12 Figure 2. Structure of the Dissertation ..................................................................................... 19 Figure 3. Perspectives on Generative Systems .......................................................................... 30 Figure 4. Taxonomy development method as proposed by Nickerson et al. (2013) .................. 71 Figure 5. Cognitive Map for Data Interpretation ................................................................... 109 Figure 6. Generative Mechanisms Leading to Improved Densities ........................................ 110 Figure 7. Generative Mechanisms in a Systems of Service Systems Context ........................ 123 Figure 8. Overview of the Methods contributing to TRIGGER ............................................. 138 Figure 9. Mechanisms Underlying LiCoDi ............................................................................ 142 Figure 10. Evaluation Trajectory for the Development of the DiDesigner............................. 171 Figure 11. Power Point Slides as Artifact for ex ante Evaluation in Eval 1 .......................... 174 Figure 12. Design Specification of Artifact for ex ante Evaluation in Eval 2 ........................ 178 Figure 13. Representation of Design Specification in Visual Basic Tool in Eval 2 ................ 181 Figure 14. Patterns for Resource Density Enhancement Presented in Eval 3 ....................... 185 Figure 15. DiDesigner as Instantiation in Eval 4 .................................................................. 190 Figure 16. Component Job Steps, Actors, and Activities of DiDesigner (I) ........................... 196 Figure 17. Component Job Steps, Actors, and Activities of DiDesigner (II) .......................... 197 Figure 18. Component Information Liquification of DiDesigner ........................................... 199 Figure 19. Component Constraints of DiDesigner ................................................................. 201 Figure 20. Component Unbundling and Rebundling of DiDesigner (I) ................................ 203 Figure 21. Component Unbundling and Rebundling of DiDesigner (II) ............................... 205 Figure 22. Component Fine Tuning of DiDesigner ................................................................ 207 Figure 23. House of Quality for Expository Instantiation ...................................................... 209 Figure 24. Translation of Expert Knowledge into Actionable Trade-offs ............................... 233 Figure 25. Mutual Dependencies of Components in a Design Theory ................................... 236 Figure 26. Utilization of Prescriptive Knowledge Units Among a Broader Public................ 254

List of Tables

Table 1. Overview on Research Design ..................................................................................... 51 Table 2. Scope of the Systematic Literature Review .................................................................. 67 Table 3. Literature Extraction Process ...................................................................................... 76 Table 4. Taxonomy of Extant Prescriptive Knowledge Contributions ..................................... 78 Table 5. Research Directions for Engineering Service Systems in the Digital Age ................. 90 Table 6. Overview and Background Information on Selected Cases ....................................... 104 Table 7. Invention as Set of Generative Mechanisms ............................................................. 111 Table 8. Improvement as Set of Generative Mechanisms ........................................................ 114 Table 9. Exaptation as Set of Generative Mechanisms ........................................................... 117 Table 10. Requirements Elicitation for the Initial Design of the Method ............................... 136 Table 11. Artificial Evaluation of TRIGGER by means of requirements elicited ................... 145 Table 12. Design Principles for Emergent Design Theory ..................................................... 224 Table 13. Key Contributions Arising from the Research ........................................................ 246 Table 14. Linkages of Contributions to Relevant Research Paths in Literature ..................... 248 Table 15. Research Directions for Maturation of Body of Design Knowledge........................ 256

List of Abbreviations

CPS

Cyber Physical Systems

CVC

Customer Value Constellation

DSR

Design Science Research

ICT

Information and Communication Technology

IoT

Internet of Things

IT

Information Technology

IS

Information Systems

LiCoDi

Liberation from Constraints by Digitization

PPT

PowerPoint

SE

Service Engineering

SSE

Service Systems Engineering

TRIGGER Method for Engineering Digitally Enabled Service Systems VBA

Visual Basic

VCE

Value Constellation Experience

I Introduction: Objective of this Research

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_1

The Relevance of Engineering Novel Service Systems in the Digital Age

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The Relevance of Engineering Novel Service Systems in the Digital Age

Consider a manufacturing firm that has produced bearings and machine components for ages. Its customers traditionally demand for precision products with high quality standards and long lifetimes. To date, the firm used data generated in the course of internal test bench runs in order to further perfect their products and provide information concerning their capabilities to its customers. However, in the digital age, with the rise of global communication networks, ubiquitous sensing of environmental as well as social conditions, and novel actors being integrated in widely ramified ecosystems, customers tend to shift their anticipation of value. In this context, increasing automation and high maturity in manufacturing processes allow for products with a high performance and quality being produced by a broad variety of firms, often from sectors formerly being regarded as neglectable. This leads to value creation being perceived as a construct that mainly addresses the underlying value creating mechanisms ingrained in the physical matter of tangible resources. This, in turn, fosters deemphasizing the role of products as carriers of knowledge that is frozen into their physicality in the course of their development and production. In this vein, novel actors such as Tesla still install bearings within their cars in order to enable them to move from one destination to another but, antithetically, foster the anticipation of the car as part of a value-creating constellation that is far more extensive. Thus, the value of moving in the most convenient and, in the case of Tesla admittedly, most prestigious way is enabled by providing a network of free charging stations, locationindependent automated updates for more engine power and novel features, and various forms of autonomous driving. Value creation in such systems is thus enabled by a complex configuration of manifold resources, including not only physical components but, taking into account the affordances concomitant with the digital age, predominantly also data, layers of knowledge, communication channels and networked actors. Referring back to the manufacturing firm, its bearings can still be considered state of the art products that can be installed in a Tesla but, beyond that, constitute a part of a bigger value creation constellation. The data formerly produced

4

Introduction: Objective of this Research

in test bench runs could be produced location-independently and forwarded to various actors that configure and model underlying information entities as central resource to mobilize contextually relevant knowledge for the multitude of stakeholders involved. Hence, knowing how to engineer these intangible and hard to delineate systems constitutes the foundation for a broader set of innovation opportunities on behalf of the manufacturing firm. As sounded out in the illustrative case above, the value creation context of today allows a much broader variety of resource configurations, thus inducing a radical shift in terms of how the nature and process of innovation is anticipated among varied audiences. In the digital age, the focus of many innovations is no longer only on tangible goods but on intangible offerings in which the extent of information content is high – that is, with an information-centric focus (Glazer, 1991; Lusch & Nambisan, 2015; Lycett, 2013). For most of human civilization, information was embedded in physical matter (e.g., writings or drawings on stone and paper). Artifacts that mankind developed were essentially frozen ideas or knowledge, which Vargo and Lusch (2004) refer to as “informed matter” (Lusch, Vargo, & Tanniru, 2010). However, for information to be useful, it must be shared with others and modeled in different ways so as to generate novel insights and knowledge (Benaroch, 1998; Gruber, 1995; Lusch & Nambisan, 2015). The emergence of digital computers enabled the digitization of information, i.e., the encoding of analog information into a digital format (Yoo, Henfridsson, & Lyytinen, 2010) and the associated capability to decouple the information from the technologies (or devices) that store, transmit or process it (Lusch & Nambisan, 2015). “Digitization makes physical products programmable, addressable, sensible, communicable, memorable, traceable, and associable” (Yoo et al., 2010, p. 725). However, and even more important, this digital decoupling is accompanied by socio-technical processes that bear the potential to forge new social connections and cognitive models that open up novel innovation opportunities in service systems (Barrett, Davidson, & Vargo, 2015; Lusch & Nambisan, 2015; Tilson, Lyytinen, & Sørensen, 2010). Service systems embody an abstraction of value creation (Spohrer, Vargo, Caswell, & Maglio, 2008) and consist of entities or configurations of resources (including people, information, and technology) that are connected by value propositions (Vargo, Maglio, & Akaka, 2008). In fact, especially the emergence of

The Relevance of Engineering Novel Service Systems in the Digital Age

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digital technology has laid the foundation of novel forms of generative innovation in these complex systems (Eaton, Elaluf-Calderwood, Sørensen, & Yoo, 2015; Yoo et al., 2010; Zittrain, 2006). In a broader sense, with digitization, ubiquitously distributed computing capabilities, and the rapid growth of global communications networks, the overall capacity of digital technology to produce unprompted change driven by large, varied, and uncoordinated audiences, i.e., generativity (Zittrain, 2006), is increasingly catalyzed (Lusch & Nambisan, 2015; Yoo et al., 2010). The resultant digitally enabled generativity (Yoo, 2013) allows innovation to extend beyond the original initiator and purpose and is characterized by outcomes that are unanticipated and self-reinforcing (Zittrain, 2006, 2008). From a more micro-level view, digital technology supports knowledge exchange among various actors. Together with the notion that information and knowledge are key resources for service innovation, it can be argued that opportunities for innovation in service systems in a digital world are limited only by the extent of digitization and concomitant socio-technical processes (Barrett et al., 2015; Lusch & Nambisan, 2015; Tilson et al., 2010). The accompanying multidimensional nature and complexity of resultant digitally enabled service systems is important in the context of the research question approached in this dissertation, as described in the subsequent chapter.

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Introduction: Objective of this Research

Research Objective: Toward a Body of Design Knowledge

Against the backdrop of today’s global, digital, and service-oriented economy, private and public organizations alike increasingly tend to use a service logic to develop and manage their innovation activities (Böhmann, Leimeister, & Möslein, 2014a; Chesbrough, 2011; Chesbrough & Spohrer, 2006). However, due to the unique characteristics of digital technology (Yoo et al., 2010), innovation in service systems with digital technology faces inherent tensions (Eaton et al., 2015). On the one hand, the digitally enabled generativity unleashed by digital technology (Yoo, 2013) leads to service systems which are highly evolvable, perpetually incomplete, and hard to demarcate, thus developing beyond the understanding and anticipation of those who created the service system in the first place (Eaton et al., 2015; Yoo, 2013; Yoo et al., 2010; Zittrain, 2006). On the other hand, digitally enabled generativity may not automatically result in positive outcomes (Yoo, 2013) which is why controlling generativity has become a highly prevalent issue (Eaton et al., 2015; Förderer, Kude, Schütz, & Heinzl, 2014; Pagani, 2013). Hence, with the aim to create service systems that embody a positive outcome of digitally enabled generativity, design knowledge that acknowledges the mechanisms underlying digitally enabled generativity (Yoo, 2013) with due regard to the nature of service systems (Maglio, Vargo, Caswell, & Spohrer, 2009) is needed (Böhmann et al., 2014a). Design knowledge supporting the structured and systematic design of service systems that embody a positive outcome of digitally enabled generativity, i.e., digitally enabled service systems, thus has to address the underlying principles of these generative systems (Henfridsson & Bygstad, 2013; Tilson et al., 2010) and provide mechanisms to foster beneficial configurations of resources (Maglio et al., 2009). As stated by Lusch and Nambisan (2015), a promising lens to identify such mechanisms for “controlled generativity” (Eaton et al., 2015) is constituted by the notion of resource density (Normann, 2001) in terms of conceptualizing dematerialization mechanisms that address both, the technical and the socio-technical processes concomitant with digitally enabled generativity. Hence, understanding these mechanisms and incorporating them in “principles of function”

Research Objective: Toward a Body of Design Knowledge

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(Gregor & Hevner, 2013) can lead to enhanced resource densities in digitally enabled service systems (Eaton et al., 2015; Lessard, 2015; Lusch & Nambisan, 2015). Reverting to the longhand definition of service (Lusch & Nambisan, 2015; Vargo & Lusch, 2016), enhanced resource densities are thus contingent on the rebundling of diverse resources, creating novel resources beneficial (i.e., value-experiencing) to some actors in a given context, which, in turn, can be conceptualized as positive outcome in the form of innovation in service systems (Lusch & Nambisan, 2015). In this vein, service systems engineering (SSE) calls for design knowledge (Gregor, 2006; Gregor & Jones, 2007) that allows for the prescription of guidelines on how to engineer real-world service systems that permeate our society (Böhmann et al., 2014a). SSE takes the service system as a basic unit of analysis and aims to introduce novel artifacts (constructs, models, methods, instantiations, and design theories) (Gregor & Hevner, 2013; Hevner, March, Park, & Ram, 2004) being attuned to the nature of these complex systems, thus supporting their systematic design and development (Böhmann et al., 2014a). In addition, the context of innovation in digitally enabled service systems demands for approaches that bridge the boundaries of tangible and intangible resources. As Böhmann et al. (2014a) state, new forms of resource bundling and service provision are arising from the conjunction of machine intelligence with human intelligence. To date, however, there has been a lack of design knowledge on how to engineer the resulting digitally enabled novel service systems in a systematic way. Prescriptive knowledge contributions from interdisciplinary research are regarded as promising to foster the emergence of artifacts that support the engineering of according service systems (Böhmann et al., 2014a). Against this backdrop, Ostrom, Parasuraman, Bowen, Patricio, and Voss (2015) call for research focused on evolving systems engineering approaches for developing services with the aim to integrate Information Systems (IS) expertise with other aspects of service design. As a consequence, service related contributions from interdisciplinary fields have to be taken into account in order to advance design knowledge for service systems (Fielt, Böhmann, Korthaus, Conger, & Gable, 2013). In this vein, Gregor and Hevner (2013) call for design knowledge with truth-like value (Iivari, 2007) to be ingrained in an abstract, coherent body of prescriptive knowledge that describes the principles of form and function,

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Introduction: Objective of this Research

methods, and justificatory theory that are used to develop artifacts that accomplish some end (Gregor, 2006; Gregor & Jones, 2007). Articulating this design knowledge with a higher degree of abstraction is particularly important with regard to the technology-permeated context addressed within the scope of this dissertation. The evolution of technology in general and digital technology in particular can be very pervasive and, by that, radically changes the nature of innovation endeavors (Arthur, 2009; Ridley, 2015; Yoo, Boland, Lyytinen, & Majchrzak, 2012; Yoo et al., 2010). It is then the role of science to understand how and why the newly introduced technology and concomitant phenomena impacts the surrounding world as it does. Thus, it can be posited that, in most cases, technology evolutions precede and drive science evolutions (Mokyr, 2002). In turn, science also informs technology via rigorous grounding in application domain knowledge bases (Baskerville, Baiyere, Gregor, Hevner, & Rossi, 2018). As a consequence, producing prescriptive knowledge with truth-like value (Iivari, 2007) for engineering service systems in the digital age is inhibited when solely focusing on certain artifacts or technologies that address distinctive digital technologies, i.a., the Internet of Things, 3D/4D printing, blockchain, smart advisors or advanced analytics (Denner, Püschel, & Röglinger, 2018). The focus of inquiry rather is to be shifted toward acknowledging generic new technology affordances that are enabled by digital technologies and anticipating how they influence innovation trajectories and outcomes (Nambisan, Lyytinen, Majchrzak, & Song, 2017). To sum up, presenting prescriptive knowledge with a higher degree of abstraction allows it to be generalized to other situations. New knowledge then is likely to be more highly regarded the further up the levels of abstraction it can be pushed to nascent design theory or more complete design theory (Baskerville, Kaul, & Storey, 2015; Bichler et al., 2016; Gregor & Hevner, 2013). Referring back to the manufacturing firm mentioned in the introduction, producing bearings and machine components with high quality standards and long lifetimes is accomplished by making use of knowledge that addresses the underlying characteristics of their materiality and their intended purpose. Mechanical engineers dealing with the technical configuration of novel products cannot necessarily utilize the operational knowledge gathered throughout the development of extant

Research Objective: Toward a Body of Design Knowledge

9

construction units, but revert to the body of knowledge comprised in standard work such as the DUBBEL – a handbook for mechanical engineering (Beitz & Küttner, 1994). In terms of mechanical engineering, the DUBBEL is considered as a must for German engineers. It is a handbook that is meant to be used everyday by design engineers and is loaded with useful tables, graphs and equations that emerged from extant research in scientific disciplines associated with mechanical engineering. The accumulation of knowledge that is gathered trough the contextualization of evidence from underlying physical laws and regularities allows for bringing artifacts to life that are capable to fulfill their intended purpose in dedicated application fields. Thus, unprecedented artifacts made from hitherto unknown materials can be constructed by means of utilizing design knowledge dealing with statics of rigid bodies, mechanical vibrations, theory of elasticity, finite elements methods, or laws of thermodynamics. As such, this abstracted and generalized knowledge has matured toward a level that allows it to be applied for building a broad variety of artifacts, independently of their shape and materiality. In the digital age, the emergence of novel digitally enabled service systems is rather contingent on the digitally enabled generativity unleashed by digital technology (Barrett et al., 2015; Eaton et al., 2015; Lusch & Nambisan, 2015). Accordingly, rapid and pervasive developments in the area of digital technology demand for underlying principles to be understood and ingrained in prescriptive knowledge contributions in an abstract and more general way, i.e., by means of a consistent body of knowledge, in order for them to maintain their utility throughout their further maturation (Baskerville et al., 2018; Gregor & Hevner, 2013; Nambisan et al., 2017; Yoo et al., 2012). The objective of this study is thus to develop design knowledge emerging from the intersection of IS expertise and service research that supports the engineering of digitally enabled service systems in a way that allows for the abstraction of prescriptive knowledge to be ingrained in a class of novel artifacts. Hence, the dissertation is guided by the following overarching research question: How can design knowledge for engineering service systems in the digital age be developed toward a consistent body of design knowledge? This research question constitutes the linchpin for the dissertation to which distinct contributions on a more fine-grained level can provide applicable insights. In this vein, underlying premises of the overarching research question are addressed by means of

10

Introduction: Objective of this Research

four research questions that deal as means to drive the overall contribution of this dissertation along the studies introduced in the next chapter. Hence, the overarching research question can be decomposed into the following subset of research questions: RQ1:

How can design knowledge relevant for engineering service systems in the digital age be structured in a meaningful way?

RQ2:

Which mechanisms leading to enhanced resource densities can be identified among digitally enabled service systems?

RQ3:

How can digitally enabled service systems be developed systematically and in a structured manner?

RQ4:

How can generalizable guidelines for engineering digitally enabled systems be produced and communicated by means of a digital tool?

Purpose and Scope of the Dissertation

3

11

Purpose and Scope of the Dissertation

In order to answer the overarching research question, four interrelated studies, guided by the subset of research questions introduced above, are presented in this dissertation1. With the overall objective to shape a body of design knowledge for engineering service systems in the digital age, the studies are grounded in the paradigm of design science research (DSR) (Hevner et al., 2004; March & Smith, 1995; Simon, 1996) and contribute to different facets in the context of the underlying knowledge creation process (Baskerville et al., 2015). Thus, in alignment with the central premise of DSR to produce knowledge contributions in a nexus of rigor and relevance (Gregor & Hevner, 2013; Hevner, 2007; Hevner et al., 2004; Iivari, 2007; PriesHeje & Baskerville, 2008), the development of a consistent body of knowledge for engineering digitally enabled service systems is pursued as depicted in Figure 1.

1 The research was conducted within the context of SmartDiF, a collaborative research project funded by the German Federal Ministry of Education and Research (BMBF). The project was granted as prioritary action in the context of the platform for labor organization and services (Grant Code: 02K15Z000). The author gratefully acknowledges the support by the BMBF and the project partners.

12

Introduction: Objective of this Research

Extant Body of Knowledge Relevant for Service Systems in the Digital Age Accumulation of Design Knowledge Taxonomy Study 1

Research Directions Study 1

Generative Mechanisms

TRIGGER

DiDesigner

Study 2

Study 3

Study 4

Communication of Design Knowledge Discussion Prescriptions for Expanding Toward Full-Blown Theory for Design and Action

Emergent Design Theory for Digitally Enabled Service Systems

Body of Design Knowledge for Engineering Service Systems in the Digital Age

Figure 1. Scope of the Dissertation

Purpose and Scope of the Dissertation

13

Study 1 addresses the research question of how design knowledge relevant for engineering service systems in the digital age can be structured in a meaningful way (RQ1). In DSR, rigor is predominantly achieved by appropriately applying existing foundations and methodologies in the course of developing novel artifacts that embody useful design knowledge for solving a problem (Hevner, 2007; Hevner et al., 2004; Iivari, 2007). Hence, reverting to RQ1, this study deals with developing a taxonomy that can help to bring order to the complex area of research at the intersection of research in the fields of IS and service research in order to be able to identify knowledge contributions that are promising to embody applicable design knowledge for engineering digitally enabled service systems. Guided by a rigorous research design, the objects of interest to be classified, i.e., prescriptive knowledge contributions, are identified by applying the literature review method proposed by vom Brocke et al. (2009). The taxonomy development process dealing with the classification of these objects follows the principles of the taxonomy development method by Nickerson, Varshney, & Muntermann (2013). The resulting classification is then discussed in terms of knowledge contributions valuable for providing a foundation for future artifacts embodying design-oriented knowledge for engineering digitally enabled service systems. In this vein, potential research opportunities are shed light on and promising directions for future research are prescribed. This study contributes to the overall objective of the dissertation in terms of fostering the understanding of the field and paving the way for novel knowledge contributions to be produced in the further course of the dissertation. Study 2 deals with the research question of which mechanisms leading to enhanced resource densities can be identified among digitally enabled service systems (RQ 2). The aim of Study 1 was to identify knowledge contributions that are deemed to embody valuable design knowledge for engineering digitally enabled service systems and to discuss their characterization among applicable dimensions. However, Study 1 revealed that, although valuable knowledge contributions addressing the overall scope and purpose of this dissertation are evident in extant literature, there is still a scarcity of prescriptive knowledge acknowledging the facets of the specific nature of innovation in digitally enabled service systems. In this vein, Hevner et al. (2004) state that the existing knowledge base is often insufficient for design purposes, inducing designers

14

Introduction: Objective of this Research

to rely on intuition, experience, and trial-and-error methods. A constructed artifact, in turn, demands for a designer’s well-grounded design knowledge of the problem and solution (Hevner et al., 2004). Building on this premise, Study 2 is addressing RQ 2 by means of applying a qualitative explorative approach in the context of a holistic multiple case study (Miles, Huberman, & Saldana, 2014; Yin, 2003) in order to identify generative mechanisms that bear the potential to lead to enhanced resource densities (Lusch & Nambisan, 2015; Normann, 2001) in digitally enabled service systems (Herterich, Eck, & Uebernickel, 2016; Yoo et al., 2010). The analysis of the empirical data collected among 13 cases then leads to three generative mechanisms that stem from an understanding of digitally enabled generativity in service systems that is grounded in the notion of the dematerialization mechanisms introduced by Normann (2001), i.e., liquification and unbundleability. These mechanisms, i.e., invention, improvement, and exaptation, thus embody design knowledge that is promising to be incorporated in the course of designing and developing service systems that are attuned to the premises of innovation opportunities opened up by digitally enabled generativity (Böhmann et al., 2014a; Lusch & Nambisan, 2015). Hence, as a departure from grounding design knowledge for engineering digitally enabled service systems in intuition and experience (Hevner et al., 2004), this study contributes to the overall dissertation in terms of complementing the extant body of knowledge with knowledge on “principles of function” as part of a method (Gregor & Hevner, 2013; Gregor, Müller, & Seidel, 2013) that provides the instructions for performing the goal driven activity of supporting the engineering of digitally enabled service systems. By that, knowledge is produced that is promising to allow for prescriptions of guidelines for prospective artifacts in this context. Study 3 elaborates on how digitally enabled service systems can be developed systematically and in a structured manner (RQ 3). As Study 2 predominantly allowed for prescribing principles of function to be acknowledged for engineering digitally enabled service systems, the intend of Study 3 is to shed light on the operationalization of applicable underlying foundations. Thus, beside dealing with principles of function, this study makes use of knowledge extracted from Study 1 on how to structure according development activities in a systematic way and further applicable contributions from the knowledge base in order to develop an artifact, i.e., a method

Purpose and Scope of the Dissertation

15

(Brinkkemper, 1996; Gregor & Hevner, 2013), that provides an operational view on service system analysis and design (Alter, 2012; Böhmann et al., 2014a). The respective method addresses a multitude of facets of artifacts capable to support the systematic development of digitally enabled service systems, together with ingraining prescriptive knowledge from Study 2. Hence, the initial design of the method is guided by a set of ten requirements derived from applicable foundations in the problem context and is comprised of four building blocks that, in turn, encompass methods and activities on a more fine-grained level. The interplay of these building blocks, i.e., CVC, Job Map, Service Blueprint, and LiCoDi, is defined by an overarching meta-model and is attuned to the overall aim of engineering digitally enabled service systems by means of enhancing inherent resource densities along the dimension of time, space, and actor (Lusch & Nambisan, 2015; Normann, 2001). The initial design of the artifact is then evaluated in accordance with the Human Risk & Effectiveness evaluation strategy introduced by Venable, Pries-Heje, & Baskerville (2016). Within the evaluation trajectory, an artificial-formative evaluation is combined with four cycles of naturalistic-formative evaluation settings under consideration of a set of dedicated evaluation criteria (Peffers, Rothenberger, Tuunanen, & Vaezi, 2012; Prat, ComynWattiau, & Akoka, 2014, 2015; Sonnenberg & vom Brocke, 2012b; Venable et al., 2016). The evaluation shows that the resultant artifact – referred to as meThod foR engIneerinG diGitally Enabled seRvice systems (TRIGGER) – broadly addresses the requirements inherent to digitally enabled service systems, but that it needs refinement in terms of its direct applicability. Hence, in the vein of the overall dissertation, a contribution is made in terms of providing design knowledge for engineering digitally enabled service systems that is rooted in real world applications (Böhmann et al., 2014a). By that, metaphorically spoken, a recipe to perform the task of systematically designing and developing these complex systems is contributed to the knowledge base (Gregor & Hevner, 2013; Hevner et al., 2004). Study 4 is concerned with the research question of how generalizable guidelines for engineering digitally enabled systems can be produced and communicated by means of a digital tool (RQ 4). Reverting to Study 3, its core of inquiry was to produce prescriptive knowledge to be ingrained in a method that encompasses instructions for the goaldriven activity of engineering digitally enabled service systems. On the way toward a

16

Introduction: Objective of this Research

cohesive and consistent body of knowledge on engineering service systems in the digital age as reflected in the overall objective of this dissertation, according “recipes” embody a pivotal knowledge contribution. However, prescribing how to do something with some degree of generality, i.e., giving prescriptions on how to design and develop an artifact that accomplishes some end, demands for design knowledge to be captured, written down, and communicated in a way that acknowledges a broader set of facets (Gregor, 2006; Gregor & Jones, 2007). Against this backdrop, Study 4 addresses underlying ontological foundations by means of developing an instantiation (Gregor & Hevner, 2013; March & Smith, 1995) that embodies the design knowledge produced in the course of the design and evaluation of TRIGGER, together with considering two intertwined research objectives in the context of the study’s research question. First, this expository instantiation (Gregor & Jones, 2007) – referred to as the DiDesigner – constitutes a prototype system that is used to illustrate how the notion of maximizing resource density is operationalized, with better communicative power than a natural language description. By that, the artifact itself has some representational power in terms of assisting with the communication of design principles inherent in the prescriptive knowledge produced up to this point (Gregor & Jones, 2007). Second, the DiDesigner is considered a digital tool that triggers innovation (Nambisan, 2013). In this vein, its design builds on the insights gathered in the course of the development of TRIGGER and addresses the notion of translating expert knowledge into actionable tradeoffs for lay users (Markus, Majchrzak, & Gasser, 2002). The development of the artifact as well as the documentation of the underlying design knowledge is guided by alternating design and evaluation loops in accordance with the build-evaluate patterns introduced by Sonnenberg and vom Brocke (2012b). Based on this evaluation strategy, four build-evaluation episodes are gone through, with each episode focusing on different aspects of the artifact. By reasoning about the artifact in both, the interior mode and the exterior mode (Gregor, 2009), truth-like statements about the prescriptive knowledge ingrained in the artifact is produced while it emerges throughout its development (Iivari, 2007; Sonnenberg & vom Brocke, 2012b). Therefore, this study contributes to the overall objective of the dissertation in terms of elaborating on underlying knowledge contributions in a way that allows for the prescription of inherent design principles of artifacts that support the engineering of

Purpose and Scope of the Dissertation

17

digitally enabled service systems. Moreover, with having positioned the DiDesigner as an expository instantiation, a viable artifact was produced that provides the ground for discussing prescriptive knowledge contributions with truth-like value for a prospective body of knowledge on engineering service systems in the digital age. As stated above, the overarching research objective for this dissertation deals with the question of how design knowledge for engineering service systems in the digital age can be developed toward a consistent body of design knowledge. In this context, Gregor & Hevner (2013) state that the emergence of a well-developed body of design knowledge is contingent on expressing underlying knowledge in terms that allow for prescriptions of design and action (Gregor, 2006; Gregor & Jones, 2007). Hence, with the aim of providing a sound basis for the development of prospective artifacts that address the same class of problem, i.e., engineering service systems in the digital age, the prescriptive knowledge produced in the course of this dissertation is to be documented and communicated along the components of a design theory (Gregor & Jones, 2007). In more detail, by elaborating on constituents contributing to the anatomy of a design theory, i.e., (1) purpose and scope, (2) constructs, (3) principles of form and function, (4) artifact mutability, (5) testable propositions, (6) justificatory knowledge, (7) principles of implementation, and (8) expository instantiation, principles inherent in the design of this class of artifacts can be specified in a generalized form. If research is expressed in this way, a move can be made toward a more mature and well-developed body of design knowledge (Gregor & Hevner, 2013; Gregor & Jones, 2007). Thus, following the call of SSE for design theories that allow for the prescription of guidelines of novel artifacts that enable or support the engineering of real-world service systems that permeate our society (Böhmann et al., 2014a), the discussion section answers the overarching research question by explicating the foundations for an emergent design theory along the knowledge contribution claims from the studies described beforehand. Moreover, based on this synthesized view, the contribution of the dissertation is articulated and positioned in the research field. The remainder of this dissertation is structured as follows. In Part II, the research background, in which the dissertation is grounded, is presented. In this context, relevant contributions dealing with the notion of service systems, generativity,

18

Introduction: Objective of this Research

resource density, and extant design knowledge are reviewed. The next part describes the interplay of research methods applied within the scope of the overarching DSR approach under particular consideration of the various knowledge contribution claims to be achieved. Part IV is at the core of the dissertation and reports on the studies as well as the development of according artifacts described beforehand. Part V reverts to the overall research objective of this dissertation in terms of discussing the relevance of the prescriptive knowledge produced as foundation for a consistent body of design knowledge for engineering service systems in the digital age. Ultimately, the conclusion part constitutes the last part of this work and provides a summary of the overall scope and purpose of the dissertation, together with providing insights on limitations and avenues for future research. The overall structure is depicted in Figure 2.

Purpose and Scope of the Dissertation

Extant Body of Knowledge Relevant for Service Systems in the Digital Age

Part I. Introduction: Objective of this Dissertation • Unanticipated novel service systems emerge in the digital age • Digitally enabled service systems are complex configuration of resources • Knowledge for their systematic design and development is needed Part II. Research Background: Grounding of the Dissertation • Innovation in service systems is contingent on resource reconfigurations • Generativity and resource density are promsing lenses for digitally enabled innovation • Extant design knowledge and artifacts are crucial for inquiries in knowledge creation Part III. Research Method: Consuming and Producing Knowledge • DSR is a problem-solving paradigm • Knowledge bases play varying roles as knowledge provider and consumer • Artifacts and design theories are the central outcomes of DSR • The studies within this dissertation acknowledge premises underlying DSR Part IV. Knowledge Creation: Advancing Design Knowledge • The taxonomy brings order to extant prescriptive knowledge • Generative mechansism deal as principles of function to enhance desource density • TRIGGER ingrans prescriptive knowledge in an operational way • The DiDesigner deals as digital tool with representational power Part V. Discussion: Shaping a Body of Design Knowledge • Knowledge was accumulated throughout this dissertation and ingrained in artifacts • Emergent design theory deals as means to build similar artifacts in the future • Maturing emergent design theory leads toward a cohesive body of design knowledge Part VI. Conclusion: Reflections on the Dissertation • Throughout this dissertation a broad range of knowledge was accumulated • Theoretical and practical contributions can be drawn from insights gathered • Limitations can be explicated that provide a ground for future research • The work can contribute a grain of thruth for engineering service systems in the digital age

Body of Design Knowledge for Engineering Service Systems in the Digital Age

Figure 2. Structure of the Dissertation

19

II Research Background: Grounding of the Research

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_2

The Notion of Innovation in Service Systems and Service Systems Engineering

1

23

The Notion of Innovation in Service Systems and Service Systems Engineering

Whereas most innovation throughout human civilization has captured natural phenomena to invent tangible product offerings, with the separation of information from matter and the rapid growth of global communications networks, more and more innovation will be intangible, digitally enabled, and created around social phenomena. Novel innovation opportunities thus encompass new combinations of digital and physical components to create novel market offerings and evolve from the joint action of a network of actors ranging from suppliers and partners to customers and independent inventors—that is, with a network-centric focus (Barrett et al., 2015; Lusch & Nambisan, 2015; Tilson et al., 2010; Yoo et al., 2010). Against this backdrop, applicable perspectives and approaches that support the development of according novel multifaceted offerings will be dealt with in the further course.

1.1

The Facets of Innovation in Service Systems

To advance our understanding of today’s global, digital, service-oriented economy, new theoretical lenses and perspectives are necessary (Breidbach & Maglio, 2015; Maglio & Breidbach, 2014). In this vein, service research has developed new conceptualizations of innovation, building on service-centered approaches to value creation (Lusch & Nambisan, 2015; Witell, Snyder, Gustafsson, Fombelle, & Kristensson, 2016). The traditional view of service emphasizes dyadic one-to-one service encounters. However, in order to address the larger constellations within which actors become joined by service over time and space, the notion of service system embodies a suitable abstraction on value creation (Chandler & Lusch, 2015; Spohrer et al., 2008). Such a systems perspective has more explanatory power than a singular, entity-level perspective that may focus on service customers or providers only and shifts the focus of analysis on many-to-many interactions in a networks of value creating actors (Lusch

24

Research Background: Grounding of the Research

et al., 2010; Patrício, Pinho, Teixeira, & Fisk, 2018; Vargo & Akaka, 2012a). The service system, therefore, provides an ideal analytical framework and unit of analysis for rethinking value and how it is created (Breidbach & Maglio, 2016; Maglio & Breidbach, 2014; Vargo et al., 2008). Further on, a service system approach allows for understanding its parts without losing the systemic context (Gummesson, 2007; Pinho, Beirão, Patrício, & P. Fisk, 2014). Service systems consist of a dynamic value cocreation configuration of resources, including people, organizations, shared information (language, laws, measures, methods), and technology. These are all connected internally and externally to other service systems by value propositions (Maglio & Spohrer, 2007; Maglio et al., 2009). Each service system co-creates value through integrating existing resources with those from other service systems (Vargo et al., 2008). Innovation in service systems can then be understood by means of reverting to the longhand definition of service as the application of specialized competences through deeds, processes, and performances for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015; Vargo & Lusch, 2016). Grounded in this view, service innovation can then be considered the rebundling of diverse resources that create novel resources that are beneficial (i.e., value experiencing) to some actors in a given context; this almost always involves a network of actors, including the beneficiary (Lusch & Nambisan, 2015). It is thus the ongoing recombination of resources that drives innovation, as well as value cocreation, within and among service systems (Vargo & Akaka, 2012b; Vargo et al., 2008). This is in the vein of a Schumpeterian view of innovating, suggesting that it concerns “carrying out of new combinations” (Schumpeter, 1934, p. 66). Innovation in service systems often starts with a change in a resource, which, in turn, then opens up to new combinations. In line with recent conceptualizations in service research, all innovations can then be conceptualized as recombination of existing and new resources (Witell et al., 2017, 2016).

1.2

The Interplay of Service Systems in the Digital Age

However, with innovation in service systems being induced by the recombination of resources within and, in particular, across service systems, a feasible perspective is needed to guide the delineation and demarcation of the service system to be engineered

The Notion of Innovation in Service Systems and Service Systems Engineering

25

(Patrício, Gustafsson, & Fisk, 2018). This is of particular importance for digitally enabled service systems that are contingent on the nature of the digitally enabled generativity (Yoo, 2013) and concomitant socio-technical processes (Lusch & Nambisan, 2015; Tilson et al., 2010). These systems exhibit a certain “capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences” (Zittrain, 2008, p. 70). This means that a priori undefined actors of varying capabilities, ranging from the curious individual to big organizations, may participate in a digitally enabled service system. In addition, their participation is unfiltered, i.e., they most often act autonomously and their activities tend to not be centrally controlled (Eaton et al., 2015; Eck & Uebernickel, 2016). Against the backdrop of according increased complexity in the service environment, a value network perspective is promising to provide the ground for the design and development of respective service systems (Kieliszewski, Maglio, & Cefkin, 2012; Pinho et al., 2014). Patricio, Fisk, Falcao e Cunha, and Constantine (2011) advocate a multilevel view distinguishing between service systems at an organizational level and customer value constellations at the network level. This value constellation (Normann & Ramírez, 1993) can be conceptualized as a value network, i.e., a system of service systems that together provide integrated support to customer activities (Patricio et al., 2011). Value networks can then be defined as spontaneous combinations of actors interacting to co-produce service offerings, exchange them, and co-create value (Lusch et al., 2010; Patrício, Pinho, et al., 2018; Pinho et al., 2014) and thus provide a promising view for understanding and designing the interplay among systems of digitally enabled service systems.

1.3

The Engineering of Service Systems

Research on SSE (Böhmann et al., 2014a) responds to this paradigm shift by recognizing service as a collaborative process that creates context-specific value (Edvardsson, Ng, Min, Firth, & Yi, 2011; Vargo & Lusch, 2004). SSE further adopts a systems perspective as a way of thinking that aims to understand service and service innovation (Alter, 2011, 2012; Maglio et al., 2009). It takes the service system as the basic unit of analysis and emphasizes the importance of design knowledge on service

26

Research Background: Grounding of the Research

systems. This conceptualization extends traditional service engineering research that proposes models, methods, and principles to engineer individual services (Leimeister, 2012), often adapting approaches from product and software engineering for this purpose (Bullinger, Fähnrich, & Meiren, 2003). It is argued that the inherent productcentric thinking of extant approaches does not reflect service-centric business models and strategy (Ostrom et al., 2010, 2015; Patrício, Gustafsson, et al., 2018) and that service engineering research does not take full advantage of the opportunities for systemic, interactive, and collaborative service innovation that can be derived from advances in the digital age (Böhmann et al., 2014a; Spohrer & Kwan, 2009). This places the onus on SSE to advance knowledge on models, methods, and artifacts that are attuned to the nature of complex service systems. In this vein, SSE calls for research leading to actionable knowledge for systematically designing, developing and piloting service systems, based upon understanding the underlying principles of service systems (Böhmann et al., 2014a). After having elaborated on the constituents of innovation in service systems and approaches that guide their systematic design and development, the next chapter deals with perspectives that foster the understanding of underlying principles in the context of digitally enabled service systems.

The Concepts of Generativity and Resource Density as Lenses on Digitality

2

27

The Concepts of Generativity and Resource Density as Lenses on Digitality

Although leading to novel value creation opportunities among actors from broad and varied audiences (Lusch et al., 2010; Vargo & Akaka, 2012a; Zittrain, 2008), innovation in digitally enabled service systems faces inherent tensions that are contingent on the mechanisms underlying digitally enabled generativity (Eaton et al., 2015; Yoo, 2013). In order to deepen the understanding of these mechanisms, together with providing a foundation for producing knowledge contributions that acknowledge the positive outcomes of what they induce (Eaton et al., 2015; Förderer et al., 2014; Pagani, 2013), central notions are dealt with in the following.

2.1

The Facets of Digitally Enabled Innovation

A necessary but not sufficient condition for innovation in digitally enabled service systems is that novel configurations of resources rely on digitization, i.e., the encoding of analog information into a digital format (Tilson et al., 2010; Yoo, 2010). This decoupling of information from its physical matter is mainly driven by the emergence of digital computers and fosters the ability for information to be shared with others (Tilson et al., 2010). By configuring and modeling this decoupled information in different ways, novel insights and contextually relevant knowledge can be generated (Benaroch, 1998; Gruber, 1995). Thus, in the vein of the central notion of innovation in service systems, i.e., the rebundling of diverse resources that create novel resources that are beneficial (i.e., value experiencing) to some actors in a given context (Lusch & Nambisan, 2015), the technical process of digitization constitutes a basic prerequisite. However, it is predominantly the socio-technical processes accompanying such digitization that open up novel innovation opportunities (Lusch & Nambisan, 2015; Nambisan, 2013; Tilson et al., 2010), thus constituting the sufficient condition for innovation in digitally enabled service systems.

28

2.2

Research Background: Grounding of the Research

The Nature of Digital Technology

The according forging of novel socio-technical assemblages is particularly enforced by continuing developments of digital technology (Barrett et al., 2015; Eaton et al., 2015; Tilson et al., 2010; Yoo et al., 2012). Understanding the nature of innovation in digitally enabled service systems is then contingent on considering how digital technology differs from earlier technologies (Yoo et al., 2010). Before the emergence of digital technology, products and services were tightly coupled to dedicated devices, networks, and infrastructures. For instance, content such like movies and TV programs was tightly coupled to cable or public broadcasting infrastructure and devices (e.g., televisions). Banking services were tightly coupled with particular banking infrastructures, imposing customers to be physically present at the designated bank. However, these layers are increasingly decoupled, a process that three unique characteristics of digital technology that differ from other technologies have expedited (Seo, 2017; Seo & Sherif, 2009): (1) the reprogrammability, (2) the homogenization of data, and (3) the self-referential nature of digital technology (Yoo, 2013; Yoo et al., 2012, 2010). The notion of (1) reprogrammability builds on the von Neumann computing architecture (Langlois, 2002) in terms of enabling the separation of the semiotic functional logic of the device from the physical embodiment that executes it, thus allowing a digital device to perform a wide array of functions (such as calculating distances, word processing, video editing and web browsing) (Yoo et al., 2010). In fact, reprogrammability enables a smart phone to be a physical container that carries various content and services (e.g., downloading and deleting applications) instead of being coupled to a pre-defined and fixed set of content and service (e.g., in case of voice only mobile phones) (Seo, 2017). The (2) homogenization of data refers to the digital representation of data in terms of mapping any analog signal into a set of binary numbers, i.e., bits. By that, any digital content can be stored, transmitted, processed and displayed using the same digital devices and networks. For example, an iPhone is not only a phone, but also a camera, a music player, and a video player. Moreover, unlike analog data, digital data can be decoupled from heterogeneous sources and can be combined easily with other digital service so as to generate novel insights and contextually relevant knowledge (Chowdhury, Bergquist, & Åkesson, 2014; Yoo et al.,

The Concepts of Generativity and Resource Density as Lenses on Digitality

29

2010). Finally, (3) a self-referential nature means that innovation driven by digital technology requires and induces the use of further digital technology. Drastic improvements in the cost-benefit ratio computers and the ubiquitous emergence of the Internet have made the digital tools necessary for innovation more affordable to a multitude of previously excluded stakeholders (Yoo et al., 2010). Digital technology, therefore, has lowered entry barriers to service systems, allowing various value creating actors to participate in processes of collaborative value creation with multiple stakeholders (Blau, van Dinther, Conte, Xu, & Weinhardt, 2009; Eaton et al., 2015).

2.3

The Prevalence of Generativity

Yoo et al. (2010) argue that the emergence of digital technology has made possible novel forms of generative innovation (Eaton et al., 2015; Herterich & Mikusz, 2016; Lusch & Nambisan, 2015). In more detail, combined with the rapid diffusion of personal computers and the Internet, the layered nature and unique characteristics of digital technology have brought unprecedented levels of generativity (Barrett et al., 2015; Yoo et al., 2012, 2010). As already briefly elaborated on above, generativity refers to “a system’s capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences” (Zittrain 2008, p. 70). The generativity unleashed by digital technology, i.e., digitally enabled generativity (CecezKecmanovic, Galliers, Henfridsson, Newell, & Vidgen, 2014; Yoo, 2013), thus allows innovation to extend beyond the original initiator and purpose and is characterized by outcomes that are unanticipated and self-reinforcing (Fielt & Gregor, 2016; Zittrain, 2006, 2008). Reverting to underlying premises, the term generativity has old philosophical roots, going back to Leibniz (Smith, 2011), and is commonly used in modern sciences such as evolutionary biology, cybernetics and linguistics to express the basic idea that the observed complexity of a phenomenon (e.g., biological diversity, social systems and language) can be traced back to some basic elements and their mechanisms for interaction (Bygstad, 2017; Phelan, 2001). Although being attached to a large number of distinct concepts in various research domains (Avital & Te’Eni, 2009; Eck, Uebernickel, & Brenner, 2015), the notion of generativity introduced by Zittrain (2008) is deemed as promising to provide a foundation for understanding innovation

30

Research Background: Grounding of the Research

in digitally enabled service systems due to its prevalence in contributions at the intersection of IS and service research (Barrett et al., 2015; Eaton et al., 2015; Herterich & Mikusz, 2016; Lusch & Nambisan, 2015). However, as Eck and Uebernickel (2016) argue, the notion of generativity leads to different conclusions on how to describe a generative system. As illustrated in Figure 3, the first perspective emphasizes the notion of generative properties and considers generativity as consequence of system design with the system’s main achievement being constituted by catalyzing human ingenuity, whereas the second perspective deals with generative patterns as consequence of system evolution over time, with the system being capable to evolve into directions that were initially unimaginable (Eck & Uebernickel, 2016).

Generative System (as consequence of design)

Generative System (as consequence of evolution)

Figure 3. Perspectives on Generative Systems

In the context of producing knowledge contributions relevant for the emergence of a body of knowledge on how to engineer service systems in the digital age, it can be argued that an understanding of how generative systems evolve is promising to provide a ground for engineering generative systems that are built on the insights gathered from permeating according generative patterns. Thus, by understanding the patterns that underlie evolving digitally enabled service systems, implications for generative properties that guide their design and development in the future can be drawn. Hence, in the following, light is shed on the nature of these two perspectives in more detail. The first perspective, i.e., the notion of generative properties (Eck & Uebernickel, 2016), rests on the insight that distinct system properties let actors engage with artifacts in ways that lead to unanticipated outcomes. It other words, it assumes a system in which a priori unknown actors contribute their creativity and skills and engage with

The Concepts of Generativity and Resource Density as Lenses on Digitality

31

the system to produce results that those who created the system had not in mind at the first place. The system as a whole, however, largely maintains its overall design (Eck & Uebernickel, 2016). In this vein, positive outcomes of generativity are fostered by imposing guiding structures that are attuned to the application of knowledge and skills (Lusch & Nambisan, 2015) from formerly unknown actors (Eaton et al., 2015; Förderer et al., 2014; Pagani, 2013; Um, Yoo, Wattal, Kulathinal, & Zhang, 2013; Yoo, 2013). Through system design and guiding arrangements, the system per se is generative because of some inherent qualities that it possesses and can be regarded as a ‘toolbox for unanticipated change’. The system’s generative capacity then is a function of its inherent generative properties and the number and diversity of actors that can potentially engage with it. To sum up, this view highlights the central role of the design of the system and the ones who created it, together with uncovering which properties enable and foster generativity (Eck & Uebernickel, 2016). The second perspective, i.e., the notion of generative patterns (Eck & Uebernickel, 2016), regards how and to which extent a system develops elements, structures and behaviors that surpass the imagination or ambition of those who created the system in the first place. However, instead of inherent characteristics, time is regarded as evocative of generativity and the evolutionary path a system has taken is shed light on. According to this view, a system has evolved generatively because of the aggregated interactions of actors in and among systems that have produced unanticipated change. Hence, this perspective embodies the focus to detect generative patterns that underlie events and which contingently explain generative evolution across a broader range of contexts. The order of events that reflects a certain pattern then leads the system to evolve generatively (Eck & Uebernickel, 2016). Here, identifying according situational mechanisms (macro-micro level), action-formation mechanisms (socio-technical action), and transformational mechanisms (micro-macro level) (DeLanda, 2006; Hedström & Swedberg, 1998) is of particular importance for fostering the understanding of how generative systems evolve over time (Bygstad, 2017; Hanseth & Lyytinen, 2010; Henfridsson & Bygstad, 2013). To conclude, the generative patterns perspective allows for identifying and analyzing how the interplay of resources and actors in and among systems may coalesce to a trajectory that leads to its evolvement in unanticipated ways over time (Eck & Uebernickel, 2016).

32

Research Background: Grounding of the Research

With digitally enabled services systems being the generative entity whose engineering is ought to be supported by a class of artifacts in the context of this research, the “unknown” has to be structured and elaborated in the process of prescribing principles inherent in the design of these artifacts. Bringing artifacts to live being an act to change the state of the world including with new unknown alternatives thus also requires applicable prescriptive knowledge to account for the generativity unleashed by digital technology. Accordingly, the strength and uniqueness of a body of design knowledge in this context is contingent on its ability to conceptualize and create non-existent alternatives (Hatchuel, Le Masson, Reich, & Subrahmanian, 2018). In analogy to generativity in the context of systems referring to “a system’s capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences” (Zittrain 2008, p. 70), design knowledge in the realms of engineering service systems in the digital age can then be characterized as permeated by generativity in terms of possessing the capability to generate new propositions that are made of known building blocks but are still different from previously known combinations of these building blocks (Hatchuel et al., 2018; Hatchuel, Reich, Le Masson, Weil, & Kazakçi, 2013). Reverting to organizations that engage in the development of resultant novel offerings, respective innovation design activities are to be attuned toward underlying premises (Le Masson & Hatchuel, 2010). Against this backdrop, a promising lens to address this context is elaborated on in the following chapter.

2.4

The Idea of Resource Density

The main objective of this research is to develop design knowledge that supports the engineering of digitally enabled service systems in a way that allows for the abstraction of prescriptive knowledge to be ingrained in a class of novel artifacts. Thus, in order to foster the emergence of a body of knowledge on engineering service systems in the digital age, understanding the generative patterns underlying the socio-technical processes concomitant with digitally enabled generativity is needed. The idiographic scientific knowledge (Baskerville et al., 2015) produced in this context then can deal as grounding for deriving generative properties to be ingrained in novel constructs, models, methods, instantiated artifacts, and design theories (Gregor & Hevner, 2013;

The Concepts of Generativity and Resource Density as Lenses on Digitality

33

Hevner et al., 2004) that are attuned to the nature of these complex systems, thus supporting their systematic design and development (Böhmann et al., 2014a). Hence, with the aim to understand how generative properties and mechanisms are to be identified or ingrained in digitally enabled service systems, an appropriate lens that acknowledges the constituents of service systems as abstraction of value creation (Spohrer et al., 2008) is needed. Therefore, as elaborated on in the further course, this research coalesces the concept of digitally enabled generativity unleashed by digital technology and the idea of resource density as a prerequisite to produce prescriptive knowledge for the engineering of service systems in the digital age. The notion of resource density is regarded as one of the most enriching concepts in service research (Lusch et al., 2010; Michel, Vargo, & Lusch, 2008; Vargo et al., 2008) and provides foundational premises to understand the generativity unleashed in digitally enabled service systems and concomitant generative mechanisms leading to beneficial resource configurations (Lusch & Nambisan, 2015). Density is a measure of the amount of information, knowledge, and other resources that an actor has at any given time and/or place to solve problems (Vargo & Akaka, 2012a, 2009). In this logic of value creation, the nature of digital technology constitutes a driving force to enhance resource density (Herterich & Mikusz, 2016; Lusch & Nambisan, 2015), as it provides the infrastructure and artefacts that liberates service systems from inherent constraints related to when things can be done (time), where things can be done (place), who can do what (actors) and with whom it can be done (configurations/constellations) (Barrett et al., 2015; Chandler & Lusch, 2015; Kowalkowski & Brehmer, 2008; Lycett, 2013; Normann, 2001). In particular, the unique characteristics of digital technology (Yoo et al., 2010) enforce two intertwined dematerialization mechanisms that lead to the creation of new densities, namely liquification and unbundleability. Liquification refers to dematerialization through the separation of information from the physical world, i.e., the technical process of digitization, allowing it to be easily moved about and remanifested in many different ways. Liquification drives unbundleability, which refers to the separation of activities hitherto well defined and held together in time and place and by actor, i.e., the socio-technical process accompanying digitization, thus initiating unanticipated change among the audiences incorporated in the service system (Lusch & Nambisan, 2015; Michel et al., 2008; Normann, 2001; Yoo, 2013).

34

Research Background: Grounding of the Research

Reverting to the longhand definition of service as the application of specialized competences through deeds, processes, and performances for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015; Vargo & Lusch, 2016), dematerialization through liquification and unbundleability promotes rebundleability, which allows the creation of improved densities (Michel et al., 2008; Normann, 2001). Hence, improved densities are achieved by rebundling diverse resources, creating novel resources beneficial (i.e., value-experiencing) to some actors in a given context, which can then be conceptualized as innovation in service systems (Eaton et al., 2015; Lusch & Nambisan, 2015). Thus, by building on the conceptualization of dematerialization mechanisms, the notion of resource density allows for both, understanding unanticipated change triggered by digitally enabled generativity in service systems based on liquification and unbundleability and controlling this generativity based on rebundleability in order to systematically design and develop digitally enabled service systems with enhanced resource density.

The Role of Extant Design Knowledge

3

35

The Role of Extant Design Knowledge

The previous chapters dealt with justificatory knowledge that provides an explanation of why an artifact addressing the problem of engineering service systems in the digital age is to be constructed as it is and why it works (Gregor & Jones, 2007). However, explicating principles inherent in the design of a class of artifacts that address a similar problem in a generalized way also demands for acknowledging prior prescriptive knowledge or existing artifacts (Gregor & Hevner, 2013). Against this backdrop, synthesized knowledge contributions with relevance for engineering service systems in the digital age are delineated in the following in order to envision the demarcation of the prescriptive knowledge produced in the further course. Hence, with the aim to provide insights on prescriptive knowledge contributions that encompass promising implications for engineering digitally enabled service systems, literature is reviewed along a continuum from extant work predominantly dealing with the notion of service systems (Beverungen, Lüttenberg, & Wolf, 2018; Frost & Lyons, 2017) to approaches that deal with underlying or associated premises of digitally enabled generativity in the realms of service innovation (Kleinschmidt, Peters, & Leimeister, 2016; Knop, Galipoglu, Lubarski, & Poeppelbuss, 2017). These contributions themselves embody systematic literature reviews that elaborate on extant literature streams and exhibit a certain number of intersections among their respective units of analysis. Hence, with the focus on carving out the nature of promising prescriptive knowledge, this sample embodies an admittedly not exhaustive but rather representative synthesis (Cooper, 1988) of extant prescriptive knowledge and artifacts in the problem context. Additional details on dedicated knowledge contributions at the intersection of IS and service research, however, are provided in study 1, i.e., in the course of developing a taxonomy on knowledge in the context of SSE. In the course of elaborating on extant prescriptive knowledge contributions, a classification of prior work is developed in the following. Accordingly, prior work can be classified into three types. Type A approaches can be defined as approaches that are in agreement with the notion of service systems as an abstraction of value creation,

36

Research Background: Grounding of the Research

albeit not necessarily embodying prescriptions on their engineering in the context of digitally enabled generativity. Type B approaches shed light on the premises concomitant with digitally enabled generativity and implications for innovation in service systems. Ultimately, Type C approaches encompass contributions that are characterized by a high degree of betweenness centrality, i.e., the degree to which papers connect different areas or research streams that are promising to provide valuable foundations for the emergence of novel design knowledge.

3.1

The Systematic Development of Service Systems

Referring to Type A approaches, several methods can be identified that, although they came to being before the notion of service systems was conceptualized at it is used nowadays (Maglio et al., 2009), encompass a systemic model scope for the development of a certain service offering (Edvardsson & Olsson, 1996; Johnson, Menor, Roth, & Chase, 2000). Of course, further contributions for the systematic design and development of service offerings are evident in literature before the notion of service systems emerged, but according approaches mostly focus on designing value propositions instead of service systems or view service independent of physical goods (Beverungen et al., 2018), thus being grounded in a product-centric thinking (Bullinger et al., 2003). Concerning contributions that dedicatedly build on the conceptualization of service systems set out by Maglio et al. (2009), a richer body of literature with a prescriptive focus can be delineated. In their study about the evolution of research on service systems analysis and components, Frost & Lyons (2017) classify the research foci of extant contributions based on the categories research outcomes, methods, theories, and applications (Cooper, 1988). Along these lines, Wang et al. (2016) deal with issues concomitant with the modeling of service systems and report on the development and application of a tool for modeling the function, context, behavior, state, principle, and structure of service systems. In a similar vein, Lessard & Yu (2013) utilize the evaluation notation of the i * modelling approach to develop a method for evaluating the outcome of value creation interactions in service systems based on referring to the resources, value propositions, expected benefits, high-level interests, and entities relevant among

The Role of Extant Design Knowledge

37

these interactions. Grounded in a systems of service systems perspective, Wang, Lai, & Hsiao (2015) prescribe a six step-approach for analyzing service value networks by developing a set of dedicated activities, i.e., defining the objectives of an analysis, identifying actors in the network at hand, determining the interactions among these actors, developing initial system models, testing these models by comparing them to the actual behavior of the system, and deriving policies and improvements based on the findings of the model testing. Emerging from a related worldview, Patricio et al. (2011) introduce a multilevel service analysis and design method that encompasses the use of value constellation modeling techniques, architectural modeling techniques, and service blueprinting techniques. With a focus on the perception and properties of service systems, Hung & Yuan (2014) elaborate on the notion of productivity and analyze pivotal underlying drivers to develop a model for evaluating, managing, and improving the quality of service productivity. In a similar vein, Campbell, Maglio, & Davis (2011) explore methods for improving service quality by shifting the service boundary between customers and providers and envision varying self-service and super-service

scenarios.

Concerning

rather

abstract

prescriptive

knowledge

contributions, Edvardsson, Skålén, & Tronvoll (2012) apply a sociologically grounded theory to a case study of a telecommunications company and explicate how social structures have implications for value creation and resource integration in service systems. Moreover, Edvardsson, Ng, Min Choo, & Firth (2013) conduct an empirical study of the performance of service-dominant versus goods-dominant service systems. Based on conducting a sentiment analysis method that acknowledges the influence of service-dominant characteristics on service system performance, they conclude that factoring a service-dominant orientation into system design leads to better service systems (Frost & Lyons, 2017). Apart from the contributions extracted from the synthesis of literature provided by Frost & Lyons (2017) up to now, further applicable Type A approaches can be identified (Alter, 2012; Deokar & El-Gayar, 2013; Drăgoicea et al., 2014; A Golnam, Regev, & Wegmann, 2013; Arash Golnam, Viswanathan, Moser, Ritala, & Wegmann, 2013; Kieliszewski et al., 2012; Kutsikos, Konstantopoulos, Sakas, & Verginadis, 2014; Lemey & Poels, 2011; Nardi et al., 2015; Neff et al., 2014; Poels, Van Der Vurst, & Lemey, 2013), but are put into consideration in Study 1 in order to avoid redundancies at this point.

38

3.2

Research Background: Grounding of the Research

The Premises Concomitant with Digitally Enabled Service Innovation

Type B approaches deal with premises associated or underlying the notion of digitally enabled generativity as a driver for innovation in service systems. In this context, the role of information and communication technology (ICT) is particularly shed light on. Although per se not exhibiting the unique characteristics of digital technology (Yoo et al., 2010), ICT has been recognized as playing a dual role as both an enabler and initiator for service innovation, and, by that, shares certain commonalities with the conceptualization of digital technology (Barrett et al., 2015; Lusch & Nambisan, 2015). Thus, reviewing extant literature on ICT and according implications for the emergence of novel service systems is promising to gather insight on potentially valuable prescriptive knowledge contributions for engineering digitally enabled service systems.

Reverting to Kleinschmidt, Peters, et al. (2016), applicable

contributions can be categorized along a service innovation management process that addresses the notion of ICT-enabled change in the context of service systems (Alter, 2008; Markus, 2004) and encompasses four phases, i.e., understanding, designing & implementing, operating & changing, and value capture (Kleinschmidt, Peters, et al., 2016). Among these phases, designing & implementing is put into particular consideration for further analysis. In this vein, Levenburg and Klein (2006) analyzed how companies can select ICT for improving the financial success of service innovations and identified the understanding of the beneficiaries’ needs as pivotal factor to be considered to successfully design according novel service offerings. Based on these findings, they propose guidelines for the development of digitized service offerings and present a combination of best practices with concrete proposals for emerging configurations (Levenburg & Klein, 2006). Dealing with factors to be considered in the design of ICT-enabled service systems, Yang, Stafford, and Gillenson (2011) state that the satisfaction with these systems prevalently depends on the system quality and system usefulness and recommend to focus on these aspects. With a similar intention, i.e., maximizing the output of ICT-related service innovations through design, Theotokis, Vlachos, and Pramatari (2008) examine the degree of technology usage required among different service systems. Grounded in the perspective of

The Role of Extant Design Knowledge

39

technology readiness, they develop a classification framework that deals with the level of customer-technology interaction in the service system to be designed. With a focus on the notion of service system transformation, Skålén, Aal, & Edvardsson (2015) show how ICT tools can serve as a facilitator for service innovation and propose a service system design using an interplay of interdependent ICT tools. Regarding the processual facets of developing innovative service offerings, (H. Yang & Hsiao, 2009) elucidate mechanisms for different development phases. These mechanisms can then be utilized to assess how ideas, requirements, and specifications can stimulate the development of ICT-enabled service systems in organizations (H. Yang & Hsiao, 2009). In their review, Kleinschmidt, Peters, et al. (2016), classify these contributions along the constituting parts of a service system as conceptualized by Maglio (2015), i.e., people, information, organizations, and technologies. However, although organizations and technologies are rather well addressed in extant literature, there is a scarcity of work dealing with the role of people and information (Kleinschmidt, Peters, et al., 2016) – elements that can be deemed as pivotal in digitally enabled service systems that are built on liquefied information that is shared with a multitude of actors (Lusch & Nambisan, 2015). In their systematic literature review, Zhang, Chen, Wang, and Ordóñez de Pablos (2016) deal with the diffusion of ICT in the nexus of service innovation and product innovation and analyze extant literature according to the logic of Nambisan (2013). Grounded in this view, two primary roles for ICT in innovation can be identified, namely, enabler and trigger (Nambisan, 2013). Drawing on this view, it is evident that extant studies mainly focus on the role of ICT as an innovation enabler in terms of focusing on the uses of IT in internal organizational processes (Zhang et al., 2016). They emphasize the value of IT as a complementary resource to influence the structure and behavior of teams or organizational units. In this vein, connectivity induced by ICT affects scope, reach, and cost of communication and coordination among actors, thus enabling innovation by facilitating team collaboration (Marion, Meyer, & Barczak, 2015) or enhancing a firm’s agility to market (Barczak, Hultink, & Sultan, 2008; Sambamurthy, Bhradwaj, & Grover, 2003). However, although ICT in its role as innovation enabler facilitates the interaction of existing links among actors, it does not initiate changes to the structure of knowledge and resource integration in innovation

40

Research Background: Grounding of the Research

(Lyytinen, Yoo, & Boland, 2016). It is rather the diffusion of digital technology that blurs the boundaries of products and industries, leading to innovation characterized by digital convergence (Yoo et al., 2012). As emphasized in more recent publications, innovation practices are thus no longer limited to the confines of an organization (Zhang et al., 2016). In fact, the use of ICT in the form of digital technology increases the heterogeneity of knowledge resources necessary for innovation, introduces new links between previously unconnected actors in more dynamic and complex network structures, and ultimately initiates innovation. In this role, ICT acts as a trigger for innovation (Lyytinen et al., 2016; Nambisan, 2013). Having elaborated on extant knowledge contributions in this context, Zhang et al. (2016) conclude that prior studies related to the role of ICT as an enabler mainly focus on strategic alliances and collaboration, knowledge management, and orchestration processes, whereas the role of ICT or digital technology as an innovation trigger potentially emphasizes concepts and insights from areas such as technology development or design science under consideration of according generative characteristics. However, they also stress that the specific mechanisms behind the dual effects of ICT on innovation are still ambiguous. In particular, the role of ICT as innovation trigger demands for further research, e.g., in terms of what the trigger effect is or how it actually works (Zhang et al., 2016).

3.3

The Intersection of Research Streams in IS and Service Research

Type C approaches encompass contributions that are characterized by a high degree of betweenness centrality. As advocated by Barrett et al. (2015), it is the infusion of IS research streams in topics dealing with the engineering of service systems that allows for elaborating on the implications emerging from the increasing prevalence of technology in innovative service offerings. In this context, extant contributions from IS literature are deemed promising to deal with questions such as how digital technology embedded in products might enable innovation in service systems or how the paradox of generativity and control of digital infrastructure can be managed within service systems (Barrett et al., 2015). Thus, in the following, light is shed on pivotal contributions that are positioned at the intersection of IS and Service Research and exhibit a high degree

The Role of Extant Design Knowledge

41

of betweenness centrality, i.e., the tendency of bringing together different areas or research streams (Everett & Borgatti, 1999). In their bibliometric study, Knop et al. (2017) apply bibliographic methods to the intersection of research in the fields of service innovation, IS, and ICT in order to analyze the development of various research streams in this areas over time. Concerning the most important contributions according to their betweenness centrality in more recent research, i.e., from 2010 on, the rise of design science research as a new research paradigm can be observed. Among the two most foundational contributions, Hevner et al. (2004) give guidance on how to conduct and evaluate design science research in the IS discipline whereas Gregor and Jones (2007) provide a blueprint for formulating design theories. Moreover, concerning pivotal position papers that postulate service as a distinct academic field, Spohrer and Maglio (2008) report on the emergence of a service science discipline that aims to overcome academic silos as well as to advance service innovation more rapidly. Building upon that, the aforementioned notion of SSE (Böhmann et al., 2014a) and its call for design-oriented IS research has increasingly gained momentum in recent years. Hence, in an overall view, a growing importance of references to papers postulating design-oriented approaches at the intersection of service innovation, IS, and ICT can be determined, which constitutes a departure from other established reference disciplines such as marketing that have a long tradition in service innovation research (Knop et al., 2017). One example reflecting this development is constituted by the prevalence of the contribution provided by Patricio et al. (2011) that prescribes an approach dealing with the embedding of ICTenabled interactions into various interaction channels in and among service systems. Concerning its betweenness centrality, this design oriented approach outperforms well-established theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, & Davis, 2003) or Cohen's and Levinthal's (1990) concept of absorptive capacity (Knop et al., 2017). As such, these contributions can be regarded as promising key pillars of research at the intersection of service innovation, IS, and ICT that help to leverage the potentials concomitant with digitally enabled generativity for developing innovative service offerings (Knop et al., 2017). However, design-oriented research within an interdisciplinary service science also requires an empirically grounded understanding of the intertwined behavior of

42

Research Background: Grounding of the Research

humans and technology (Cecez-Kecmanovic et al., 2014) as an impetus for fostering the coalescence of design-oriented and behavioral-oriented research activities (Knop et al., 2017; March & Smith, 1995). To sum up, the classification developed above deals as a foundation for carving out the nature of promising extant prescriptive knowledge and artifacts in the problem context. In this vein, extant scholars have demonstrated the emergence of various research streams that are promising to encompass prescriptive knowledge valuable for engineering digitally enabled service systems. As such, it became evident that Type A approaches are mainly capable of addressing the service system as a unit of analysis and design object, whereas Type B approaches focus on the role of ICT, digital technology, and further premises concomitant with digitally enabled generativity in the context of service innovation. Type C approaches then provide a foundation for bringing together these research streams, thus driving the emergence of prescriptive knowledge contributions in future research avenues. Against this backdrop, the next chapter reports on the research method applied for approaching this intent in the course of this dissertation.

III Research Method: Consuming and Producing Knowledge

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_3

The Paradigm of Design Science Research

1

45

The Paradigm of Design Science Research

In contrast to traditional research approaches that are used for exploring or confirming hypotheses, this dissertation follows a design science research (DSR) approach with the primary goal to develop novel artifacts from which generalizable prescriptive knowledge can be explicated (Gregor & Jones, 2007; Hevner et al., 2004). Reverting to its roots, Deng & Ji (2018) refer to DSR as a problem-solving research paradigm (March & Storey, 2008). Its objective is to create and evaluate artifacts designed to solve identified organizational problems, thus enabling the transformation from the "present situation" to the "desired situation" (Hevner et al., 2004; March & Smith, 1995; March & Storey, 2008). In accordance with Simon (1996, p. 130), “everyone designs who devises courses of action aimed at changing existing situations into preferred ones.” With its roots in engineering and the sciences of the artificial (Simon, 1996), design science was initially introduced to remedy the shortcomings of traditional sciences, such as natural science or social science, concerning their ability to explicate the objectives of prescribing solutions and methods or designing novel artifacts to solve given problems (Deng & Ji, 2018). These constraints are predominantly contingent on the objectives of traditional sciences, that is, to explore, to describe, to explain and, when possible, to predict (Romme, 2003; van Aken, 2004). In other words, traditional sciences focus on understanding reality, whereas the main aim of design science is to build artifacts that serve human purposes (March & Smith, 1995). Hence, with its objective to solve real-world problems, the application of DSR is promising to reduce the gap in between theory and practice (Romme, 2003; van Aken, 2004, 2005) while emphasizing the notion of rigor in research activities (Benbasat & Zmud, 1999; Hevner et al., 2004). To sum up at this point, DSR can be regarded as procedure of knowledge creation with the aim of achieving both the purposes of producing scientific knowledge and solving real organizational problems (Deng & Ji, 2018; Dresch, Antunes, & Lacerda, 2014)

46

2

Research Method: Consuming and Producing Knowledge

The Roles of Knowledge and Knowledge Bases

A fundamental issue in the context of knowledge creation is that nothing is really “new”, that is, everything is made of something else or is built on some previous idea and involves a high level of reinvention and rediscovery (Cash, 2018; Gregor & Hevner, 2013; Le Masson, Dorst, & Subrahmanian, 2013). Accordingly, design activities in the context of DSR can be described as a search process leading to the emergence of useful solutions (Hevner et al., 2004; Simon, 1996). The main aim of DSR as a problem solving paradigm is thus constituted by seeking utility in favor of searching for the best or optimal design that, in turn, is often intractable for realistic information systems problems (Hevner et al., 2004). Hence, the design of useful solutions in design-oriented research demands for knowledge creation to be grounded in useful knowledge that is accumulated at the intersection of applicable knowledge bases (Barquet, Wessel, & Rothe, 2017; Drechsler & Hevner, 2018). Understanding the underlying premises of knowledge creation (Baskerville et al., 2015) is thus contingent on understanding the activities of consuming and producing knowledge via DSR (Gregor & Hevner, 2013). Drawing on Mokyr (2002), two major genres of inquiry contribute to knowledge creation (Baskerville et al., 2015; Drechsler & Hevner, 2018). Science-oriented research activities primarily deal with the growth of descriptive or propositional knowledge (denoted Ω) that encompasses the “what” knowledge about natural, artificial and human phenomena, together with underlying laws, regularities as well as relationships among them (Baskerville & Pries-Heje, 2010; Gregor & Hevner, 2013; March & Smith, 1995). Classifying, observing, measuring, and cataloging allows for these descriptions to be made accessible to the human mind (Barquet et al., 2017; Nagel, 1979). Design-oriented research activities primarily focus on the emergence of prescriptive or artifact knowledge (denoted Λ) that embodies the “how” knowledge of human-built artifacts that belong to the science of the artificial (Baskerville et al., 2015; Chandra, Seidel, & Gregor, 2015; Gregor & Hevner, 2013; Mandviwalla, 2015; Simon, 1996).

The Roles of Knowledge and Knowledge Bases

47

An addition of knowledge to Ω encompasses the discovery of new facts or laws that had always existed but had not been understood and described until now, whereas contributions to Λ typically comprise knowledge about technological innovations that can be useful for individuals, organizations, and society or provide the ground for future technological innovations (Drechsler & Hevner, 2018; Gregor & Hevner, 2013). This accumulation of knowledge then leads to the growth of both, Ω and Λ knowledge bases, which, in turn, provide the raw materials through which DSR is accomplished (Hevner, 2007; Hevner et al., 2004; Owen, 1998). In the context of design-oriented research projects, utilizing the knowledge in both knowledge bases together is deemed as crucial for the emergence of novel valuable knowledge contributions (Briggs & Schwabe, 2011; Drechsler & Hevner, 2018; Niederman & March, 2012; Nunamaker, Jr. & Briggs, 2011). Hence, inquiries in DSR may consume knowledge from these knowledge bases, combine applicable foundations and methodologies (Hevner et al., 2004), produce novel knowledge, and contribute to or induce the flow between Ω and Λ knowledge bases (Beck, Weber, & Gregory, 2013; Gregor & Hevner, 2013). Grounded in this view, descriptive knowledge from the knowledge base might inform prescriptive knowledge contributions, e.g., when explanatory statements are combined with goals into prescriptive statements (Goldkuhl, 2004) or when little is known about a certain phenomena and classification schema or taxonomies (Gregor, 2006) prompt future research (Barquet et al., 2017).

48

3

Research Method: Consuming and Producing Knowledge

The Nexus of Artifacts and Design Theories as Knowledge Contribution

In a broader sense, the outcome of an inquiry in DSR is design science knowledge (Vaishnavi & Kuechler, 2015). However, from a more narrow view, this conceptualization leaves room for the demarcation of two major schools of thought with different foci (Deng & Ji, 2018), represented by a pragmatic-design camp (Hevner & Chatterjee, 2010; Hevner et al., 2004; March & Smith, 1995; Nunamaker Jr., Chen, & Purdin, 1991) and a design theory-camp (Gregor & Jones, 2007; Kuechler & Vaishnavi, 2008; Markus et al., 2002; Walls, Widmeyer, & El Sawy, 1992). The pragmatic-design camp posits that artifacts are the core outcome of DSR, with design theory at most being one type of artifact (Baskerville et al., 2018; Deng & Ji, 2018). In this vein, March & Smith (1995), define four types of artifacts: constructs, models, methods, and instantiation. Among them, instantiations, in their role as a physical realization of an artifact in its environment, are of particular importance, since they operationalize underlying constructs, models, and methods, together with demonstrating and validating their feasibility and effectiveness. This view allows for an instantiation preceding the complete articulation of underlying constructs, models, and methods in favor of designing a solution that is innovative and valuable. Theories, however are preserved for natural science and behavioral science in this context, which is why they are not acknowledged as an outcome of DSR according to the pragmaticdesign camp (Deng & Ji, 2018; Hevner et al., 2004; March & Smith, 1995). The design-theory camp, in turn, positions design theories (including both nascent design theories as well as well-developed design theories) as key contribution of DSR, while regarding instantiations, i.e., material artifacts, as the only artifact to be acknowledged. Abstract artifacts such as constructs, models, methods, design principles, and technical rules are conceptualized as part of nascent design theories (Deng & Ji, 2018). In this context, the structural nature of theories relevant in the realms of DSR is to be shed light on. Among the theory categories conceptualized by (Gregor,

The Nexus of Artifacts and Design Theories as Knowledge Contribution

49

2006) theory for design and action (type 5 theory) is contingent on the interplay of theories for analyzing (type 1), explaining (type 2), predicting (type 3), and explaining and predicting (type 4) and encompasses explicit prescriptions (e.g., methods techniques, principles of form and function) for constructing an artifact. As such, theory for design and action embodies prescriptive statements in terms of how to do something (Gregor, 2006). In more detail, theory for design and action can be expressed by means of distinct constituents that allow for specifying and communicating underlying design principles. Building on extant work on basic components of design theories (Dubin, 1978; Simon, 1996; Walls et al., 1992), Gregor & Jones (2007) propose eight components, i.e., (1) purpose and scope, (2) constructs, (3) principles of form and function, (4) artifact mutability, (5) testable propositions, (6) justificatory knowledge, (7) principles of implementation, (8) expository instantiation, trough which a design theory can be articulated in a structured manner, together with emphasizing the potential importance of instantiations for the purposes of theory representation or exposition (Gregor & Jones, 2007). Thus, taking the notion of instantiations in both camps into particular account, a potential convergence between the two camps can be held out in prospect (Deng & Ji, 2018). In fact, artifacts and design theories can be regarded as two sides of the same coin (Baskerville et al., 2018). The demonstration of a novel artifact can be a knowledge contribution in itself that embodies design ideas and theories yet to be articulated, formalized and fully understood. Thus, it can be argued that the design of artifacts precedes the development of nascent design theories as a natural sequence of activities in a DSR project. Once the artifact is realized and evaluated in context, the focus of inquiry might shift to reflect and generate design principles for broader impacts of the embedded artifact knowledge to a wider range of applications (Baskerville et al., 2018). This design theorizing (Gregor, 2009) then provides the ground for the development of a theory for design and action (Gregor, 2006) – a desirable goal in the context of DSR in terms of supporting longitudinal research goals that foster the maturation of a welldeveloped, consistent body of knowledge (Baskerville et al., 2018; Gregor & Hevner, 2013; Nagel, 1979).

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4

Research Method: Consuming and Producing Knowledge

The Research Design and Intended Contributions

Reverting to the research objective of this dissertation, the main aim is to produce knowledge contributions that are promising to be incorporated in a coherent body of knowledge for engineering service systems in the digital age. Hence, the overarching research question, i.e., “How can design knowledge for engineering service systems in the digital age be developed toward a consistent body of design knowledge?” is answered by acknowledging the nexus of knowledge consumption and production as catalyst for knowledge creation (Baskerville et al., 2015; Gregor & Hevner, 2013) as elaborated on above. In more detail, a continuum of knowledge contributions is dealt with, ranging from the development of certain artifacts (Hevner et al., 2004; March & Smith, 1995) to explicating more general prescriptions of guidelines for further artifacts of the same type (Gregor & Jones, 2007; Markus et al., 2002). Hence, in the course of answering the research question stated for the distinct studies contained in this dissertation, knowledge contributions are produced accumulatively in order to allow for explicating the foundations of an emergent design theory (Gregor, 2006; Gregor & Jones, 2007) as an answer to the overarching research question. Following Gregor & Hevner (2013), when research expressed in according terms, with more explanation, more precision, more abstraction, and more testing of beliefs facilitated, then a move can be made toward a more mature and well-developed body of knowledge on engineering service systems in the digital age (Gregor & Hevner, 2013; Nagel, 1979). Against this backdrop, light is shed on the research design that addresses the main research objective of this dissertation in the following. For the sake of clarity, the presentation of the research design is structured according to the subset of research question presented above, albeit with a rather representative intent. An overview is depicted in Table 1. Details on the distinct research methods applied within the studies are provided in the respective sections.

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51

Table 1. Overview on Research Design Overarching research question:

How can evidence-based design knowledge for engineering service systems in the digital age be developed toward a consistent body of design knowledge? Study 1

Research Question

How can design knowledge relevant for engineering service systems in the digital age be structured in a meaningful way? Method •

Systematic literature review (vom Brocke et al., 2009); Analysis of 1.703 articles and extraction of 48 articles.

•

Method for taxonomy development (Nickerson et al., 2013); Classification of knowledge contributions along 33 characteristics.

Contribution Model for the demarcation of relevant prescriptive knowledge and the

identification of prospective inquiries. Study 2

Research Question

Which mechanisms leading to enhanced resource densities can be identified among digitally enabled service systems? Method Exploratory qualitative multiple case study; Data collection from 13 semi-structured interviews among SMEs from German manufacturing industry. Contribution Principles of function as part of a method for enhancing resource densities in digitally enabled service systems.

52

Study 3

Research Method: Consuming and Producing Knowledge

Research Question

How can digitally enabled service systems be developed systematically and in a structured manner? Method •

Pragmatic-design DSR approach (Hevner et al., 2004); Grounding of initial artefact design in requirements derived from justificatory knowledge.

•

Human Risk & Effectiveness evaluation strategy (Venable et al., 2016); artificial evaluation guided by criteria-based analysis naturalistic evaluation among five focus groups

Contribution Method that ingrains principles of form and function for the systematic

and structured development of service systems. Study 4

Research Question

How can generalizable guidelines for engineering digitally enabled systems be produced and communicated by means of a digital tool? Method Design-theory DSR approach (Sonnenberg & vom Brocke, 2012b); Alternating design and evaluation of expository instantiation among four evaluation episodes with participants from four organisations. Contribution Instantiation (pragmatic-design worldview) that ingrains insights for actionable trade-offs and expository instantiation (design-theory worldview) that assists with communication of accumulated prescriptive knowledge. Study 1 addresses the research question of how design knowledge relevant for engineering service systems in the digital age can be structured in a meaningful way (RQ1).

The Research Design and Intended Contributions

53

Following the assumption that little is know about the phenomena underlying the engineering of digitally enabled service systems (Gregor & Hevner, 2013), a taxonomy is developed that prompts future design-oriented research in general (Barquet et al., 2017; Gregor, 2006) and, in particular, provides insights for the further development of design knowledge within the scope of this dissertation. Put simply, this study aims for bringing order to extant design knowledge that is deemed relevant for engineering digitally enabled services systems. Against this backdrop, this study utilizes the approach for conducting a systematic literature review set out by vom Brocke et al. (2009) to extract promising prescriptive knowledge contributions from various research endeavors, which are then classified by means of the taxonomy development method introduced by Nickerson et al. (2013). The first contribution towards the maturation of a body of knowledge for engineering service systems in the digital age is thus a model (Gregor & Hevner, 2013; March & Smith, 1995) that allows for the demarcation of relevant prescriptive knowledge, together with providing insights on inquiries to be considered in the further course of this dissertation. Study 2 deals with the research question of which mechanisms leading to enhanced resource densities can be identified among digitally enabled service systems (RQ 2). This study is grounded in the view that knowledge creation is contingent on the evolution of knowledge contributions in the interplay of knowledge production and consumption among Ω and Λ knowledge bases. Thus, discovering new facts or laws that had not been understood and described until now, provides the ground for developing prescriptive knowledge that addresses the phenomena under investigation (Gregor & Hevner, 2013). When combined with design-oriented goals, descriptive knowledge from the Ω knowledge base then can be further developed toward prescriptive knowledge in accordance with the problem-solving philosophy of DSR (Goldkuhl, 2004; March & Storey, 2008). In order to understand the generative patterns (Eck & Uebernickel, 2016) of innovation in service systems induced by digitally enabled generativity, this study applies a holistic multiple case study approach (Yin, 2003) among 13 firms that are concerned with the introduction of novel service-oriented offerings. With the aim to acknowledge the special nature of service systems (Böhmann et al., 2014a; Maglio et al., 2009), the notion of resource density (Lusch & Nambisan, 2015; Lusch et al., 2010; Normann, 2001) is utilized to understand the generative

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mechanisms (Henfridsson & Bygstad, 2013) underlying digitally enabled generativity in service systems. By combining these generative mechanisms with the prescriptive goal of enhancing resource density in service systems, a foundation for the development of applicable prescriptive knowledge that deals with a system’s generative properties is provided (Eck & Uebernickel, 2016; Goldkuhl, 2004). The second knowledge contribution is thus constituted by principles of function as part of a method (Gregor & Hevner, 2013; Gregor et al., 2013) that provide the instructions for performing the goal driven activity of supporting the engineering of digitally enabled service systems by considering the underlying notions of generativity in the context of these systems through the lens of the concept of resource density. Study 3 elaborates on how digitally enabled service systems can be developed systematically and in a structured manner (RQ 3). This study is grounded in the view that the artifact precedes the development of nascent design theories in order to allow for longitudinal reflections on its design principles for a wider range of applications in the aftermath (Baskerville et al., 2018). Thus, in accordance, with the design-pragmatic camp (Hevner et al., 2004; March & Smith, 1995; Nunamaker Jr. et al., 1991), the development of a method is at the core of this study. Hence, with the aim to produce an artifact as main outcome of this DSR inquiry at the expense of theorizing on principles inherent in its design (Baskerville et al., 2018), the development of the method is characterized by a focus on rather formative than summative development activities (Venable, Pries-Heje, & Baskerville, 2012). This is reflected in the Human Risk & Effectiveness evaluation strategy according to Venable et al. (2016) that is applied to evaluate the design of the artifact in early stages of its development. Along these lines, the initial design of the artifact is grounded in an understanding of DSR as set out by Hevner et al. (2004) and addresses design requirements that are governed by foundations that deal with the notion of digitally enabled service systems. The resulting method is then evaluated along a evaluation trajectory that combines an artificial-formative evaluation together with four cycles of naturalistic-formative evaluation settings under consideration of a set of dedicated evaluation criteria (Peffers et al., 2012; Prat et al., 2014, 2015; Sonnenberg & vom Brocke, 2012b; Venable et al., 2016). Concerning the contribution of this study to the overall research objective of the dissertation, a formatively evaluated method that embodies valuable prescriptive

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knowledge is acknowledged as central outcome (Gregor & Hevner, 2013; Hevner et al., 2004; March & Smith, 1995). Study 4 is concerned with the research question of how design knowledge for engineering digitally enabled service systems can be produced and communicated in ways that allow for prescribing generalizable guidelines (RQ 4). This study represents the motivation of this dissertation to acknowledge the longitudinal goals of DSR in terms of reflecting on the knowledge contributions produced up to this point in ways that allow for generalizable prescriptions for the development of further artifacts in which this knowledge is ingrained (Baskerville et al., 2018). Grounded in the design-theory school of thought, an expository instantiation (Gregor & Jones, 2007) is developed that, on the one hand, addresses design implications derived from the formative evaluation conducted beforehand, and, on the other, provides the ground for assisting with the communication and exposition of generalizable principles inherent in the design of artifacts that support the engineering of service systems in the digital age. The development of this artifact as well as the documentation of the underlying design knowledge is guided by alternating design and evaluation loops in accordance with the build-evaluate patterns introduced by Sonnenberg and vom Brocke (2012). Based on this evaluation strategy, four build-evaluation episodes are gone through, with each episode focusing on different aspects of the artifact. By reasoning about the artifact in both, the interior mode and the exterior mode (Gregor, 2009), truth-like statements about the prescriptive knowledge ingrained in it is produced while it emerges throughout its development (Iivari, 2007; Sonnenberg & vom Brocke, 2012b). Therefore, the knowledge contribution of this study encompasses an expository instantiation (Gregor & Jones, 2007) that provides the ground for discussing prescriptive knowledge contributions with truth-like value for a prospective body of knowledge on engineering service systems in the digital age. Ultimately, the knowledge contributions that are produced by means of the interplay of research approaches applied within the studies allow for the prescription of guidelines of novel artifacts that enable or support the engineering of real-world service systems that permeate our society (Böhmann et al., 2014a). As a move toward a more mature and well-developed body of knowledge for engineering service systems

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in the digital age, these guidelines are presented along the components of a design theory as introduced by Gregor & Jones (2007). Thus, the overall contribution of this dissertation is the development and abstraction of design knowledge for artifacts that support the development of digitally enabled service systems. By that, a possible starting point for the emergence of a theory for design and action (Gregor, 2006) that acknowledges underlying principles in this problem context is provided for future research avenues.

IV Knowledge Creation: Advancing Design Knowledge

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_4

Study 1: Bringing Order to Design Knowledge – A Taxonomy

1

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Study 1: Bringing Order to Design Knowledge – A Taxonomy

Digitally enabled generativity leads to novel forms of resource integration, thus providing the foundation for innovative service systems that permeate our society in the digital age. Research on service systems engineering (SSE) fosters the systematic design and development of these complex systems and calls for design knowledge that stems from real-world applications. Promising knowledge contributions are rooted in interdisciplinary research fields, albeit exhibiting diverging conceptualizations of premises underlying the notions of SSE and digitally enabled generativity. In DSR, rigor is predominantly achieved by appropriately applying existing foundations and methodologies in the course of developing novel artifacts that embody useful design knowledge for solving a problem (Hevner, 2007; Hevner et al., 2004; Iivari, 2007). As Iivari (2007, p. 52) states, “it is not enough for the artifact just to come out of the blue”. Against this backdrop, Study 12 reports on the development of a taxonomy that provides a foundation to structure and classify extant knowledge contributions for engineering novel service systems in the digital age among various research fields. The development of the taxonomy is guided by rigorous approaches for identifying relevant contributions from extant research in the literature (vom Brocke et al., 2009) and classifying them according to applicable characteristics (Nickerson et al., 2013). The resulting classification is discussed in terms of knowledge contributions valuable for providing a foundation for delineating research directions that deal with designoriented knowledge for digitally enabled service systems. This study contributes to existing knowledge in terms of developing a taxonomy that addresses the issue of how design knowledge for engineering service systems in the digital can be classified, thus fostering the understanding of the field and providing suggestions for future research

2 An earlier version of this research has been under review for the special issue on Service Systems Engineering in Business & Information Systems Engineering (BISE) 05/2018. The current version thoroughly ingrained the feedback from experienced senior scholars gathered throughout the review process.

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avenues to researchers that deal with the engineering of novel service systems stemming from the opportunities unleashed by digitally enabled generativity in service systems. By that, a demarcation of extant prescriptive knowledge contributions relevant for engineering digitally enabled service systems is achieved, which, in turn, allows for prescribing foci of inquiry to be addressed in further research endeavors. Thus, this study contributes to the overall objective of the dissertation in terms of fostering the understanding of the field and paving the way for novel knowledge contributions to be produced in the further course of the dissertation. The remainder of this study proceeds as follows. First, an introduction to the problem context is provided, together with elaborating on the research objective guiding this study. The theoretical foundations underpinning the design of the taxonomy are described in the next section. Afterwards, the research approach for the development of the taxonomy is introduced. Next, the taxonomy as a whole as well as its content and structure are presented. Subsequently, the characteristics of the contributions incorporated in the taxonomy are discussed, together with deriving implications for future research on design knowledge from real-world applications in the field of SSE. The study ends with a summery and conclusion, incorporating implications for future research.

1.1

Purpose and Scope

Research on SSE (Böhmann et al., 2014a) recognizes service as a collaborative process among multiple stakeholders that creates context-specific value (Edvardsson et al., 2011; Vargo & Lusch, 2004). SSE further adopts a systems perspective as a way of thinking for understanding service and service innovation (Alter, 2011, 2012; Maglio et al., 2009). Thus, SSE takes the service system as the basic unit of analysis and aims to introduce more precise models of service systems that are attuned to design and operations. Central research challenges in SSE deal with issues in the context of engineering service architectures, engineering service systems interactions, and engineering resource mobilization (Böhmann et al., 2014a). However, the context of digitally enabled generativity demands for approaches that bridge the boundaries of tangible and intangible resources and address new forms of resource bundling and

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service provision that arise from the conjunction of machine intelligence with human intelligence. Hence, there is a need for design knowledge from interdisciplinary research in order to foster the systematic design and development of according service systems (Böhmann et al., 2014a). Against this backdrop, Ostrom et al. (2015) call for research focused on evolving systems engineering approaches for developing services with the aim to integrate Information Systems (IS) expertise with other aspects of service design. As a consequence, service related contributions from interdisciplinary fields have to be taken into account in order to advance design knowledge for service systems (Fielt et al., 2013). However, the notion of service and service systems has been characterized in different disciplines and by different authors from various points of view (Nardi et al., 2015) which increases the complexity of research in the area of SSE. In this vein, Alter (2008) states that “Even if different communities of practice can do fine with their own somewhat inconsistent views of service, conflicting views of service surely cannot facilitate effective communication between business and IT practitioners and between business and computer science researchers” (Alter 2008, p.3). Against this backdrop, Alter (2008) concludes that conflicting views of service constitute an obstacle for the development of a new science of services as postulated by Chesbrough and Spohrer (2006). Although Böhmann et al. (2014a) conclude that the emergence of a separate discipline of service science is not to be expected in the near future, a growing awareness of service-related contributions across disciplinary boundaries as well as increased openness for interdisciplinary work related to service research can be observed (Fielt et al., 2013, Böhmann et al., 2014). This, in turn, leads to the need of a basis for communication, consensus and alignment of the various approaches and perspectives underlying the notion of service (Nardi et al., 2015). Hence, with the aim to produce prescriptive knowledge that addresses the engineering of digitally enabled service systems, it can be regarded as pivotal to provide a common ground for characterizing and structuring potentially valuable contributions from and across heterogeneous disciplines. Guided by the notion that prescriptive knowledge ingrained in artifacts or explicated in design theories does not come “out of the blue” (Iivari, 2007), the purpose of this study is thus to identify and systematize potentially relevant design knowledge for engineering digitally enabled service systems as a foundation to gather insights on the demarcation of valuable prospective knowledge

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contributions that are subject to knowledge creation inquiries in the further course. Accordingly, the following research question is drawn: How can design knowledge relevant for engineering service systems in the digital age be structured in a meaningful way? This research objective is addressed by developing a taxonomy according to the taxonomy development method proposed by Nickerson et al. (2013) and deriving research opportunities based on various research gaps and according research opportunities revealed by the taxonomy (Rowe, 2014; Schryen, 2015; Schryen et al., 2017; Webster & Watson, 2002). The objects of interest for the taxonomy, i.e., relevant contributions from the literature, were identified by applying the approach for systematic literature reviews by vom Brocke et al. (2009). By developing a model that supports the classification of design knowledge for engineering service systems in the digital age, the understanding of the domain is fostered and a contribution to the knowledge base dealing with the engineering of digitally enabled service systems is made. Moreover, the call of SSE for research on design knowledge for systems that permeate our society is addressed (Böhmann et al., 2014a).

1.2

Background

SSE calls for research on service from a systems perspective (Alter, 2011, 2012; Maglio et al., 2009), thus focusing on the systematic design and development of service systems (Böhmann et al., 2014a). However, especially service systems in the digital age are hard to delineate, complex by nature, and include not only data and physical components, but also layers of knowledge, communication channels, and networked actors. This places the onus on SSE to advance knowledge on models, methods, and artifacts that enable or support the engineering of these intangible systems. Such knowledge types per se favor design-oriented research approaches that contribute design knowledge from real-world applications (Böhmann et al., 2014a) and acknowledge the underlying premises of digitally enabled generativity (Lusch & Nambisan, 2015; Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010).

Study 1: Bringing Order to Design Knowledge – A Taxonomy

1.2.1

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Characterization and Positioning of Design Knowledge

The notion of design knowledge to be rooted in the design, implementation, and evaluation of real-world service systems constitutes a central concept in the field of SSE (Böhmann et al., 2014a). This is in line with the paradigm of DSR that concentrates on understanding the context of organizational phenomena and creating and evaluating artifacts that solve organizational problems (Hevner et al., 2004). Whereas descriptive knowledge provides the theoretical bases for the design of practical and useful artifacts, prescriptive knowledge is conceptualized as the knowledge on “how to do something” (Gregor & Hevner, 2013; Simon, 1996) and can thus be considered as knowledge contribution relevant for advancing design knowledge for engineering service systems in real-world contexts. Hence, prescriptive knowledge is at the core of the artifact designed and can be classified according to five dimension (Gregor & Hevner, 2013): constructs, models, methods, instantiations, and design theory. Constructs provide the vocabulary and symbols used to define and understand problems and solutions; models constitute designed representations of the problem and possible solutions; methods provide the instructions for performing goal-driven activities; instantiations are physical realizations that act on the natural world (Gregor & Hevner, 2013; March & Smith, 1995). A design theory is an abstract, coherent body of prescriptive knowledge that describes the principles of form and function, methods, and justificatory theory that are used to develop an artifact or accomplish some end (Gregor, 2006; Gregor & Hevner, 2013; Gregor & Jones, 2007). Further on, in order to understand and position the knowledge contribution constituted by designing an artifact according to the premises of DSR, its novelty can be assessed. Therefore, Gregor and Hevner (2013) propose a framework that allows for characterizing knowledge contributions along the dimensions of application domain maturity and solution maturity. Hence, routine design applies known solutions to known problems, improvement refers to the development of novel solutions to known problems, exaptation can be characterized by applying known solutions to new problems, and invention requires novelty of both the problem and the solution (Gregor & Hevner, 2013).

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1.2.2

Knowledge Creation: Advancing Design Knowledge

Digitally Enabled Generativity and Digital Technology

A necessary but not sufficient condition for innovation in digitally enabled service systems is that novel configurations of resources rely on digitization, i.e., the technical process of encoding analog information into a digital format (Tilson et al., 2010; Yoo, 2010). However, it is predominantly the socio-technical processes accompanying such digitization that open up rather disruptive innovation opportunities (Lusch & Nambisan, 2015; Nambisan, 2013; Tilson et al., 2010), thus constituting the sufficient condition for innovation in digitally enabled service systems. The according forging of novel socio-technical assemblages is particularly enforced by continuing developments of digital technology (Barrett et al., 2015; Eaton et al., 2015; Yoo et al., 2012). In this vein, Yoo et al. (2010) argue that the emergence of digital technology has made novel forms of generative innovation possible (Eaton et al., 2015; Herterich & Mikusz, 2016; Lusch & Nambisan, 2015). In more detail, combined with the rapid diffusion of personal computers and the Internet, the layered nature and unique characteristics of digital technology have brought unprecedented levels of generativity (Barrett et al., 2015; Yoo et al., 2012, 2010). The generativity unleashed by digital technology can then be defined as digitally enabled generativity (Cecez-Kecmanovic et al., 2014; Yoo, 2013) that allows innovation to extend beyond the original initiator and purpose, together with inducing outcomes that are unanticipated and self-reinforcing (Fielt & Gregor, 2016; Zittrain, 2006, 2008). Accordingly, the degree of resource integration in digitally enabled service systems is contingent on the affordances of the digital technology incorporated within the service system (Lusch & Nambisan, 2015). In this context, Nambisan (2013) presents a framework that describes the two primary roles of digital technology for innovation. In its more traditional role, digital technology might manifest itself as a resource that an actor acts on to obtain support for executing a task. To the contrary, in its role as driver of generativity, digital technology acts on other resources to produce effects; that is, it acts or operates on other things rather than being operated on (Nambisan, 2013; Vargo & Lusch, 2004). For the latter, Lusch and Nambisan (2015) envision digital technology to seek out and pursue unique resource integration opportunities on their own by mining data on and creating bridges across diverse resources to discover novel opportunities. In more detail, Nambisan (2013) divides the roles of digital technology into digital components and digital tools that either have an impact on the innovation

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process or the innovation outcome. Based upon that, four roles of digital technology for innovation in digitally enabled service systems can be distinguished. Digital components in their role as an innovation trigger reflects the generativity that can potentially be unleashed by new digital technology; digital components in their role as an innovation enabler envisions the support functionality that digital components can provide in service innovation; digital tools in their role as an innovation trigger relates to how digital tools can initiate or lead to new innovation processes or associated organizational routines and mechanisms; digital tools in their role as an innovation enabler refers to the assumption that the use of digital tools can enhance the efficiency and effectiveness of development activities (Nambisan, 2013). Hence, with the notion of digitally enabled generativity being contingent on the roles of digital technology, understanding their capabilities and how they contribute to resource integration and reconfiguration in service systems is crucial in the course of engineering novel digitally enabled service systems.

1.3

Research Method

As stated by Nickerson et al. (2013), taxonomies can help to bring order to complex areas of research by explaining similarities as well as differences among objects of interest and thus provide the foundation for the identification of future research fields. Guided by this notion, this study develops a taxonomy for classifying extant design knowledge for engineering novel service systems in the digital age. For the sake of a rigorous research design, the well-established method for taxonomy development by Nickerson et al. (2013) is applied. The objects of interest, i.e., knowledge contributions promising to provide applicable design knowledge, were identified in extant literature by applying the literature research method presented in vom Brocke et al. (2009). The taxonomy resulting from applying the taxonomy development method describes and classifies these objects of interest and thus provides the utility to help researchers to understand the domain. Hence, in the following sections, the procedures for examining, i.e., conducting a systematic literature review, and classifying applicable contributions, i.e., developing a taxonomy, are described.

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1.3.1

Knowledge Creation: Advancing Design Knowledge

Systematic Literature Review

The systematic literature review was conducted by applying the methodological guidelines for systematic literature reviews set out by vom Brocke et al. (2009) since they are both rigorous and equally possess a degree of flexibility that is promising for effectively analyzing contributions from various fields of research (Frost & Lyons, 2017), thus dealing as suitable approach to identify interdisciplinary work embodying relevant design knowledge for engineering novel digitally enabled service system (Böhmann et al., 2014a) and creating a solid starting point for all other members of the academic community that are interested in the topic (Mulrow, 1987; Paré, Trudel, Jaana, & Kitsiou, 2015; Pfeffer & Sutton, 2006). As such, the systematic literature review goes beyond merely assembling and describing past work by identifying and highlighting knowledge gaps between what is known and needs to be known. It thus can be conceptualized as theoretical review (Paré et al., 2015). The method applied depicts dedicated phases for conducting a systematic literature review (vom Brocke et al., 2009): (phase I) scoping the review, (phase II) conceptualizing the topic, (phase III) searching the literature, (phase IV) analyzing and synthesizing the findings of the literature search, and (phase V) delineating relevant research opportunities and directions from the review. As recommended by vom Brocke et al. (2009), the scope of the review (phase I) at hand is characterized based upon the taxonomy of literature reviews proposed by Cooper (1988) which comprises the dimensions (1) focus, (2) goal, (3) organization, (4) perspective, (5) audience, and (6) coverage. The taxonomy to be developed deals with the classification of design knowledge for engineering novel service systems in the digital age. As illustrated in Table 2, identifying this kind of knowledge contributions requires combining the suggested (1) foci in order to identify relevant objects of interest, i.e., papers from extant literature. By that, papers are acknowledged that deal with research outcomes, e.g., the evaluation of a design method for service systems, research methods, e.g., design science research as inherently design-oriented research approach for engineering service systems, theories, e.g., design theories for service systems, and applications, e.g., the application of a design method for engineering service systems. Hence, the (2) goal of the review is constituted by identifying central

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issues concomitant with the topic of design knowledge for engineering novel service systems in the digital age. The (3) organization of the results is conceptual, thus aiming for grouping works relating to the same abstract ideas together in order to prearrange a structure for the taxonomy to be developed in the further course. Guided by the underlying premises of taxonomy development, the (4) perspective taken for reviewing the literature is neutral and allows for distilling relevant works and allocating them to different categories. Against the backdrop of fostering interdisciplinary contributions in the field of SSE, not solely specialized scholars but also a (5) broader audience, i.e., general scholars are addressed. The (6) coverage of the review is representative rather than exhaustive, thus seeking to achieve a demarcation of relevant prescriptive design knowledge instead of aiming for an exhaustive, comprehensive awareness of all literature relevant recent literature on service systems or digitally enabled generativity. Table 2. Scope of the Systematic Literature Review Characteristic (1) Focus

Categories Research Outcomes

Research Methods

Theories

(2) Goal

Integration

Criticism

(3) Organization

Historical

Conceptual

(4) Perspective

Neutral Representation

Applications Central Issues Methodological

Espousal of Position

(5) Audience

Specialized Scholars

General Scholars

Practitioners/Politicians

General Public

(6) Coverage

Exhaustive

Exhaustive and Selective

Representative

Central/Pivotal

The conceptualization of the topic (phase II) is informed by the theoretical foundations provided above. Building on these foundations, the topic of design knowledge for engineering novel service systems in the digital age deals with knowledge contributions that stem from real-world problem solving situations (Gregor & Hevner, 2013) and are promising to address both, the challenges concomitant with engineering service systems (Böhmann et al., 2014a) from a systems perspective (Alter, 2011, 2012; Maglio et al., 2009) and the role of digital technology as a potential driver for digitally enabled generativity (Lusch & Nambisan, 2015; Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010). Grounded in the normative theory of citing behavior (Baldi, 1998; Stewart, 1983), the literature search process (phase III) was guided by a three step forward search approach. This normative perspective of citing behavior defines a citation as an

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acknowledgement of the intellectual use of other authors’ work. Hence, citations represent an intellectual or cognitive influence of the cited paper on the citing paper (Baldi, 1998; Stewart, 1983; Wagner, Prester, & Schryen, 2017). The aim of the systematic literature review is to identify representative works that provide a foundation for the demarcation of prescriptive knowledge contributions relevant for the objective of engineering digitally enabled service systems. Against this backdrop, the literature research process for achieving the intended coverage started off with (step 1) selecting papers that cite the paper for SSE by Böhmann et al. (2014a) in order to identify papers that dedicatedly intended to contribute to this field of research. With the aim to acknowledge knowledge contributions from literature that does not explicitly contribute to SSE but is grounded in a similar worldview, papers that follow the proposal “that research on service should adopt a systems perspective” (Böhmann et al., 2014, p. 74) in the vein of Maglio et al. (2009) and Alter (2011, 2012) – papers explicitly cited by Böhmann et al. (2014a) – were further incorporated (step 2). Further on, papers were selected that deal with the notion of digital technology as a driver for digitally enabled generativity. Hence, papers citing Tilson et al. (2010) were added. In this context it is to be mentioned that, although Yoo et al. (2010) provide valuable insights on the role of digital technology and generativity for innovation in general, Tilson et al. (2010) acknowledge the premises of according socio-technical phenomena in more depth, which is why papers citing this article are deemed to encompass a more multifaceted view on the role of digital technology as a driver for digitally enabled generativity. Moreover, this sample is complemented by papers referring to contributions that further elaborate on this conceptualization (Barrett et al., 2015; Lusch & Nambisan, 2015; Nambisan, 2013), thus providing promising viewpoints for characterizing the role of digital technology in the context of engineering service systems in the digital age. Google Scholar was used as scholarly database to identify articles with an applicable citation behavior since pretests with common databases such as EBSCOhost, Scopus and Proquest provided evidence that pivotal journals in the area of research on service systems, e.g., “Service Science”, are not incorporated in their respective catalogues. However, these databases provide functions to exclude non-scientifical contributions which is why they were used to assess the quality of papers identified via Google Scholar on a sample base. Articles were excluded if they

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did not adhere to the following inclusion criteria: (1) written in English; (2) published in a peer-reviewed scholarly journal or conference proceeding; (3) available in full text; (4) contributing to the field of SSE or/and conceptualizing service systems in the vein of Maglio et al. (2009) and Alter (2011, 2012), or dealing with the underlying premises of digital technology as a driver for digitally enabled generativity according to Tilson et al. (2010) or further applicable contributions building on this notion (Barrett et al., 2015; Lusch & Nambisan, 2015; Nambisan, 2013) in accordance with the normative theory of citing behavior (Baldi, 1998; Stewart, 1983), that is, by citing applicable references; (5) exhibiting design-oriented research approaches as proposed by Böhmann et al. (2014a). According to vom Brocke et al. (2009), after collecting sufficient literature on a topic, it has to be analyzed and synthesized (phase IV). In the context of the study at hand, this is accomplished by developing the taxonomy described in the further course. Further on, based upon this taxonomy, directions for future research can be derived (phase V). 1.3.2

Taxonomy Development

Addressing the necessity to analyze the body of literature emerging from the systematic literature review in a structured way, vom Brocke et al. (2009) suggest compiling a concept matrix (Webster & Watson, 2002) which subdivides topic-related concepts into different units of analysis. This then allows for arranging, discussing, and synthesizing prior research (vom Brocke et al., 2009). However, neither Webster and Watson (2002) nor vom Brocke et al. (2009) provide insights into the concrete process of creating concept matrices. Along these lines, Wolfswinkel et al. (2013) call for more precision and analytical rigor in the course of creating a thorough review, thus raising the necessity for even more explicitness and care in underlying process stages (Wolfswinkel et al., 2013). Hence, with the aim to analyze and synthesize the identified knowledge contributions in a rigorous manner, their classification is based on the classification principles as introduced by Nickerson et al. (2013). The resultant taxonomy developed within this study is thus built on the foundational premises of a concept matrix, that is, structuring concepts along the articles identified (Webster &

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Watson, 2002), albeit concurrently acknowledging the nature of service systems and SSE as domains embodying a variety of disorderly concepts. In more detail, service systems are deemed to be hard to delineate, complex by nature and include not only data and physical components, but also layers of knowledge, communication channels and networked actors. SSE seeks to advance knowledge on models, methods, and artifacts that enable or support the engineering of service systems, thus favoring design oriented approaches (Böhmann et al., 2014a). By following the approach introduced by Nickerson et al. (2013), the complexity of the domain is addressed in terms of bringing order to it, together with providing a point of departure for designing useful, not necessarily optimal solutions that are informed by the design-oriented knowledge contributions classified within the taxonomy (Hevner et al., 2004; Nickerson et al., 2013). The papers identified in the course of the systematic literature review comprise various kinds of knowledge contributions which, from a taxonomy development point of view, constitute objects of interest that are to be classified (Nickerson et al., 2013). In order to ensure a rigorous development of the taxonomy at hand, the seven-step approach of Nickerson et al. (2013) as illustrated in Figure 4 is applied. This approach extends common taxonomy development approaches such as the one presented by (Bailey,

1994)

in

terms

of

combining

conceptualization/deduction

and

empiricism/induction strategies and providing an iterative procedure to reach a useful taxonomy. In addition to that, by including specific ending conditions that test the taxonomy during its development, this approach is consistent with the design science research paradigm described by Hevner et al. (2004) and thus aims to provide a useful, not necessarily optimal solution (Nickerson et al., 2013).

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71

Start

1. Determine Meta-Characteristics

2. Determine Ending Conditions Empirical-toconceptual

Conceptual-toempirical

3. Approach?

4e. Identify (new) subset of objects

4c. Conceptualize (new) characteristics and dimensions of objects

5e. Identify common characteristics and group objects

5c. Examine objects for these characteristics and dimensions

6e. Group characteristics into dimensions to create (revise) taxonomy

6c. Create (revise) taxonomy

No

7. Ending conditions met? Yes End

X.e.: empirical-to-conceptual X.c.: conceptual-to-empricial with 4 ≤ X ≤ 6

Figure 4. Taxonomy development method as proposed by Nickerson et al. (2013)

Following Nickerson et al. (2013), the first step in the course of taxonomy development is to identify a meta-characteristic which is based on the purpose of the taxonomy and in turn addresses the users and their expected use of the taxonomy. In this study, the meta-characteristic is derived from the research question presented above and is thus defined as design knowledge for service systems engineering in the digital age. The users of this taxonomy are specialized as well as general scholars that either aim for developing service systems in a systematic and structured way or intend to contribute design knowledge to immature research fields. The second step deals with defining ending conditions that lead the iterative development of the taxonomy (Nickerson et al., 2013). In this context, the ending conditions from Nickerson et al. (2013) were adopted with the exception of the following conditions: First, “Each cell (combination of characteristics) is unique and is not repeated (i.e., there is no cell duplication)” (Nickerson et al., 2013, p. 9) was not incorporated. This mainly stems from the nature of design-oriented research in which knowledge contributions are commonly developed in an iterative way (Hevner et al., 2004). Hence, contributions that, for instance, deal with one design science research project, can build on several papers with merely slight adjustments concerning the

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respective research aim. Second, “At least one object is classified under every characteristics of every dimension” (Nickerson et al., 2013, p. 9) was regarded as inhibiting the identification of potential future research fields which is why this condition was discarded. The third step is comprised by selecting the taxonomy development strategy (Nickerson et al., 2013). Due to the iterative nature of the method, this strategy will change several times until the ending conditions are met. Hence, in the following, the respective iterations with the fourth, fifth, sixth, and seventh steps are described in more detail. Iteration 1 In their pivotal paper on SSE, Böhmann et al. (2014a) define research challenges that call for design knowledge for engineering service architectures, engineering service systems interactions, and engineering resource mobilization. Hence, the first iteration applied a conceptual-to-empirical approach (3) and conceptualizes these challenges as dimensions according to which design knowledge addressing underlying issues can be classified. (4c). However, at this initial stage, no objects of interest, i.e., knowledge contributions from the literature review providing applicable design knowledge, have been taken into consideration which is why step 5c and 6c are skipped. By that, especially the ending condition “All objects or a representative sample of objects have been examined” (Nickerson et al., 2013, p. 9) is not fulfilled (7) which is why the next iteration was conducted. Iteration 2 The second iteration applied an empirical-to-conceptual approach (3) in order to classify the objects of interest derived from the literature review. With the aim to identify characteristics of knowledge contributions that reflect the worldview of SSE to a broad extent, solely papers citing Böhmann et al. (2014a) were taken into account at this point (4e). By creating conceptual labels based on open coding (Corbin & Strauss, 1990; Ryan & Bernard, 2003), common characteristics of the objects were identified and categorized inductively (5e) (Bailey, 1994; Nickerson et al., 2013). These characteristics were then either grouped into the existing dimensions (e.g., ‘interaction channels’ (e.g.,

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Grenha Teixeira et al., 2016) are grouped into ‘engineering service systems interactions’) or into a new dimension dealing with knowledge contributions that address business model development issues concomitant with SSE (6e). Here, especially the ending condition “All objects or a representative sample of objects have been examined” (Nickerson et al., 2013, p. 9) was not met (7). Hence, the development proceeded with the next iteration. Iteration 3 The focus of the third iteration was laid on shaping the characterization of the objects classified in the iteration above in accordance with central premises of SSE. This was due to the insight that knowledge contributions not only exhibited characteristics that could be grouped in the dimensions of design knowledge for engineering service architectures, services systems interactions, and resource mobilization, but also addressed the call by Böhmann et al. (2014a) for design knowledge on more finegrained issues associated with these broad research challenges. Hence, the third iteration applied a conceptual-to-empirical approach (3) in which new dimensions and characteristics were derived from statements in Böhmann et al. (2014a). In this context, elaborative coding was applied (Auerbach & Silverstein, 2003; Miles et al., 2014). This top-down coding approach (Auerbach & Silverstein, 2003) was utilized in order to refine the preconceived ideas presented in Böhmann et al. (2014a), thus leading to novel themes and categories. By that, characteristics of knowledge contributions, e.g., providing

design-knowledge

for

the

modularization,

standardization

or

reconfiguration issues for engineering service system, that can be grouped in subdimensions such like “Advanced Models, Methods and Tools” (Böhmann et al., 2014, p. 75) were conceptualized (4c). Based upon this conceptualization, the objects of interest were examined accordingly (5c). In a further step, the characteristics derived from the conceptual labels in the second iteration were aligned with the ones derived from the current conceptual-to-empirical approach which imposed merging and splitting dimensions and characteristics (6c). This then lead to repeating the method, since the ending condition “No dimensions or characteristics were merged or split in the last iteration” remained unfulfilled (7).

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Iteration 4 The fourth iteration made use of the empirical-to-conceptual approach (3) with the aim to incorporate the knowledge contributions provided in papers from the literature review (4e) that cited Maglio (2009), Alter (2011, 2012), Barrett et al. (2015), Nambisan (2015), Lusch and Nambisan (2015), or Tilson et al. (2010). Common characteristics were identified (5e) whereas the majority of the objects of interest could be characterized by the characteristics and dimensions derived beforehand (6e); exceptions were constituted by characteristics of knowledge contributions that, for instance, provide design knowledge for developing approaches that deal with the issue of assessing the maturity of service systems (Neff et al., 2014). Due to the fact that “new dimensions or characteristics were added in the last iteration” (Nickerson et al., 2013, p. 9), the next iteration followed (7). Iteration 5 The focus of the preceding iterations laid on characterizing knowledge contributions based upon which issues in service systems engineering they address. However, in order to also classify the type as well as novelty of the artifacts being informed by the design knowledge for engineering service systems that the identified knowledge contributions provide, applicable characteristics can be derived from (Gregor & Hevner, 2013). Moreover, the understanding of the role of digital technology in the context of digitally enabled generativity within the identified knowledge contributions can be characterized by the framework proposed by Nambisan (2013). Hence, the fifth iteration applied a conceptual-to-empirical approach (3) in terms of deriving the following dimensions with respective characteristics: (I) type of knowledge contribution with the characteristics constructs, models, methods, instantiations, and design theories; (II) novelty with the characteristics exaptation, improvement, and invention; and (III) role of digitalization with the characteristics digital component as an innovation trigger, digital component as an innovation enabler, digital tool as an innovation trigger, and digital tool as an innovation enabler. In this context, it is to be emphasized that the characterization of the ‘type of knowledge’ is alignment with the pragmatic-design camp (Hevner & Chatterjee, 2010; Hevner et al., 2004; March & Smith, 1995; Nunamaker Jr. et al., 1991). For instance, knowledge contributions that

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deal with instructions for performing goal-driven activities, i.a., algorithms, frameworks, mechanisms, architectures, approaches, design principles and processes, are all to be classified as method (Deng & Ji, 2018; Hevner et al., 2004). The objects of interest were examined for these dimensions and characteristics (5c) by which a revised taxonomy (6c) is developed. However, the condition “at least one object is classified under every characteristic of every dimension” (Nickerson et al., 2013, p. 9) is not met since characteristics such like ‘invention’ were not applicable for the sample of objects of interest (7). Based upon that, a further iteration was conducted. Iteration 6 Based on the findings from the fifth iteration, the dimensions and characteristics that were not applicable for characterizing the sample of objects of interest were discarded. Hence, in this conceptual-to-empirical approach (3), dimensions were reduced by characteristics not contributing to the classification of the sample (4c). By that, at least one object is classified under every characteristic of every dimension (5c), a revised

taxonomy could be developed (6c), and both, the objective and subjective ending conditions are met. Ultimately, after having conducted six iterations, a useful taxonomy for classifying extant design knowledge for engineering service systems in the digital age was developed.

1.4

Results

The research design to answer the research objective within this study posits identifying relevant extant design knowledge for engineering service systems in the digital age and classifying them. The former was accomplished by applying an approach for systematic literature reviews (vom Brocke et al., 2009), the latter followed the principles of taxonomy development in order to bring order to this complex area of research (Nickerson et al., 2013). In the following, the respective results are presented.

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Knowledge Creation: Advancing Design Knowledge

1.4.1

Literature Analysis

Applying the systematic literature review method proposed by vom Brocke et al. (2009) led to analyzing and selecting papers among various phases. Table 3 summarizes the numbers of papers analyzed in the course of applying the proposed literature review method (vom Brocke et al., 2009). In total, 1703 papers were initially found by applying the forward search approach described above. These papers were analyzed based upon their title and abstract. By that, a sample of 199 relevant contributions for further investigation was created. Following the inclusion criteria, a number of 68 articles was found to be integrated in the taxonomy. Ultimately, by eliminating duplicates, the number of objects of interest to be classified decreased to 48. Table 3. Literature Extraction Process

Alter (2011, 2012)

Barrett et al. (2015)

66

169

7

15

3

8

1.4.2

Forward search source Lusch and Böhmann et Maglio Nambisan al. (2014a) (2009) (2015) Forward Search 99 340 483 Title/Abstract Analysis 77 19 65 Full Text Analysis 26 10 17 Elimination of Duplicates Articles to be classified in taxonomy: 48

Sum

Nambisan (2013)

Tilson et al. (2010)

117

429

1703

6

10

199

0

5

68 48

Resulting Taxonomy

As illustrated in Table 4, the resulting taxonomy is comprised by 33 characteristics that are grouped in nine (sub-) dimensions. Each of the 48 papers from the systematic literature review can be classified by at least four characteristics. The taxonomy incorporates knowledge contributions that provide design knowledge for engineering service systems in the digital age and classifies them along their type, novelty, claims for service systems engineering, and the role of digital technology among them. This taxonomy does not have any obvious counterparts in prior literature. Frost and Lyons (2017) present a systematic literature review that deals with service systems analysis methods and components, but with a broader and less design-oriented focus. Dwivedi et al. (2014) analyze patterns of artifact generation and knowledge generation in the

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design science community, however not acknowledging the notions of service systems or SSE. The notion of digital technology as a driver for digitally enabled generativity is addressed in various contributions from literature, but rather in a descriptive or conceptual manner (e.g., Eck et al. (2015) or Herterich and Mikusz (2016)). Against the backdrop of these individually informed deficiencies, the taxonomy developed within this study constitutes a promising departure from extant approaches by integrating their underlying, yet not explicitly applicable, premises in the context of shaping design knowledge for service systems engineering in the digital age. Hence, for both, general and special scholars, a foundation for understanding the field and deriving implications for future research is provided. In the following, the findings are summarized along the dimensions of the taxonomy. Type of Knowledge Contribution In accordance with the theoretical background depicted above, design knowledge for engineering service systems that stems from real-world applications can be conceptualized as prescriptive knowledge (Gregor & Hevner, 2013) that focuses on the “systematic design and development of service systems” (Böhmann et al., 2014, p. 2). As proposed by Gregor and Hevner (2013), five types of prescriptive knowledge can be defined. These are represented to varying degrees among the knowledge contributions provided by the papers. Although one knowledge contribution can incorporate various knowledge types (Dwivedi et al., 2014), the taxonomical classification at hand is aligned with the nature of the underlying systematic literature review which is why the most representative knowledge types are exclusively emphasized in order for the taxonomy to be meaningful (Nickerson et al., 2013). (I) Constructs are represented by one contribution that proposes an ontology from a commitment perspective (Nardi et al., 2015). (II) Models are comprised of (1) frameworks dealing with service capabilities (Bärenfänger, Leveling, & Otto, 2016) or crowdfunding service configurations (Haas & Blohm, 2017; Haas, Blohm, Peters, & Leimeister, 2015); (2) taxonomies dealing with use cases of CPS (Herterich, Holler, Uebernickel, & Brenner, 2015) and according industrial service systems (Herterich, Buehnen, Uebernickel, & Brenner, 2016),

Bärenfänger et al. (2016)

x

Beverungen et al. (2011)

x

Blaschke et al. (2017)

x

Brocke et al. (2011a)

x

Brocke et al. (2011b)

Chew (2016)

x

Dörbecker and Böhmann (2015)

x

Dragoicea et al. (2016)

x

x

x

Drăgoicea et al. (2015)

x

x

x

Fischbach et al. (2011)

x

x

Gnewuch et al. (2017)

x

x

Goldschmidt et al. (2012)

x

x

Grenha Teixeira et al. (2016)

x

x

x x

x

x

x

x

x

x

x

x

x

x

x

x x

x

x

x x

x

x

x

x

x

x

x

x

x

x x

x x x

x

x

x

x

x

x

x

x

x

Digital Tools as an Enabler

Digital Tool as a Trigger

Digital Component as an Enabler

Digital Component as a Trigger

Maturity

Business Model Patterns

Business Model Alignment

Business-model-based management

Capabilities

Information Resources

Physical Resources

Human Resources

Interaction Channels

Simulation

Critical Interactions

Perception of Service Systems

Evaluation of patterns and

Contextualization and Collaboration

Service Support Systems

Product Service Systems

Simulation

Modularization

Adaptiveness and Resilience

Multiple stakeholders

Invention

Exaptation

Improvement

Routine Design

Design Theory

Instantiations

Methods

Models

Constructs

Engineering Service Architectures

Role of Digital Technology

Engineering Business Models

Engineering Resource Mobilization

Engineering Service Systems Interactions

CPS Context

Advanced Models, Methods, and Tools

Architectural Innovation

Claims of Knowledge Contribution

Novelty of Know-ledge Contribution

Type of Knowledge Contribution

78 Knowledge Creation: Advancing Design Knowledge

Table 4. Taxonomy of Extant Prescriptive Knowledge Contributions

Amrou and Böhmann (2016)

x x x x

Amrou et al. (2015)

x x x x

x x

x

x

x

x

x

Study 1: Bringing Order to Design Knowledge – A Taxonomy

79

Haas and Blohm (2017)

x

x

x

x

Haas et al. (2015)

x

x

x

x

x

Herterich (2017) Herterich et al. (2016)

x

Herterich et al. (2015)

x

x

x

x

x

x

Karppinen et al. (2013a)

x

Karppinen et al. (2013b)

x

Karppinen et al. (2014)

x

Kieliszewski et al. (2012)

x x

x

x

x

x

x

x

x

x

x x

x

x x

x

x

x

x

x

Kleinschmidt and Peters (2017a)

x

x

x

x

Kleinschmidt and Peters (2017b)

x

x

x

x

Kleinschmidt et al. (2016)

x

x

x

x

Klör et al. (2017)

x

Knote and Blohm (2016)

x

x

x

x

Knote and Söllner (2017)

x

Kummler (2017) Li and Peters (2016)

x

Metzger et al. (2016)

x

Metzger et al. (2017) Nardi et al. (2015) Neff et al. (2014)

x

x

x

x x

x x

x

x x x

x

Peters (2014)

x

x

x

x x

x

x x

x

Patricio et al. (2011)

x

x

x x

x

x x

x

x

x

x

x

Niemöller et al. (2017)

x x

x

x

x

x

x

x x

x

x

x

x

x

x

Peters et al. (2015a)

x

x

x

x

Peters et al. (2015b)

x

x

x

x

Pfeiffer et al. (2017)

x

x

Schreieck (2016)

x

x

x

Rauer (2014)

x

Semmann and Grotherr (2017)

x

Thornton and O’Flaherty (2015)

x

Weber (2015)

x

Weinrich et al. (2016)

x

x

x

x

x

x x

x

x

x

x x

x

x

x

x x

x

x

x

x x

x

x x

x x

x

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Knowledge Creation: Advancing Design Knowledge

or the modularization of digital services (Schreieck, Wiesche, & Krcmar, 2016); (3) morphological boxes dealing with business model patterns (Peters, Blohm, & Leimeister, 2015), service bundling settings (Beverungen, Kohlborn, & Fielt, 2011), or business models of complex services (Peters, Kromat, & Leimeister, 2015); and (4) a model for assessing the maturity of service systems (Neff et al., 2014). The majority of knowledge contributions can be classified as (III) methods, as for instance (1) design principles for digitized industrial products (Herterich, 2017), social conversational agents (Gnewuch, Morana, & Maedche, 2017), or digital infrastructure design (Weinrich, Muntermann, & Gregory, 2016); (2) design methods for modular services (Dörbecker & Böhmann, 2015), service support systems (Niemöller, Metzger, Fellmann, Özcan, & Thomas, 2016), or complex service systems (Grenha Teixeira et al., 2016; Patricio et al., 2011); or (3) evaluation methods for service systems and corresponding business models (Kleinschmidt & Peters, 2017b). Novelty of Knowledge Contribution According to Gregor and Hevner (2013), routine design occurs when existing knowledge for a problem area is well understood and when existing artifacts are used to address the problem domain. In contrast to that, inventions can be defined as a radical breakthrough that did not emerge from a clearly defined research problem or a well-grounded justification of the value of the solution (Gregor & Hevner, 2013). Although evident in extant literature (Germonprez, Holovoka, & Collopy, 2007; Kolfschoten & de Vreede, 2009; Lin, Gray, & Jouault, 2007; Sakao, Shimomura, Lindahl, & Sundin, 2006), no knowledge contribution incorporated in the taxonomy exhibits characteristics for them to be regarded as routine design or invention. The majority of knowledge contributions can be classified as improvements, i.e., addressing a known problem with a new solution (Gregor & Hevner, 2013). For instance, Gnewuch et al. (2017) state that interacting with computers through natural language and according problems date back to the 1960ss (known problem). In the course of addressing these problems, they discuss several issues that hinder the success of current conversational agents which ultimately leads to proposing design principles for novel cooperative and social conversational agents (new solution). In a similar vein, Dörbecker and Böhmann (2015) argue that although the principle of modularity has been increasingly applied to

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services in recent years, methods in this field are insufficient for specific requirements of service modularization (known problem). They propose a novel approach (new solution) that covers distinct phases of the design of a modular service architecture (Dörbecker & Böhmann, 2015). In contrast to that, exaptation is characterized by extending and refining already existing design knowledge to new application areas (Gregor & Hevner, 2013). One example for exaptation is constituted by the knowledge contribution provided by Bärenfänger et al. (2016) in terms of combining service system design and capability modeling (known solutions) in order to derive an approach dealing with service-capabilities that are relevant for designing businesses in the digital age (new problem) (Bärenfänger et al., 2016). Another exemplary contribution is constituted by Metzger et al. (2017). They state, that virtual reality and head mounted displays have a long history (known solutions), but only few business-related questions and use cases were discussed (new problem) (Metzger et al., 2017). Moreover, since SSE aims to overcome the product-centric thinking of traditional approaches from fields such as service engineering (Bullinger et al., 2003), perspectives that reflect service-centric business models and strategy (Ostrom et al., 2010) are promising to be integrated in design knowledge for engineering service systems in the digital age. In this contest, knowledge contributions such as the one provided by (Blaschke, Haki, Riss, & Aier, 2017) can be depicted as applicable exaptation. Guided by notion that the rise of globe-spanning service-based business models has transformed the way the world works (new problem) (Maglio & Spohrer, 2013), Blaschke et al. (2017) exploit the foundational premises of service-dominant logic (Vargo & Lusch, 2004, 2008a) in order to develop design principles for business-model based management methods. Claims of Knowledge Contribution As stated by Böhmann et al. (2014a), SSE calls for research leading to actionable knowledge for systematically designing, developing and piloting service systems, based upon a thorough understanding of underlying principles. Hence, they propose three key challenges for SSE that demand for applicable design knowledge: engineering service architectures, engineering service systems interaction, and engineering resource mobilization (Böhmann et al., 2014a). As elaborated above, these

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challenges provide a meaningful foundation to classify knowledge contributions according to “what they are capable of”, i.e., which underlying issues they address. However, since a number of contributions extend the conceptualization of service systems towards a business model perspective, the taxonomy provides an additional dimension in order to group characteristics dealing with business model related aspects in the course of engineering novel service systems. Engineering Service Architectures. This dimension consists of three sub-dimensions according to the foundations provided by Böhmann et al. (2014a): (1) architectural innovation, (2) advanced models, methods, and tools for service architecture development, and (3) cyber-physical systems contexts. In the context of (1) architectural innovation, design knowledge on architectures that allows creating value in parallel processes of collaborative value creation with multiple stakeholders (Benkler, 2006; Blau et al., 2009; Böhmann et al., 2014a) is comparatively well represented. Applicable contributions are constituted by principles for ecosystem-oriented management (Blaschke et al., 2017), methods incorporating the concept of customer value constellations (Grenha Teixeira et al., 2016; Patricio et al., 2011), the work systems snapshot by Alter (2011, 212), maturity dimensions concerning enterprise integration (Neff et al., 2014), or ecosystem & technology analysis process steps (Pfeiffer, Krempels, & Jarke, 2017). Issues in the context of adaptivity or resilience, by contrast, are sparsely addressed, e.g., in terms of design principles for flexible data models for data storage (Weinrich et al., 2016) or reverse engineering approaches for recovering existing service design (Henri Karppinen, Huiskonen, & Seppänen, 2013a). The sub-dimension (2) advanced models, methods, and tools for service architecture development deals with characteristics of design knowledge that addresses the issue of modularization and concomitant aspects in terms of standardization, contextualization and reconfiguration of service components and resources as well as the modelling and simulation of service systems and their key actors (Böhmann et al., 2014a). The issue of modularization is at the core of the knowledge contributions provided by Beverungen et al. (2011), Dörbecker and Böhmann (2015), Haas and Blohm (2017), Haas et al. (2015), Klör, Monhof, Beverungen, and Bräuer (2017), Peters (2014), and Schreieck et al. (2016). With a focus on standardization aspects in the context of modularization, Brocke, Uebernickel, and Brenner (2011a, 2011b) provide design knowledge for designing

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standardized on-demand service request processing, provision and operations. Other contributions integrate knowledge contributions addressing these issues crosssectionally, thus rather coarse-grained (Chew, 2016; Fischbach, Puschmann, & Alt, 2011; Neff et al., 2014; Pfeiffer et al., 2017; Weinrich et al., 2016). In the context of the modeling and simulation of service systems, their dynamic nature in terms of composing, recomposing and decomposing (Maglio et al., 2009) places the onus on design knowledge to tightly couple underlying premises. Respective knowledge contributions such as the ones provided by Drăgoicea, Borangiu, and Voinescu (2016), Drăgoicea, Falcão E Cunha, and Pătraşcu (2015), Kieliszewski et al. (2012); Nardi et al. (2015) address this issue by combining modeling and simulation in coherent approaches. The third sub-dimension deals with the (3) design of architectures that emerge from cyber-physical systems and thus have to address the merging of physical and virtual worlds (Böhmann et al., 2014a). Knowledge contributions dealing with according issues for service systems engineering are scare, but dedicatedly address distinct aspects. Herterich (2017), Herterich, Buehnen, et al. (2016), Herterich, Holler, et al. (2015), Neff et al. (2014), and Niemöller, Metzger, and Thomas, 2017) provide design knowledge on how to align the development of the physical resources of cyber physical systems with the overarching engineering of service systems whereas the knowledge contributions by Metzger et al. (2017) and Metzger, Niemöller, and Thomas (2016) address issues relating to the support of operational activities during service delivery. Engineering Service Systems Interactions. Interactions between service systems are crucial for value creation and can be structured along the activities proposal, agreement,

and

realization

(Maglio

2009).

Advances

in

information

and

communication technology allow for novel forms of information-intensive interactions, thus expanding the opportunities for contextualization and collaboration (Böhmann et al., 2014a; Kieliszewski et al., 2012). In this vein, for instance, Amrou and Böhmann (2016) and Amrou, Semmann, and Böhmann (2015) provide knowledge contributions that address the issue of developing IT components that enhance collaboration between training customers and providers as well as contextualization to meet the individual training needs. Moreover, the engineering of interactions can be enhanced through design knowledge relevant for the evaluation of patterns in information intensive interactions (Böhmann et al, 2014a) as elaborated on in

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contributions such as the ones by Gnewuch et al. (2017), Kummler (2017), and Weber (2015). Further on, by dealing with issues such as the perceived lack of responsiveness during interactions, Gnewuch et al. (2017) provide knowledge contributions applicable for engineering the perception of service systems. Critical interactions with service systems refer to potential failures among service interaction activities (Maglio 2009, Böhmann et al., 2014a). In this context, Karppinen et al. (2013) introduce an artifact that captures employee experience within a service delivery system in order to improve the performance of the service process. Weber (2015) further elaborates on service encounters in financial intermediary services and provide relevant design knowledge for these critical service system interactions. Similarly, Gnewuch et al. (2017) provide knowledge contributions addressing the issue of error-handling strategies despite potential misunderstanding in the course of service interactions. The call for simulation of interactions (Böhmann et al., 2014a) is solely addressed by Dragoicea et al. (2016) by means of constructing an agent-based model that expresses value-creation interactions among service system’s stakeholders. As stated by Böhmann et al. (2014a), the increasing integration of IT-enabled interactions into a choice of channels fosters the need to better understand and improve design methods for service systems interactions. Applicable knowledge contributions dealing with this issue are provided by, for instance, Grenha Teixeira et al. (2016), Patricio et al. (2011), and Thornton and O’Flaherty (2015) in terms of proposing further developed versions of service blueprints adapted to the affordances of novel information technology developments. Engineering Resource Mobilization. The mobilization of resources addresses the opportunities for extending the access to and the use of resources by ubiquitous information systems (Böhmann et al., 2014a). In the context of the taxonomy at hand, several contributions provide design knowledge for engineering the mobilization of human resources, e.g., in terms of user-generated services in techno change (Li & Peters, 2016) or supporting intrapreneurs in incumbent firms to develop and implement extraordinary ideas (Knote & Blohm, 2016). Other contributions such as the one by Weinrich et al. (2016) deal with the mobilization of information resources by means of developing approaches that foster data and information processing in digital infrastructures.

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Engineering Business Models. The integration of research on service systems and business models constitutes an issue which is dealt with in several knowledge contributions in the taxonomy. In this context, Bärenfänger et al. (2016) provide an approach that combines service systems design and capability modeling for digital businesses. Blaschke et al. (2017) elaborate on design principles for business-modelbased management methods from the perspective of service-dominant logic. The majority of knowledge contributions provides design knowledge concerning the alignment of service systems and corresponding business models in the course of both, their integrated design (Chew, 2016; Kleinschmidt, Burkhard, Hess, Peters, & Leimeister, 2016; Kleinschmidt & Peters, 2017a; Pfeiffer et al., 2017) and evaluation (Kleinschmidt & Peters, 2017b). Further on, with the aim to give a structured view on business models of service providers, Peters, Blohm, et al. (2015) and Peters, Kromat, et al. (2015) develop an approach for the classification of business models and the identification of patterns among them. Ultimately, Neff et al. (2014) develop a maturity model that provides design knowledge on service systems in terms of fostering the understanding of service systems in industry goods companies and the corresponding requirements for the appropriation of information systems. Role of Digital Technology In order to characterize the role of digital technology as a potential driver for digitally enabled generativity among the knowledge contributions incorporated within the taxonomy, the framework proposed by Nambisan (2013) is adopted. Hence, the objects of interest are classified along the characteristics ’digital component as an innovation trigger’, ’digital component as an innovation enabler’, ’digital tool as an innovation trigger’, and ’digital tool as an innovation enabler’ (Nambisan, 2013). Several knowledge contributions conceptualize digital components as an innovation trigger. For instance, Blaschke et al. (2017) state that management methods should focus on the decoupling of information and matter, the de-linking of ownership and value creation, and the systematic use of IT as means to achieve collaborative competence, thus leading innovative value propositions. Similar conceptualizations are evident in the contributions by Herterich (2017), Pfeiffer et al. (2017), and Weinrich et al. (2016). The role of digital components as innovation enabler is reflected in the

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majority of contributions, e.g., in terms of head mounted displays for service support systems (Metzger el al., 2016; Niemöller et al., 2017), information technologies to be integrated in various interaction channels (Grenha Teixeira et al., 2016; Patricio et al., 2011), or conversational agents for customer service (Gnewuch et al., 2017). Digitals tools can be regarded as innovation trigger when they have an impact on the innovation process in that initiating new innovation processes (Nambisan, 2013). This notion is prominent in contributions dealing with crowdfunding services (Haas & Blohm, 2017; Haas et al., 2015), modularized services for unleashing the potential of intrapreneurs as peripheral innovators (Knote & Blohm, 2016), or engagement platforms (Semmann & Grotherr, 2017). The last characteristic in this dimension is depicted by the role of digital tools as an innovation enabler. Hence, the digital tool deals as means to enhance the efficiency and effectiveness of development activities (Nambisan, 2013). This is reflected in contributions that, for instance, deal with transfer-supporting IT components (Amrou & Böhmann, 2016; Amrou et al., 2015), training systems for technical customer service services (Metzger et al., 2017) or platforms that support “what-if” analyses by stakeholders and policy makers (Kieliszewski et al., 2012).

1.5

Discussion

The taxonomy developed within this study addresses the question of ‘How can design knowledge relevant for engineering service systems in the digital age be structured in a meaningful way?’ by means of classifying relevant prescriptive knowledge contributions according to their type, novelty, and claims for engineering service systems, together with characterizing the role of digital technology as a driver for digitally enabled generativity among them. As elaborated on in the further course, explaining similarities as well as differences among these objects of interest builds the foundation for the identification of future research fields (Nickerson et al., 2013). The primary contribution and value of this approach thus lies in its ability to develop novel conceptualizations or extend current ones by highlighting knowledge gaps between what is known and what is needed to be known (Paré et al., 2015; Webster & Watson, 2002).

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Against this backdrop, this section aims to identify research opportunities, together with developing research questions along these research opportunities that deal as avenue for future design-oriented research (Schryen, 2015; Schryen et al., 2017; vom Brocke et al., 2009; Webster & Watson, 2002). Since the resulting taxonomy depicts a model that dynamically emerged in the course of analyzing knowledge contributions, its underlying dimensions can be deemed as promising to provide a concise structure for delineating future research directions (Wolfswinkel et al., 2013). Hence, following the recommendation by (Rowe, 2014), research opportunities are elaborated on along the same structure that was used for analyzing and synthetizing. Based upon this, a set of future research directions is introduced. Research Opportunity 1 – Documenting Knowledge Contributions in a Way that Allows for Explicating a Design Theory. Although one knowledge contribution can incorporate various knowledge types (Dwivedi et al., 2014), the taxonomical classification at hand is aligned with the nature of the underlying systematic literature review which is why the most representative knowledge types are exclusively emphasized in order for the taxonomy to be meaningful (Nickerson et al., 2013). Among the objects of interest, numerous contributions could be classified as either models or methods whereas constructs were merely represented and design theories not at all. The absence of knowledge contributions that could be classified as design theory is mainly due to criteria for a design theory proposed by Gregor and Jones (2007). Hence, well-developed knowledge contributions such as the method provided by Grenha Teixeira et al. (2016) are positioned as nascent design theory. According to Gregor and Hevner (2013), in order to evolve to the stage where design knowledge could be termed design theory, e.g., an explanation why the method works as it does or a good account of the specific conditions under which it holds should be provided. By dealing with a reference ontology for services, the work of Nardi et al. (2015) constitutes a valuable contribution in terms of developing constructs that are promising to be incorporated as component in a design theory, but lacks vocabulary and symbols that can be used to define and understand problems and solutions (Gregor & Hevner, 2013) in the context of the systematic development of service systems. Although other knowledge contributions

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address further criteria of design theories, e.g., in terms of expository instantiations (Amrou & Böhmann, 2016; Niemöller et al., 2017), there is a lack of research that documents prescriptive design knowledge in a way that allows for explicating a design theory along the components introduced by Gregor and Jones (2007). Research Opportunity 2 – Initiating the Development of Artifacts that Depict a Departure from Accepted Ways of Thinking. Concerning the novelty of knowledge contributions classified within the taxonomy, improvement and exaptation are most widely balanced, whereas neither routine design nor inventions are present. Since the former compromises the notion of SSE as field for future research (Böhmann et al., 2014a), the focus of future work should focus on approaches that lead to inventions, i.e., radical breakthroughs. In this context, the idea of the knowledge contribution or the knowledge contribution by itself is new (Gregor & Hevner, 2013). Research Opportunity 3 – Developing Design Knowledge that Addresses the Role of Business Models in the Realms of Engineering Service Systems. Knowledge contribution claims are fairly wide-spread among the underlying and associated issues of engineering service system, i.e., (1) engineering service architectures, (2) engineering service systems interactions, (3) engineering resource mobilization, and (4) engineering business models. (1) Especially in the context of digitally enabled generativity, pivotal aspects concerning joint value creation in digitally enabled service systems are not addressed. Although several contributions deal with the multitude of actors incorporated in collaborative value creation (e.g., Patrício et al., 2011; Grenha Teixeira et al., 2016), only a minority addresses the role of these actors as potentially valuable stakeholders with specialized knowledge and skills in systems of service systems (Patrício, Pinho, et al., 2018; Pinho et al., 2014). (2) Knowledge contributions addressing issues in the context of service systems interactions are fairly scattered. For instance, the call for simulation of interactions (Böhmann et al., 2014a) is solely addressed by Drăgoicea et al. (2016) by means of constructing an agent-based model that expresses value-creation interactions among service systems’ stakeholders. (3) The maturity of knowledge contributions dealing

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with the issue of resource mobilization is rather low. Evidence dealing with the mobilization of physical resources was not present although this topic is dealt with in numerous descriptive knowledge contributions (e.g., Koskela-huotari et al., 2016; Remane et al., 2016; Barile et al., 2016) that could deal as a foundation to derive applicable design knowledge for service systems. (4) However, the taxonomy also reveals that the notion of business models in the context of service systems engineering has been increasingly taken into account in recent knowledge contributions. The maturity and high quality of these contributions as well as their positioning in the realms of information systems (e.g., Peters et al., 2015a; Chew 2016; Kleinschmidt et al., 2016) denote the relevance of design knowledge on business model related issues, thus calling for future research on underlying principles with the aim to further integrate the notions relevant in the context of (1), (2), and (3). Research Opportunity 4 – Understanding Digital Technology as a Trigger for Innovation in Service Systems It can be argued that opportunities for service innovation in the digital world are limited only by the extent of digitization and concomitant socio-technical processes altered by digital technology as a driver for digitally enabled generativity (Barrett et al., 2015; Lusch & Nambisan, 2015; Tilson et al., 2010). However, only a small number of contributions addresses the role of digital technology in a profound way, i.e., in terms of acknowledging the unanticipated change that is triggered by decoupling information from its physical matter and distributing this information to varied audiences (Lusch & Nambisan, 2015; Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010). In this context, the concepts of generativity (Tilson et al., 2010; Weinrich et al., 2016) or resource density with according dematerialization mechanisms (Normann 2001; Blaschke et al., 2017; Herterich 2017; Pfeiffer et al., 2017) provide promising views for understanding the capabilities of digital components in terms of triggering innovation in and across service systems. Similarly, digital tools exhibit the capability to initiate innovation processes (e.g., Knote and Blohm 2016). Taking this into account, novel design knowledge could address the question of “in what way can IT support actors in searching for and bundling (mixing and matching) resources within and across service platforms?” (Lusch and Nambisan 2015, p. 163). Hence, with information being the

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crucial resource in the context of digitally enabled service systems, according digital tools could initiate innovation processes by gathering and visualizing data in a way that addresses the notion that more and more innovation will be intangible in the digital age (Bae & Leem, 2014; Lusch & Nambisan, 2015). Prescribing Novel Research Directions for Engineering Service Systems in the Digital Age Using the research opportunities identified above, a set of research directions with according research questions can be derived that provide various entry points for future research along the research trajectory illustrated in Table 5.

Table 5. Research Directions for Engineering Service Systems in the Digital Age Interplay of Research Directions

Routine Design

Exaptation

Digital Component as a Trigger

Digital Component as an Enabler 1.

2. Improvement

Invention

Digital Tool as a Trigger

Digital Tool as an Enabler

Novel Artifacts Design Theory

Models

Instantiations

3.

Methods

Constructs

Business Models

Service Architectures

4. Service Resource Systems Mobilization Interactions

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Research Questions Guiding Future Research Directions (RQD) RQD 1: How can digital components be designed as a trigger for innovation in terms of

seeking out and pursuing unique resource integration opportunities on their own to discover novel innovation opportunities? RQD 2: How can digital tools be designed as trigger for innovation in terms of initiating

unanticipated outcomes that stem from the mechanisms underlying digitally enabled generativity? RQD 3: How can prescriptive design knowledge on novel digital components, tools, artifacts

and digitally enabled service systems be documented in a way that allows for explicating a design theory? RQD 4: Which facets of service systems have to be acknowledged in the course of explicating

business model-oriented design knowledge for digitally enabled service systems?

The (1.) starting point (addressing RQD 1) in this trajectory is depicted by elaborating on the notion of digital components or digital tools as a trigger for innovation. As Lusch and Nambisan (2015) state, digital components of a service platform may seek out and pursue unique resource integration opportunities on their own by mining data on and creating bridges across diverse resources to discover novel innovation opportunities. The generativity of these digital components (Yoo et al., 2010) then can lead to innovations in service systems that often are not anticipated by those who created the service system in the first place (Eaton et al., 2015; Yoo, 2013). Moreover, understanding underlying generative mechanisms (Henfridsson & Bygstad, 2013; Lessard, 2015) through the lens of resource density (Lusch & Nambisan, 2015; Normann, 2001) can provide the foundation for the development of design knowledge promising to be incorporated in digital tools that support the design of beneficial, albeit unanticipated, configurations of resources in novel service systems. Hence, the (2.) invention process (addressing RQD 2), i.e., the explorative search over a complex problem space that requires cognitive skills of curiosity, imagination, creativity, insight, and knowledge of multiple realms of inquiry (Gregor & Hevner, 2013), can be triggered by digital components or digital tools fostering the emergence of digitally enabled service systems in a real world context that, in turn, embody novel configuration of resources or artifacts. With the aim of prescribing guidelines for further digital components and tools or artifacts and service systems whose

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development is triggered, the underlying knowledge contributions can be documented by means of a (3.) design theory (addressing RQD 3) (Gregor & Jones, 2007). This demands for theorizing in a way that allows for truth statements about corresponding artifacts and provides the foundation for explicating a design theory along its underlying structural components (Gregor & Jones, 2007; Iivari, 2007; Sonnenberg & vom Brocke, 2012b). Regarding the (4.) claim of novel design theories for engineering digitally enabled service systems (addressing RQD 4), novel work could address the notion of business model in the context of service systems, thereby acknowledging pivotal aspects that address the socio-technical processes concomitant with the innovation opportunities opened up by digitalization (Lusch & Nambisan, 2015). Hence, future research dealing with design-oriented knowledge on business models in the realms of SSE could, i.a., deal with the multitude of stakeholders incorporated in collaborative processes of value creation (engineering service architectures), the simulation of interactions among these stakeholders (engineering service systems interactions), and the role of physical resources (engineering resource mobilization). This, in turn, provides the foundation for the development of novel digital components and tools. Hence, as illustrated in Table 5, the interplay of research opportunities leads to a number of research questions that define various avenues for future research.

1.6

Contribution and Conclusion

The aim of this research work is constituted by developing a taxonomy that can help to bring order to the complex area of research in the field of SSE by explaining similarities as well as differences among the objects of interest and thus provides the foundation for the identification of future research fields. The resulting taxonomy addresses the issue of how design knowledge for engineering services systems in the digital age can be classified in a meaningful way. Guided by a rigorous research design, the objects of interest to be classified, i.e., prescriptive knowledge contributions, were identified by applying the systematic literature review method proposed by vom Brocke et al. (2009). The taxonomy development process dealing with the classification of these objects followed the principles of the taxonomy development method by Nickerson et al. (2013). The resulting taxonomy then dealt as point of departure for

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setting out a set of research directions embodying research questions that are promising to be addressed in future research. The novelty of the study at hand is constituted by dedicatedly addressing the notion of design knowledge for service systems in the digital age that stems from real-world applications. By that, for both, general and special scholars, a foundation for understanding the field and deriving implications for future research is provided. Hence, this research work contributes to the knowledge base in terms of developing a taxonomy that supports the systematic and structured classification of knowledge contributions that are promising to provide prescriptive knowledge for engineering service systems in the digital age, thus addressing the pivotal call of SSE for design knowledge for such systems that permeate our society (Böhmann et al., 2014a). Moreover, by defining various research entry points along the research trajectory introduced in the course of developing a set of research directions, future research based on this foundation is inherently guided towards acknowledging knowledge contributions from diverse disciplines, thus bridging the boundaries of disciplines relevant for SSE. In this vein, an essentialist research goal is addressed in terms of identifying essences in the research territory and their relationships (Iivari, 2007). The resulting knowledge contribution can be acknowledged as a contribution to theory for design and action (Gregor & Jones, 2007) since it focuses on how to structure objects of interest, i.e., knowledge contributions relevant for engineering service systems in the digital age. More precisely, applying both, the method for systematic literature reviews by vom Brocke et al. (2009) and the method for taxonomy development by Nickerson et al. (2013) in the course of identifying and classifying promising knowledge contributions for SSE can be regarded as exaptation whereas the taxonomy and the intertwined set of research directions can be characterized as a model (Gregor & Hevner, 2013). Although not being subject to an evaluation intervention, this conceptual artifact thus encompasses insights that are valuable for the demarcation of a prospective body of knowledge on engineering service systems in the digital age and, by that, offers a foundation for further design theorizing (Gleasure, 2014, 2015; Iivari, 2007).

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Study 2: Gathering Design Knowledge – Generative Mechanisms

The aim of Study 1 was to identify knowledge contributions that are deemed to embody valuable design knowledge for engineering digitally enabled service systems and to discuss their characterization among applicable dimensions. However, Study 1 revealed that, although valuable knowledge contributions addressing the overall scope and purpose of this dissertation are evident in extant literature, there is still a scarcity of prescriptive knowledge acknowledging the facets of the specific nature of innovation in digitally enabled service systems. In this vein, Hevner et al. (2004) state that the existing knowledge base is often insufficient for design purposes, inducing designers to rely on intuition, experience, and trial-and-error methods. A constructed artifact, in turn, demands for a designer’s well-grounded design knowledge of the problem and solution (Hevner et al., 2004). Building on this premise, Study 23 applies a qualitative explorative approach in the context of a holistic multiple case study (Miles et al., 2014; Yin, 2003) in order to identify generative mechanisms that bear the potential to lead to enhanced resource densities (Lusch & Nambisan, 2015; Normann, 2001) in digitally enabled service systems (Herterich, Eck, et al., 2016; Yoo et al., 2010). The analysis of the empirical data collected among 13 cases then leads to three generative mechanisms that stem from an understanding of digitally enabled generativity in service systems that is grounded in the notion of the dematerialization mechanisms introduced by Normann (2001), i.e., liquification and unbundleability. These mechanisms, i.e., invention, improvement, and exaptation, thus embody design knowledge that is promising to be incorporated in the course of designing and developing service systems that are attuned to the premises of innovation opportunities opened up by

3 Earlier versions of this research have been presented at the European Academy of Management (EURAM) 2016 conference in Paris, France and at the European Association for Research on Services (RESER) 2016 conference in Naples, Italy. The current version thoroughly ingrained the feedback from the fruitful discussions at the conferences and will be the basis for a further developed submission to a service research journal.

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digitally enabled generativity (Böhmann et al., 2014a; Lusch & Nambisan, 2015). Hence, as a departure from grounding design knowledge for engineering digitally enabled service systems in intuition and experience (Hevner et al., 2004), this study contributes to the overall dissertation in terms of complementing the extant body of knowledge with knowledge on “principles of function” (Gregor et al., 2013) that provide the instructions for performing the goal driven activity of supporting the engineering of digitally enabled service systems. By that, knowledge is produced that is promising to allow for prescriptions of guidelines for prospective artifacts in this context. The remainder of this study proceeds as follows. First, an introduction to the problem context is provided, together with elaborating on the research objective guiding this study. Second, the theoretical foundations underpinning the case study are described. Afterwards, the research approach for identifying mechanisms leading to enhanced resource densities is introduced. Next, the findings are presented along a three dimensional framework. Subsequently, the implications for designing according digitally enabled service systems are discussed, together with deriving implications for future research on design knowledge that builds on a thorough understanding of the mechanisms underlying digitally enabled generativity. The study ends with a summary and conclusion, incorporating implications for future research.

2.1

Purpose and Scope

With the separation of information from matter and the rapid growth of global communication networks, more and more innovation is intangible, digitally enabled, and created around social phenomena. Together with the notion that shared information and technology are key resources in the context of service innovation, this leads to novel forms of resource configurations making use of the knowledge exchange initiated among various actors incorporated in collaborative value creation (Barrett et al., 2015; Lusch & Nambisan, 2015; Maglio et al., 2009; Tilson et al., 2010). Within this context, service systems embody an abstraction of value creation (Spohrer et al., 2008) and consist of a dynamic value cocreation configuration of resources, including people, organizations, shared information (language, laws, measures, methods), and technology, all connected internally and externally to other service systems by value

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propositions (Maglio & Spohrer, 2007; Maglio et al., 2009). The digitally enabled generativity unleashed by digital technology and the rapid diffusion of personal computers and the Internet (Yoo et al., 2010) leads to service systems that possess the “capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences” (Zittrain, 2008, p.70), i.e., digitally enabled service systems. According

novel socio-technical assemblages open up innovation

opportunities (Lusch & Nambisan, 2015), but also induce contradictions, rupture, and incompatibility within these systems (Eaton et al., 2015). Design knowledge supporting the structured and systematic design of digitally enabled service systems thus has to address the underlying principles of these generative systems (Henfridsson & Bygstad, 2013; Tilson et al., 2010) and provide mechanisms to foster beneficial configurations of resources (Maglio et al., 2009). As stated by Lusch and Nambisan (2015), a promising lens to identify such mechanisms for “controlled generativity” (Eaton et al., 2015) is constituted by the notion of resource density (Normann, 2001) in terms of conceptualizing dematerialization mechanisms that address both, the technical as well as socio-technical processes concomitant with digitization and the digitally enabled generativity unleashed by digital technology (Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010). Hence, understanding these mechanisms can lead to enhanced resource densities in digitally enabled service systems. Guided by that, knowledge on digitally enabled service systems can be advanced and a knowledge contribution for prescriptive design knowledge for their structured and systematic design and development can be made (Böhmann et al., 2014a; Dwivedi et al., 2014; Gregor & Hevner, 2013; Lessard, 2015). Against this backdrop, this study aims to answer the following research question: Which mechanisms leading to enhanced resource densities can be identified among digitally enabled service systems? This research question is answered by drawing on a holistic multiple case study among 13 firms. The research contribution is twofold: First, a more precise

understanding of the anatomy of digitally enabled service systems is provided. Second, by identifying mechanisms that lead to enhanced resource densities among these systems, implications for their structured and systematic design and development can

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be drawn. By answering the research question in terms of identifying according mechanisms for controlled generativity, the understanding of the domain is fostered and a contribution to the knowledge base on engineering digitally enabled service systems is achieved.

2.2

Background

Although leading to novel value creation opportunities among actors from broad and varied audiences (Lusch et al., 2010; Vargo & Akaka, 2012a; Zittrain, 2008), innovation in digitally enabled service systems faces inherent tensions that are contingent on the mechanisms underlying digitally enabled generativity (Eaton et al., 2015; Yoo, 2013). In order to deepen the understanding of these mechanisms, together with providing a foundation for producing knowledge contributions that acknowledge the positive outcomes of what they induce (Eaton et al., 2015; Förderer et al., 2014; Pagani, 2013), central notions are dealt with in the following. 2.2.1

Generativity and Generative Mechanisms

In order to advance design knowledge on service systems in the digital age, understanding the underlying principles of these systems is crucial (Böhmann et al., 2014a). As Lusch and Nambisan (2015) state, the socio-technical processes concomitant with digitization and the wide-spread diffusion of digital technology unleash digitally enabled generativity in terms of forging new social connections and cognitive models. In this context, generativity refers to a system’s capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences (Zittrain, 2006, 2008). However, as Eck and Uebernickel (2016) argue, this conceptualization leads to different conclusions on how to describe a generative system. The first perspective refers to the notion of generativity as consequence of system design with the system’s main achievement being constituted by catalyzing human ingenuity, whereas the second perspective regards generativity as consequence of system evolution with the system being capable to evolve into directions that were initially unimaginable (Eck & Uebernickel, 2016). In the context of service systems that emerge from new innovation opportunities opened up by digitally enabled generativity, the

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second perspective is particularly promising in order to understand their underlying dynamics (Eaton et al., 2015; Lusch & Nambisan, 2015; Nambisan, 2013). Hence, designoriented understanding of these service systems can be achieved by identifying the generative mechanisms that tend to produce according novel configurations of resources (Lessard, 2015; Maglio et al., 2009; van Aken, 2004). Grounded in this view from critical realism (Bhaskar, 1975), generative mechanisms can be defined as causal structures that generate observable events (Bhaskar, 1975; Henfridsson & Bygstad, 2013). More specifically, especially action-formation mechanisms are promising to explain the socio-technical actions leading to unanticipated change in generative systems (DeLanda, 2006; Hedström & Swedberg, 1998; Henfridsson & Bygstad, 2013). Thus, in order to advance design knowledge on service systems in the digital age, understanding the generative mechanisms underlying the socio-technical processes concomitant with digitally enabled generativity in service systems is needed. The idiographic scientific knowledge (Baskerville et al., 2015) produced in this context then can deal as grounding for novel constructs, models, methods, instantiated artifacts, and design theories (Gregor & Hevner, 2013; Hevner et al., 2004) that are attuned to the nature of these complex systems, thus supporting their systematic design and development (Böhmann et al., 2014a). 2.2.2

Resource Density and Dematerialization Mechanisms

As sounded out above, one lens to address the mechanisms underlying digitally enabled generativity and the resulting potential for innovation in service systems is depicted by Normann (2001), who introduces the concept of “density” of offerings. Density is a measure of the amount of information, knowledge, and other resources that an actor has at any given time and/or place to solve problems (Vargo & Akaka, 2012a, 2009). Maximum density then occurs when the “best combination of resources is mobilized for a particular situation – e.g., for a customer at a given time in a given place – independent of location, to create the optimal value/cost result” (Normann 2001, p.27). Normann (2001) emphasizes two intertwined dematerialization mechanisms that lead to the creation of new densities, namely liquification and unbundleability. Liquification refers to dematerialization through the separation of information from the physical world by digitization, allowing it to be easily moved

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about and remanifested in many different ways (Lusch & Nambisan, 2015; Michel et al., 2008; Normann, 2001). By configuring and modeling this decoupled information in different ways, novel insights and contextually relevant knowledge can be generated (Benaroch, 1998; Gruber, 1995). Liquification drives unbundleability, which refers to the separation of activities hitherto well defined and held together in time and place and by actor. Reverting to the longhand definition of service as the application of specialized competences (knowledge and skills) through deeds, processes, and performances for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015;

Vargo

&

Lusch,

2016),

dematerialization

through

liquification

and

unbundleability promotes rebundleability, which allows the creation of improved densities (Michel et al., 2008; Normann, 2001). Hence, improved densities are achieved by rebundling diverse resources, creating novel resources beneficial (i.e., valueexperiencing) to some actors in a given context, which can then be conceptualized as service innovation (Lusch & Nambisan, 2015). In the course of fostering innovation in service systems, many resources and activities can be dematerialized and unbundled in terms of place (where things can be done), time (when things can be done), and actor (who can do what) and then be rebundled with a denser level of resource integration (Kowalkowski & Brehmer, 2008; Normann, 2001). Although maximum density is conceptualized as the best combination of resources mobilized for a particular situation to create the optimal value/cost result for a customer, this theoretical maximum never exists (Lusch et al., 2010). The business models that currently most closely approach maximum density are internet search solutions, such as Google. An individual anywhere in the world with a connected PC can find the answer to virtually any question on demand. The same process of answer-seeking 25 years ago was afflicted with diverse constraints. For instance, information in a library could only be accessed during opening times, and the books carrying this information could only be read or rented in the respective library building. Such constraints are reflected by a rather low level of resource density (Normann, 2001). In contrast to that, the current model of digitally enabled answerseeking exemplifies a higher density (Lusch et al., 2010).

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Research Method

The general intent of this study is to gather insights on how digitally enabled generativity can lead to novel innovation opportunities in digitally enabled service systems. Against this backdrop, the larger context of the synergistic interactions of technology and science is to be shed light on (Arthur, 2009; Baskerville et al., 2018; Kelly, 2010; Mokyr, 2002; Ridley, 2015). The major goal of science is to gain a better understanding of how the world works, whereas the goals of technology are constituted by growing the prescriptive knowledge base of purposefully designed artifacts to improve human capabilities (Gardner, 1994, 1995; Iivari, 2007; Layton, 1974). However, the evolution of technology in general and digital technology in particular can be very pervasive and, by that, radically changes the nature of innovation endeavours (Arthur, 2009; Ridley, 2015; Yoo et al., 2012, 2010). Hence, in the vein of the design-science duality in DSR (Baskerville et al., 2015), technology informs science by means of providing the opportunity to study creative solutions to relevant, real-world problems (Arthur, 2009; Kelly, 2010). It is then the role of science to understand how and why the newly introduced technology and concomitant phenomena impacts the surrounding world as it does. Thus, it can be posited that, in most cases, technology evolutions precede and drive science evolutions (Mokyr, 2002). In turn, science also informs technology via rigorous grounding in application domain knowledge bases. By that, when combined with design-oriented goals, explanatory statements can be further developed into prescriptive knowledge contributions (Baskerville et al., 2018; Goldkuhl, 2004). From a knowledge production point of view, the main aim of this study is thus to produce idiographic scientific knowledge to understand the underlying causes, structures, and generative mechanisms responsible for observed patterns that are induced by digitally enabled generativity in service systems (Baskerville et al., 2015). Combined with the general intent of engineering digitally enabled service systems, a ground is provided for the development of according prescriptive knowledge in this context.

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101

Research Objective

The objective of this study is to identify generative mechanisms (Bhaskar, 1975; DeLanda, 2006; Hedström & Swedberg, 1998; Henfridsson & Bygstad, 2013) leading to improved densities (Lusch & Nambisan, 2015; Lusch et al., 2010; Normann, 2001) in service systems (Maglio et al., 2009; Spohrer et al., 2008) that emerge from the innovation opportunities opened up by digitally enabled generativity (Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010). Thus, the socio-technical actions (DeLanda, 2006; Hedström & Swedberg, 1998) leading to novel configurations of resources and activities are analyzed along the dimensions of place, time, and actor through the lens of resource density (Kowalkowski & Brehmer, 2008; Normann, 2001). 2.3.2

Research Design

Investigating generative mechanisms fostered by digitally enabled generativity that lead to novel configurations of resources and activities in service systems through a resource density lens constitutes an emerging research area. Hence, a qualitative explorative approach was chosen in order to explore in-depth insights on real-world experiences (Miles et al., 2014). Building upon first insight from previous single case studies by Eaton et al. (2015) and Henfridsson and Bygstad (2013), a holistic multiple case study (Yin, 2003) was conducted that allows for in-depth knowledge on a wider variety of cases (Bryman & Bell, 2015). Taking the notion of generativity into account, an abductive approach (Dubois & Gadde, 2002; Mueller & Urbach, 2017) was chosen in order to address the “unanticipated change through unfiltered contributions from broad and varied audiences” (Zittrain 2008, p. 70) in the course of identifying generative mechanisms that lead to improved resource densities in service systems. Phases of induction and deduction (Dubois & Gadde, 2002; Locke, 2010) were combined, thus allowing for iteration between the empirical and the theoretical knowledge that is critical for deepening the understanding of the phenomenon under consideration through case study research (Locke, 2010). Following the premises of service science and SSE, the service system represents the central unit of analysis within this study (Böhmann et al., 2014a; Maglio et al., 2009). The case selection was driven by the notion that digitally enabled service systems

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increasingly emerge into an inherent component of industrial productions systems and new business models in manufacturing (Neff et al., 2014; Zolnowski, Schmitt, & Böhmann, 2011). Hence, firms from the manufacturing industry with concomitant subsectors constituted the research context. Each case in the multiple case study represents the system of service systems (Maglio et al., 2009; Patricio et al., 2011) comprised by the configuration of resources integrated by the firm under consideration, its value creating stakeholders, and customers. The concept of resource density (Normann, 2001) is regarded as one of the most enriching concepts in service research (Lusch et al., 2010; Michel et al., 2008; Vargo et al., 2008) and provides foundational premises that are promising to understand the generativity unleashed in digitally enabled service systems and concomitant generative mechanisms leading to beneficial resource configurations. Hence, by conceptualizing the liquification of information as technical processes, i.e., digitization, and unbundleabilty as accompanying socio-technical process, i.e., digitally enabled generativity (Lusch & Nambisan, 2015; Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010), that are fostered by the interplay of digital technology (Yoo et al., 2010), a perspective for advancing design-oriented knowledge for service systems in the digital age with improved densities (driven by rebundleability) is introduced. 2.3.3

Data Collection

The selection of cases was guided by a theoretical sampling approach in order to ensure that all cases were comparable and sufficiently represented the emergence of digitally enabled service systems as the phenomenon under investigation (Eisenhardt, 1989; Miles et al., 2014; Yin, 2003). In this vein, manufacturing SMEs were considered the primary subject of interest since these organizations seldomly have the resources to build new organizational units or create new specialties, but rather differentiate themselves trough new value constellations within business networks (Kowalkowski, Witell, & Gustafsson, 2013) – a phenomenon which is catalyzed by digitally enabled generativity to a certain extent. Against this backdrop, an initial sample of potentially relevant organizations was obtained from a subdivision of the German Chamber of Industry and Commerce, encompassing 4.055 SMEs with a maximum size of 499

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employees from economic sectors such as Metal production and processing, Manufacture of electrical equipment, Mechanical engineering, Manufacture of motor vehicles and parts of motor vehicles, Repair and installation of machinery and equipment, Shipping, Aviation, and Engineering offices for mechanical and plant engineering. Screening this sample and sorting out irrelevant entries resulted in 327 SMEs that were approached via E-Mail and telephone. In the course of establishing first contacts, the suitability as well as the willingness to be available for an interview among the companies approached was assessed. Ultimately, 13 cases from the German manufacturing industry with concomitant sub-sectors were selected. The empirical data collected in the 13 cases include qualitative interview data that was obtained through semistructured in-depth interviews among 21 participants, including managing directors, senior managers, project managers, and line managers from the respective firms. Table 6 provides an overview of the firms that were incorporated in the multiple case study. The bearing producer SFL constitutes an exception in this context, since the firm as a whole has more than 499 employees. However, the interview partner was part of a rather small internal consulting department that deals with issues in the context of digital transformation and, by that, could be regarded as valuable interviewee. The interviews were conducted in the time between December 2015 and July 2016. Interview questions were developed in alignment with existing literature and were adjusted towards avoiding academic language in order to allow participants to express ideas in their own words (Coviello, 2005). With the exception of two interviews that were conducted via telephone, all participants were interviewed at their own location. All interviewees were asked the same questions concerning their position in the organization, their perception of digital transformation, recent developments and innovative solutions stemming from the opportunities opened up by digital transformation, and the role of novel technologies in this context. Finally, the participants were asked to provide a statement in terms of potential future developments. In the course of these interviews, the critical incident technique was applied in order to facilitate the investigation of significant occurrences, i.e., events or processes that lead to novel developments in the context of digital transformation. By that, access to the underlying principles from the perspective of the interviewee could

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be gained, taking into account their individual experiences from the near past (Gremler, 2004). Table 6. Overview and Background Information on Selected Cases Name

Focus and Interviewees

Number of employees

ABG

Software for ship building • Chief Executive Officer • Technical Manager Industrial sensors • Project Manager Software for industrial automation • Chief Executive Officer Uninterrupted power supplies • Chief Executive Officer Baking machines • Head of IT • Head of Marketing • Division Manager • In-house Consultant Automation technology • Chief Executive Officer Automation technology • Chief Technical Officer Machine builder • Chief Executive Officer • Head of IT Machine builder • Chief Executive Officer • Head of Project Engineering • Production Manager Bearing producer • Chief Digital Officer Processing of plastics • Project Manager Manufacturer of electronic components • Chief Executive Officer Software for industrial applications • Chief Executive Officer • In-house Consultant

20-49

SPA GMI ADP MIE

IAG SYS OTC

AAG

SFL

RES EMS SIN

100-249 20-49 10-19 51-200

50-99 20-49 51-200

51-200

500+

10-19 51-200 51-200

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105

Data Analysis

All interviews were audio recorded and transcribed verbatim. The data was analyzed in accordance with the recommendations and processes proposed by Yin (2011), Miles et al. (2014), and Eisenhardt (1989). Hence, the analysis process was separated into within and cross-case analysis stages. In line with the guidelines from Yin (2011), the within-case analysis followed the steps of compiling, disassembling and reassembling and made use of the coding approach introduced by Miles et al. (2014). Based on the descriptive, interpretive, and pattern codes created in this context, emerging constructs addressing the objective of the explorative interviews could be identified (Coffey & Atkinson, 1996; Henfridsson & Bygstad, 2013; Normann, 2001). The cross-case analysis followed a variable-oriented strategy in order to identify similar notions across cases. The underlying constructs of (1) service, i.e., the application of specialized competences through deeds, processes, and performances for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015; Vargo & Lusch, 2016), (2) resource density, i.e., the amount of information, knowledge, and other resources that an actor has at any given time and/or place to solve problems (Vargo & Akaka, 2012a, 2009), and (3) service innovation and resource density enhancement, i.e., unbundling and rebundling of diverse resources that create novel resources that are beneficial (i.e., value experiencing) to some actors in a given context by means of liquification and unbundleability (Lusch & Nambisan, 2015; Michel et al., 2008; Normann, 2001) were used as key variables to compare findings across cases (Miles et al., 2014). By that, relationships among constructs could be identified abductively (Dubois & Gadde, 2002), thus providing a foundation for the discussion of emergent generative mechanisms that are promising to improve resource density in digitally enabled service systems. 2.3.5

Data Interpretation

Idiographic design knowledge encompasses knowledge that is applicable to a particular problem setting or artifact which devises a course of action that changes an existing situation into a preferred one (Baskerville et al., 2015; Simon, 1996). In the context of digitally enabled service systems, digitally enabled generativity induces

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unanticipated change, albeit not necessarily with a positive outcome. Thus, engineering digitally enabled service systems with beneficial configurations of resources is contingent on controlling generativity. Acknowledging underlying premises in the course of their systematic design and development then demands for identifying and understanding generative mechanisms that lead to this preferred situation. Against this backdrop, this study’s intent is to produce idiographic scientific knowledge (Baskerville et al., 2015) that, when combined with design-oriented goals, can be further developed into prescriptive knowledge contributions. Therefore, the knowledge moment in this study encompasses identifying generative mechanisms that, in the context of digitally enabled service systems, tend to produce a positive outcome of digitally enabled generativity (van Aken, 2004). With applying an abductive reasoning approach, an understanding of the underlying causal structures that lead to beneficial configurations of resources in digitally enabled service systems can be gathered. This allows for inferences on which generative mechanisms are to be taken into consideration as an explanation of this preferred positive outcome. In the vein of the notion of resource density, these mechanisms are then the most parsimonious explanation of enhanced resource densities within these systems (Baskerville et al., 2015; Kuechler & Vaishnavi, 2012; Mueller & Urbach, 2017). Taking the overarching objective of this research into account, i.e., to set a foundation for the emergence of a consistent body of design knowledge for engineering service systems in the digital age, the abductive approach is useful for design theorizing since the purpose of design knowledge is to enable search for a satisfying solution for a given design problem. Thus, the intent of this study is neither to derive a hypothesis from the existing body of knowledge and test it in a closed system (deductive theorizing) nor does it intend to infer a conclusion from an observation in an open system (inductive theorizing) (Gregor, 2009; Lee, Pries-Heje, & Baskerville, 2011); it rather seeks to abductively identify mechanisms as a form of analytical frames that help to articulate ideas and, by that, both classify and characterize phenomena (Mueller & Urbach, 2017; Sæther, 1998). In order to gather an understanding of what mechanisms must exist (Wynn & Williams, 2012) that lead to enhanced resource densities in digitally enabled service

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systems, data analysis was performed with the qualitative data analysis software MAXQDA as suggested by Miles et al. (2014). In accordance with the notion of systematic combining, the analysis can be characterized as going back and forth between theoretical foundations and empirical data, thus creating fruitful crossfertilization (Dubois & Gadde, 2002). The initial analytical framework for identifying generative mechanisms was attuned to the notion of resource density. In this vein, enhanced resource densities in digitally enabled service systems might emerge through the liberation from constraints of the physical world. In more detail, digitally enabled generativity drives dematerialization mechanisms, i.e., liquification and unbundleability, that allow for rebundleability, i.e., the rebundling of activities along the dimensions place (where things can be done), time (when things can be done), and actor (who can do what) (Lusch & Nambisan, 2015; Normann, 2001). Accordingly, place, time, and actor were considered as a priori constructs (Eisenhardt, 1989) for further analysis. Further on, in accordance with the notion of abductive reasoning, the longhand definition of service as well as the conceptualization of innovation within service systems were considered as theoretical constructs to identify a range of potential solutions (Gregor, 2010; Lee et al., 2011) for alternations along the dimensions place, time, and actor that induce the situation of enhanced resource densities. Reverting to the longhand definition of service as the application of specialized competences (knowledge and skills) through deeds, processes, and performances for the benefit of another entity or the entity itself, knowledge and skills, deeds, processes, and performances as well as beneficiary

were

conceptualized

as

dimensions

whose

manifestations

are

interdependent on shifts along the dimensions place, time and/or actor. Acknowledging the facets of innovation in digitally enabled service systems, an initially anticipated resource density that is constrained by the physical world can initially be changed toward an unanticipated, not necessarily better, density level by digitally enabled generativity. It is then the generative mechanisms as sets of multivariate combinations of manifestations along the aforementioned dimensions that lead to an unanticipated resource density that surpasses the imagination or ambition of those who created the service system in the first place. The coding process was conducted in accordance with the notion of systematic combining as introduced by Dubois and Gadde (2002) with the objective of matching

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theory and reality. In this vein, the matching process was characterized by going back and forth between the constructs mentioned above, data from the interviews, and analysis (Dubois & Gadde, 2002). The manifestations along the dimensions elicited above constitute the result of this non-linear, non-sequential, iterative process and provide a ground for understanding the most parsimonious explanation for enhanced resource densities in digitally enabled service systems. In total, 644 quotes were used for grounding the identified generative mechanisms and their subsets of variants. The underlying logic guiding the coding process is illustrated in Figure 5 by means of a cognitive map (Tegarden & Sheetz, 2003).

Study 2: Gathering Design Knowledge – Generative Mechanisms

Constraints of the Physical World

Initially Anticipated Resource Density

109

Digitally Enabled Generativity

Dematerialization Liquification

Unbundleability

Rebundleability Liberation from Constraints

Focus novel dpp

Focus new location/time

Focus new actors Generative Mechanisms

Altered k&S

Initial k&s

Dimension Knowledge and Skills

Initial Location

Altered Location

Initial Point of Time

Dimension Place

Altered Point of Time Dimension Time

Initial dpp

Altered dpp

Novel dpp

Dimension Deeds, Processes and Performances

Initial Actor

New Actor

Dimension Beneficiary

k&s: knowledge and skills dpp:deeds, processes, and performances

Unanticipated Enhanced Resource Density

Figure 5. Cognitive Map for Data Interpretation

Initial Actors

New Actors Dimension Actor

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Knowledge Creation: Advancing Design Knowledge

Results

By gathering insights on past and future digitally enabled innovation endeavors among the 13 cases, three main mechanisms by which enhanced resource density in digitally enabled service systems is accomplished could be identified, that is, three common ways in which the creation of new activities and resources and the development of existing ones creates beneficial configurations of resources. Against the backdrop of providing a knowledge contribution to the knowledge base, these generative mechanisms are promising to embody prescriptive design knowledge for engineering digitally enabled service systems in accordance with the definition by Gregor and Hevner (2013). Applying this notion on a more micro-level view, also the identified generative mechanisms can be conceptualized as knowledge contributions from the point of view of the entity aiming to engineer novel digitally enabled service systems. Hence, in line with the framework provided in Gregor and Hevner (2013), the three sets of mechanisms, as shown in Figure 6, are named (1) Invention (focus novel deeds, processes, and performances), (2) Improvement (focus new location/time), and (3) Exaptation (focus new actors). Place New actor

Exaptation

Extant actor

Deeds, processes, and performances

Improvement Invention

time

Figure 6. Generative Mechanisms Leading to Improved Densities

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2.4.1

111

Invention

According to Gregor and Hevner (2013), the invention process can be described as an exploratory search over a complex problem space that requires cognitive skills of curiosity, imagination, creativity, insight, and knowledge of multiple realms of inquiry to find a feasible solution. Hence, the first type of generative mechanisms involves one actor integrating existing or slightly changed knowledge and skills into novel deeds, processes and performances (Lusch & Nambisan, 2015). The actor makes use of the information being liquefied in the course of digitization and combines this information with his existing or slightly further developed knowledge and skills. Hence, liquification of information triggers the integration of knowledge and skills, thus leading to novel deeds, processes and performances. As shown in Table 7, invention can be differentiated among the dimensions of knowledge and skills integrated in deeds, processes and performances as well as the beneficiary. Table 7. Invention as Set of Generative Mechanisms Existing actors

New actors

as beneficiary of novel

as beneficiary of novel activity

activity Application of

Can existing specialized

existing

knowledge and skills be applied and skills be applied beneficially for

specialized

beneficially for existing actors? new actors?

knowledge and

(MIE)

(ABG, ADP)

Application of

Can further developed

Can further developed knowledge

further developed

knowledge and skill be applied

and skills be applied beneficially for

knowledge and

beneficially for existing actors? new actors?

skills

(SPA, GMI)

Can existing specialized knowledge

skills

(IAG)

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Application of existing specialized knowledge and skills to existing actors The introduction of new digitally enabled service offerings was guided by a clearly defined customer’s need in the case of MIE. Guided by their core competence in the field of temperature management in baking, the firm introduced new services based on the data generated at its customers’ facilities and machines. ‘The core competency of our house lies in factory air conditioning and processes of baking. When a facility is standing sill or is falling out, it is not only annoying and you call the service the next day. Rather, all of the dough being processed in the facility at that point of time is lost. Hence, the initial trigger was a 24/7 monitoring of cooling devices for baking facilities. That was introduced on a remote base several years ago and is working in a broader application field.’ (MIE) Application of existing specialized knowledge and skills to new actors At ABG, it could be observed that the firm aims to apply its knowledge and skills in big data analytics in the field of marine technology to other industrial sectors. ‘Building upon our wealth of experience that we had aggregated over several years, we have started to go into areas beyond shipbuilding by utilizing our Cassandra-database. We aim to focus more on the topic. Not many SMEs have got the experience that we have. Most of them start with something, but do not know where they want to go to.’ (ABG) Building upon data that is liquefied by digitization, ADP is thinking about to approach customers in distinct regions in a new way. ‘I mean, for instance, if we knew in which region more power cuts occur – that is data that is not provided to us. There are empirical approaches needed in order to find out in which city, at what time and how long a power cut occurred. If we would have got this information, we could approach customers in the respective regions with new advertising campaigns and tell them: ‘look, yesterday at half past ten your light has failed.’ We could tell this to our customer. He might not have registered this incident because he has been sleeping and did not know why his computer was driving crazy and where this comes from.’ (ADP)

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Application of further developed knowledge and skills to existing actors SPA is thinking about its role as a producer of sensors and their position in the supply chain of data from a machine in the field to a machine builder. ‘We ask ourselves, where to draw the line. What is the status quo today? Are we solely providing data? Alternatively, we could also pre-process the data for the manufacturer.’ (SPA) GMI outlines its focus on a certain operation system as a thing of the past and stresses the importance of enlarging its operational scope to a broader application context. ‘In the past, we were extremely fixated on Microsoft. However, we see ourselves more and more as a software provider that also works in the area of embedded systems, that also works in other operating system environments, that ultimately has to work way more openly – not just focused on one operational systems base.’ (GMI) Application of further developed knowledge and skills to new actors IAG provided evidence that there is a vision among customers concerning the introduction of platforms that provide data from distinct production facilities to further interest groups in order to offer a marketplace for production facilities. ‘He has a production facility for producing monopiles. These steel tubes are used for carrier systems in offshore facilities, oil rigs or wind power plants. He wants to market his productions facilities on a mall or platform. That is his vision. He wants to offer his capacities on a kind of platform when they are available. There might be a stock market in the future, where you can convert your production task with free capacities to an order via online auctions.’ (IAG) 2.4.2

Improvement

In alignment with the conceptualization of improvement provided by Gregor and Hevner (2013), the main goal behind generative mechanisms fostering improvement is to create better solutions in the form of more efficient and effective deeds, processes and activities in terms of time (when things can be done), and place (where things).

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Hence, generative mechanisms in the context of improvements are constituted by either a shift in time induced by novel insights and knowledge from information that is decoupled, liquefied and modelled in different ways or a shift in location due to technology that allows for altering where deeds, processes and performances take place. The set of generative mechanism to be considered as an Improvement is illustrated in Table 8. Table 8. Improvement as Set of Generative Mechanisms Activity is conducted

Activity is conducted

at another point of time

at another place

Can activity be beneficially conducted at

Can activity be beneficially conducted at

another point of time due to novel insights

another place due to the use of technology?

and knowledge from modeling information? (ABG, SPA, ADP, SYS, MIE)

(OTC, ADP, SYS, MIE)

Activities are conducted at another point of time One example of an improvement is the maintenance scheduling among huge vessels with which ABG has to deal with. Since concomitant activities are part of their core businesses in the area of shipbuilding, the impact of having information decoupled from its physical matters is regarded as an improvement. Hence, the big data analytics conducted by ABG induce a time shift in maintenance operations among different types of ships. ‘The topic of predictive maintenance is not new in this area. You are not waiting for one year passing by. You are collecting the respective data and evaluate if maintenance is needed earlier or later. These are the cost savings that could bill into the millions when a cruise ship can be on tour for one more year.’ (ABG) Closely connected to the topic of maintenance, SPA sheds light on the provision of spare parts that could be adjusted according to data that is liquefied from the sensors

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being installed in the machines and provided to customers by a machine builder. Here, also a time shift becomes evident. ‘If we had access to it (the data), we would know that customer XY needs spare parts at a certain point of time. Then we could, for instance, stockpile our devices in our production and warehouses. We would know during production, how the need looks like. That would be an advantage. […] We would know earlier about the demand and could react by adjusting our production because we need more sensors from the type XY.’ (SPA) Activities are conducted at another place In case of operations that have to be conducted directly on site at the customer’s facilities, OTC puts the ubiquitous availability of data via ICT into focus which underlines the foundational premise of digitization – liberating information from physical matter in order to be moved about. ‘I can drive out to the customer and via iPad or something like that, I get direct information, have access on numbers and dedicated areas.’ (OTC) In one of its projects, ADP is part of a system that controls the power supply of universities throughout Germany which enables the firm to react in real-time and without geographical constraints on circumstances occurring on site. However, ADP also mentions that certain knowledge and skills are needed in order to make sense out of the data. ‘When I would go to my laptop right now and get access to the University of Erlangen – I can do that, I have a VPN connection to prevent hacking attacks – I can have a look at the UPS (uninterrupted power supply), I can have a look at the data, I can have a look at every single battery, I can see which voltage, internal resistance, which temperature they have. That means, I can go through all these systems and tell you the state of health of the system. […] Based upon this information, we can decide whether one our workers is told to get pack his bags immediately or whether we can say ‘something is coming up in three to four weeks, we have to be there beforehand’ […].’ (ADP)

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Such an access on facilities in the field, independently of geographical constraints, also becomes apparent in the cases of SYS and MIE. Although these firms are from different industrial sectors, getting access to information is conducted similarly to some extent. ‘The biggest advantage of digital production is that you basically could access all data and could intervene in case of little aches and pains or just define new intervention limits. In case of the money production systems, we have unlimited access […].’ (SYS) ‘[…] A station tells us, in which state it is, in order to be able to take action preventively. From our point of view, this can ensure a broad reliability among the facilities. This plays a great role for our customers.’ (MIE) 2.4.3

Exaptation

Gregor and Hevner (2013) revert to biological evolution to characterize the notion of exaptation. Thus, exaptation is the adaptation of a trait for a different purpose from its original purpose. Drawing on an example from bird evolution, Gould and Vrba (1982) introduce the exaptation of bird feathers to the purposes of flight from the original purported purposes of bodily temperature regulation. In this vein, exaptation encompasses different ways of how various actors can take part in activities they were formerly not applying their knowledge and skills into. Generative mechanisms of the exaptation type thus alter the dimension of actors, i.e., who performs an activity, in order to enhance the resource density in the service system to be engineered. Guided by this, exaptation is conceptualized as a shift of actors that are integrating their knowledge and skills in a certain activity as illustrated in Table 9.

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Table 9. Exaptation as Set of Generative Mechanisms Actor with inferior specialized knowledge and skills is shifted to formerly unconsidered activities

Actor with superior specialized knowledge and skills is shifted to present activities

Can knowledge and skills be beneficially applied for enabling Actor with inferior actors with inferior knowledge knowledge and and skills to take over formerly skills is enabled to unconsidered activities? take over activities (ABG, SFL, SYS, RES, EMS, IAG)

Can knowledge and skills be beneficially applied by actors with superior knowledge and skills to take over present activities?

Can knowledge and skills be Actor with inferior beneficially applied for supporting actors with inferior knowledge and knowledge and skills is supported skills to be shifted to formerly unconsidered activities? in activities

Can knowledge and skills be beneficially applied by actors with superior knowledge and skills to support present activities?

(ADP, MIE, SYS)

(ABG, IAG, AAG, MIE)

(MIE, GMI, IAG, SIN)

Actor with inferior knowledge and skills takes over formerly unconsidered activities. In terms of incorporating actors with an inferior degree of knowledge and skills in the course of conducting a certain activity, one statement provided by AAG helps outlining the concomitant situation in complex environments such as manufacturing: ‘[…] the machine operators that operate a facility have no clue about vibration engineering. Even most of the machine builders that build facilities for 5 million do not have any clue about vibration engineering.’ (AAG) Arising from this issue, firms aim on making the information, liquefied within the course of increasing digitization, available and usable for further actors with inferior

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knowledge and skills. Some of the firms state that they want to enable their stakeholders to conduct certain activities on their own or to let it be done by further actors in order to ensure maximum resource density. In terms of analyses, ABG and SFL shed light on reducing the complexity of information for respective stakeholders. ‘What he wants is, with as less as applications possible, just with some clicks, without our help, to determine where the shoe pinches. […] At the moment when clicking is not working anymore, he comes back to us in our role as extended work bench and tells us which add-ons he would need.’ (ABG) ‘Simple user interfaces. That means to depict that what the customer wants with few parameters, instead of providing the whole complexity comprised by a company. The focus shall be laid upon understanding and compiling the problem internally in order to provide a manageable sample of variations to the customer.’ (SFL) In order to realize maximum resource density, also thinking about the potential of substituting actors seems natural among the interviewees from SYS, RES, EMS, OTC, e.g., by putting technology in place. ‘Actually, the biggest value creation for the customer lies in saving personnel, for instance when the people can focus on things that are more important.’ (SYS) ‘Our focus is to optimize processes. That means that all handling and inserting functions where employees are in charge could be fulfilled by robots.’ (OTC) ‘We could also develop that further and substitute the guy with an optical sensor.’ (RES) ‘[…] and the expensive employee just has to deal with exceptions.’ (EMS) However, these developments are not only driven by the goal of generating cost savings. IAG also mentions the shortage of skilled workers as a trigger for actor shifts. ‘Even if I want to, I do not have these experienced people that listened to the machines, stroked them and refilled a bit of oil to make it run again – figuratively spoken. […] When they retire, I have to handle the business with less people which have to become more efficient.’ (IAG)

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Actor with inferior knowledge and skills is supported in formerly unconsidered activities. Another approach that enables a shift towards other actors that conducts a certain activity is constituted by guiding them through its underlying process steps, as outlined by ADP: ‘We have partners that also sell our products. We conducted a first-level training with them in order to prepare them for the easy things to be done, e.g., battery changes and so on. When it goes more in-depth, we are there as a backup for them. […] This topic can be transferred to the extent that you put a movie on your iPhone, send it to them and tell them: ‘you have to twist this screw, it is all about that parameter’.’ (ADP) When thinking about the technologies underlying digitization, this process can also be conducted in a more automated manner where the user can be involved to a varying degree. ‘[…] We have so called fixed control systems with a keyboard and typing, there are touch screens and even well-developed user interfaces that provide a very good user guidance. What can done with that? For instance, you can lead the user through the process. You can do that either do that with the device on site or arrange that via a remote solution.’ (MIE) Still, in some cases, it was found that the initial actor wants to keep his self-reliance when it comes to enable the firm to take over activities. ‘Preventive maintenance systems are already in use on our behalf. However, they can only establish a connection when the customer grants access […]’ (SYS) Besides paving the way for shifting activities to actors with a lower degree of knowledge and skills, also the need for assigning activities to actors with further developed competences seems beneficial to enable maximum resource density.

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2.4.3.1 Actor with superior knowledge and skills takes over present activities. In case of ABG, the firm makes sense out of the information provided to them and takes over the role of an “extended workbench”. ‘A ship is equipped with automation technology by a general contractor, e.g., Siemens, that is using our tools and our know-how. […] There is surely no shipping company that does not own its own mechanical engineering department that makes predictions for maintenance cycles based on this data (e.g., excessive temperature). In earlier times, the machine operator decided that with gut instinct. […] All this data is aggregated and statistics are derived. Then, a know-how carrier, surely not us, but a machine builder on site takes that and says: ‘okay, here we need maintenance.’ […] Also in the future, we see ourselves as an extended workbench. […] That is closely connected to the topic that, with our current structure, we are not able to cover a lot of parts within that service. However, when it comes to this small part of the extended workbench: we can do that better than anyone else.’ (ABG) Similarly, IAG mentions: ‘I could imagine, a bit visionary, that we would have a small cluster server and we say: we take over the data hosting and provide a platform where you as a machine builder could log yourself in and conduct your service concepts with your own IT systems. We cannot conduct the service concept per se, because in the end, you need a certain infrastructure when the point is reached to exchange a spare part. However, I can determine which occurrences are to be regarded as critical and have to be shared or which occurrences are uncritical. So, we actually take over the role of a pre-filter.’ (AAG) In the same vein, AAG sees itself with a unique core competence in vibration control technology. ‘In this area, we closely work together with the University of HAN. They have an institute for vibration theory. I do not know a better institute in Germany. […] Hence, we are really heading to go deeper into that topic, because the machine operators that operate a facility have no clue about vibration engineering. Even most of the machine builders that build facilities for 5 million do not have any clue about vibration engineering. Following the

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slogan, the more the merrier, something is done that goes down the drain and something is not working. And then: ‘Your stuff is not working. Do something!’ Therefore, it is interesting for us to determine proactively when changes occur during operation.’ (AAG) A further example of a shift of activities towards an actor with superior knowledge and skills is mentioned by MIE: ‘One or another says: ‘Actually, my IT department is fully engaged. We do not want to deal with that stuff. Just analyse the data for us and send us a weekly report. The report is enough to draw our conclusions. We do not want to deal with that data jumble.’ (MIE) Actor with superior knowledge and skills supports present activities. The interviewees also mention the role of competences in the area of intermediaries as a crucial factor for enabling new value propositions in the context of digitization. Here, especially competences in the field of ICT are regarded as crucial as MIE states: ‘We have introduces our first apps for remote control, remote monitoring and for flow monitoring on site of the customer. Therefore, we, of course, have brought in externals that are specialized in app development.’ (MIE) Other interviewees especially address this issue and integrate their knowledge and skills when it comes to the underlying technological issues of digitally enabled innovation. ‘We are more challenged to support our customers with the interconnection of various systems, i.e., our systems with external systems, because there is a lot of catching-up to do on behalf of our customers.’ (GMI) ‘[…] we can say that we leverage the data, independently of their origin, and make them all look similarly.’ (IAG) ‘On the one hand, we can conduct the app development because we have everything in place, but on the other hand, we can also just enable the flow of data.’ (SIN)

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Discussion

Digitally enabled generativity bears the potential to forge new social connections that open up innovation opportunities (Lusch & Nambisan, 2015; Tilson et al., 2010). However, although the notion of generativity is identified as an essential driver for service innovation (Barrett et al., 2015), scholars and practitioners struggle to understand and describe how underlying generative mechanisms give birth to the dynamic changes of emergent novel service systems in this context (Herterich, Eck, et al., 2016; Lusch & Nambisan, 2015; Nambisan, 2013; Yoo, 2013). This study addresses this issue by providing a novel lens to identify generative mechanisms fostering digitally enabled generativity (Yoo, 2013) in service systems, i.e., digitally enabled service systems (Herterich, Eck, et al., 2016; Yoo et al., 2010). Drawing on the notion of resource density as one of the most potentially enriching concepts for understanding service and service innovation (Lusch & Nambisan, 2015; Michel et al., 2008; Normann, 2001), these mechanisms tend to produce enhanced resource densities in service systems (Lessard, 2015; van Aken, 2004) and thus are promising for providing prescriptive design knowledge (Gregor & Hevner, 2013) for engineering service systems in the digital age (Böhmann et al., 2014a). Drawing on a rather traditional view of service that emphasizes dyadic one-to-one encounters (Chandler & Lusch, 2015), invention deals with a service provider introducing novel deeds, processes and processes for the benefit of a beneficiary, whereas improvement leads to altering these activities, and exaptation fosters the shift towards other actors that take them over. However, a systems perspective on service and service innovation demands accounting for the multiple actors contributing to one another’s service systems (Böhmann et al., 2014a; Chandler & Lusch, 2015) which leads to the notion that the generative mechanisms identified within the scope of this study have to be put into the context of systems of service systems (Lusch et al., 2010; Patrício, Pinho, et al., 2018; Pinho et al., 2014). The configuration of how these generative mechanisms can be applied in multi-actor contexts is envisioned in Figure 7.

Study 2: Gathering Design Knowledge – Generative Mechanisms

Service Provider n

Invention – extant actor, novel dpp Existing k&s in novel activities for new actors

Further developed k&s in novel activities for existing actors

Further developed k&s in novel activties for new actors

Existing k&s in novel activities for existing actors

Improvement – extant actor, altered dpp Another point of time due to information modelling

Another place due to technology use

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k&s: knowledge and skills dpp:deeds, processes, and performances

Exapation – novel actor in dpp Actor with inferior k&s takes over formerly unconsidered activities

Actor with superior k&s takes over present activities

Actor with inferior k&s is supported in formerly unconsidered activities

Actor with superior k&s supports present activities

Beneficiary n Service Provider n+1

Invention – extant actor, novel dpp Existing k&s in novel activities for new actors

Further developed k&s in novel activities for existing actors

Further developed k&s in novel activties for new actors

Existing k&s in novel activities for existing actors

Improvement – extant actor, altered dpp Another point of time due to information modelling

Another place due to technology use

Exapation – novel actor in dpp Actor with inferior k&s takes over formerly unconsidered activities

Actor with superior k&s takes over present activities

Actor with inferior k&s is supported in formerly unconsidered activities

Actor with superior k&s supports present activities

Beneficiary n+1

Figure 7. Generative Mechanisms in a Systems of Service Systems Context

Drawing on this worldview, especially invention provides a means for an actor (Service Provider n) to apply his existing or further developed skills in novel activities for the benefit of new actors from his point of view. Reverting to the notion of generativity in this context, unanticipated change is achieved on behalf of the beneficiary since his service system is evolving into directions that were initially unimaginable (Eck & Uebernickel, 2016; Woodard & Clemons, 2014). Hence, invention leads to novel activities in which an actor (Service Provider n) is capable of applying

his knowledge and skills for the benefit of further actors in various configurations: (1) directly for the benefit of an actor (Service Provider n+1 or Beneficiary n+1), or (2)

indirectly in terms of applying his knowledge and skills in activities relevant in the context of improvement or exaptation for the benefit of the actors relevant for these generative mechanisms (Service Provider n+1 or Beneficiary n+1), or a combination of (1) and (2). By that, a controlled generativity (Eaton et al., 2015) from the point of view of the focal actor is achieved. For the sake of simplicity, this relational construct is

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limited to n = 1 in Fig. 1. For n > 1, invention among further actors (currently grayed out) has to be considered, albeit leading to reciprocity and recursiveness among resulting constructs which, in turn, cannot be considered in this context. Invention, improvement and exaptation constitute “principles of function” (Gregor & Hevner, 2013) that provide the instructions for performing the goal driven activity of supporting the engineering of digitally enabled service systems by considering the underlying notions of generativity in the context of this systems through the lens of the concept of resource density. Hence, according to the framework for characterizing knowledge contributions provided by (Gregor & Hevner, 2013), a method is introduced that addresses the research question dealt with within the scope of this study. Taking into account the overall aim of this dissertation, i.e., the development of design knowledge relevant for a prospective body of knowledge for engineering service systems in the digital age, the generative mechanisms identified within the scope of the study could be enriched by foundations from scientific theories and methods or meta-artifacts (Hevner, 2007; Iivari, 2007). Such a grounding can be achieved

by

incorporating

knowledge

contributions

fostering

the

further

operationalization of principles concomitant with the generative mechanisms identified within this study; for instance in terms of the role of data or information that is liquefied and modeled for various actors (e.g., Lim and Kim (2014), Schüritz et al., (2017), Tempini (2017), Lim et al. (2018)) or concerning the multitude of actors and their roles being joined by service over time and space (e.g., Ekman, Raggio, & Thompson (2016), Grenha Teixeira et al. (2016), Sampson (2012)).

2.6

Contribution and Conclusion

This research applied a qualitative explorative approach in the context of a holistic multiple case study (Miles et al., 2014; Yin, 2003) in order to identify generative mechanisms that bear the potential to lead to enhanced resource densities in digitally enabled service systems. The three identified sets of generative mechanisms stem from an understanding of digitally enabled generativity in service systems that is grounded in the notion of the dematerialization mechanisms introduced by Normann (2001), i.e., liquification and unbundleability. With this being one of the most potentially enriching concepts for understanding service and service innovation (Lusch & Nambisan, 2015;

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Michel et al., 2008), the sets of mechanisms identified, i.e., invention, improvement, and exaptation, embody design knowledge that is promising to be incorporated in the course of designing and developing service systems that are attuned to the premises of digitally enabled generativity (Böhmann et al., 2014a; Lusch & Nambisan, 2015; Yoo, 2013). The novelty of the resulting method (Gregor & Hevner, 2013) thus is constituted by taking the service system as the basic unit of analysis which addresses the paradigm shift concomitant with an increasing service logic among private and public organizations (Ostrom et al., 2015). Especially by operationalizing the notion of resource density (Normann, 2001) and putting it into the context of digitally enabled service systems, the resulting opportunities for innovation in these systems are specifically addressed. This constitutes a departure from extant research in fields such as service engineering with an inherent product-centric-thinking (Böhmann et al., 2014a). Moreover, as Menschner and Leimeister (2011) state, there is a lack of approaches specifically dealing with the role of knowledge and information in the course of developing new services. By adopting the view of resource density (Normann 2001; Lusch & Nambisan, 2015) to understand the underlying mechanisms of digitally enabled generativity (Yoo, 2013) in service systems, the resulting artifact, i.e., the generative mechanisms invention, improvement, and exaptation embody a method that deals as exaptation type of DSR knowledge contribution (Gregor & Hevner, 2013). This research work contributes to the knowledge base in terms of introducing generative mechanisms that support the systematic and structured engineering of digitally enabled service systems. Furthermore, a contribution is made by elaborating on the question of how the generativity of a system can be managed for competitive advantage in terms of providing a lens for understanding the disruptive changes concomitant with digitally enabled generativity (Woodard & Clemons 2014; Yoo, 2013). Hence, as a departure from grounding design knowledge for engineering digitally enabled service systems in intuition and experience (Hevner et al., 2004), this study contributes to the overall dissertation in terms of complementing the extant body of knowledge with knowledge on “principles of function” (Gregor et al., 2013) that provide the instructions for performing the goal driven activity of supporting the engineering of digitally enabled service systems. By that, knowledge is produced that is promising to allow for prescriptions of guidelines for prospective artifacts in this context.

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Study 3: Ingraining Design Knowledge – A Method

As Study 2 predominantly allowed for prescribing principles of function to be acknowledged for engineering digitally enabled service systems, the intend of study 34 is to shed light on the operationalization of applicable underlying foundations. Thus, beside dealing with principles of function, this study makes use of knowledge extracted from Study 1 on how to structure according development activities in a systematic way and further applicable contributions from the knowledge base in order to develop an artifact, i.e., a method (Brinkkemper, 1996; Gregor & Hevner, 2013), that provides an operational view on service system analysis and design (Alter, 2012; Böhmann et al., 2014a). The respective method addresses a multitude of facets of artifacts capable to support the systematic development of digitally enabled service systems, together with ingraining prescriptive knowledge from Study 2. Hence, the initial design of the method is guided by a set of ten requirements derived from applicable foundations in the problem context and is comprised of four building blocks that, in turn, encompass methods and activities on a more fine-grained level. The interplay of these building blocks, i.e., CVC, Job Map, Service Blueprint, and LiCoDi, is defined by an overarching meta-model and is attuned to the overall aim of engineering digitally enabled service systems by means of enhancing inherent resource densities along the dimension of time, space, and actor (Lusch & Nambisan, 2015; Normann, 2001). The initial design of the artifact is then evaluated in accordance with the Human Risk & Effectiveness evaluation strategy introduced by Venable, Pries-Heje, & Baskerville (2016). Within the evaluation trajectory, an artificial-formative evaluation is combined with four cycles of naturalistic-formative evaluation settings under consideration of a set of dedicated evaluation criteria (Peffers et al., 2012; Prat et al.,

4 An early version of this research has been presented at the European Academy of Management (EURAM) 2017 conference in Glasgow, United Kingdom. A further developed version has been presented at the International Conference on Information Systems (ICIS) 2017 in Seoul and was published in the conference proceedings as Höckmayr and Roth (2017). The current version is based on the work presented at ICIS, but thoroughly ingrained the feedback from the fruitful discussions at the conference.

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2014, 2015; Sonnenberg & vom Brocke, 2012b; Venable et al., 2016). The evaluation shows that the resultant artifact – referred to as meThod foR engIneerinG diGitally Enabled seRvice systems (TRIGGER) – broadly addresses the requirements inherent to digitally enabled service systems, but that it needs refinement in terms of its direct applicability. Hence, in the vein of the overall dissertation, a contribution is made in terms of providing design knowledge for engineering digitally enabled service systems that is rooted in real-world applications (Böhmann et al., 2014a). By that, metaphorically spoken, a recipe to perform the task of systematically designing and developing these complex systems is contributed to the knowledge base (Gregor & Hevner, 2013; Hevner et al., 2004). The remainder of this study proceeds as follows. First, an introduction to the problem context is provided, together with elaborating on the research objective guiding this study. Second, the theoretical foundations underpinning the initial design of the method are described. Afterwards, the research approach is introduced. Next, the method is derived and its initial design described. In the subsequent section, the results of the evaluation cycles are presented. The study ends with a discussion and conclusion, incorporating implications for future research.

3.1

Purpose and Scope

A major topic in service innovation literature deals with the question of how these services are innovated, that is, the process of developing new services. It is argued that services must be planned systematically in order to be successful (de Brentani, 1995; Ramaswamy, 1996). This structured view regards services as units of output and conceptualizes the service innovation process as rational and sequential, distinguishing between phases such as idea generation, idea assessment, design, testing and validation, and market launch (Bowers, 1989; Scheuing & Johnson, 1989; Skålén, Gummerus, von Koskull, & Magnusson, 2015). In this context, service engineering (SE) proposes models, methods and principles to engineer individual services (Satzger et al., 2010), often adapting approaches from product and software engineering for this purpose (Bullinger et al., 2003). By that, SE has advanced the industrialization of services (Böhmann et al., 2014a; Karmarkar, 2004).

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More recently, Alter (2012), Maglio et al. (2009) and Satzger et al. (2010) propose that research on service should adopt a systems perspective. Instead of "delivering" a service, such a systems perspective emphasizes the notion of value creation being guided by a value proposition and enabled by a configuration of resources, with actors and information to be considered as playing a key role (Böhmann et al., 2014a; Maglio et al., 2009). However, as Menschner, Peters, & Leimeister (2011) have shown, extant service engineering approaches most often lack an information or knowledge-based perspective or do not possess a suitable level of granularity for engineering complex information-centric service offerings. In this context, research on service systems engineering (Böhmann et al., 2014a) constitutes a departure from traditional SE research by recognizing service as a collaborative process that creates context-specific value (Edvardsson et al., 2011; Vargo & Lusch, 2004), together with adopting a systems perspective that acknowledges the variety of stakeholders in this multi-sided value logic (Benkler, 2006; Blau et al., 2009; Maglio et al., 2009). This mindset drives the understanding of service systems towards more precise models of service systems that are attuned to design and operations (Alter, 2012). The ubiquitous availability of data and vast opportunities for automation extend the playground for service systems innovation significantly (Böhmann et al., 2014a). In particular, digitally enabled generativity is promising to create diverse innovations that are often not anticipated by those who designed the service system in the first place (Eaton et al., 2015; Zittrain, 2006). To date, however, there is a lack of approaches that deal with the engineering of according digitally enabled service systems based on an operational view on service systems analysis and design (Alter, 2012, 2013; Böhmann et al., 2014a). The research question within this study addresses this gap by acknowledging the need for approaches that aim for providing a systematic process for developing novel service systems and recognize the opportunities for innovation opened up by digitally enabled generativity. Hence, the following research question is drawn: How can digitally enabled service systems be developed systematically and in a structured manner?

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This research question is answered by applying a design science research (DSR) approach following Hevner et al. (2004) to design a method for engineering digitally enabled service systems. This method incorporates the assumptions that arise from the way service innovation in the digital age is conceptualized, with a focus on how constraints in current or future service systems can be overcome systematically - which is referred to as ‘liberation from constraints by digitization’ (LiCoDi). Against this backdrop, the initial design of the respective artifact was applied within an illustrative scenario, and two evaluation cycles were conducted according to the Human Risk & Effectiveness-oriented evaluation strategy proposed by Venable et al. (2016). By answering the research question in terms of designing and evaluating a method that supports the development of digitally enabled service systems, a contribution is made to the knowledge base dealing with the engineering of digitally enabled service systems.

3.2

Background

As stated by Böhmann et al. (2014a), service logic has diffused increasingly into academic theory and business models. Hence, there is a growing awareness of servicerelated contributions across disciplinary boundaries (Fielt et al., 2013) as well as increased openness to the publication of interdisciplinary work related to service research (e.g., Barrett et al. (2015), Huang and Rust (2013)). On the one hand, the work provided within this study picks up that notion and aims to incorporate various promising views for understanding the underlying premises of digitally enabled generativity and its role in service-centric business models and strategies. On the other hand, it also considers an operational view, inspired by the notion of SSE, when it comes to the service innovation process that leads to novel service systems. 3.2.1

Digitally Enabled Innovation – A Systems Perspective

In order to address the implications derived from increasing digitally enabled innovation in today’s businesses, new perspectives on value creation are needed (Matzner et al., 2018). Against this backdrop, in order to address the larger constellations within which actors become joined by service over time and space, a

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systems perspective has more explanatory power than a singular, entity-level perspective, that may focus only on service customers or providers (Spohrer et al., 2008). The service system, therefore, provides an ideal analytical framework and unit of analysis for rethinking value and the way in which it is created (Breidbach & Maglio, 2016; Maglio & Breidbach, 2014; Vargo et al., 2008). According to Breidbach and Maglio (2015), service

innovation can then be conceptualized as service system

reconfiguration. A service system is composed of multiple entities that interact to cocreate value. Service system entities are composed of a variety of resources and share access to their resources within value networks, i.e., constellations of connected service systems (Breidbach & Maglio, 2015; Spohrer & Maglio, 2010; Vargo, Lusch, & Akaka, 2010). Service systems provide the ability to integrate and apply resources within a specific context. By considering the improvements derived from the integration and application of resources, value emerges in the use or application of resources (Lusch & Vargo, 2006). Thus, value can be defined as service system improvement, which is contingent on the evolution of the system itself (Breidbach & Maglio, 2015; Maglio & Spohrer, 2013; Spohrer et al., 2008; Vargo et al., 2008). 3.2.2

Digitally Enabled Innovation – An Activity Perspective

Reverting to the longhand definition of service, i.e., the application of specialized competences (knowledge and skills) through deeds, processes, and performances for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015; Vargo & Lusch, 2016), the lens of resource density as introduced by Normann (2001) is promising to address the mechanisms underlying innovation in digitally enabled service systems. Along these lines, improved densities are achieved by rebundling diverse resources, creating novel resources beneficial (i.e., value-experiencing) to some actors in a given context, which can then be conceptualized as innovation in service systems (Lusch & Nambisan, 2015). Although maximum density is referred to as the best combination of resources mobilized for a particular situation to create the optimal value/cost result for a customer, this theoretical maximum never exists (Lusch et al., 2010). As sounded out in Study 2, however, by acknowledging generative mechanisms in the course of engineering digitally enabled service systems, novel densities can be created:

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Actor-based service system reconfiguration (Exaptation) entails new knowledge and skills being integrated into existing or slightly changed deeds, processes, and performances. Guided by this, actor-based service system reconfiguration is conceptualized as a shift of actors that are integrating their knowledge and skills into a certain activity. This can take place in two ways: either, actors with inferior knowledge and skills can be incorporated via information that enables them to act as an actor within an activity, or actors with a higher degree of knowledge and skills suitable for taking over a certain activity. Adaptive service system reconfiguration (Improvement) entails a firm’s existing or slightly developed resources being integrated in new ways into existing or slightly developed deeds, processes, and performances. The scope of service system reconfiguration is thus modest. Small stepwise changes may lead to extensive changes over time. Hence, adaptive service system reconfiguration is defined by a shift in time and place in the course of conducting certain activities. Activity-based service system reconfiguration (Invention) involves integrating existing or slightly changed knowledge and skills into new deeds, processes, and performances. Firms make use of the information being liquefied by digitization and combine this information with their existing or slightly further developed knowledge and skills in order to introduce new activities. Hence, liquification of information triggers the integration of knowledge and skills as crucial resources leading to new activities among firms.

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Research Method

Grounded in the pragmatic-design view (Hevner & Chatterjee, 2010; Hevner et al., 2004; March & Smith, 1995; Nunamaker Jr. et al., 1991), within this study, an established DSR approach (Hevner et al., 2004) is applied. In this vein, DSR is primarily regarded as a problem-solving paradigm (Hevner et al., 2004) that seeks to create artifacts addressing so-called wicked problems (Pries-Heje & Baskerville, 2008). The wicked problem within this study is the research question presented above. By addressing this problem utilizing DSR, this research aims to produce an artifact in the form of a method (i.e., the solution space) to help firms to develop digitally enabled services in a systematic manner. In the course of developing an artifact, building and evaluation constitute central activities (Hevner et al., 2004). The building process deals with constructing an artifact for a specific purpose, whereas the evaluation process determines the quality of the constructed artifact (Hevner et al., 2004; March & Smith, 1995). The evaluation of the artifact then provides feedback information and a better understanding of the problem which acts as a foundation for improving both the quality of the artifact and the design process. This build-and-evaluate loop is typically iterated a number of times before the final design artifact is generated (Hevner et al., 2004; Markus et al., 2002).

3.4

Artifact Development

In terms of the initial building process of the artifact within this work, applicable design requirements are governed by the theoretical foundations presented above (Walls et al., 1992) and thus serve as justificatory knowledge (Gregor & Hevner, 2013) that gives a basis and explanation for the resulting initial design of the artifact (Gregor & Jones, 2007; Pries-Heje & Baskerville, 2016). Since the evaluation of design artifacts is considered to be a central and critical part of DSR (Hevner et al., 2004; March & Smith, 1995), the build phase was combined with two evaluation phases. Within this context, Venable et al. (2016) propose a framework for developing an appropriate evaluation strategy. Building upon that, the evaluation strategy within this work is Human Risk & Effectiveness-oriented. As a result, after an initial artificial, formative

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evaluation, the artifact is evaluated in a naturalistic setting at an early point in the evaluation trajectory (Venable et al., 2016). Details on the particular evaluation design and results are provided in the respective sections. 3.4.1

Requirements Elicitation

The requirements for the initial design of the artifact are derived from the theoretical background elaborated in 3.2.1 and 3.2.2, together with acknowledging the underlying premises of SSE as a paradigm that focuses on the systematic design and development of service systems. For this purpose, a framework is developed that represents the requirements the artifacts is adjusted to. Generally, a framework is derived from existing contents and research results, whereby relevant components are extracted from current work and related to each other in an appropriate way (Berkovich, Leimeister, & Krcmar, 2011). Within this context, the task is not only to illustrate the subject area, i.e., SSE in the context of digitization, but also to explicitly present the knowledge and assumptions underlying the requirements elicitation (Goeken & Patas, 2010). A prerequisite for this procedure is that there is an explicit agreement on the present subject in research, which can be explicitly captured through the framework. According to Berkovich et al. (2011) and Goeken and Patas (2010), the framework as such has to fulfil the following requirements: (I) the framework should depict essential components of a method for developing digitally enabled services; (II) the framework should reflect all relevant relations between the components; (III) the relations between the components should be scientifically substantiated. Hence, the requirements for a method that supports the development of digitally enabled service systems are derived from the premises of (1) a systems perspective on service and service innovation, (2) an activity perspective on service innovation, with (1) and (2) being directly driven by the nature of (3) digitally enabled service systems. Furthermore, requirements can be derived from (4) SSE as an approach for systematically developing novel service systems. Based on these four central elements, a set of requirements can be developed and translated into applicable goals. In accordance with Hickey and Davis (2004), these a priori requirements then provide a

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ground for the further development of the artifact from a functional point of view (Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007). As elaborated above, the service system provides an ideal analytical framework and unit of analysis to address the larger constellations within which actors become joined by service over time and space in the context of today’s global, digital, service-oriented economy (Breidbach & Maglio, 2015; Spohrer et al., 2008). Normann & Ramírez (1993) developed the concept of a value constellation, which represents the network of actors and their relationships that jointly create an offering. This value constellation can be viewed as a system of service systems. According to Normann (2001), a firm can

upframe its perspective by understanding the firm’s offering as an input into creating customer value while also considering the inputs offered by other firms. This perspective widens the service design space, enabling companies to creatively design frame-breaking systemic solutions that change the whole value-creating system. Based on this, the following requirements can be derived: R1: The method has to address larger constellations within which multiple actors become joined over time and space. R2: The method has to understand service as service systems, i.e., configuration of resources (including, people, information, and technology), that are connected by value propositions Service means applying specialized competences (knowledge and skills) through deeds, processes, and performances for the benefit of another actor or the actor itself (Vargo & Lusch, 2004). This conceptualization emphasizes the process of doing something beneficial for and in conjunction with some entity, rather than focusing on units of output, i.e., immaterial goods (Vargo & Lusch, 2008b). By separating information from physical matter, these deeds, processes and performances can be broken down into pieces that can be rebundled (Lusch & Nambisan, 2015) which ultimately can be considered as service innovation. The concept of resource density addresses

this

conceptualization

of

service

innovation

by

introducing

dematerialization mechanisms, i.e., liquification (separation of information from the physical world) and unbundleability (separation of activities from time/place/actor),

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that lead to the creation of new densities (Normann, 2001). This leads to a set of further requirements: R3: The method has to acknowledge the role of knowledge and skills that are applied by various actors. R4: The method has to provide a level of analysis that addresses activities, i.e., deeds, processes and performances, in which knowledge and skills are applied. R5: The method has to acknowledge the role of information that is breaking down activities R6: The method has to acknowledge the interrelation of activities that are conducted by an actor at a given time and place. R7: The method has to support the creation of new densities For information to be useful, it must be shared with others. As stated, maximum density occurs when the best combination of resources is mobilized for a particular situation (Lusch et al., 2010; Normann, 2001). With information being a central resource for the creation of new densities, there is a need to mobilize contextually relevant knowledge in the most effective and efficient way (i.e., enhance resource density). In order to generate respective novel insights and knowledge, techniques and algorithms are needed to configure or model information in different ways (Lusch & Nambisan, 2015). Hence, especially in the context of digitally enabled service systems, this places an onus on mobilizing the best combination of information for a particular situation. Thus, a further requirement is: R8: The method has to deal with how information can be modelled for various actors. Research on service systems engineering responds to the paradigm shift associated with service logic and seeks to advance design knowledge for service systems that enhance collaborative and contextualized value creation. Service systems engineering thus calls for systematically designing, developing and piloting service systems, based upon understanding the underlying principles of service systems. Within this context, service engineering research has achieved important conceptual advances. What is missing, however, is design knowledge rooted in the design, implementation, and evaluation of real-world service systems. Hence, novel work should seek to enhance the possibilities for modularization, standardization, contextualization and re-

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configuration of service components and resources, as well as for modeling and simulation of the behavior of service systems and their key actors. Based upon that, the following requirements are applicable: R9: The method has to take the service system as basic unit of analysis. R10: The method should focus on the systematic design and development of service systems. Hence, by recognizing the nature and role of the distinct building blocks that have to be incorporated for the initial design of the method, the requirements listed in Table 10 are elicited. Table 10. Requirements Elicitation for the Initial Design of the Method Foundation

Requirements …from a Service Systems Perspective

Innovation in Digitally Enabled Service Systems

R1: The method has to address larger constellations within which multiple actors become joined over time and space. R2: The method has to understand service as service systems, i.e., configurations of resources (including people, information, and technology) that are connected by value propositions. R3: The method has to acknowledge the role of knowledge and skills applied by various actors.

…from an Activity Perspective

R4: The method has to provide a level of analysis that addresses activities, i.e., deeds, processes, and performances, in which knowledge and skills are applied. R5: The method has to acknowledge the role of information that is breaking down activities. R6: The method has to acknowledge the interrelation of activities that are conducted by an actor at a given time and place. R7: The method has to support the creation of new densities.

…and Knowledge Creation Service Systems Engineering

R8: The method has to deal with how information can be modeled for various actors. R9: The method has to take the service system as the basic unit of analysis. R10: The method should focus on the systematic design and development of service systems.

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3.4.2

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Initial Design of the Method – Building Blocks and Meta-Model

The artifact designed within the DSR process incorporates complementary methods from various research fields at distinct developmental stages. These methods address the requirements derived above to varying degrees and are combined into a metamodel. For an overview, see Figure 8. On the one hand, the systematic development on a systems level is addressed by the customer value constellation (CVC), a method that recognizes that value is co-created within a network of organizations beyond the firm’s boundaries (Patricio et al., 2011). On the other hand, the implications derived from conceptualizing service innovation as breaking down activities, i.e., deeds, processes, and performances, by separating information from physical matter (Lusch & Nambisan, 2015; Vargo & Lusch, 2016) are addressed by developing a method that operationalizes the notion of resource density and its underlying mechanisms (Normann, 2001) on an activity level. It is referred to as method for liberation of constraints by digitization (LiCoDi) (Höckmayr, Genennig, Roth, & Möslein, 2016; Höckmayr & Roth, 2017; Höckmayr, Roth, & Möslein, 2016, 2017; Roth, Höckmayr, & Möslein, 2017) and builds upon the mechanisms presented above, i.e., actor-based service system reconfiguration, adaptive service system reconfiguration, and activity-based service system reconfiguration, and the respective manifestations presented in Study 2. However, the levels of analysis and design in between the CVC (systems level) and LiCoDi (activity level) are rather diverging. Hence, methods are introduced that ensure consistency between these two main building blocks. Here, job mapping and service blueprinting are applied as so-called bridging methods. Following the notion of Brinkkemper (1996), the complementary interplay of the methods then builds a meta model that depicts dedicated development steps to engineer digitally enabled service systems. Within this research, the overarching method is introduced as TRIGGER (meThod foR engIneerinG diGitally Enabled seRvice systems) and structures the application of the method building blocks by means of the sequence described below. However, designing complex service systems requires a holistic systems thinking approach that addresses the interactions between the parts of the service system and thus avoids optimizing one part in isolation without considering the overall system performance (Patricio et al., 2011). Against this backdrop, the notion of systems modelling (Saradhi, 1992) deals as a foundational

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premise for ensuring that the system to be designed addresses its intended purpose and thus contributes to the rigor of the artifact (Hevner et al., 2004). TRIGGER - Systematic development of digitally enabled service systems from a system to activity level

Initial resource density

Customer Value Constellation (CVC)

Job Map

Service Blueprint

Liberation from Constraints by Digitization (LiCoDi)

Identification of firm’s positioning among customers' and value creating stakeholders' service systems

Identification of potentials for service system improvement based upon positioning in CVC

Draft of novel service system according to structured view of job map, including activities, actors, information flows, and technologies

Reconfiguration of service system in order to derive digitally enabled service system with maximum resource density

System level

Bridging Methods

Activity Level

Enhanced resource density

Figure Ų. Overview of the Methods contributing to TRIGGER 3.4.3

Assembly of the Method – Development Activities and Interrelations

In an overarching view, TRIGGER combines the exaptated methods CVC/VCE (Patricio et al., 2011), Job Map (Bettencourt & Ulwick, 2008), and Service Blueprint (Lim & Kim, 2014) with LiCoDi, i.e., a newly developed method in the context of this research that is based on the mechanisms identified in Study 2 and further extant knowledge contributions (Höckmayr, Genennig, et al., 2016; Höckmayr & Roth, 2017; Höckmayr, Roth, et al., 2016; Höckmayr et al., 2017; Roth et al., 2017), and defines their interplay. Hence, this research develops a twofold prescriptive knowledge contribution: on the one hand, the novelty of TRIGGER is constituted by extending and refining the already existing methods CVC, Job Map, and Service Blueprint to the new problem context of engineering service systems in the digital age, together with assembling them by means of a consistent meta model. On the other hand, the development of TRIGGER is not only grounded in the exaptation of known design knowledge, but also encompasses the operationalization of the notion of resource density by means of introducing LiCoDi – a unique prescriptive knowledge contribution that makes use of the knowledge gathered throughout this research. The

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characteristics of these method building blocks and how they are attuned to the problem context in this research will be dealt with in the following. Customer Value Constellation (CVC) By broadening the design space beyond the firm’s boundaries with the CVC, the firm can analyze its current service offering and explore new alternatives for repositioning its service concept to enhance its contribution to the value constellation experience (VCE). The VCE is co-created through the interactions between the customer and all organizations that enable a given customer activity. The broader view of VCE is crucial for understanding customer experiences beyond the narrower view of the firm. This helps the firm aiming for engineering its service system to understand the broader context within which customers use their services, opening up new possibilities for service innovation (Grenha Teixeira et al., 2016; Patricio et al., 2011). Accordingly, the notion of a multi-sided value logic is fostered, which posits that value is not only created in a simple dichotomy between the customer and the firm, but involves parallel processes of collaborative value creation with multiple actors that become joined by service over time and space (Böhmann et al., 2014a; Chandler & Lusch, 2015). Hence, from a systems modeling perspective, by elaborating on the firm’s positioning in the CVC, the interaction of the firm’s service system with its environment is addressed in terms of inputs and outputs which, ultimately, constitutes the basic prerequisite for the novel system to be engineered to accomplish its defined work (Saradhi, 1992). Job Map However, the approaches of CVC and VCE do not comprise a dynamic view upon which resources are applied through distinct activities to achieve a dense level of resource integration. Hence, especially when offering new services to support a customer’s VCE, a firm needs to understand what a customer is trying to achieve in the course of a certain activity. Arising from that, there is a need for approaches that drill down to a more detailed view of the intentions behind a customer’s activity in order to derive potentials for service innovation. Here, the approach of job mapping (Bettencourt, 2010; Bettencourt & Brown, 2013; Bettencourt, Lusch, & Vargo, 2014)

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constitutes a method that breaks down the job a customer wants to have done in the context of a certain customer activity into a series of discrete processes. By taking the job to be done underlying an activity out of the customer’s VCE as unit of analysis and breaking this job down into a series of discrete steps, the firm is able to determine which resources can be applied through activities, i.e., deeds, processes, and performances, for the benefit of the customer. Hence, job mapping constitutes a bridge between the broad and high level view of CVC on a systems level and the micro level view of LiCoDi on an activity level. The starting point within job mapping for identifying innovation opportunities is to map out - from the customer’s perspective - the steps involved to get a particular job done (Bettencourt & Ulwick, 2008). In this context, the focus is laid upon identifying incoherencies between the activities conducted on behalf of the customer, the firm, and other supporting stakeholders, i. a. from the CVC, and the underlying job the customer wants to get done. Following the notion of resource density (Lusch & Nambisan, 2015; Normann, 2001) as a measure of the amount of information, knowledge, and other resources that an actor has at any given time and/or place in order to solve problems (Vargo & Akaka, 2012a), these incoherencies are concomitant with a rather low level of resource density. In contrast to that, maximum density occurs when the best combination of resources is mobilized for a particular situation (Lusch & Nambisan, 2015; Lusch et al., 2010; Normann, 2001), which is reflected by the job to be done in this context. Altogether, the ability to get a job done well is rather more valued by the customer than a particular service solution (Bettencourt, 2010; Bettencourt et al., 2014) and thus demands the maximum level of resource density. From a service modeling perspective, mapping the jobs to be done constitutes a prerequisite for “building the right system” (Saradhi, 1992, p. 62). Based upon this validation (Saradhi, 1992), the intended purpose of the novel service system to be developed is captured and can be utilized as an objective demanding the best combination of resources to be mobilized (i.e., enabling maximum resource density). Service Blueprint In order to depict which activities are conducted, or, in the event of a new service offering, planned in order to get the customer’s job done, approaches that identify these

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activities on a micro level are needed. Here, the method of service blueprinting (Shostack, 1984) as developed further by Lim and Kim (2014) acts as a foundational approach to provide a structured view for identifying activities that are suitable to address the respective job steps defined beforehand. The identification and explicit visualization of information interchanges by information production and delivery technologies is fostered, which ultimately triggers an information-oriented thinking (Lim & Kim, 2014). Furthermore, in order to promote a holistic systems thinking in this context, the firm’s positioning in the CVC is again elaborated on within this method building block. In more detail, the actors identified in the CVC that enable the customer activity under consideration on a systems of systems level along the VCE are incorporated into distinct swim lanes within the service blueprint. Particularly when blueprinting a newly to be developed service system, this approach ensures the recognition of all relevant actors and their specialized competences that can be potentially applied through their activities (Lusch & Nambisan, 2015; Vargo & Lusch, 2016). Hence, the service blueprinting approach serves as a means to define the overall system functionality that addresses its intended purpose and thus allows for the demarcation of the system from its environment. This is considered as essential for successful systems modeling and constitutes the foundation for verifying the design of the system, i.e., for building the system right (Saradhi, 1992). Liberation from Constraints by Digitization (LiCoDi) LiCoDi (Höckmayr, Genennig, et al., 2016; Höckmayr & Roth, 2017; Höckmayr, Roth, et al., 2016; Höckmayr et al., 2017; Roth et al., 2017) is then introduced as newly developed method in the context of this research that operationalizes the notion of resource density (Lusch & Nambisan, 2015; Normann, 2001) by means of a systematic and structured approach that utilizes the graphical representation of the service system depicted in the service blueprint. It recognizes the two dematerialization mechanisms that lead to new densities, i.e., liquification and rebundleability, as central method elements for engineering novel digitally enabled service systems. Moreover, the approach utilizes empirically derived mechanisms (LiCoDi mechanisms) that stem from the generative mechanisms identified in Study 2 and guide this process on an activity level in order to achieve a maximum level of resource density. LiCoDi directly

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responds to the level of analysis applied at the recent stage and operationalizes the notion of increased resource density (Lusch & Nambisan, 2015; Normann, 2001) in the development of novel service systems along a set of complementary development activities: (1) liquification of information, (2) identification of information modeling competences, (3) unbundling, (4) rebundling and enhancing resource density, and finally (5) maximizing resource density (see Figure 9). Information Resources

Liquification Activities

Unbundling

Rebundling

Adaptive service system reconfiguration

Liquefied information

Liquification Novel resources

Information

Figure ų. Mechanisms Underlying LiCoDi Guided by the notion of Lusch and Nambisan (2015), innovation in digitally enabled service systems is triggered by liquification. The deeds, processes, and performances through which specialized competences (knowledge and skills) are applied can be broken down and rebundled for improved density by separating information from physical matter (Lusch & Nambisan, 2015). LiCoDi addresses the information-oriented thinking posited in the service blueprint approach by Lim and Kim (2014) in the sense of (1) regarding the information entities relevant for conducting certain activities as ubiquitously available for all kinds of stakeholders, e.g., from the CVC. In other words, information is liquefied and made available in an “information pool”. However, as stated by Lusch and Nambisan (2015), these information entities have to be modeled in different ways so as to generate contextually relevant knowledge in the most effective and efficient way in order to enhance resource density. Hence, the (2) identification and assessment of actors which potentially possess according specialized competences

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(knowledge and skills) in information modeling “information modelers” that could be applied through respective technologies, techniques, and algorithms (e.g., Benaroch (1998), Gruber (1995)) constitutes a further development activity. Furthermore, the notion of (3) unbundling or unbundleability is addressed by negating the causal relations between the activities depicted in the service blueprint. (4) Rebundling, i.e., enhancing resource density, is then conducted by applying the LiCoDi mechanisms mentioned above. Using trigger questions such as: “Is the customer (beneficiary) able to conduct an activity on his own when information from the pool of information is provided to him in the right way? Can I stay passive in general?”, a systematic service system improvement by means of enhancing resource density is achieved. (5) Maximizing resource density then involves mapping the reconfigured service system against the job steps depicted above and ensuring that all relevant actors and “information modelers” are addressed or incorporated. LiCoDi is the last method building block within TRIGGER, and aims to provide a foundation for the further development of a service system with the maximum degree of resource density. It thus contributes to achieving the intended purpose derived from the respective job to be done on behalf of the customer and thus verifies the design of the service system (Saradhi, 1992). This verification, i.e., “building the system right” (Saradhi 1992, p. 62) then ultimately ensures that the resulting design requirements are addressed (Saradhi, 1992).

3.5

Artifact Evaluation

The initial design of the artifact proposed - TRIGGER - deals with the implications for engineering of digitally enabled service systems based on four central foundations (see Figure 1). Furthermore, it incorporates methods for bridging these foundations in a systematic manner. The Human Risk & Effectiveness evaluation strategy chosen within this work emphasizes formative evaluations early on in the process, commencing with artificial-formative evaluations, but progressing quickly to more naturalistic-formative evaluations (Venable et al., 2016). Hence, based on a twofold evaluation approach, in the following sections, the results of an initial artificial-

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formative evaluation of the artifact are complemented by the results from an early naturalistic-formative evaluation. 3.5.1

Artificial Evaluation of the Artifact

As Venable et al. (2016) state, artificial evaluation may be empirical or non-empirical (e.g., logical/rhetorical) and is nearly always positivist and reductionist, being used to test design hypotheses (Walls et al., 1992). Furthermore, in an attempt to better understand why an artifact works the way it does, interpretive techniques may also be used. Even critical techniques may be used, but these generally supplement the main goal of proving or disproving the utility of the artifact at hand (Venable et al., 2016). Artificial evaluation typically includes laboratory experiments, simulations, criteriabased analysis, theoretical arguments, and mathematical proofs (Gummesson, 2000; Venable et al., 2016). 3.5.1.1 Evaluation Design In accordance with Venable et al. (2016), Sonnenberg and vom Brocke (2012) argue that if the artifact is not being applied to some reality, the according evaluation is artificial. They suggest the design specification, i.e., the method introduced earlier within this work, to be evaluated against its correctness and completeness. Hence, this evaluation activity aims to validate the principles of form and function specified during the design activity. In terms of evaluation methods, demonstrations, simulations, and formal proofs (exemplary) constitute suitable approaches (Sonnenberg & vom Brocke, 2012b). 3.5.1.2 Evaluation Results Building upon that, this section provides a criteria-based analysis of TRIGGER, as suggested for artificial evaluation settings by Venable et al. (2012) and Venable et al. (2016) and proven suitable by Berkovich et al. (2011). By means of logical reasoning (Hevner et al., 2004), the fulfilment of the requirements introduced previously among the distinct method building blocks was assessed. The initial artificial-formative evaluation of the artifact provides evidence that the artifact as a whole addresses the

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requirements elicited to a broad extent, but also reveals areas for improvement among the distinct method building blocks. However, to the extent that an artificial evaluation setting is unreal, evaluation results may not correspond to real use (Venable et al., 2016), which is why this evaluation step predominantly deals as precedent-setting for the subsequent formative-naturalistic evaluation cycle. Table 11 summarizes the evaluation and provides an overview of the degree of fulfilment among the method building blocks. Table 11. Artificial Evaluation of TRIGGER by means of requirements elicited Requirements R1: The method has to address larger constellations within which multiple actors become joined over time and space. R2: The method has to understand service as service systems, i.e., configurations of resources (including people, information, and technology) that are connected by value propositions. R3: The method has to acknowledge the role of knowledge and skills applied by various actors. R4: The method has to provide a level of analysis that addresses activities, i.e., deeds, processes, and performances, in which knowledge and skills are applied. R5: The method has to acknowledge the role of information that is breaking down activities. R6: The method has to acknowledge the interrelation of activities conducted by an actor at a given time and place. R7: The method has to support the creation of new densities. R8: The method has to deal with how information can be modeled for various actors. R9: The method has to take the service system as the basic unit of analysis. R10: The method should focus on the systematic design and development of service systems.

●

Completely fulfilled.

◐

Partially fulfilled.

VCE and CVC

Job Map

Service Blueprint

LiCoDi

● ◐ ○ ◐ ○ ◐ ◐ ○ ● ●

○ ○ ○ ◐ ○ ◐ ● ○ ◐ ●

◐ ● ○ ● ● ● ○ ◐ ● ●

◐ ● ● ● ● ● ● ◐ ● ●

○

Not fulfilled.

Larger constellations within which multiple actors become joined by service over time and space (R1) are addressed by TRIGGER to a broad extent, especially at the front

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end stage with the integration of VCE and CVC. However, the Job Map postulates a dyadic understanding of service between the customer and the firm which leads to the notion that this requirement is not fulfilled by this building block. R2 deals with the conceptualization of service systems as configurations of resources, including people, information, and technology that are connected by value propositions. By addressing information entities and technologies that aim to produce and deliver these information entities, the version of the service blueprint introduced within TRIGGER fulfills the according requirement. The same is true for LiCoDi, which deals with the liquification of this information and evaluates the way it can be delivered to new actors conducting an activity by the use of technology. VCE and CVC admittedly comprise a thinking in systems of service systems, but do not drill down to the resources relevant in this context. The Job Map provides a universal structure to describe a job, but does not conceptualize this job as a configuration of resources, which is why this requirement is not fulfilled by this approach. The role of knowledge and skills as a crucial resource in service that is applied by an actor for the benefit of another entity or itself is solely dealt with in LiCoDi. Thus it is the only building block that fulfills R3. A level of analysis that deals with activities conducted by a certain actor is prevalent among all methods, whilst the Service Blueprint and LiCoDi specifically deal with activities that directly contribute to value creation. In comparison to that, VCE and CVC comprise a high level view on activities on various firms’ behalf that support a customer activity. In the context of the Job Map, activities are seen as a means to an end, which is why the underlying jobs to be done are put into focus. Hence, these two methods fulfill R4 only partially. The role of information that is addressed by R5 and the determination of activities along the dimensions of actor/time/place that is addressed by R6 are core to the Service Blueprint and LiCoDi. As with R3, VCE and CVC as well as the Job Map are not capable of recognizing information as a crucial resource, but provide a view that acknowledges that dedicated actors conduct activities in a consecutive order. Based upon this notion, they partially fulfill R6.

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The goal of creating new densities as reflected in R7 is supported by VCE and CVC, as they provide a structured view of the firm’s service system as well as other service systems that support a customer’s activity. Based upon that, a firm can derive a profound decision upon how it reconfigures its service system. Hence, this method is capable of partially fulfilling R7. The Service Blueprint does not fulfill this requirement since it solely provides a graphical illustration of the service system. In contrast to that, LiCoDi is specifically built upon the concept of resource density and the Job Map derives potentials for service innovation by mapping out job steps. R8 addresses the need for modeling information that is liquefied in order to create knowledge among the actors applying their knowledge and skills through activities. This requirement is partially fulfilled by the Service Blueprint, since it provides swimlanes that support a structured listing of actors that are potentially capable of modeling information for the benefit of themselves or another actor. LiCoDi provides mechanisms that specifically deal with how the modeling of information can contribute to the reconfiguration of the service system. However, the type of information which is relevant is looked upon in an unstructured manner. Here, there is a need to give guidance upon which information layers are suitable for generating knowledge among the various actors involved. SSE places the onus to take the service system as the basic unit of analysis (R9) and to focus on the systematic design and development of service systems (R10). In an overarching view, these requirements are largely fulfilled by TRIGGER. Here, the Job Map denotes a mitigation, since it neither acknowledges the larger constellations of actors that are joined by service, nor provides a view that reflects the abstraction of value creation as service systems. 3.5.2

Naturalistic Evaluation of the Artifact

After having conducted the first evaluation by means of a formative-artificial approach, the evaluation strategy chosen within this study – ‘Human Risk & Effectiveness’ – demands that the artifact is evaluated in a naturalistic setting early in the further process (Venable et al., 2016). Moreover, concerning the functional purpose, this strategy emphasizes its formative character in order to produce empirically-based

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interpretations that constitute the basis for successfully improving the characteristics or performance of the artifact. Hence, formative evaluations focus on consequences and support the kinds of decisions intended to improve the artifact (March & Smith, 1995; Venable et al., 2016). 3.5.2.1 Evaluation Design In the course of implementing this formative-naturalistic approach within the chosen evaluation strategy, illustrative scenarios were applied as a feasible evaluation method that is predominantly adjusted to demonstrate the efficacy of the artifact (Prat et al., 2015). Peffers et al. (2012) refer to illustrative scenarios as the “application of an artifact to a synthetic or real-world situation aimed at illustrating suitability or utility of the artifact”, whereas a case study in terms of DSR is conceptualized as the “application of an artifact to a real-world situation, evaluating its effect on the realworld situation” (Peffers et al., 2012, p. 402).5 The overall aim of this evaluation activity is to demonstrate if and how well the artifact performs while interacting with organizational elements. Besides demonstrating the applicability of the artifact, this evaluation activity also aims to prove that the artifact instance is consistent with its specification, i.e., that it ingrains the principles of form and function validated in the preceding evaluation (Sonnenberg & vom Brocke, 2012b). Based upon that, this evaluation cycle incorporates the criteria from the artificial evaluation beforehand and complements them with a broader set of criteria derived from the artifact’s evaluation together with real users of the method. Against this backdrop, the development of a digitally enabled grease cartridge exchange is applied as illustrative scenario within this context. This solution was developed as a new service provided by a machine producer to its customers, i.e., plant

5 Within the course of their taxonomy, Prat et al. (2015) analyze IS artifact evaluation practice based upon a literature review among 121 research papers. They mention the prevalence of illustrative scenarios within descriptive approaches (49 percent), whereas case studies appear in only 13 percent of the papers. Within this context, they state that the term “case study” implies a real-world problemsolving situation, which is why a close examination of according papers revealed that many “case studies” were illustrative scenarios (Prat et al., 2015). Based upon this notion, the evaluation method within this work is conceptualized as an illustrative scenario.

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operators, within the course of an ongoing research project. The initial situation within the course of this project can be described as follows: during ongoing operation, the machine tools on the customer’s site need a constant supply of various lubricants in order to ensure minimum downtime. The machine producer introduced a lubrication system that makes use of grease cartridges that can easily be exchanged. However, although these grease cartridges possess a number of sensors, the maintenance staff still have to carry out a visual examination of the filling level of each grease cartridge among the machines at the plant, which leads to long runways and inefficiencies in the maintenance strategy as a whole. As a foundation for a new service within this context, the use of the information that could be aggregated using the sensors already implemented in the grease cartridges was put into focus. The data generated via these sensors should be transferred to the machine control, from where it can be further processed in order to store it on a cloud platform that could be accessed via the World Wide Web. Thus, by making the data available to a broad range of stakeholders, the opportunity arose to develop a service that builds upon the incorporation of a multitude of actors sharing information entities that are modeled according to their needs. With the rough concept of this service already in mind, the method was applied among four workshop sessions that were complemented by discussions in the form of focus groups (Morgan, Krueger, & King, 1998; Tremblay, Hevner, & Berndt, 2010) to various degrees. Focus group methodologies were found to allow deeper insights due to the interactive and synergetic nature of group discussion. By that, feedback from focus groups may contribute to identifying new concepts that could be used to refine the design of an artifact (Adagha, Levy, Carpendale, Gates, & Lindquist, 2017; Anastassova, Mégard, & Burkhardt, 2007; Nunamaker Jr. et al., 1991). The workshop participants consisted of various stakeholder representatives in order to obtain different points of view on the one hand. On the other hand, by inviting at least two representatives per stakeholder group with a homogenous background, a free-flowing conversation was fostered (Morgan, 1997). Hence, the workshop participants can be assigned to groups as follows: Group 1 (G1) encompassed two research assistants from a university chair in the area of information systems, with one being the author of this dissertation; Group 2 (G2) was constituted by two members from a research organization focusing on different fields of applied science, that is,

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systematic service development in this case; Group 3 (G3) incorporated members from the machine producer mentioned beforehand; members of Group 4 (G4) came from a manufacturing and electronics company with a competence focus on data visualization and systems architecture; Group 5 (G5) consisted of representatives from various SMEs and associations with an interest in developing new services in the context of digital transformation. In the course of the workshops conducted, triangulation was used to extend and validate data collection using multiple sources of evidence (Eisenhardt, 1989; Yin, 2003). Within the first workshop (W1), participants from G1, G2, G3, and G4 took part and elaborated the application of the front-end method building blocks, i.e., stakeholder mapping for the CVC and structuring the job to be done underlying the grease cartridge exchange according to the job map. This was complemented by a requirements elicitation and identification following the approach introduced by Berkovich et al. (2011) and Goeken and Patas (2010). During the workshop, especially in case of requirements elicitation and identification, data collection was mainly based on the thinking aloud method (Nielsen, 1994). After the workshop, notes were provided by G3 and a focus group discussion was held among G1 and G2 with notes being taken by G1. The second workshop (W2) was part of an event hosted by G5, with participants from G1, G2, and G5 and consisted of giving an overall view of the method and its distinct building blocks throughout the service development process. The session was audio-taped and supplemented by the notes taken by G2. The third workshop (W3) followed a similar approach, albeit without G5 and notes taken by G1. The fourth workshop (W4) picked up the constellation of W1, but primarily focused on the elaboration of the development steps subsequent to the job map. The workshop was again audio-taped, with feedback being fostered by the thinking aloud method (Nielsen, 1994). Notes were taken by G1. The aim of W1 was to incorporate a stakeholder constellation that was promising to give profound feedback on the construction of the front-end method building blocks and their interplay. In this case, this could be achieved due to the participants’ affiliation in the ongoing research project and their background knowledge concerning the illustrative scenario, i.e., the grease cartridge exchange solution to be developed.

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Thus, insights about the applicability of the method could be derived without distractions from misunderstandings concerning the illustrative scenario. W2, with participants from various backgrounds and limited knowledge concerning the design activities of the method or the illustrative scenario, focused on obtaining feedback on aspects such as overall accessibility, understandability, and simplicity. W3 had the character of an expert evaluation (Peffers et al., 2012) since the participants already possessed knowledge in the field. Therefore, the insights from the previous workshops could be incorporated and reflected against already existing approaches for systematic service development used within the daily work of the participants. W4 was set up similarly to W1. However, by elaborating the development activities that were not incorporated in W1, the participants obtained an impression of the overall interplay of the method building blocks and their interdependent goal achievement. Data analysis was conducted according to the interpretive tradition (Walsham, 2006). The audio tapes were transcribed and the notes from the workshops were consolidated. In the further course, these data and documents were coded and analyzed in accordance with Miles et al. (2014). The coding tactics were aligned with the requirements and criteria derived from the formative-artificial evaluation, from W1, and those from well-established DSR evaluation approaches (Peffers et al., 2012; Prat et al., 2014, 2015; Sonnenberg & vom Brocke, 2012b). Concerning the latter, the elicitation of criteria is guided by the evaluation patterns introduced by Sonnenberg and Vom Brocke (2012) and relates to the efficacy of the method in terms of the illustrative scenario (Prat et al., 2015), i.e., completeness and understandability are taken into consideration. 3.5.2.2 Evaluation Results As Venable et al. (2016) state, formative evaluation should be conducted as early as practicable in an evaluation trajectory or strategy in order to identify difficulties and areas for improvement as early as possible. By influencing and improving the design of the artifact at an early stage, the development of a resulting higher quality artifact can be supported. In doing so, costs could be reduced by resolving uncertainties and risks (Venable et al., 2016). Hence, the evaluation results focus on areas for

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improvement rather than on neutral or well-suited aspects of the method. Based upon the hierarchy of evaluation criteria introduced by Prat et al. (2015), the following sections present the evaluation results. Completeness According to Prat et al. (2015), completeness is conceptualized as the degree to which the structure or the activity of the artifact contains all necessary elements and relationships between elements (Prat et al., 2015). Within this context, the criterion functionality constitutes a specific case of the completeness criterion, i.e., the capability of the artifact to provide functions which meet stated and implied needs when the artifact is used under specific conditions (ISO/IEC/IEEE, 2012; Prat et al., 2015). Within this study, the requirements derived for the initial artificial evaluation predominantly address this evaluation criterion, since they are of functional nature and are applied within the course of an illustrative scenario for evaluation purposes. Since these requirements were already assessed explicitly as part of the artificial evaluation conducted beforehand, areas for improvement have been derived implicitly, i.e., deductively according to the statements of the workshop participants, in this evaluation step. Liquification of Information Digitization, as stated above, exhibits the potential to liquefy information in order to create novel service systems with increased resource density (Lusch & Nambisan, 2015; Normann, 2001). Against this backdrop, the role of information and the way it is utilized within the method is put into focus. The focus group sessions provided a variety of comments and feedback concerning activities that deal with this aspect of the artifact. Most participants expressed a general understanding of the intended purpose of assessing activity-relevant information, decoupling it from their activities and making it available for other actors in order to contribute to the improvement of the service system. However, some participants demanded a clearer definition of which kinds of information are relevant for an activity under consideration. Representative comments regarding these aspects included:

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‘Where does this information come from? And which is already available and which is not? Also the possibility to classify them: that would be something that you could do in Visio as a dropdown-box: Which is available? Which is not available? Where does it come from? And so on. But besides that, I liked it.’ And ‘I think that you need a certain framework and a procedure, a cluster of some sort, along which one could make his own way hand over hand.’ Unbundling and Rebundling In the course of improving the service system, the information being pooled and liquefied serves as a foundation for its reconfiguration. Within this context, the LiCoDi mechanisms act as guidance to drive this reconfiguration along the dimensions of actor, time, place, or new activities to be introduced. However, the workshop participants mention the possibility of a “make a wish” draft of a possible service system as a best guess that could be redefined by the mechanism in a further step. ‘Basically, you always have the business case in mind to some degree when you sketch your process and the information that we have. And, what matters in the end when you take a look in the future: what might such a grease cartridge exchange look like in 2040? So that I then think which information I could get in addition. I could map this

information on it [the process] and, by that, would design the perfect process of the future.’ And ‘There is the question of whether we could not do both. Both choices have their pros and cons. And together they would be more efficient. You would have to try that.’ The general opinion was that thinking about how activities could be shifted by means of the LiCoDi mechanisms is a valid and useful approach, but one that is also demanding for the workshop participants in terms of their imagination capabilities.

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Maximizing Resource Density According to Lusch and Nambisan (2015), maximum density occurs when the best combination of resources is mobilized for a particular situation – e.g., for a customer at a given time in a given place – independent of location, to create the optimal value result. In terms of the method evaluated within this context, a scenario for enabling such a maximum density is created based on resources that have to be shifted within the service system or newly to be introduced. Against this backdrop, the workshop participants mentioned the feasibility of such scenarios in the context of an organization’s environment as an aspect that needs to be assessed when engineering the resulting novel service system. They suggested the incorporation of an ‘assessment step’ as a final element within the method as a feasible approach to ensure broad applicability among potential users. ‘So, I think that another important point would be to have an intermediate step, because there are issues incorporated which we never could put into practice because there is simply not enough influence [concerning surrounding organizational/technical aspects]. The target right now would be to determine which information would be helpful within this process in order to provide the resulting service.’ And ‘So, we do not want to have a service where machines have to be newly developed because new sensors have to be installed that record completely different things that have never been thoroughly thought through.’ To sum up, the participants thought of a classification concerning the feasibility of different scenarios. The result could then be a guidance concerning which information, technologies, or other stakeholders (e.g., consultants with knowledge in introducing new software that is needed) need to be incorporated further down the line in order to realize the new service.

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Larger constellations of actors incorporated The method evaluated within this study addresses the multitude of actors in systems of service systems that are connected by value propositions (Spohrer et al., 2008; Vargo et al., 2008) in various means. By introducing the CVC and VCE, these aspects are explicitly acknowledged in the front-end stages of the method. In terms of the backend stages, this notion is addressed by introducing separate swimlanes for the actors involved apart from the dyadic relationship between service offerer and beneficiary. Within this context, the workshop participants appreciated the role of the ‘information modeler’ as an actor with competences in modeling data and information according to the needs of other actors incorporated within the service system and beyond. ‘The actual and the calculated need for lubrication is something that is not provided by the grease cartridge exchange system. That is something that has to come out of the machine. And then, a bunch of other information has to be combined. Hence, there is the need for another partner you could ask, yet another competence.’ Furthermore, some of the participants opined that the modeling of information can be regarded as a certain value proposition that connects the extant service system with the information modeler’s service system and demand for a framework that is able to depict this relation. Understandability Understandability can be defined as the degree to which the artifact can be comprehended, both at a global level and at the detailed level of the elements and relationships inside the artifact (ISO/IEC/IEEE, 2012; Prat et al., 2015). Against the backdrop of the formative intent of artifact development, this criterion is, in addition to the above-mentioned functionality, a relevant aspect, regarded as crucial for ensuring the efficacy of the artifact. Global Level With the aim of designing a method that focuses on the systematic design and development of digitally enabled service systems, the artifact evaluated within this work is built upon four method building blocks that are interrelated and exhibit

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dedicated design activities in the course of engineering a novel service system. As expressed by the workshop participants, this design makes the artifact easily understandable as a whole. The participants consider the adjustment of the method building blocks as logical and valid. However, in terms of applying the artifact in a workshop setting, some participants demanded a clear, overarching process guidance that leads them through the whole method. ‘So that you would have something like a liquid level indication [reference to illustrative scenario grease cartridge exchange] in the workshop. In which step are we in right now? You had it beforehand with these interconnected arrows where you indicated the distinct phases. If something like that is visualized in the course of a workshop, it is quite convenient for the participants to be able to assess where we are right now.’ Besides addressing the general understandability, the participants also refer to the potential incorporation of user groups that merely take part in solution development workshop settings in their daily business. ‘Where am I? What do I have to do? And a sketch with three or four catchwords. For now, it is the target to give that understanding to the people. As I mentioned, it is hard enough, especially in SMEs, to get people out of their everyday e-mail work.’ Detailed Level In terms of elaborating on the activities proposed within the distinct method building blocks, aspects such as appropriate wording (Herterich, Buehnen, et al., 2016), clearly stated objectives, and an adequate degree of simplicity (Prat et al., 2015) constitute applicable areas for evaluation. Within the method, the distinct method building blocks exhibit a varying degree of complexity and development activities. In general, the workshop participants were able to make use of the activities conducted within this context and adapted their way of thinking to respective underlying premises, e.g., concerning the abstraction of service systems as a way of thinking about economic exchange (Maglio et al., 2009). Yet, potential areas for improvement were revealed based on the participants’ feedback. As the initial design of the method is informed by interdisciplinary theoretical foundations that are suitable to contribute to

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the field of SSE, the wording of the respective approaches utilized within the artifact tends to use terminologies commonly used in academic contexts. For instance, in case of CVC and VCE, the workshop participants engaged in differentiating the concepts from already known approaches which could have been avoided by using a more accessible wording. Another subject raised by the workshop participants dealt with the “flying height”, i.e., the level of granularity, for conducting the activities proposed by the artifact. Regarding the job map, one participant stated: ‘When there is a new job or a job that is not commonly occurring, then I have to count it in, which means that I have to structure its whole accompanying procedure. Is that to be done in the “define” step? So would I define the target from scratch every time again or where should I incorporate such activities? Or are these separate jobs that act as preparation for the next one?’ Another participant mentioned the various backgrounds from potential workshop participants as an aspect to acknowledge: ‘When you apply the method for a process that appears differently in each company, the first participant describes it in one way, the second introduces an alternative and the third brings up something completely different.’ Against this backdrop, he mentioned the possibility of a guiding framework to ensure an appropriate level of granularity: ‘In order to provide something like a thoughts structure, you would have to think about on which level of granularity am I? Am I quite near to the bottom when I need the liquid level or maybe already on a higher level? The aim would be to always have information on the same level.’ To sum up, the workshop participants with applicable knowledge in the field of systematic service development particularly appreciated the aim of the method building blocks and considered them as suitable for the overall aim of engineering digitally enabled novel service systems, but also raised awareness concerning the incorporation of stakeholder groups with limited knowledge in the field.

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Discussion

The initial artificial-formative evaluation of the artifact provides evidence that the artifact as a whole addresses the requirements elicited to a broad extent, but also reveals areas for improvement among the distinct method building blocks. However, to the extent that an artificial evaluation setting is unreal, evaluation results may not correspond to real use (Venable et al., 2016), which is why this evaluation step predominantly deals as precedent-setting for the subsequent formative-naturalistic evaluation cycle. The naturalistic-formative evaluation was conducted by applying an illustrative scenario in terms of a grease cartridge exchange service developed by one of the workshop participants. The results of this evaluation show that the method as a whole is considered as complete and well-structured. However, on a more detailed level, the artificial-formative evaluation already opened up a range of potential fields for improvement, yet without emphasizing distinct design uncertainties. These were addressed by the naturalistic-formative evaluation in more depth. Within this context, the role of information that is liquefied and thus contributes to the reconfiguration of the service system was highlighted by the workshop participants. The logical foundation was considered valid and useful, but demands a high degree of imagination. The same goes for an assessment of the expected effort to generate, model, and distribute relevant data or information in order to implement the service designed. Against this backdrop, the demand for a structuration of potential data sources and modeling approaches can be derived (e.g., Geum et al. (2016), Herterich, Buehnen, et al. (2016), Holler et al. (2016), Liu et al. (2016), Mikusz (2015), Oks et al. (2017); Opresnik and Taisch (2015); Rizk et al. (2017); Schüritz et al. (2017), Wünderlich et al. (2013), Zolnowski et al. (2017)). In terms of recognizing the larger constellations within which multiple actors become joined over time and space, the artifact incorporates the methods CVC/VCE that specifically address this aspect. In later stages, the concomitant systems of service systems thinking is less evident since the value propositions provided by the distinct actors, i.e., service systems, are not explicitly articulated (e.g., in the service blueprint). Facing this design issue means incorporating design elements that derive value propositions from the activities in which the distinct actors apply their knowledge and skills in order to define potential

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links to further relevant service systems. One promising approach in this context is constituted by incorporating elements from methods such as the value blueprint introduced by Alter (2013) or approaches that exhibit a multi-stakeholder system perspective (Haas et al., 2015). Concerning the evaluation results that deal with the understandability of the artifact, the majority of the statements address the translation of expert knowledge into actionable tradeoffs for lay users as elaborated on in Markus et al. (2002). Since nonexpert users may not understand expert jargon, the knowledge base must be translated into terms that non-experts can understand (Markus, 2001). Within this context, Barrett et al. (2012) introduce approaches from design thinking as a participative and iterative view that highlights the situated nature of service and the according uncertainty of outcomes that can always be redefined (Barrett et al., 2012; Suchman, Blomberg, Orr, & Trigg, 1999). Hence, approaches such as the ones introduced in Segelstrom (2013) and Stickdorn and Schneider (2011) are promising in terms of supplementing the artifact evaluated within this work with tools that aim to translate the underlying theoretical premises into actionable guidelines that support the design process towards the resulting digitized artifact (Barrett et al., 2015; Herterich & Mikusz, 2016).

3.7

Contribution and Conclusion

This study followed the DSR approach given by Hevner et al. (2004) and evaluated the initial artifact design by applying the Human Risk & Effectiveness strategy introduced by Venable et al. (2016). Hence, a method for developing digitally enabled service systems in a systematic and structured manner is proposed and evaluated by means of two formative evaluation cycles (artificial and naturalistic) in order to iteratively inform the design of the artifact within the formative stage reported on. The initial design of the artifact addresses the requirements that arise from the theoretical foundations that drive the understanding of innovation in digitally enable service systems, i.e., on a systems of service systems level (Breidbach & Maglio, 2015, 2016; Maglio & Breidbach, 2014; Normann & Ramírez, 1993; Spohrer et al., 2008; Vargo et al., 2008) and an activity level (Lusch & Nambisan, 2015; Normann, 2001; Tilson et

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al., 2010). The novelty of the proposed method arises from taking the service system as the basic unit of analysis which addresses the paradigm shift concomitant with an increasing service logic among private and public organizations (Ostrom et al., 2010). Especially by operationalizing the notion of resource density driven by the dematerialization mechanisms introduced by Normann (2001) and put into the context of service innovation in the digital age by Lusch and Nambisan (2015), the resulting opportunities for innovation in digitally enabled service systems are specifically addressed. This constitutes a departure from extant research in fields such as service engineering with an inherent product-centric-thinking (Böhmann et al., 2014a). Moreover, as Menschner and Leimeister (2011) state, there is a lack of approaches specifically dealing with the role of knowledge and information in the course of developing new services. However, by adopting already existing approaches and exaptating them with insights from the conceptualization of service innovation that is triggered by digitization and digitally enabled generativity, the artifact deals as exaptation type of DSR knowledge contribution (Gregor & Hevner, 2013). Hence, solution knowledge is well advanced, but recognition of how to apply that solution to the specific application area is low (Gregor & Hevner, 2016). This is reflected by the Human Risk & Effectiveness evaluation strategy that emphasizes formative evaluations in the beginning in order to reduce risks due to design uncertainties (Venable et al., 2016). Within this context, TRIGGER offers a systemic view that enables the engineering of digitally enabled service systems, starting with a system of systems perspective in order to understand the larger constellations of stakeholders that have to be addressed in today’s global, digital, service-oriented economy and drilling down to an activity level that deals with reconfiguring the service system by generative mechanisms. Building upon methods from different fields, TRIGGER extends conceptual service frameworks and operationalizes them into a unified SSE method. Within this context, dedicated development steps are conducted by making use of complementary method building blocks that are combined into a meta model according to the notion of Brinkkemper (1996). The interplay of the method building blocks then comprises a means for both, the design and validation of the novel digitally enabled service systems to be developed. Hence, as a basic prerequisite for the novel service system to be

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developed to accomplish its defined work, the interactions on a system of systems level among the firm, its customer, and further stakeholders are delineated. Based upon that, the definite purpose of the novel service system can be defined in order to build “the right system” (Saradhi 1992, p. 62). Moreover, a structured approach is provided that allows for the description of the overall system functionality addressing the system’s definite purpose. Ultimately, with the aim of developing a digitally enabled service system with a maximum level of density, the verification of the system is put into focus. In this course, dedicated development mechanisms are applied that address the notion of digitally enabled generativity as a trigger for innovation in service systems and thus assure “building the system right” (Saradhi 1992, p. 62). This study contributes to the methodological knowledge base for engineering service systems in the digital age in terms of introducing the design of a method that supports the systematic and structured engineering of digitally enabled service systems together with elaborating on the results of its evaluation. Furthermore, a contribution is made to the IS research knowledge base by following the evaluation strategy proposed by Venable et al. (2016) and reporting on the activities conducted within the suggested evaluation steps. The practical contribution is constituted by providing a structured and systematic approach that addresses the real-world problem of today’s firms to develop digitally enabled services in order to maintain competitiveness in the long run. Hence, in the vein of the overall dissertation, a contributions is made in terms of providing design knowledge for engineering digitally enabled service systems that is rooted in real world applications (Böhmann et al., 2014a). By that, metaphorically spoken, a recipe to perform the task of systematically designing and developing these complex systems is contributed to the knowledge base (Gregor & Hevner, 2013; Hevner et al., 2004).

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Study 4: Preserving and Communicating Design Knowledge – A Digital Tool

Reverting to study 3, its core of inquiry was to produce prescriptive knowledge to be ingrained in a method that encompasses instructions for the goal-driven activity of engineering digitally enabled service systems. On the way toward a cohesive and consistent body of knowledge for engineering service systems in the digital age as reflected in the overall objective of this dissertation, according “recipes” embody a pivotal knowledge contribution. However, prescribing how to do something with some degree of generality, i.e., giving prescriptions on how to design and develop an artifact that accomplishes some end, demands for design knowledge to be captured, written down, and communicated in a way that acknowledges a broader set of facets (Gregor, 2006; Gregor & Jones, 2007). Against this backdrop, Study 46 addresses underlying ontological foundations by means of developing an expository instantiation (Gregor & Hevner, 2013; March & Smith, 1995) that embodies the design knowledge produced in the course of the design and evaluation of TRIGGER, together with considering two intertwined research objectives in the context of the study’s research question. First, this expository instantiation (Gregor & Jones, 2007) – referred to as the DiDesigner – constitutes a prototype system that is used to illustrate how the notion of maximizing resource density is operationalized, with better communicative power than a natural language description. By that, the artifact itself has some representational power in terms of assisting with the communication of design principles inherent in the prescriptive knowledge produced up to this point (Gregor & Jones, 2007). Second, the DiDesigner is considered a digital tool that triggers innovation (Nambisan, 2013). In this vein, its design builds on the insights gathered in the course of the development of TRIGGER and addresses the notion of translating expert

6 An earlier version of this research has been under review for the special issue on Design Science Research and Digital Innovation in Business & Information Systems Engineering (BISE) 01/2019. The current version thoroughly ingrained the feedback from experienced senior scholars gathered throughout the review process.

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knowledge into actionable tradeoffs for lay users (Markus et al., 2002). The development of the artifact as well as the documentation of the underlying design knowledge is guided by alternating design and evaluation loops in accordance with the build-evaluate patterns introduced by Sonnenberg and vom Brocke (2012b). Based on this evaluation strategy, four build-evaluation episodes are gone through, with each episode focusing on different aspects of the artifact. By reasoning about the artifact in both, the interior mode and the exterior mode (Gregor, 2009), truth-like statements about the prescriptive knowledge ingrained in the artifact can be articulated while it emerges throughout its development (Iivari, 2007; Sonnenberg & vom Brocke, 2012b). Therefore, this study contributes to the overall objective of the dissertation in terms of elaborating on underlying knowledge contributions in a way that allows for the prescription of inherent design principles of artifacts that support the engineering of digitally enabled service systems. Moreover, with having positioned the DiDesigner as an expository instantiation, a viable artifact was produced that provides the ground for discussing prescriptive knowledge contributions with truth-like value for a prospective body of knowledge for engineering service systems in the digital age. The remainder of this study is as follows: First, an introduction to the problem context is provided, together with elaborating on the research objective guiding this study. Second, the theoretical foundations underpinning the design of the DiDesigner are described. Afterwards, the research approach is introduced. Next, the development of the artifact is described along the continuum of the design-evaluation-trajectory proposed by Sonnenberg and vom Brocke (2012b). In the subsequent section, the knowledge contributions embodied in the DiDesigner are discussed concerning their relevance for an emergent design theory. The paper ends with a conclusion, incorporating implications for future research.

4.1

Purpose and Scope

Due to the unique characteristics of digital technology (Yoo et al., 2010), innovation in digitally enabled service systems faces inherent tensions (Eaton et al., 2015). On the one hand, the digitally enabled generativity unleashed by digital technology (Yoo, 2013) leads to novel service systems which are highly evolvable, perpetually

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incomplete, and hard to demarcate, thus developing beyond the understanding and anticipation of those who created the service system in the first place (Eaton et al., 2015; Yoo, 2013; Yoo et al., 2010; Zittrain, 2006). On the other hand, digitally enabled generativity may not automatically result in positive outcomes (Yoo, 2013) which is why controlling generativity has become a highly prevalent issue (Eaton et al., 2015; Förderer et al., 2014; Pagani, 2013). Hence, with the aim to create digitally enabled service systems that embody a positive outcome of digitally enabled generativity, understanding the generative mechanisms that lead to enhanced resource densities and incorporating them in “principles of function” (Gregor & Hevner, 2013) can lead to beneficial configurations of resources in these systems (Eaton et al., 2015; Lessard, 2015; Lusch & Nambisan, 2015). In this vein, SSE calls for design theories (Gregor, 2006; Gregor & Jones, 2007) that allow for the prescription of guidelines of novel artifacts that enable or support the engineering of real-world service systems that permeate our society (Böhmann et al., 2014a). As Sonnenberg and vom Brocke (2012b) state, a prerequisite for the specification of an emergent design theory is constituted by building and evaluating respective emergent artifacts in a way that allows for the documentation of truth-like statements (Iivari, 2007; Sonnenberg & vom Brocke, 2012b) along the components inherent in a design theory (Gregor & Jones, 2007). The objective of this study is thus to develop an artifact that supports the engineering of digitally enabled service systems that embody positive outcomes of digitally enabled generativity – the DiDesigner – in a way that allows for documenting truth-like statements (Iivari, 2007) as a prerequisite for showing the principles inherent in its design as well as prescribing guidelines for further artifacts of the same type. Building on the conceptualization of digital tools as an innovation trigger in the context of digital technology by Nambisan (2013), the study is guided by the following research question: How can generalizable guidelines for engineering digitally enabled systems be produced and communicated by means of a digital tool? This research question is answered by applying a design science research (DSR) approach following Hevner et al. (2004) to design the DiDesigner as a digital tool

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(Nambisan, 2013) that supports the engineering of digitally enabled service systems, concomitant with prescribing guidelines for further artifacts of the same type (Gregor & Hevner, 2013; Gregor & Jones, 2007). The development of the artifact as well as the documentation of the underlying design knowledge is guided by alternating design and evaluation loops in accordance with the build-evaluate patterns introduced by Sonnenberg and vom Brocke (2012b). By elaborating on how different components of an emergent design theory for tools such as the DiDesigner (Gregor & Hevner, 2013; Gregor & Jones, 2007) are considered, the knowledge contribution of the study is articulated.

4.2

Background

Digital technology (Yoo et al., 2010) enhances a system’s capability to produce unanticipated change through unfiltered contributions from broad and varied audiences (Zittrain, 2006, 2008). Hence, in order to foster positive outcomes, suitable theoretical lenses for understanding underlying mechanisms (Ω knowledge) are needed as well as prescriptive knowledge (Λ knowledge) that incorporates this understanding with the aim of providing applicable ‘principles of function’ (Gregor & Hevner, 2013). 4.2.1

Understanding Digitally Enabled Generativity in Service Systems

The notion of unanticipated change suggests that generativity is a relational construct, thus dependent on the specification of who is surprised by what (Eck & Uebernickel, 2016). In this context, Yoo (2013) elaborates on the concepts of modularity and generativity with regard to the perception of the changes produced among the audiences incorporated. Modularity posits that modules are created through the decomposition of a complex system, thus offering simplicity dealing with these systems (Sanchez & Mahoney, 1996; Schilling, 2000). Hence, a system is designed first, parts and subsystems are designed later with standardized interfaces (Sanchez & Mahoney, 1996; Schilling, 2000). However, this perspective makes implicit assumptions that the boundary of a system is fixed and clearly articulated a priori by a central authority (Nickerson & Zenger, 2004). Therefore, the flexibility of a system and its

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variations take place within the confinements of a given architectural scheme (Ulrich, 1995). Numerous variations of systems can emerge from the recombination of its diverse components, albeit not leading to unanticipated change perceived by the audiences incorporated due to the constraints imposed by the fixed boundaries of the overall system (Um et al., 2013; Yoo, 2013). To the contrary, generativity induced by the characteristics of digital technology, i.e., digitally enabled generativity, leads to systems capable to evolve into directions that were initially unimaginable (Eck & Uebernickel, 2016; Yoo, 2013). The modules constituting such systems are most often designed without fully knowing the overall design of the system and how each module will be integrated with other modules (Gawer, 2009). Hence, as emphasized by Yoo (2013), the generativity, not the modularity, of systems emerging from digital technology, makes them highly evolving. Thus, the boundary of these systems is unknowable, with them remaining perpetually incomplete and the changes initiated being widely perceived as unanticipated among the audiences incorporated (Um et al., 2013; Yoo, 2013; Yoo et al., 2010). Referring to novel service systems in the context of generativity, the use of digital technology makes innovation in these systems unbounded (Yoo et al., 2010; Zittrain,

2006), albeit leading to inherent contradictions, rupture, and incompatibility within their configuration of resources (Eaton et al., 2015). With the aim to control generativity in digitally enabled service systems (Eaton et al., 2015; Förderer et al., 2014), designoriented understanding of these service systems can be achieved by acknowledging the generative mechanisms that tend to produce according beneficial configurations of resources (Lessard, 2015; Maglio et al., 2009; van Aken, 2004). Grounded in the notion of resource density (Lusch & Nambisan, 2015; Normann, 2001) as lens for anticipating beneficial configurations in digitally enabled service systems, maximum density occurs when the “best combination of resources is mobilized for a particular situation – e.g., for a customer at a given time in a given place – independent of location, to create the optimal value/cost result” (Normann 2001, p.27). In this context, tangible products or resources can be effective instruments into which activities and knowledge can be ‘frozen’ and made available to actors for their present and future value-creating activities. This effectiveness is predominantly based

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on the notion that these resources are reproducible and predictable (Michel et al., 2008; Normann, 2001). However, such a perspective imposes service systems resulting from the combination of these resources to be constrained by their inherent boundaries, thus depicting modular systems that are predictable, i.e., limited in their capabilities to produce unanticipated change among the audiences incorporated (Chandler & Lusch, 2015; Michel et al., 2008; Normann, 2001; Yoo, 2013; Zittrain, 2006). In this logic of value creation, the nature of digital technology constitutes a driving force to enhance resource density (Herterich & Mikusz, 2016; Lusch & Nambisan, 2015), as it provides the infrastructure and artefacts that drive the dematerialization mechanisms underlying the creation of new densities. In this vein, digital technology liberates service systems from inherent constraints, thus inducing unanticipated change in the form of digitally enabled generativity in service systems (Eaton et al., 2015; Tilson et al., 2010; Yoo, 2013; Yoo et al., 2010). Improved densities are then achieved by controlling generativity to foster positive outcomes (Eaton et al., 2015; Förderer et al., 2014; Lusch & Nambisan, 2015; Pagani, 2013) i.e., by the rebundling of diverse resources, creating novel resources beneficial (i.e., value-experiencing) to some actors in a given context. To sum up, by

building on the conceptualization of dematerialization mechanisms, the notion of resource density allows for both, understanding unanticipated change triggered by digitally enabled generativity in service systems based on the dematerialization mechanisms liquification and unbundleability and controlling this generativity based on rebundleability in order to systematically design and develop digitally enabled service systems with enhanced resource density. 4.2.2

Engineering Digitally Enabled Generativity in Service Systems

SSE calls for novel artifacts that incorporate prescriptive design knowledge for the systematic design and development of service systems (Böhmann et al., 2014a; Gregor, 2006; Gregor & Jones, 2007). However, although being at the core of pivotal contributions (Barrett et al., 2015), the knowledge base incorporating design oriented contributions for engineering service systems in the digital age is still nascent. Central notions underlying the concept of generativity are dealt with in extant literature, albeit with a divergent focus, e.g., on the design of digitized products to be used in innovative industrial service offerings (Herterich, 2017; Herterich, Buehnen, et al., 2016; Herterich,

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Eck, et al., 2016; Herterich, Uebernickel, & Brenner, 2015) or design principles for flexible data models for data storage (Weinrich et al., 2016). Contributions building on the perspective of resource density are evident in the literature, but either focus on conceptual foundations (Nambisan, 2013) or often do not address underlying mechanisms thoroughly (Blaschke et al., 2017; Pfeiffer et al., 2017). The development of TRIGGER has focused on operationalizing the premises concomitant with resource density in the context of digitally enabled service systems. In this context, Study 3 elaborated on the potential for novel service systems that emerge from the sociotechnical processes concomitant with digitally enabled generativity and developed a method for engineering these system by acknowledging prevalent perspectives that address the requirements imposed for systematically designing and developing digitally enabled service systems. The findings from the formative evaluation trajectory suggest that the approach is valid and useful for engineering service systems with enhanced resource density, but also demands for a high degree of imagination for understanding the underlying premises as wells as translating them into actionable guidelines (Markus et al., 2002). This study builds on this work and extends the conceptualization of resource density in terms of developing actionable design knowledge that addresses the underlying premises of resource density for controlling generativity in the design and development of novel digitally enabled service systems.

4.3

Research Method

The prevalent focus of DSR is to build artifacts while producing prescriptive knowledge (Gregor & Hevner, 2013; Sonnenberg & vom Brocke, 2012b). However, as with conceptual knowledge, prescriptive knowledge has no truth value from an epistemological point of view (Iivari, 2007). As Iivari (2007) emphasizes, only descriptive knowledge, i.e., observations, empirical regularities, and theories have a truth value. In this vein, Sonnenberg and vom Brocke (2012b) argue that truth statements about an artifact can be made by documenting and accumulating corresponding prescriptive knowledge in a way that allows for step-wise evaluation as it emerges in the DSR process. Evaluation approaches such like the ones introduced by

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Peffers et al. (2007) support this view by conceptualizing evaluation activities and thus support the articulation of truth statements, albeit predominantly ex post, i.e., after an artifact has been constructed (Pries-Heje, Baskerville, & Venable, 2008). Moreover, although producing descriptive knowledge, ex post evaluations impose theorizing about an artifact in the exterior mode (Gregor, 2009), thus treating the artifact as a black box and only assessing significant design features with regard to achieving various utilitarian ends (Gregor, 2009; Sonnenberg & vom Brocke, 2012b). In contrast, theorizing in the interior mode (Gregor, 2009) deals with prescriptive statements about how artifacts can be designed, developed and brought into being and, by that, fosters ex ante evaluations to be conducted before an artifact has been applied to a real world problem. Adding truth to this prescriptive knowledge demands for documenting the emerging artifact in a way that allows for reasoning about its purpose, its rationale, its inner structure, the conditions under which the artifact is expected to work, the steps required to actually use the artifact in practice, or testable propositions that can be evaluated in the exterior mode (Sonnenberg & vom Brocke, 2012b). Besides contributing to the emergence of prescriptive knowledge with truth-like value throughout a DSR process, the documentation of ex-ante evaluations during the build phase also builds the foundation for developing a design theory (Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b). Hence, by reasoning about artifacts in the interior mode, i.e., its build phase, and documenting prescriptive knowledge in a particular way, a design theory that allows for the prescription of guidelines for further artifacts of the same type can be explicated and communicated (Gregor & Jones, 2007). Addressing underlying notions, Sonnenberg and vom Brocke (2012b) propose a set of comprehensive evaluation patterns that address both, the necessity of ex ante as well as ex post evaluations (Gregor, 2009) and the documentation of prescriptive knowledge in a way that corresponds with specifying a design theory (Gregor & Jones, 2007). Hence, with the aim of producing and communicating generalizable guidelines for engineering digitally enabled service systems by means of designing a tool as an expository instantiation, the artifact development process reported on in this study is aligned with the build-evaluate patterns conceptualized by Sonnenberg and vom Brocke (2012b).

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Artifact Development and Evaluation

Due to the notion that specifying the constituents of an emergent design theory demands for documenting and communicating prescriptive knowledge generated by theorizing in the interior mode (Gregor, 2009), the development of the artifact within this paper is conducted along a trajectory of alternating design and ex ante as well as ex post evaluation loops. By that, artifact description and evaluation follow a more fine grained and reciprocal pattern, which constitutes an alteration of the DSR scheme proposed by Gregor and Hevner (2013). Thus, the DiDesigner, as a digital tool that aims to support engineering digitally enabled generativity in service systems, is developed in accordance with the DSR evaluation activities proposed by Sonnenberg and vom Brocke (2012b), concomitant with explicating knowledge contributions for the design of artifacts of the same type by reference to the eight components of a design theory introduced by Gregor and Jones (2007). Hence, the alternating design and evaluation of the artifact is structured along four generic evaluation episodes, with each episode focusing on different aspects of the artifact: artifact justification (relevance, suitability) (EVAL1), consistency of artifact design and applicability (EVAL2), ability to be instantiated (applicability) (EVAL3), and usefulness in practice (EVAL4) (Sonnenberg & vom Brocke, 2012b). The overall trajectory is depicted in Figure 10.

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Figure 10. Evaluation Trajectory for the Development of the DiDesigner

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The Eval1 activity is concerned with justifying the relevance of the addressed problem (Sonnenberg & vom Brocke, 2012b). In accordance with Peffers et al. (2007), the purpose of ensuring that a meaningful DSR problem is selected and formulated can be achieved by explicating the research entry points that trigger the interest in the DSR project. Moreover, the relevance of the artifact envisioned can further be strengthened by applying applicability checks that address its underlying notions, i.e., importance, accessibility, and suitability (Rosemann & Vessey, 2008; Sonnenberg & vom Brocke, 2012b). Input In the context of the DSR project reported on, the input to this activity is constituted by a combination of a problem-centered initiation and an objective-centered initiation (Peffers et al., 2007). The problem-centered initiation is informed by the research need

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stated above, i.e., the need for design knowledge for digitally enabled service systems (Böhmann et al., 2014a) that acknowledges the positive outcomes of digitally enabled generativity (Eaton et al., 2015; Förderer et al., 2014; Lusch & Nambisan, 2015; Normann, 2001; Yoo, 2013). This is complemented by an objective-centered initiation that focuses on exaptating design objectives from extant constructs, models, methods, instantiations, and design theories that are regarded as promising to deal as knowledge base (Gregor & Hevner, 2013) for addressing the stated problem. Evaluation Method Hence, with the aim to justify the development of the DiDesigner as an artifact embodying prescriptive design knowledge for engineering digitally enabled service systems, the initiations depicted as entry points for the DSR project were evaluated by means of a twofold approach. One the one hand, justificatory insights were gathered from the taxonomy developed in Study 1. One the other hand, the evaluation was grounded in informed arguments that made use of the information from the prescriptive knowledge accumulated in Study 2 and Study 3. Concerning the justification of the inquiry at hand, the research entry points depicted for the development of the DiDesigner can be regarded as in accordance with the research paths opened up by RQD 2, i.e., ‘How can digital tools be designed as trigger for innovation in terms of initiating unanticipated outcomes that stem from the mechanisms underlying digitally enabled generativity?’ and RQD 3, i.e., ‘How can prescriptive design knowledge on novel digital components, tools, artifacts and digitally enabled service systems be documented in a way that allows for explicating a design theory?’ in Study 1. RQD 1 and RQD 4 are deemed as beyond the scope of this dissertation, albeit constituting potential research entry points for future research endeavors. Further on, the informed arguments conducted within this evaluation activity made use of the knowledge base accumulated throughout Study 2 and Study 3 in order to build a convincing argument for the prospective artifact’s utility (Hevner et al., 2004). In detail, knowledge contributions entailing relevant design knowledge for engineering digitally enabled service systems were extracted from the accumulated knowledge base, fragmented, exaptated, configurated and assembled (Brinkkemper,

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1996; Gregor & Hevner, 2013; Karlsson & Ågerfalk, 2004) in order to allow for insights on the prospective artifact (Sonnenberg & vom Brocke, 2012b). Thus, fragments from the work dealing with the operationalization of the notion of resource density (generative mechanisms and TRIGGER) were combined with underlying principles from knowledge contributions dealing with the notion of controlled generativity (Eaton et al., 2015; Förderer et al., 2014; Um et al., 2013; Yoo, 2013) and its incorporation in actionable design knowledge for service systems (H. Brocke et al., 2011b; Klör et al., 2017; Niemöller et al., 2017). The informed arguments were conducted in the context of two workshops. In these settings, MS Power Point (PPT) slides were used to represent fragments of the design of the immature artifact, together with providing an illustrative scenario (Peffers et al., 2012) of its application in the context of industrial services (see Figure 11). The participants were comprised of members of the research project already mentioned in the course of the development of TRIGGER and took part in varying constellations: the first workshop encompassed three research assistants from a university chair in the area of information systems and two members from a research organization focusing on different fields of applied science, that is, systematic service development in this case; the second workshop was constituted by the same constellation but was complemented by two experts in the field of digital technologies and data visualization from an engineering company as well as two experts in the field of digital service development from an automotive, aerospace, and industrial supplier. The sessions were audio-taped with the audio-tapes being transcribed in the further course. Coding took place in accordance with (Miles et al., 2014) and followed the interpretive tradition (Walsham, 2006).

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Figure 11. Power Point Slides as Artifact for ex ante Evaluation in Eval 1

Evaluation Results The aim of confronting the prospective artifact with findings from the taxonomy development as wells as insights from the informed arguments was to evaluate it against its importance, accessibility, and suitability (Rosemann & Vessey, 2008). The

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relevance of the artifact was thus exposed in a dual manner. On the one hand, the development of the artifact can be regarded as important since it addresses two promising research paths (c.f. RQD2 and RQD3) stemming from the analysis and synthesis of extant literature in Study 1. On the other hand, this perception was further strengthened by experts in terms of addressing aspects that deal with the accessibility and suitability of the prospective artifact. In more detail, the concept of unbundleability, together with reconfiguring the design of a digitally enabled service system in accordance with the notion of maximizing resource density, was emphasized as crucial issue. For instance, one expert from the field of digital technologies and data visualization stated: ‘Right now, what we are doing here, that is absolutely interesting and, in particular with involving a cost factor, very very relevant for us. We have talked about this shift here. Basically, by introducing a novel service, also a share of these costs is shifted.’ He further illustrates relevant perspectives by an example: ‘I am installing a new temperature sensor. I will deliver data to a cloud. What is the worth of that? With that approach, we cannot calculate that in detail, but we can go into that direction. Thus, deliver a starting point to calculate that – or, put simply, just give an estimation of what is the value of the data.’ Output The mandatory output of this evaluation activity is a justification of the prospective artifact (Sonnenberg & vom Brocke, 2012b). Thus, in the context of this study, the output of Eval1 is constituted by a (1) justified research problem, i.e., the need for design knowledge for digitally enabled service systems that permeate our society and acknowledge the positive outcomes of digitally enabled generativity; a (2) justified research gap, i.e., the lack of contributions that provide prescriptive design knowledge that guides the systematic design and development of digitally enabled service systems with regards to the notion of fostering the positive outcomes of digitally enabled generativity; and (3) justified design objectives, i.e., in terms of providing actionable design mechanisms that deal with the operationalization of the premises concomitant with resource density in the context of digitally enabled service systems and consider

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the notion of controlled generativity in order to foster positive outcomes in the development of novel service systems. In the course of justifying the value of the prospective artifact, the purpose and scope as well as relevant constructs of a design theory (Gregor & Jones, 2007) for engineering digitally enabled service systems can be specified. The appropriateness of constructs can further be strengthened by referring to constructs that have been used for solving similar problems (justificatory knowledge). Moreover, initial assumptions on testable propositions can be made at this stage (Sonnenberg & vom Brocke, 2012b). 4.4.2

Design and Eval2

The Eval2 activity is concerned with showing that an artifact design progresses to a solution of the stated problem (Sonnenberg & vom Brocke, 2012b). However, the social component of the prospective artifact imposes challenges concerning the evaluation of its design specification. Evaluation methods such like formal proofs or simulations may not be feasible in this context since these methods only address the technological aspects of a solution. The evaluation method chosen thus has to address both, the technological as well as the social aspect of an artifact (Abraham, Aier, & Winter, 2014). Input In the context of the development of the DiDesigner, the input to this activity encompasses a design specification that is represented by means of a Visual Basic (VBA) tool that was realized in MS Excel. However, as Sonnenberg and vom Brocke ( 2012b) emphasize, the use of such design tools has to be justified since the design specification of the artifact should be understandable and meaningful to all of its stakeholders. In this context, the use of this design tool can be regarded as suitable since the artifact to be developed embodies design knowledge for engineering digitally enabled generativity in service systems. Understanding the design principles of form and function that foster the positive outcomes of digitally enabled generative in service systems is thus facilitated by a tool in terms of being easier to cope with than the actual object to be systematically designed and developed, i.e., service systems that are hard to delineate and complex by nature (Böhmann et al., 2014a).

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The design specification is aligned with the design objectives justified in Eval1. Hence, one central aspect of the design of the artifact is depicted by the notion that the artifact fulfills the function of fostering the positive outcomes of unanticipated changes that are opened up by digitally enabled generativity in the course of the systematic design and development of novel digitally enabled service systems. The core of the design of the artifact thus follows the premises of the structured analysis and design technique (Congram & Epelman, 1995; Ross, 1977) in order to describe the functions that lead to enhanced resource densities, i.e., positive outcomes of digitally enabled generativity, in digitally enabled service systems. As such, the artifact guides a transformation process in the course of the design of a novel service system by transforming an input (Congram & Epelman, 1995; Ross, 1977), i.e., the draft of the system to be developed, into an output, i.e., a blueprint of the resultant digitally enabled service system, based on mechanisms, i.e., mechanisms that foster positive outcomes of digitally enabled generativity by enhancing resource density, and constrained by controls, i.e., inherent constraints that are evident in the draft of the novel service system. In more detail, the design specification builds on extant knowledge units (Karunakaran, Purao, & Cameron, 2009) accumulated in the knowledge base in the course of the preceding studies, that is, knowledge ingrained in the artifacts designed, but also knowledge produced in the course of the evaluation of TRIGGER. In the course of applying TRIGGER for engineering digitally enabled service systems, all constituents were considered important and suitable, albeit not necessarily accessible (Rosemann & Vessey, 2008). For instance, thinking about how activities could be shifted by means of the LiCoDi mechanisms (Höckmayr, Genennig, et al., 2016; Höckmayr & Roth, 2017; Höckmayr et al., 2017) was considered as a valid and useful approach, but also contingent on a certain degree of imagination capabilities among workshops participants. In contrast, rather well-established method building blocks such as CVC/VCE (Patricio et al., 2011), Job Map (Bettencourt & Ulwick, 2008), and Service Blueprint (Lim & Kim, 2014) that were exaptated (Gregor & Hevner, 2013) and incorporated in TRIGGER were regarded as broadly accessible. Hence, with the aim to contribute an improvement (Gregor & Hevner, 2013) of the back-end stages of TRIGGER to the knowledge base, the design of the DiDesigner addresses the

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intersection of an initial idea of a service systems and its further development toward a digitally enabled service systems with a maximized degree of resource density. 3.

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Figure ūŬ. Design Specification of Artifact for ex ante Evaluation in ŸŠ•ȱŬ As illustrated in Figure 12, the input (Congram & Epelman, 1995; Ross, 1977) is constituted by a basic idea of a job to be done (Bettencourt et al., 2014; Bettencourt & Ulwick, 2008) that is addressed by the service system to be developed. As an initial activity in (1.) the transformation process, a demarcation of the system is initiated by decomposing the job to be done into concise subsystems, i.e., job steps (Bettencourt & Ulwick, 2008). This modularization offers simplicity (Sanchez & Mahoney, 1996; Schilling, 2000), thus providing the foundation for identifying deeds, processes, and performances through which specialized competences are applied for the benefit of another entity or the entity itself (Lusch & Nambisan, 2015; Vargo & Lusch, 2016) in accordance with the respective job to be done. Hence, building on the notion of resource density, a further activity (2.) in the transformation process deals with identifying these deeds, processes, and performances and delineating them related to when they can be done (time), where they can be done (place), who can do what (actors) and with which information they can be done (relevant information). The altering of the last dimension in this context is due to the information-centric focus of innovation in service systems (Glazer, 1991; Lusch & Nambisan, 2015). By that, the information

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relevant for deeds, processes and performances is acknowledged as central resource in the context of digitally enabled service systems and regarded as uncoupled from by whom it is actually integrated (Lusch & Nambisan, 2015; Lusch et al., 2010). This is further strengthened by visualizing resultant configurations based on the structure of the information-oriented service blueprint (Lim & Kim, 2014). However, although this perspective allows for the demarcation of the service system to be developed, the underlying notions lead to the assumption of the system to be confined by the principles concomitant with the premises of modularity (Um et al., 2013; Yoo, 2013). The overall design of the system can then be regarded to be imposed with fixed boundaries and constraints, thus not possessing the characteristics to be deemed as developing beyond the understanding and anticipation of those who created the idea of the service system in the first place (Eaton et al., 2015; Yoo, 2013; Yoo et al., 2010; Zittrain, 2006). As a consequence, designing and developing digitally enabled service systems that possess the capability to overcome these constraints is dependent on acknowledging the nature of digital technology as a driving force that liberates service systems by means of enhancing inherent resource densities. The perspective denoted in TRIGGER (Höckmayr, Genennig, et al., 2016; Höckmayr & Roth, 2017; Höckmayr et al., 2017) addresses this notion by operationalizing the premises concomitant with resource density in the context of digitally enabled service system. By that, service systems with unanticipated design variations can be developed, albeit not necessarily embodying a positive outcome of digitally enabled generativity. The design of the prospective artifact addresses this notion by complementing the activity of (2.) by factoring in (3.) inherent constraints along the dimensions time, place and actors (information is deemed to be unconstrained in the context of digital technology and digitization (Lusch & Nambisan, 2015; Yoo et al., 2010)). These controls (Congram & Epelman, 1995; Ross, 1977) are dependent on the understanding and anticipation of those who created the idea of the service system in the first place, thus providing the foundation for acknowledging positive outcomes of digitally enabled generativity, i.e., enhanced resource densities, in the course of engineering novel digitally enabled service systems. In the context of the prospective artifact, (4) information relevant for the deeds, processes, and performances (Lim et al., 2018) that address the job to be done is regarded as not bound to a specific time/place/actor constellation, but possesses the

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capability to break down these deeds, process, and performances into pieces (i.e., unbundling) that can be rebundled for improved density (Lusch & Nambisan, 2015). This (5.) unbundling is deemed to lead to an unanticipated design of the digitally enabled service systems resulting from the capabilities of digitally enabled generativity within the system, albeit not necessarily constituting a positive outcome of the development process. In order to foster positive outcomes of digitally enabled generativity in the course of designing and developing novel digitally enabled service systems, the transformation process from an initial idea of a service system towards a blueprint of a service system with enhanced resource density is guided by an alteration of the empirically derived generative mechanisms developed in Study 2 (Höckmayr, Genennig, et al., 2016; Höckmayr, Roth, et al., 2016) and tailored toward design prescriptions in Study 3 (Höckmayr & Roth, 2017; Höckmayr et al., 2017). Combining these generative mechanisms resulted in actionable tradeoffs (Markus et al., 2002) in the form of (6.) patterns (Alexander et al., 1977; Buckl, Matthes, & Schweda, 2010; Chatterjee, 2015; Gregor & Jones, 2007) that, depending on the controls shaped by the understanding and anticipation of those who created the idea of the service system in the first place, provide a generic blueprint of a service system with enhanced resource density. Complementing this generic solution with a guidance on how which liquefied information (Lim et al., 2018) has to be modeled by actors with applicable knowledge and skills (Benaroch, 1998; Gruber, 1995) to realize these patterns then leads to a situated blueprint of the service system with maximized resource density. Hence, the output of the prospective artifact is constituted by a blueprint of a digitally enabled service system with maximized resource density based upon a job to be done (input) and constraints (controls) articulated by those who initiated the development process of the service system in the first place. Evaluation Method With the aim to evaluate the design specification against its correctness and completeness as well as to assess whether it is understandable and meaningful to all of its stakeholders (Sonnenberg & vom Brocke, 2012b), an ex ante demonstration (Peffers et al., 2007; Sonnenberg & vom Brocke, 2012a) was conducted in the course of a focus group discussion (Leukel, Mueller, & Sugumaran, 2014; Venable et al., 2012). The

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design specification was presented based on the VBA tool as illustrated in Figure 13 and put into context by means of an illustrative scenario (Peffers et al., 2012) that was derived from the case considered in Study 3. The participants were comprised by five members from the research organization focusing on different fields of applied science described above, with two being a member of the aforementioned ongoing research project and three dealing with business model development in the context of novel digital services. The session was audio-taped with the audio-tapes being transcribed in the further course. Coding took place in accordance with Miles et al. (2014) and followed the interpretive tradition (Walsham, 2006).

Figure 13. Representation of Design Specification in Visual Basic Tool in Eval 2

Evaluation Results This evaluation activity focused on evaluating the design specification against its inner structure, i.e., dealing with the how of artifact construction (Gregor, 2009). Hence, besides completeness and correctness (Sonnenberg & vom Brocke, 2012b), further evaluation criteria dealing with the structure of an artifact such as simplicity,

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understandability, consistency, or homomorphism (Prat et al., 2015) were considered to be of note in the course of Eval2. Evidence from the focus group revealed that the constructs used in the design specification as well as their relationship correspond the to the stated design objectives. Addressing the notion of digitally enabled generativity, one participant elaborates on the positive outcomes fostered by the prospective artifact: ‘For the reconfiguration, it is not necessarily the case that I have to do something with digitization, is it? Actually, digitization is in my understanding only a vehicle to make something better, but I can use it if it fits and if it is beneficial for me.’ Another participant emphasizes the notion of prescriptive design knowledge that guides the systematic design and development of novel digitally enabled service systems: ‘So, if I have understood that correctly, then the thing that, for instance Osterwalder, or more precisely his canvas, is not that good at, is this operationalization. I have a cool service and then you ask yourself: And what do I do now? And who has to do which tasks and when? And if I have understood it correctly, this tool helps.’ However, besides that, the researchers also elaborated on aspects dealing with to which degree the artifact, together with its inherent components and their relationships, can be comprehended by various stakeholders: ‘That's always the question: should someone sit alone in front of it, who has no idea of the methodological background? Or is there still someone else who can lead him through it? Someone who can always ask: Yes ok, what should be achieved? What is the purpose of the process in this case?’ Depending on that, an outlook on varying perceptions of the artifact’s completeness, simplicity, and homomorphism could be identified within the focus group: ‘So the tool is first of all there to design and look at the ideas in different ways: How can I implement these ideas later on? And the idea is an input that I got somewhere in a workshop or whatever. Then this is the initial thing with which I then go into this tool. What do I need before? What do I have before?’

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Hence, one idea raised by a participant addressed the opportunity to complement the artifact with further components: ‘The tool is digital, maybe a physical part could be doing some kind of tutorial video, twohour training, or something else. Maybe then a medium-sized company will be able to use the thing. How's he supposed to automatically do it like that? Maybe you just need a mini briefing, training, whatever.’ Output The mandatory output of this evaluation activity is a validation of the design specification (Sonnenberg & vom Brocke, 2012b). This validation is achieved by focusing on theorizing in the interior mode (Gregor, 2009) in the course of the evaluation activity conducted. By that, a foundation for developing a useful artifact that can be applied to some reality (Sun & Kantor, 2006) is provided. In particular, the degree to which the constructs used in the design specification as well as their relationships correspond to the stated design objectives is assessed. Moreover, in terms of fostering the specification of a design theory, statements regarding its components dealing with principles of form and function as well as justificatory knowledge can be explicated, together with providing a nascent perspective on principles of implementation (Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b). 4.4.3

Construct and Eval3

The Eval3 activity serves to initially demonstrate if and how well the artifact performs while interacting with organizational elements. Moreover, this activity allows for identifying initial inferences on the utility of the artifact. However, since this activity links ex ante as well as ex post evaluations, reflecting an artifact’s design is deemed as crucial to stimulate subsequent iterations of the design activity if necessary (Sonnenberg & vom Brocke, 2012b). In this context, the notion of the three realities as introduced by Sun and Kantor (2006) is prevalent since the artifact should be deployed at least in one of them, e.g., in terms of conducting real tasks with real users, albeit still constituting an artificial evaluation with an emergent artifact (Venable et al., 2012, 2016).

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Input In the context of the development of the DiDesigner, the input to this activity is a prototype (Cleven, Gubler, & Hüner, 2009; March & Storey, 2008) that encompasses a web application ingraining the principles of form and function validated in Eval2 as well as a further developed version of the VBA tool as a supplement for addressing nascent implementation aspects of the web application. By reflecting the generativity that can potentially be unleashed by new digital resources together with initiating the design and development of novel digitally enabled service systems, this artifact instance constitutes a nascent digital tool as innovation trigger (Nambisan, 2013). With its main purpose to foster the positive outcomes of digitally enabled generativity, the core of the artifact is constituted by factoring in inherent constraints of the design of a novel service system based upon the assessment of those who created the idea of the service system in the first place. Hence, based on the dimensions dealing with which actor applies his specialized competences through deeds, processes, and performances at which time, at which place, and with which information being relevant in this context and dependent on the constraints factored in along these dimensions, a number of patterns that lead to service systems with enhanced resource density is demarcated. In more detail, assessing constraints on behalf of those who created the idea of the service system in the first place is reflected by assigning numerical values for these constraints on behalf of the DiDesigner. Identifying extrema and minima as well as significant means among these values then leads to the selection of appropriate patterns from a repository of suitable patterns of digitally enabled service systems with enhanced resource density as illustrated in Figure 14.

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Figure 14. Patterns for Resource Density Enhancement Presented in Eval 3

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These patterns are characterized along the dimensions of actor (V), time (T) and place (O) and can be regarded as relational constructs in relation to the initial idea of the service system. For instance, the pattern V2T2O0 denotes an actor shift from the initial (A0) actor to an actor with less specialized competences that is enabled by configuring liquefied information for the new actor so as to generate novel knowledge. Adding to that, a shift in the time (T) when these competences are applied can be enabled by modeling liquefied information in a way that allows for generating applicable novel insights (Benaroch, 1998; Gruber, 1995; Lim et al., 2018; Lusch & Nambisan, 2015). However, no shift in place is fostered since this is deemed to be a not necessarily positive outcome in relation to the initial idea of the service system. In a broader sense, these patterns also lead to a reciprocal thinking, for instance, in terms of acknowledging initially unanticipated actors that possess the capability to apply their specialized knowledge and skills to model information in accordance with the needs of the novel actor with less specialized knowledge and skills (V2). Evaluation Method With the aim to evaluate this instantiated artifact against its applicability, an evaluation based on the prototype was conducted with a real task and real users (Sun & Kantor, 2006). The task was reflected by the aim of deriving design alternatives for the industrial service whose development was initiated by the automotive, aerospace, and industrial supplier in cooperation with the engineering company involved in the ongoing research project described in Study 3. The users were represented by three experts in the field of digital technologies and data visualization from the engineering company. The task of designing the nascent digitally enabled service system was conducted collaboratively in a workshop setting with feedback on the artifact and its applicability being fostered by the thinking aloud method (Boren & Ramey, 2000). The session was audio-taped with the audio-tapes being transcribed in the further course. Coding took place in accordance with (Miles et al., 2014) and followed the interpretive tradition (Walsham, 2006).

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Evaluation Results This evaluation activity focused on demonstrating the applicability of the artifact instance, together with proving that it ingrains the principles of form and function validated in Eval2 (Sonnenberg & vom Brocke, 2012b). Since the artifact was applied in a context with real users and a real task, a further focus was laid upon assessing its perception among its users and their respective organizational environment as well as its capability to adapt to various unanticipated tasks that emerge from the context of digitally enabled generativity (Yoo, 2013). Hence, evaluation criteria dealing with the environment, e.g., perceived usefulness and perceived ease of use (Davis, 1989), and evolution, e.g., learning capability and robustness, of the artifact (Prat et al., 2015) were considered to be of note in the course of Eval3. Evidence from the workshop with the prototype revealed that the artifact possesses the capability to interact with organizational elements in a way that is suitable for explicating applicable design knowledge for engineering digitally enabled service systems. One of the participants with an academic background in service engineering elaborates on the notion of service and how the underlying premises are reflected by the purpose and scope of the artifact: ‘Basically, that is the nature of service. So I can remember that I once wrote: the starting point is that the customer cannot or does not want to do the service on his own. So these are the two things: can or want. So, ‘can’ means he does not have the skills and ‘want’ means he has other ways of earning money. This means that he does not want to use his capacity for this. Basically, this system exactly supports this kind of decision-making.’ His colleague further elaborates on the applicability of the artifact in the course of everyday business scenarios with his customers: ‘First of all, I really liked the standardized suggestions in terms of that I am able to say: "For your situation, dear customer, there are the following possibilities for action. You should take a look inside.’ However, he also provides remarks concerning its efficacy and generality. In more detail, he emphasizes identifying activity relevant information as partially overloaded

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‘Are all these information really relevant to the digital service? Because here a lot of information is collected.’ and refers to the scope of the artifact’s goal: ‘As, for example, when I think of a production line. We start with a park of two or three machines. I probably have a lot of jobs that need to be done. Does that work? There it gets exciting because you can find out where I can dive in with digitization.’ However, in general, the principles of form and function ingrained in the artifact were recognized as understandable and valuable for the systematic design and development of novel digitally enabled service system among the participants: ‘I basically have different dimensions of a problem and there are possible solutions for it and I can combine them with each other. And this liberation from constraints actually means: I will have new combination possibilities, which I had not seen before or which were not technically feasible because of constraints. And there is a big block of physical things as well as digital things that can be separated from each other. And we are actually concentrating more on digital things now. So how can I use knowledge, in the form of data? How can I support decisions and make processes more efficient? And that is where I think the value lies.’ Aspects dealing with how people interact with the artifact were prevalently put into relation with the capability of the artifact to evolve with use over time. In this context, one participant states: ‘We want to involve different actors. We also want to give SMEs a chance to be part of this creativity. That does make sense. You just have to be careful that it is not too technical and stuffy, I would say. Not in the way that you only have masks and have to fill in a thousand things and say in the end: "Now I have completely lost track".’ And ‘Basically, these input masks are also the ones with which the system can learn. So, anyone who works with it and invents new alternatives, puts them into the pool and every subsequent person can help themselves from the pool and can combine these alternatives

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anew. This makes it even more powerful and eventually it becomes confusing. Then you probably have to implement procedures that ensure that those that are often chosen slide up in an Amazon-like way.’ Output Besides demonstrating the applicability of the artifact instance, this evaluation activity should also proof that the artifact instance is consistent with its specification, i.e., that it ingrains the principles of form and function validated in the preceding evaluation activity Eval2 (Sonnenberg & vom Brocke, 2012b). The mandatory output of Eval3 is thus constituted by an validated artifact instance in an artificial setting (Venable et al., 2012, 2016). This validation is achieved by surrogating the real system (Sun & Kantor, 2006) with a prototype of the artifact in the context of a workshop setting with a real task and real users, together with an interplay of theorizing in the interior and exterior mode (Gregor, 2009) in the course of the evaluation activity conducted. With regard to developing a design theory, this activity is concerned with validating the component expository instantiation as well as artifact mutability. Moreover, evidence is gathered with regard to the ability of the artifact to behave according to its purpose and scope (Sonnenberg & vom Brocke, 2012b). 4.4.4

Use and Eval4

Eval4 serves to ultimately show that an artifact is both applicable and useful in practice (Sonnenberg & vom Brocke, 2012b). The evaluation activity thus reflects the nature of a naturalistic evaluation (Venable et al., 2012, 2016) which is characterized by encompassing the interplay of all three realities (Sun & Kantor, 2006). As stated in Sonnenberg and Vom Brocke (2012b), Eval4 also reverts to the initial input of Eval1, i.e., the research entry points described by (Peffers et al., 2007). Input In the context of the DSR project reported on, the input to this activity is an instantiation (Gregor & Hevner, 2013) of the DiDesigner (Nambisan, 2013) that acts on the natural world and constitutes a further developed version of the web application

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described in Eval3. This artifact is illustrated in Figure 14 and encompasses the formerly nascent implementation aspects supplemented by the VBA tool.

Figure 15. DiDesigner as Instantiation in Eval 4

Evaluation Method With the aim to evaluate the artifact against its applicability and usefulness in a natural setting, a field experiment (Siau & Rossi, 2011) was conducted on site at a plant of the automotive, aerospace, and industrial supplier. The six participants were comprised of managers on various levels dealing with the execution of the strategy on digital transformation and service orientation in the context of their company. Since

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the task described in Eval3 and Study 3 initially emerged from the involvement of their colleagues in the ongoing research project, it was deemed to be particularly valuable to revert to this task with the perspective of formerly not incorporated stakeholders. The task of designing the nascent digitally enabled service system was again conducted collaboratively in a workshop setting with feedback on the artifact and its applicability being fostered by the thinking aloud method (Boren & Ramey, 2000). The session was audio-taped with the audio-tapes being transcribed in the further course. Coding took place in accordance with (Miles et al., 2014) and followed the interpretive tradition (Walsham, 2006). Evaluation Results This evaluation activity focused on showing that the DiDesigner is both applicable and useful in practice. Hence, together with acknowledging the research entry points elaborated on in Eval1, the underlying premises of applicability checks (Rosemann & Vessey, 2008), i.e., the notions of importance, accessibility, and suitability of an artifact, and criteria dealing with the goal of the artifact (Prat et al., 2015), e.g., goal attainment, utility, feasibility and generality, were taken into consideration. Moreover, since the artifact is deployed to the reality of a broader set of real users and works in a real environment (Sun & Kantor, 2006), criteria addressing its perception in its environment, e.g., concerning its alignment with business and absence of side effects, as well as criteria assessing its activity, e.g., concerning its performance and trustworthiness (Prat et al., 2015), were considered to be of note in this context. Evidence from the field experiment revealed that the artifact is broadly perceived as applicable among the participants. One participant emphasized the importance of the context that the artifact addresses and to which degree organizations are able to cope with underlying challenges: ‘There is an advantage of digitization in itself, which perhaps has not yet been sufficiently considered. Because we always start from a process. From a model that a human being models. And that's where we always have the problem when it becomes multidimensional. Then the human being is quickly at its end. And that would be something that the

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computer can really master. So this three-dimensional matrix here or this threedimensional swimlane. And you could also benefit from this.’ However, he also raised the alignment with a user’s business as a crucial point to consider in terms of the artifact’s suitability: ‘I see a risk in this approach. It's very good, I don't want to talk that down. But maybe just as a clue. It will become a product. The risk, however, is that the customer does not need this product at all, because he can't allocate it at all, because it simply doesn't fit into his business.’ From a contrary point of view, another participant elaborates on this point in terms of the socio-technical processes that are concomitant with digitally enabled generativity and have an influence on how companies do their business, thus anticipating the suitability of the artifact from another perspective: ‘There is something else that makes digitization different from what we have always done before. That's risk awareness. That's what this startup thinking is like. Just like you said, what comes out does not necessarily have to work. That's what this thinking is like. Nine out of ten startups don't work. They disappear, money was burned. However, the one thing that remains is worth it.’ Besides that, the artifact and its underlying notions were perceived as understandable and accessible among the various participants: ‘As I understood it, it is prevalently a suggestion tool in the sense: “What are possible potentials in the context of digital transformation?” And I think that is a good support. A systems architect might have these ideas on his own. He knows what a computer is capable of. He is less afraid of that stuff. However, a colleague who is not too much into working with IT might not have these ideas.’ or put shortly ‘The result of this tool from my point is: think about what is possible.’

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Dealing with the usefulness of the artifact, one participant elaborates on aspects dealing with the artifacts operational feasibility and performance and states: ‘I really very much like the thing to showcase variants. But I would rather not use it as a foundation for a decision. Nobody would decide something based on that. What is missing here is: “What do I get from that?” Thus, a ratio or a value in Euro.’ and ‘Actually, I would consider the added value of the tool in an earlier stage. In the sense that you are introduced to the topic in the first place and then, structured and based on the predefined patterns introduced by the tool, elaborate on all the possible things. And then all these pictograms are derived and when the thing is finished, the users can look in each other’s eye and say: “that might make sense.”’ In this vein, a colleague further elaborates on the generality of the artifact in terms of its adaptability to various organizational settings: ‘Is this configurator configurable?’ And ‘Imagine taking this tool to the innovation management department within a company with the aim to establish a standardized innovation or digitization process, then the tool should possess the capability to assess the company specific requirements. Then I could implement an automotive, aerospace, an industrial supplier-tool or a VW-tool etc.…’ Output Besides showing the applicability and usefulness of the artifact in practice, this evaluation activity should also proof that the DiDesigner is consistent with the initiation of the DSR project, i.e., the research entry points elaborated on in Eval1. This validation is prevalently achieved by focusing on theorizing in the exterior mode (Gregor, 2009) in the course of the evaluation activity conducted. The mandatory output of this evaluation activity is thus constituted by a validated artifact instance in a naturalistic setting (Venable et al., 2012, 2016). Hence, in terms of fostering the

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specification of a design theory, statements regarding the component dealing with testable propositions can be explicated (Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b).

4.5

Artifact Description

Reverting to the objective of this study, the DiDesigner plays a dual role. First, in its representational role as expository instantiation (Gregor & Hevner, 2013; March & Smith, 1995), it deals as means to assist with the communication of design principles inherent in the prescriptive knowledge produced up to this point (Gregor & Jones, 2007). Second, in its functional role as digital tool that triggers innovation (Nambisan, 2013), it deals as support in the course of engineering novel digitally enabled service systems. Hence, for the purpose of both, theory representation and description of the artifact design, the DiDesigner in its current form is described in more detail in the following. The prototype is implemented as single page web application7 based on the Angular8 framework. The graphical user interface was built by making use of Google’s Material Design9 language due to its wide distribution in Android operating systems or common Google applications. By that, a high degree of familiarity can be achieved among users, which, in turn, fosters the accessibility of the DiDesigner as a whole. The interface of the application is in alignment with the design specification developed beforehand and is structured along the components (1) Job Steps, Actors, and Activities, (2) Information Liquification, (3) Constraints, (4) Unbundling and Rebundling, (5) Fine Tuning.

Accessible via http://smartdif.de/Publikationen https://angular.io/ 9 https://material.io/ 7 8

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Job Steps, Actors, and Activities Following the assumption that every job to be done can be decomposed into concise subsystems, i.e., job steps, in (1), the user is guided through this process by retrieving his inputs along the eight steps prescribed for job mapping. In Figure 16, this is illustrated by means of the exemplary job to be done of getting a cup of coffee at a coffee shop. For instance, the user is defining the execution step by answering the question of what are the most central tasks that must be accomplished in getting the job done?. In the context of this example, a user entry could be Ordering coffee. Moreover, the deeds, processes, and performances through which various actors apply their specialized competences in order to get the job step done are retrieved. Here, one of the activities conducted on behalf of the customer to get Ordering coffee done could be to Place order. As illustrated in Figure 17, these deeds, processes, and performances and according actors are assigned to the job steps defined beforehand and constitute a means to an end to get them done, albeit reflecting a degree of resource density that is contingent on the imagination and ambition on behalf of the user.

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Figure 16. Component Job Steps, Actors, and Activities of DiDesigner (I)

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Figure 17. Component Job Steps, Actors, and Activities of DiDesigner (II)

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Information Liquification This component predominantly deals with the premises associated with the technology-permeated process of uncoupling information from its carrier by means of digitization. With liquefied information being a crucial resource in digitally enabled service systems, (2) acknowledges the various kinds of information entities relevant for the deeds, processes, and performances delineated in (1). As depicted in Figure 18, the user is asked to assign information entities to certain deeds, processes, and performances in reference to whether they are needed for or produced during their execution. With the aim of guiding the user through this process, information entities can be classified according to pre-defined categories. Referring back to the example introduced above, the customer receipt produced during Pay coffee contains the information Point of time of order placement. In accordance with the dematerialization mechanism liquification, this information can be uncoupled, configured and modeled in different ways so as to generate novel insights for a variety of actors within and across the digitally enabled service system to be developed. By that, a necessary condition for enhanced resource densities is accomplished.

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Figure 18. Component Information Liquification of DiDesigner

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Constraints The main aim of this component is to gather an understanding of the constraints anticipated by the ones who created the idea of the service systems in the first place, thus providing the foundation for acknowledging the positive outcomes of digitally enabled generativity, i.e., enhanced resource densities, in the development process toward a novel digitally enabled service system. In (3), inherent constraints in terms of when, where, and by whom deeds, processes, and performances can be executed are factored in as controls that induce a number of variations in the design of the resultant digitally enabled service system in the further course. In the context of the example introduced above, Collect coffee is an activity that is conducted by the Customer (beneficiary). The customer has to wait at his table and cannot do something else (e.g., going to the toilet) until he is called up. In a crowded shop, he might have to queue up again in order to get his coffee. The coffee might be could in the end. However, with him knowing what the barista knows, i.e., when the coffee is ready, he could get up earlier and get the coffee at the counter without being constrained to so something else in the meantime. Hence, as illustrated in Figure 19, this activity is deemed to be constrained with a certain level of flexibility, that is, ZS3: We could do that at another point of time if we had the right information available in this case. Reverting to the notion of generativity as a relational construct, the assessment of deeds, processes, and performances in terms of inherent constraints allows for proposing configurations of resources that were initially unimaginable from the viewpoint of the user of the DiDesigner.

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Figure 19. Component Constraints of DiDesigner

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Unbundling and Rebundling In accordance with the notion of resource density, this component predominantly deals with dematerialization of activities hitherto well defined and held together in time and place and by actor. Based on the user entries dealing with the delineation of constraints among the deeds, processes, and performances determined beforehand, in (4), the user is confronted with unanticipated changes in the design of the digitally enabled service system to be developed. Based on the patterns that were derived from the generative mechanisms identified throughout this research and depending on the constraints defined beforehand, a number of service systems with unanticipated variations in their design can be displayed. In Figure 20, a novel configuration of an digitally enabled service system that addresses the initially defined job to be done, i.e., getting a cup of coffee at a coffee shop, is depicted. Here, the user might choose a maximum level of innovation in order to get suggested a blueprint that is vastly liberated from the constraints defined beforehand. For instance, when provided with information that is modelled in an appropriate way, a New actor (specialized competencies) might take over the activity of Collect coffee. Therefore, he might be provided with knowledge ingrained in the information entities to be liquefied (e.g., Type of coffee or/and Point of time of order placement) within the resultant digitally enabled service system. Food delivery businesses such as Foodora10 or Lieferando11 have specialized themselves in picking up food and beverages from restaurants without an own delivery service and could act as a new actor to be incorporated.

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https://www.foodora.com/about/ https://corporate.takeaway.com/about-us/what-we-do/

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Figure 20. Component Unbundling and Rebundling of DiDesigner (I)

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However, as depicted in Figure 21, also rather small changes are promising to enhance resource density. The activity Prepare coffee might be conducted at a Better Point of Time when the barista is provided with the information Type of coffee in a way that is not bound to the materiality of paper receipts. By that, the user is enabled to adjust a rather extreme reconfiguration in accordance with his special business needs. In the end, a blueprint of a digitally enabled service system with an unanticipated level of resource density can be derived and a positive outcome of digitally enabled generativity is achieved from the viewpoint of the user.

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Figure 21. Component Unbundling and Rebundling of DiDesigner (II)

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Fine Tuning The patterns that guide the reconfiguration of the digitally enabled service system to be engineered are based on the generative mechanisms that tend to lead to enhanced resource densities. However, in order to achieve configurations of resources that reflect a maximized level of resource density from the viewpoint of the user, the generic blueprints created in (4) are to be complemented by insights on how to realize them in the context of the user’s organization. Hence, (5) provides guidance for assessing which actors could potentially possess the specialized competencies to model the liquefied information in a way that enables the reconfiguration and according shifts suggested beforehand. As depicted in Figure 22, the liquefied information directly or indirectly relevant for a certain job step is displayed and put into context of a shift. As already mentioned beforehand, a New actor (specialized competencies) might take over the activity of Collect coffee. In order to enable the shift of this activity towards him, the Store owner is considered as actor that could help model the information Order time in a way that mobilizes the contextually relevant knowledge in the most effective and efficient way. By that, a compaction of the blueprint for the digitally enabled service system suggested beforehand is achieved in terms of maximizing inherent resource densities. Against the backdrop of fostering a collaborative development of the service system among a multitude of stakeholders, the resultant draft of the digitally enabled service system to be developed can be further distributed and/or edited. For this purpose, the options Save, Import, Share Link, and Export as PDF are provided. Ultimately, the DiDesigner provides support to transform the rough idea of a job to be done with a certain level of resource density into a digitally enabled service system with a maximized level of resource density from the viewpoint of the user.

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Figure 22. Component Fine Tuning of DiDesigner

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Discussion

In accordance with the premises for presenting design science research introduced by Gregor & Hevner (2013), this section provides a summary of what has been learned by expressing the design knowledge gained in terms of the design theory framework specified by Gregor and Jones (2007). Having documented the development of the DiDesigner in a way that fosters the emergence of truth-like statements (Iivari, 2007) about the expository instantiation, allows for explicating and communicating the prescriptive knowledge ingrained in it (Gregor, 2006; Gregor & Hevner, 2013; Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b). Against the backdrop of the overall objective of this dissertation to set a foundation for the emergence of a coherent and consistent body of knowledge for engineering service systems in the digital, the principles inherent in the design of the expository instantiation can be articulated along eight structural components (Gregor & Jones, 2007): (1) purpose and scope (causa finalis), (2) constructs (causa materialis), (3) principles of form and function, (4) artifact mutability, (5) testable propositions, (6) justificatory knowledge, (7) principles of implementation, and (8) expository instantiation. The evaluation activities elaborated on above address these attributes to varying degrees by imposing various requirements to be addressed in the course of the evaluation trajectory. Hence, in order to provide a means for the transparent communication of knowledge for an emergent design theory (Mueller & Urbach, 2017; Piirainen & Briggs, 2011), the linkages in between the components of a design theory according to Gregor and Jones (2007) and underlying knowledge contributions produced in the course of the evaluation activities conducted are illustrated in accordance with the premises of Quality Function Deployment (Akao, 1990). In particular, the “House of Quality” (Akao, 1990), as illustrated in Figure 23, allows for assessing the fit of evaluation activities to the components of an emergent design theory. According to Gregor & Hevner (2013), if research can be expressed in these terms, with more explanation, more precision, more abstraction, and more testing of beliefs facilitated, then there is a move toward a more mature and well-developed body of knowledge—the ultimate goal in DSR (Gregor & Hevner, 2013; Nagel, 1979).

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Figure 23. House of Quality for Expository Instantiation Reverting to the research question of how generalizable guidelines for engineering digitally enabled systems can be produced and communicated by means of a digital tool, the alternating design and evaluation of the DiDesigner throughout the development trajectory allows for inferences on the truth value of the prescriptive knowledge ingrained in it, which, in turn, deals as foundation for explicating prescriptions of guidelines for further artifacts that support the engineering of digitally enabled service systems by means of theorizing in both, the interior as well as exterior mode. Along these lines, the inter mode is where theorizing is done to produce theory for design and action, with prescriptive statements about how artifacts can be designed, developed,

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and brought into being. The exterior mode, which also could be referred to as ‘indirect design theorizing’, aims at analyzing, describing, and predicting what happens as artifacts exist and are used in their external environments. This theorizing is still design-oriented theorizing, even though no artifacts are produced in this mode. However, theorizing in the exterior mode differs from traditional non-design theorizing, since it recognizes a special feature of artifacts, that is, their goaldirectedness and focuses on design features that can be manipulated in the achievement of goals (Baskerville et al., 2018; Gregor, 2006, 2009). The ex ante evaluation of the artifact in its representation as Power Point slides in Eval1 focused on justifying the development of the prospective artifact. By theorizing in the interior mode, statements with truth-like value (Iivari, 2007) about the purpose and scope, underlying constructs, applicable justificatory knowledge, and preliminary testable propositions (Gregor & Jones, 2007) can be articulated. Eval2 aimed at achieving a validation of the artifact’s design specification in the course of an ex ante evaluation of the artifact in its form as VBA tool. As with Eval1, this evaluation setting could still be considered as purely artificial. However, dealing with the how of artifact construction (Gregor, 2009) in the interior mode of theorizing provides the ground for explicating statements regarding the form and function as well as underlying justificatory knowledge for the design of the artifact in the current stage, together with inferences of principles of implementation. The focus of Eval 3 was to initially demonstrate if and how well the artifact performs while interacting with organizational elements. Thus, the artifact, i.e., a combination of an early version of a web application and the VBA tool, was partly exposed to the three realities as defined by Sun & Kantor (2006). In this vein, this evaluation activity built a bridge between ex ante and ex post evaluation, thus fostering the explication of inferences on more fine-grained principles of form and function (based on Eval2), the purpose and scope addressed by these principles, insights on how to bring an expository instantiation into being, and perspectives on artifact mutability by means of an interplay of theorizing in the interior and exterior mode. Eval4 served to show that an artifact is both applicable and useful in practice. This evaluation activity addressed all three realities (Sun & Kantor, 2006), thus mainly focusing on the ex post evaluation of the artifact in its form as a more mature web application. Beside proofing its consistency with the initiation of the DSR project

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depicted in Eval1, theorizing in the exterior mode at this stage fosters the formulation of testable propositions as means to assess the capabilities of artifacts that are built on the prescriptive knowledge ingrained in the DiDesigner. To sum up, the development of the DiDesigner made use of the prescriptive knowledge produced in the preceding studies with the aim to provide a ground for the structured communication of underlying principles. By specifying points of departure for the further explication of the accumulated prescriptive knowledge, it can be expressed along the components of a design theory (Gregor & Jones, 2007). By presenting this knowledge with a higher degree of abstraction, it can be generalized to other situations an emerge toward a more comprehensive body of knowledge for engineering service systems in the digital age. In other words, by setting the foundation for theorizing in both, the interior and exterior mode, this expository instantiation allows for the articulation of principles inherent in its design in terms of a design theory, which ultimately shapes a more mature body of knowledge (Gregor, 2006; Gregor & Hevner, 2013; Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b).

4.7

Contribution and Conclusion

Digital technology changes the dynamics of innovation (Eaton et al., 2015; Lusch & Nambisan, 2015). In fact, especially the emergence of layered module architectures enabled by digital technology has laid the foundation of novel forms of generative innovation (Yoo et al., 2010; Zittrain, 2006). The present study reports on the development of the DiDesigner, a digital tool for engineering digitally enabled generativity in service systems in terms of acknowledging the positive outcome of unanticipated change in the course of their systematic design and development, and specifies prescriptions of guidelines for artifacts of the same type by documenting knowledge with truth-like (Iivari, 2007) value based on alternating design and evaluation loops (Sonnenberg & vom Brocke, 2012b). From a DSR perspective, two intertwined contributions can be claimed. As an instantiation (Gregor & Hevner, 2013), the DiDesigner addresses the notion of digitally enabled generativity in service systems in terms of acknowledging potential positive

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outcomes of unanticipated change induced by digitally enabled generativity in the course of their systematic design and development. The novelty of this artifact is constituted by embodying prescriptive design knowledge in terms of guiding the systematic design and development of digitally enabled service systems based on controls and mechanisms that dedicatedly address the complex and intangible nature of service systems in the digital age. By providing generative mechanisms (Bygstad, 2017; Henfridsson & Bygstad, 2013; van Aken, 2004) that are built in accordance with the conceptualization of the dematerialization mechanisms underlying the concept of resource density, the design and development of novel digitally enabled service systems with enhanced resource densities (Lusch & Nambisan, 2015; Normann, 2001) is fostered. In sum, the DiDesigner can be considered a digital tool that triggers innovation (Nambisan, 2013) by operationalizing the established notion of resource density in the novel context of digitally enabled generativity (Yoo, 2013) that is increasingly fostered by the emergence of digital technology (Yoo et al., 2010). Thus, the knowledge contribution can be characterized as an improvement (Gregor & Hevner, 2013) that addresses the nascent aspects of TRIGGER, thus mainly contributing to the Λ knowledge base (Gregor & Hevner, 2013). Contributions to both, the Λ and Ω knowledge base (Gregor & Hevner, 2013), are made in terms of truth statements (Iivari, 2007) about the artifact by documenting the alternating design and evaluation of the DiDesigner along the evaluation activities introduced by (Sonnenberg & vom Brocke, 2012b). Explicating this knowledge along the components of a design theory according to (Gregor & Jones, 2007) then allows for the prescription of guidelines for further artifacts of the same type (Gregor & Jones, 2007). From a rather micro-level view, the nature of the knowledge produced thus guides the development of artifacts that support the systematic design and development of digitally enabled service systems (Böhmann et al., 2014a). Adding to that, from a more macro-level view, this knowledge is in vein with the nature of innovation in the digital age in general by assuming innovation as less bounded in terms of innovation outcomes or processes and considering the role of digital tools as enabler (or trigger) for innovation (Nambisan et al., 2017).

V Discussion: Shaping a Body of Design Knowledge

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_5

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Following Bem (2003), the discussion section goes back to the generalities imposed by the overarching research objective. In this vein, Gregor and Hevner (2013) suggest to delineate what has been learned throughout the preceding inquiries by expressing the respective design knowledge gained in terms of the design theory framework specified by Gregor and Jones (2007). A well-developed example for this approach is provided by Moody (2009). As stated in the beginning, the overarching research objective for this dissertation deals with the question of how design knowledge for engineering service systems in the digital age can be developed toward a consistent body of design knowledge. In this context, Gregor & Hevner (2013) state that the emergence of a well-developed body of design knowledge is contingent on expressing underlying knowledge in terms that allow for prescriptions of design and action (Gregor, 2006; Gregor & Jones, 2007). Hence, with the aim of providing a sound basis for the development of prospective artifacts that address the same class of problem, i.e., engineering service systems in the digital age, the prescriptive knowledge produced in the course of this dissertation is to be documented and communicated along the anatomy of a design theory as introduced by Gregor and Jones (2007). Reverting to the metaphorical analogy of a mechanical engineer that uses the DUBBEL (Beitz & Küttner, 1994) to design unprecedented artifacts from hitherto unknown materials, abstracted principles inherent in the design of a class of artifacts that support the engineering of service systems in the digital age can be specified in a generalized form along the eight constituents of a design theory (Gregor & Jones, 2007). If research is expressed in this way, a move can be made toward a more mature and well-developed body of design knowledge (Gregor & Hevner, 2013; Gregor & Jones, 2007). Thus, following the call of SSE for design theories that allow for the prescription of guidelines of novel artifacts that enable or support the engineering of real-world service systems that permeate our society (Böhmann et al., 2014a), the discussion section answers the overarching research question by explicating the foundations for

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an emergent design theory along the knowledge contribution claims from the studies described beforehand, together with prescribing an avenue for its maturation toward a consistent body of design knowledge for engineering service systems in the digital age. Moreover, based on this synthesized view, the contribution of the dissertation is articulated and positioned in the research field.

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Specifying an Emergent Design Theory

Throughout this dissertation, knowledge creation took place along a set of inquiries with different knowledge moments. In this vein, a knowledge moment can be defined as a unit of knowledge processing, triggered by a specific need for knowledge and addressed by the specific delivery of the knowledge in a manner that is aligned with a given context (Baskerville et al., 2015). Study 1 encompasses a knowledge moment that involves the creation of idiographic design knowledge, i.e., knowledge that is applicable to a particular problem or artifact in terms of devising a course of action that changes an existing situation into a preferred one. The knowledge role of the artifact is then characterized by materializing or embodying this knowledge (Baskerville et al., 2015; Simon, 1996). Along these lines, the development of the taxonomy that encompasses prescriptive knowledge contributions provides idiographic design knowledge on two levels. First, in a broader sense, by addressing the need for bringing order to a variety of fragmented knowledge contributions via the development of the taxonomy, the existing situation is changed into a preferred one (Simon, 1996). Second, from a more narrow view, the knowledge contributions classified within the taxonomy are delineated by means of various characteristics, including their type and novelty, the role of digital technology, and their knowledge contribution claim, thus providing an understanding of underlying design implications and the setting they apply to (Baskerville et al., 2015). The knowledge moment of Study 2 is constituted by its intent to produce idiographic scientific knowledge. The nature of idiographic scientific knowledge is characterized by going beyond establishing patterns of events; it rather seeks to understand the underlying causes, structures, and generative mechanisms responsible for observed patterns (Baskerville et al., 2015; Tsoukas, 1989). Hence, identifying generative mechanisms that tend to lead to enhanced resource densities in digitally enabled service systems can be acknowledged as knowledge moment that produces idiographic scientific design knowledge (Baskerville et al., 2015) that, when combined with goals

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into prescriptive statements, is promising to evolve into prescriptive knowledge (Barquet et al., 2017; Goldkuhl, 2004). The design and evaluation of TRIGGER in Study 3 depicts a further idiographic design knowledge moment, albeit with a different nature than the one described for Study 1. In this context, its value arises from three major aspects (Baskerville et al., 2015). First, insights can be gathered from the detailed and particular considerations that can be availed through interactions or experience with designs (Hook, McCarthy, Wright, & Olivier, 2013). Second, insights that stem from idiographic design can provide the basis for guiding design for broader usage (von Hippel, 1986). Third, idiographic design provides a mechanism for the validation of an artifact design (Baskerville et al., 2015; Järvinen, 2007; Winter, 2008). As a consequence, the design of TRIGGER based on dedicated requirements, together with its formatively-oriented evaluation, represents an inquiry that predominantly culminates into the creation of idiographic design knowledge. Ultimately, the development of the DiDesigner, concomitant with communicating underlying prescriptive knowledge among an interplay of ex ante and ex post evaluations throughout its development, allows for both, theorizing in the interior and exterior mode (Gregor, 2009; Sonnenberg & vom Brocke, 2012b). The inquiry in Study 4 thus provides the ground for nomothetic design theorizing, which embodies knowledge processes that aim at producing general knowledge about a class of designs. The resultant knowledge is applicable to rather general calls of design problems, general solution artifacts, and their relationships (Mandviwalla, 2015; Simon, 1996). Nomothetic design can then be expressed as more generalizable design theories that allow for prescribing principles inherent in the design of a class of artifacts that accomplish some end (Gregor, 2006; Gregor & Jones, 2007; Markus et al., 2002). Although the design and evaluation of the DiDesigner per se does not address the characteristics of nomothetic design knowledge in its entirety, it allows for the documentation of the accumulated prescriptive ingrained in the expository instantiation by means of the constituents of an emergent design theory in the further course (Gregor & Jones, 2007; Sonnenberg & vom Brocke, 2012b).

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Having positioned the DiDesigner as an expository instantiation, together with prescribing how inherent design principles of classes of artifacts that support the engineering of digitally enabled service systems can be articulated in a structured way, thus allows for explicating the prescriptive knowledge accumulated throughout this dissertation in accordance with the anatomy of a design theory (Gregor, 2006; Gregor & Jones, 2007). In this context, it can be argued that design theorizing that drives the emergence of theories for design and action (Gregor, 2006) is to be interpreted as theoretical output of design (Kuechler & Vaishnavi, 2008; Piirainen & Briggs, 2011; Walls et al., 1992). According to Gregor & Jones (2007) the formal knowledge that emerges from specifying and elaborating a design theory is pivotal because it (1) raises DSR above a craft, (2) adds to rigor and legitimacy, and (3) supports the cumulative building of knowledge that can only come into being if novel insights and ideas are elaborated as knowledge that can then be classified and compared (Mandviwalla, 2015). Adding to that, articulating knowledge with a higher degree of abstraction is particularly important in the context of the technology-sensitive problem context addressed within the scope of this dissertation. The evolution of technology in general and digital technology in particular can be very pervasive and, by that, radically changes the nature of innovation endeavors (Arthur, 2009; Ridley, 2015; Yoo et al., 2012, 2010). It is then the role of science to understand how and why the newly introduced technology and concomitant phenomena impacts the surrounding world as it does. Thus, it can be posited that, in most cases, technology evolutions precede and drive science evolutions (Mokyr, 2002). In turn, science also informs technology via rigorous grounding in application domain knowledge bases (Baskerville et al., 2018). As a consequence, producing prescriptive knowledge with truth-like value (Iivari, 2007) for engineering service systems in the digital age is inhibited when solely focusing on certain artifacts or technologies that address distinctive digital technologies, i.a., the Internet of Things, 3D/4D printing, blockchain, smart advisors or advanced analytics (Denner et al., 2018). The focus of inquiry rather is to be shifted toward acknowledging generic new technology affordances that are enabled by digital technologies and anticipating how they influence innovation trajectories and outcomes (Nambisan et al., 2017). To sum up, presenting prescriptive knowledge with a higher degree of abstraction allows it to be generalized to other situations. New knowledge then is likely

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to be more highly regarded the further up the levels of abstraction it can be pushed to nascent design theory or more complete design theory (Baskerville et al., 2015; Bichler et al., 2016; Gregor & Hevner, 2013). According to Gregor and Hevner (2013), in order to evolve to the stage where design knowledge could be termed design theory, an explanation why the method works as it does or a good account of the specific conditions under which it holds should be provided in alignment with the anatomy of a design theory (Gregor & Jones, 2007). If research is expressed in these terms, with more explanation, more precision, and more testing of beliefs facilitated, a move can be made toward a more mature and well developed body of knowledge – the ultimate goal in the course of producing prescriptive knowledge that deals with real-world phenomena (Gregor & Hevner, 2013; Nagel, 1979). Hence, as a point of departure toward the development of a consistent body of design knowledge for engineering service systems in the digital age, the prescriptive design knowledge produced throughout this dissertation is articulated along the components of a design theory as conceptualized by Gregor & Jones (2007). Gregor and Jones (2007) explicate eight structural components that are needed to specify and communicate a design theory: (1) the purpose and scope, which specifies the type of artifact to which the theory applies, together with defining its boundaries, (2) the constructs and their interplay that are of interest to the theory, (3) the principles of form and function constituting an abstract blueprint of the artifact, (4) an artifact’s mutability, which deals with the

degree of anticipated changes to the artifact

encompassed by the theory, (5) a set of testable propositions about the artifact to be constructed, (6) the underlying justificatory knowledge that gives an explanation for the design, (7) principles of implementation describing how the design is brought into being, and (8) expository instantiations for the purposes of theory representation. The distinct components of an emergent design theory for artifacts that support the engineering of digitally enabled service systems is elaborated on in the following. In the course of explicating applicable statements, the prescriptive knowledge embodying novel contributions from this research in relation to extant research is particularly emphasized. In this vein, insights from the development of the DiDesigner in its role

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as expository instantiation for theory representation are put into focus, but complemented by statements that address the unique nature of prescriptive knowledge accumulated in the overall scope of this dissertation. In this vein, this research utilizes the anatomy of a design theory as conceptualized by Gregor and Jones (2007) as structured approach to extract applicable knowledge contributions from the knowledge accumulated throughout Study 1, Study 2, Study 3, and Study 4 as well as underlying theoretical foundations in order to prescribe the constituents of an emergent design theory. By having accumulated design knowledge along the evaluation of artifacts (evaluation of TRIGGER in Study 3 and evaluation of DiDesigner in Study 4) whose design was informed by both, extant prescriptive knowledge (taxonomy in Study 1) and empirical inquiries (generative mechanisms in Study 2), prescriptive statements with truth-like value can be ingrained in the emergent design theory. Hence, this research work develops an emergent design theory that, when further theory testing and building is undergone, provides a valuable foundation for prescriptive knowledge to be developed toward a consistent body of design knowledge for engineering service systems in the digital age.

2.1

Purpose and Scope

This design component deals with “what the artifact is for,” or the set of metarequirements or goals that specifies the type of artifact to which the theory applies, i.e., the “causa finalis”, and in conjunction also defines the scope, or boundaries, of the theory (Gregor & Jones, 2007). As elaborated on in Eval1 and Eval3 in Study 4, the main purpose of an emergent design theory is thus to provide prescriptions on the design of a class of artifacts that support the engineering of digitally enabled service systems. Applicable artifacts can thus be characterized as (1) methods or instantiations that (2) exaptate knowledge from the intersection of various research fields, (3) make use of knowledge dealing with the interplay of engineering service architectures, engineering service system interaction, and engineering resource mobilization, and (4) recognize digital technology as a trigger for innovation in service systems in terms of unleashing digitally enabled generativity (cf. Study 1). Concerning (4), these artifacts aim to acknowledge the special nature of innovation in digitally enabled service systems by

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providing guidelines that aim to foster the positive outcomes of digitally enabled generativity in these systems. This can be achieved by understanding the mechanisms leading to respective beneficial resource configurations through the lens of resource density, i.e., one of the most enriching concepts in service research (Lusch et al., 2010; Michel et al., 2008; Vargo et al., 2008) that is particularly attuned to information-centric intangible offerings (Lusch & Nambisan, 2015) (cf. Study 2). Moreover, artifacts supporting the engineering of digitally enabled service systems foster a systematic and structured development of service systems that, on the one hand, considers value creation from a system of service systems perspective, and, on the other hand, acknowledges the operationalization of achieving beneficial resource configurations through the rebundling of resources that create novel resources that are beneficial (cf. Study 3). Reverting to the notion of digitally enabled generativity, achieving designs of service systems that are built on the digitization of information and the modeling of this information by or for varied audiences within and across service systems is contingent on the imagination capabilities of the designers who created the idea of the service system in the first place. Therefore, applicable artifacts are to be attuned to the perception of unanticipated change among the initiator of a novel service system by means of acknowledging respective constraints and controls (cf. Study 4). As sounded out in Eval 1 and Eval 4 in Study 4, from an organizational point of view, the purpose and scope of artifacts of this class of artifacts was recognized, e.g., in terms of statements that described the expository instantiation as a suggestion tool to showcase variants that are grounded in a startup thinking on innovation in the context of digital transformation. Against this backdrop, the scope of the design theory is set at an abstract class-level that prescribes the output of the artifact rather than delineating substantive characteristics on a type-level.

2.2

Constructs

Constructs represent the theory’s entities of interest and their relationships in the sense of “causa materialis” (Gregor & Jones, 2007). Central constructs underlying the prescriptive design knowledge embodied in an emergent design theory for artifacts that support the engineering of digitally enabled service systems are dealt with in Eval1

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and Eval 2 in Study 4. These address the notions of service systems that permeate our society that interact with resources of other service systems in systems of service systems (Böhmann et al., 2014a; Lusch et al., 2010; Maglio & Spohrer, 2007; Maglio et al., 2009; Pinho et al., 2014), digital technology fostering generativity (Yoo et al., 2010), unanticipated change driven by digitally enabled generativity (Yoo, 2013; Zittrain, 2006), controlling generativity to foster positive outcomes (Eaton et al., 2015; Förderer et al., 2014; Pagani, 2013), and resource density for understanding and engineering digitally enabled generativity in service systems (Normann 2001; Henfridsson and Bygstad 2013; Lusch and Nambisan 2015). Throughout the process of knowledge accumulation in this dissertation, the value of these constructs was emphasized under consideration of various facets. For instance, in Eval2, liquification and unbundleability were understood as vehicle for making something better, without necessarily relying on the technical process of digitization to its full extent. Further statements considering the value of these constructs for artifacts that are attuned to the engineering of digitally enabled service systems are dealt with in the course of the formative-naturalistic reported on in Study 2. In this context, most participants expressed a general understanding of the intended purpose of assessing activity-relevant information, decoupling it from their activities and making it available for other actors in order to contribute to the improvement of the service system at hand, although this way of thinking demands for a certain degree of imagination capabilities among the actors involved in the engineering of novel digitally enabled service systems.

2.3

Principles of Form and Function

This component addresses the abstract “blueprint” or architecture that describes an artifact (Gregor & Jones, 2007). Central principles of form and function applicable for an emergent design theory are elaborated on in Eval2 in terms of explicating a design specification that follows the premises of the structured analysis and design technique (Congram & Epelman, 1995; Ross, 1977) in order to describe the functions that lead to enhanced resource densities, i.e., positive outcomes of digitally enabled generativity, in digitally enabled service systems. Adding to that, Eval3 provides prescriptive design knowledge on how to ingrain these principles of form and function in the course of

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developing an artifact prototype. These principles are particularly ingrained in the design of the expository instantiation described in Study 4 and mainly address the nascent aspects of TRIGGER in its back-end stages. In a broader sense, artifacts that support the engineering of digitally enabled service systems are to be attuned to the design principles inherent in the overall design of TRIGGER. As such, the principles of function explicated for the emergent design theory are contingent on the requirements elicitated for TRIGGER. An overview is provided in Table 12. These principles, in turn, are largely addressed by the generative mechanisms that are promising to lead to new resource densities in service systems identified in Study 2, i.e., Invention, Improvement, and Exaptation. Table 12. Design Principles for Emergent Design Theory Foundation

Design Principles

…from a Service Systems Perspective

Innovation in Digitally Enabled Service Systems

DP1: Larger constellations within which multiple actors become joined over time and space in systems of service systems are to be addressed. DP2: The notion of service is to be understood as service systems, i.e., configurations of resources (including people, information, and technology) that are connected by value propositions. DP3: The role of knowledge and skills applied by various actors is to be acknowledged.

…from an Activity Perspective

DP4: A level of analysis that addresses activities, i.e., deeds, processes, and performances, in which knowledge and skills are applied, is to be provided. DP5: The role of information that is breaking down activities is to be acknowledged. DP6: The interrelation of activities that are conducted by an actor at a given time and place is to be acknowledged. DP7: The creation of new densities is to be acknowledged.

…and Knowledge Creation Service Systems Engineering

DP8: The means of modelling information for various actors is to be dealt with. DP9: The service system is to be taken as basic unit of analysis. DP10: The systematic design and development of service systems is to be supported.

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The operationalization of underlying principles of function is enabled by principles of form (Gregor et al., 2013). Within the scope of the design theory, these are in line with the general outline of TRIGGER. Thus, the design of artifacts that support the engineering of digitally enabled service systems incorporates complementary methods at distinct developmental stages. These method building blocks address the design principles presented above to varying degrees and are combined into a meta-model. Since the levels of analysis and design in between the systems level and the activity level are rather diverging, so called bridging methods are to be introduced to ensure consistency between these two levels. Following the notion of Brinkkemper (1996), the complementary interplay of the methods then builds a meta model that depicts dedicated development steps to structure the application of the method building blocks. Thus, the interplay of the method building blocks comprises a means for both, the design and validation of the novel digitally enabled service systems to be developed. As a basic prerequisite for the novel service system to be developed to accomplish its defined work, the interactions on a system of systems level among the firm, its customer, and further stakeholders are to be delineated. Based upon that, the definite purpose of the novel service system can be defined in order to build “the right system” (Saradhi 1992, p. 62). Moreover, a structured approach is to be provided that allows for the description of the overall system functionality addressing the system’s definite purpose. Ultimately, with the aim of developing a digitally enabled service system with a maximum level of density, the verification of the system is to be put into focus. In this course, dedicated development mechanisms are to be applied that address the notion of digitally enabled generativity as a trigger for innovation in service systems and thus assure “building the system right” (Saradhi 1992, p. 62). Following Gregor & Hevner (2013), TRIGGER as a method that combines dedicated method building blocks constitutes knowledge as operational principles in the vein of a nascent design theory. However, in the course of prescribing an emergent design theory for artifacts that support the engineering of digitally enabled service systems, it is the underlying premises of the method building blocks depicted for TRIGGER that are to be recognized rather than the distinct methods per se. Methods such as VCE/CVC are thus a means to an end to achieve a more abstract intent, i.e., addressing the larger

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constellations of actors in systems of service systems in the course of the design of a novel digitally enabled service system. “Building the system right” by means of enhancing resource density is recognized as a development activity that demands for a rather high degree of imagination capabilities. The design of the DiDesigner is largely in line with the one depicted for TRIGGER, albeit with more focus on guiding the enhancement of resource density in the design of novel service systems by providing a more fine-grained lens on the generative mechanisms identified in Study 2. Reverting to the design specification of the DiDesigner, the design of artifacts that support the engineering of digitally enabled service systems is thus to be attuned to translating underlying premises into actionable guidelines (Markus et al., 2002). By factoring in controls that are dependent on the understanding and anticipation of those created the idea of the service system in the first place (Eaton et al., 2015), a foundation for acknowledging the positive outcomes of digitally enabled generativity is provided. Together with providing patterns of service systems with enhanced resource densities that are shaped by these controls as well as guidelines dealing with how liquefied information has to be modelled by actors with applicable knowledge and skills, a blueprint of a service system with a beneficial configuration of resources can be achieved. Evidence from Eval 2 in Study 4 suggests that the interplay of the principles of form and function underlying the emergent design theory is recognized as applicable for engineering digitally enabled service systems. Along these lines, the business model canvas introduced by Osterwalder was contrasted with the principles of form and function represented by the expository instantiation and anticipated as means to operationalize the development of initial ideas toward a number of different implementation designs. This was further emphasized in Eval 3 in Study 4 in terms of elaborating on the notion of LiCoDi as an development activity that sheds light on new combination possibilities that had not be seen before or which were not regarded as technically feasible because of constraints.

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Artifact Mutability

The artifact mutability component specifies what degree of artifact change is encompassed by the design theory (Gregor & Jones, 2007). The inherent principles in the design of the DiDesigner lead to the assumption that a key characteristic of digitally enabled generativity is unanticipated change (Yoo, 2013; Zittrain, 2006). Moreover, it can be assumed that the anticipation of this change is a relational concept in terms of varying perceptions of who is surprised by what (Eaton et al., 2015; Eck & Uebernickel, 2016). Hence, as dealt with in Eval3, an emergent design theory imposes the artifact to address the dynamics of unanticipated change in terms of allowing for altering its controls, i.e., the perception of constraints, and mechanisms, i.e., the patterns reflecting beneficial configurations of resources with enhanced resource density. This can be achieved, for instance, by defining mechanisms and spheres that stimulate interactions of users with the artifact and also between artifact users over time, e.g., gamification approaches that support the generation of user content (Wessel, Poeppelbuss, & Goeken, 2016) or based on learning algorithms that allow for prescribing future unanticipated changes based on relevant inputs from extant users (Gnewuch et al., 2017). This is reflected by the perception of the prototype system evaluated in Eval 3 in Study 4 as a system that could possess the capability to learn from extant user entries and propose according new combination of alternatives in an Amazon-like way. In this vein, everyone who works with an instantiation of the artifact puts newly designed alternatives in a pool from which subsequent users can chose combinations that work the best for them. However, in the overall context of prescribing principles inherent in the design of artifacts that accomplish the engineering of digitally enabled service systems, the configuration of methods in TRIGGER as well as the DiDesigner as a digital tool constitute possible means for this purpose; rather than being compulsory elements for the emergent design theory. Grounded in the view of Hovorka and Germonprez (2009), the interaction with artifacts in everyday practice is predominantly characterized by informal modes of teleological use, involving tinkering, tailoring, and bricolage. This informal tailoring of artifacts can lead to unplanned and unanticipated success, albeit concomitantly attenuating rational method-driven design approaches (Hovorka &

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Germonprez, 2009). Against this backdrop, it is promising to define a certain degree of freedom concerning the arrangement of distinct development activities, methods, and tools along the meta-model prescribed for engineering digitally enabled service systems. By fostering this associative emergence (Wessel et al., 2016), a broader variety of prescriptive knowledge contributions can be incorporated in artifacts that support the engineering of digitally enabled service systems. In this vein, open ontologies or taxonomies such as the one developed in Study 1 are a valuable supplement in terms of classifying and making extant knowledge contributions searchable in a way that allows for assessing their capabilities to address the principles of form and function depicted within the emergent design theory (Schryen et al., 2017).

2.5

Testable Propositions

A design theory can give rise to testable propositions or hypotheses about the artifact to be constructed (Gregor & Jones, 2007). Testable propositions thus form truth statements (Iivari, 2007) or heuristic propositions (van Aken, 2004) that can be tested during the theory’s instantiations. As a prerequisite for the move toward a more welldeveloped theory for design and action (Gregor, 2006), a set of general testable propositions, informed by insights gathered in Eval 4 in Study 4, is explicated in the following. Proposition 1

An artifact built using the emergent design theory supplements human

capabilities in the course of modelling multidimensional solution alternatives for digitally enabled service systems. Proposition 2

An artifact built using the emergent design theory demands for novel

ways of thinking about risk awareness, e.g., in a start-up manner, among organizations engaging in the engineering of digitally enabled service

systems. Proposition 3

An artifact built using the emergent design theory supports designers

with limited knowledge in IT by suggesting possible potentials and showcasing variants in the context of digital transformation that are relevant for engineering digitally enabled service systems.

Specifying an Emergent Design Theory

Proposition 4

229

An artifact built using the emergent design theory is rather being

regarded as a foundation for decisions when a cost factor is involved in the course of engineering digitally enabled service systems. Proposition 5

An artifact built using the emergent design theory has to be configurable

in order to be able to address company specific requirements in different industry sectors in the course of engineering digitally enabled service systems.

2.6

Justificatory Knowledge

According to Gregor and Jones (2007), this component encompasses the underlying knowledge that gives a basis and explanation for the design of an artifact to be constructed. Following the notion of kernel theory fundamentalists (Fischer, Winter, & Wortmann, 2010), it is essential to include justificatory knowledge in design theories, although this knowledge could be incomplete. As a consequence, justificatory knowledge provides an explanation of why an artifact is constructed as it is and why it works. Moreover, explanations are usually regarded as a desirable part of a theory specification, assisting with their communicative purpose and the facilitation of human understanding (Gregor, 2006; Gregor & Jones, 2007; van Aken, 2004). In the course of the development of the DiDesigner, justificatory descriptive knowledge (Iivari, 2007) for the design of artifacts that support the engineering of digitally enabled service systems was gathered from the evaluation activities conducted in Eval 1 and Eval 2, i.e., in terms of validating its purpose and scope as well as underlying constructs (cf. Eval 1) or principles of implementation (cf. Eval 2). In a broader sense, justificatory knowledge can be explicated throughout the overall accumulation of knowledge elaborated on in this dissertation. Hence, applicable justificatory knowledge is constituted by underlying knowledge contributions dealing with (1) the nature of innovation in digitally enabled service systems and how these systems can be systematically developed (cf. Part II, Chapter 1); (2) the nature of digital technology as a driver of digitally enabled generativity and how the idea of resource density is suitable to understand concomitant opportunities for innovation in digitally enabled service systems (cf. Part II, Chapter 2); (3) extant design knowledge in the realms of the

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intersection of IS and service research (cf. Part II, Chapter 3); (4) the demarcation of relevant prescriptive knowledge contributions in the context of SSE (cf. Study 1); the identification of generative mechanisms that are promising to enhance resource density (cf. Study 2); the formative evaluation of TRIGGER (cf. Study 3); and the evaluation of the DiDesigner as an expository instantiation.

2.7

Principles of Implementation

This component concerns the means by which the design is brought into being, thus providing a description of processes for implementing the artifact addressed by the design theory in specific contexts (Gregor & Jones, 2007). Truth statements addressing this component can be formulated based on the knowledge produced in Eval2 in Study 4 (Sonnenberg & vom Brocke, 2012b). Reverting to the development of the DiDesigner as expository instantiation, the main purpose of the artifact to be implemented is to guide the engineering of digitally enabled generativity in service systems with a beneficial configuration of resources. As a consequence, it acknowledges the potential for unanticipated change in the design of a service system in terms of encompassing generative mechanisms and patterns of service systems with enhanced resource densities. However, the notion of unanticipated change is deemed to be a relational construct dependent on the perception of those who created the idea of the service system in the first place (Eaton et al., 2015; Eck & Uebernickel, 2016). This imposes the artifact to emerge over time in terms of incorporating novel knowledge contributions and, by that, maintaining its capability to guide the design of service systems with hitherto unanticipated resource densities. Hence, in the course of implementing artifacts that acknowledge the notion of unanticipated change driven by digitally enabled generativity as a relational construct among varied audiences, bootstrapping (Eck & Uebernickel, 2016; Hanseth & Lyytinen, 2010; Henfridsson & Bygstad, 2013; Tempini, 2017; Wessel et al., 2016) is proposed as promising principle of implementation. In this context, this means that increasing amounts of users create blueprints of novel digitally enabled service systems that then can be decomposed in terms of their underlying configurations of resources

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and activities which, in turn, are perceived as unanticipated among other users that aim to engineer novel digitally enabled service systems in the aftermath. Moreover, implementing artifacts that guide the engineering of digitally enabled generativity in service systems demands for addressing the crucial role of liquefied information as a central resource in the context of enhancing resource density (Lusch & Nambisan, 2015; Normann, 2001). Hence, in case of the artifact to be implemented and integrated in existing systems within an organization, its performance can further be strengthened by leveraging internal and external data sources (Lim et al., 2018; Müller-Wienbergen, Müller, Seidel, & Becker, 2011; Tempini, 2017) and consider the information liquefied within this context as relevant resources for triggering novel beneficial resource densities. However, the emergent design theory explicated within this dissertation refrains from making specific assumptions about a certain implementation technology due to issues of technological obsolescence or perishability, which is a common problem associated with design science (Ball, 2001; Hevner et al., 2004; Jones, 2011) and particularly important in the context of the rapid and pervasive development of digital technology (Nambisan et al., 2017; Yoo et al., 2012). Instead, the embedding of the artifact in the operational process of developing service systems in various kinds of organizations is to be shed light on. Due to the inherent complexity of service systems (Böhmann et al., 2014a; Maglio et al., 2009), their systematic design and development can impose challenges for lay users (cf. Study 3). Hence, with the aim to enable lay users to use respective artifacts or enable them to create rough drafts of ideas for service systems, the knowledge base is to be translated according to their needs (Markus et al., 2002). As sounded out in Eval 2 in Study 4, this can be achieved by someone who can lead lay users through the overall process or by providing tutorial videos, mini briefings, and two-hour trainings. Closely connected to this is the notion of design thinking as an approach in which complex problems are reduce to specific situations to enable embodied cognition and experience (Dolata & Schwabe, 2016). Through its rigidity and the available hands-on guidance, Design Thinking enables for a relatively easy transfer from one context to another (Dolata, Uebernickel, & Schwabe, 2017). Hence, in the vein of associative emergence (Wessel et al., 2016) knowledge from the

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body of knowledge can be fragmented into concise knowledge units (Karunakaran et al., 2009) and transferred into actionable guidelines that are accessible for lay users (Markus et al., 2002). An illustration of how the prescriptive knowledge underlying the emergent design theory can be translated is provided in Figure 24.

Specifying an Emergent Design Theory

Figure 24. Translation of Expert Knowledge into Actionable Trade-offs

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Discussion: Shaping a Body of Design Knowledge

Expository Instantiation

An expository instantiation is a physical implementation of the artifact that can assist in representing the theory both as an expository device and for purposes of testing (Gregor & Jones, 2007). The prescription of principles inherent in the design of artifacts that support the engineering of digitally enabled service systems was initiated by the alternating design and evaluation of the DiDesigner in terms of providing a common ground for explicating further applicable statements from the knowledge accumulated throughout this dissertation in its entirety. The expository instantiation per se can be characterized as a digital tool that riggers innovation (Nambisan, 2013) by means of prescribing the development of novel service systems with beneficial configurations of resources that were not anticipated in the first place. As sounded out in Eval 3 in Study 4, the expository instantiation in its manifestation as a web application that was supplemented by a VBA tool dealt as means to communicate design principles that acknowledge the special nature of service in terms of which specialized competences or further resources are integrated by a certain actor. Since the output of engineering digitally enabled service systems are service systems that are hard to delineate, complex by nature and including not only data and physical components, but also layers of knowledge, communication channels and networked actors (Böhmann et al., 2014a), elaborating on the tangible artifact that addresses the development of these fuzzy entities is particularly promising in terms of that the artifact itself has some representational power. In this vein, expository instantiations such as the DiDesigner are capable to assist with the communication of the design principles for engineering these systems by allowing the demarcation of the system from its environment to a certain degree (Gregor & Jones, 2007; Saradhi, 1992). Moreover, expository instantiations that are built on the emergent design theory provide a ground for theory testing and validation, which, in turn fosters its maturation toward a well-developed body of knowledge (Gregor, 2006; Gregor & Hevner, 2013; Gregor & Jones, 2007). The progression of an emergent design theory toward this level is shed light on in the next chapter.

Maturing Toward a Consistent Body of Design Knowledge

3

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Maturing Toward a Consistent Body of Design Knowledge

According to Gregor & Hevner (2013), a move toward a more mature and well-

developed body of knowledge is achieved when research can be expressed in the terms of a design theory. By having articulated the prescriptive knowledge accumulated throughout this dissertation along the components of a design theory, its knowledge scope was developed from idiographic design knowledge, i.e., with respect to knowledge claims that pertain to particular artifact instances (Hevner et al., 2004; March & Smith, 1995), to nomothetic design knowledge, i.e., with respect to knowledge claims that prescribe the principles inherent in the design of a class of artifact that accomplishes some end (Baskerville et al., 2015; Gregor & Jones, 2007; Walls et al., 1992). Although prescriptive knowledge with inferences on the truth contained in it (Iivari, 2007) could be produced, the shaping of a body of knowledge for engineering service systems in the digital age, i.e., a body of mature prescriptive knowledge, is contingent on the progression of the emergent design theory toward a well-developed theory for design and action (Aier & Fischer, 2011; Bichler et al., 2016; Gregor, 2006; Kuechler & Vaishnavi, 2012). In this vein, expanding the emergent design theory (Colquitt & Zapata-phelan, 2007; Mueller & Urbach, 2017) in its current state allows for the further accumulation of truth-like knowledge (Iivari, 2007) for engineering digitally enabled service systems by means of knowledge moments that produce idiographic scientific or even nomothetic scientific knowledge (Baskerville et al., 2015). With the aim to provide a ground for the further progression of the emergent design theory, a framework guiding its development is introduced in the following. This framework is adapted from Aier & Fischer (2011) and depicts the mutual dependencies between the components of a design theory as defined by Gregor and Jones (2007) as illustrated Figure 25. As a point of departure for expanding the emergent design theory by means of consecutive cycles of theory testing and building (Cash, 2018; Mandviwalla, 2015; Mueller & Urbach, 2013), evaluating the design theory

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and its interrelated components based on dedicated evaluation criteria is deemed as promising approach (Aier & Fischer, 2011).

Figure 25. Mutual Dependencies of Components in a Design Theory

In this vein, Aier and Fischer (2011) introduce a set of evaluation criteria for design theories as an exaptation of the criteria for traditional theories introduced by (Kuhn, 1977). Hence, a design theory can be evaluated against its (1) utility, (2) internal consistency, (3) external consistency, (4) broad purpose and scope, (5) simplicity, and (6) fruitfulness of new research findings. The (1) utility of a design theory is reflected by the resulting artifact’s ability to fulfill its purpose. The purpose of the artifact is concretized by testable propositions in order to prove that the artifact fulfills its purpose. (2) Internal consistency deals with the necessity that each element of a design theory should be consistent with itself. In this context, a consistent system of constructs is regarded as the common basis for all design theory elements. Principles of form and function of the artifact, artifact mutability, principles of implementation, and testable propositions directly depend on purpose and scope. Testable propositions address principles of form and function, artifact mutability, and its principles of implementation. Justificatory knowledge should justify principles of form and function, artifact mutability, and principles of implementation. (3) External consistency concerns the consistency of the justificatory knowledge with the knowledge base as well as the consistency of constructs with constructs commonly used. (4) The scope and purpose of a design theory in terms of prescribing guidelines for a class of artifacts

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should be broad. (5) Simplicity should be achieved in order for the design theory to be easily understandable and manageable. (6) Fruitfulness of new research findings encompasses the intent of design theories to disclose new phenomena or previously unnoted relationship among already known phenomena. Furthermore, they should initiate or stimulate further research activities (Aier & Fischer, 2011; Kuhn, 1977). The realization of an expository instantiation is then informed by the interplay of the components contained in the design theory and can deal with the communication of the design principles in the theory in the course of its evaluation (Gregor & Jones, 2007). Thus, by exposing the nomothetic design knowledge contained in the emergent design theory for engineering digitally enabled service systems to an evaluative intervention, e.g., in the form of field studies, truth can be represented in a law like way (Iivari, 2007), thus constituting the creation of nomothetic scientific knowledge (Baskerville et al., 2015). To sum up, the evaluation of the emergent design theory for artifacts that support the engineering of digitally enabled service systems allows for its consecutive and iterative expanding toward a well-developed theory for design and action (Gregor, 2006), which ultimately shapes a cohesive and consistent body of design knowledge (Gregor & Hevner, 2013; Nagel, 1979) for engineering service systems in the digital age that can be demarcated from the overarching body of knowledge at the intersection of IS and service research (cf. Study 1).

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Contribution and Conclusion

The evolution of technology in general and digital technology in particular can be very pervasive and induces radical changes in the nature of innovation (Arthur, 2009; Ridley, 2015; Yoo et al., 2012, 2010). Science aims to understand how and why the newly introduced technology and concomitant phenomena impacts the surrounding world as it does. Producing prescriptive knowledge with truth-like value (Iivari, 2007) for engineering service systems in the digital age thus demands for inquiries that acknowledge generic technology affordances that are enabled by digital technology and anticipating how they influence innovation trajectories and outcomes (Nambisan et al., 2017); rather than addressing distinct technology manifestations or artifacts. By presenting prescriptive knowledge with a higher degree of abstraction allows it to be generalized to other situations (Gregor & Hevner, 2013). The aim of the discussion section was to answer the overarching research question dealing with how design knowledge for engineering service systems in the digital age can be developed toward a consistent body of design knowledge by articulating the knowledge accumulated throughout this dissertation along the anatomy of an emergent design theory for artifacts that support the engineering digitally enabled service systems. In this vein, the expository instantiation developed in Study 4 constituted the linchpin for extracting relevant contributions from the overall scope of the dissertation and ingraining them along the constituents of the emergent design theory. This allows for specifying principles inherent in the design of a class of artifacts that accomplish the end of engineering digitally enabled service systems, together with prescribing guidelines for the design of future artifacts of the same type (Gregor & Jones, 2007). In order to pave the way for the further maturation of this agglomeration of prescriptive knowledge (Gregor, 2006), a point of departure is proposed by means of mapping out future inquiries that are promising to produce nomothetic scientific knowledge (via evaluation) as well as nomothetic design knowledge (via rebuilding) (Aier & Fischer, 2011; Baskerville et al., 2015; Cash, 2018; Kuhn, 1977). By that, the emergent design theory for artifacts that support the engineering of digitally enabled

Contribution and Conclusion

239

service systems is expanded (Colquitt & Zapata-phelan, 2007) and can be further developed toward a full-blown theory for design and action (Gregor, 2006). This then leads to the demarcation of a consistent body of design knowledge (Gregor & Hevner, 2013; Nagel, 1979) for engineering service systems in the digital age from the overall body of knowledge for engineering service systems at the intersection of IS and service research. The novelty of the design theory prescribed in the discussion section can be characterized from two perspectives. Reflecting about the knowledge contribution in the interior mode (Gregor, 2009) in relation to the scope of this dissertation, this knowledge contribution constitutes an exaptation since knowledge is extracted from and contributed to both, the Λ as well as Ω knowledge bases accumulated throughout the overall scope of this dissertation. As such, respective knowledge contributions are exaptated and refined so that they can be utilized in the specification of the prospective design theory. Reflecting about the knowledge contribution in the exterior mode (Gregor, 2009) in relation to the scope of this dissertation leads to positioning the emergent design theory as an improvement, in terms of providing a better solution to the problem context of engineering digitally enabled services systems in comparison to extant approaches. Thus, a contribution to the Λ knowledge base is made in the form of an emergent design theory that exhibits anchor points that allow for it to be expanded toward a consistent body of design knowledge. Future evaluation inventions may lead to knowledge contributions to the Ω knowledge base in the form of an expanded understanding of kernel theories or the development of new behavioral theories of the artifact in use (Gregor & Hevner, 2013). In this vein, the articulation of underlying prescriptive knowledge along the anatomy of a design theory is of particular importance, since this form of documentation allows for thorough theory testing and building (Gregor & Hevner, 2013; Gregor & Jones, 2007). This constitutes a departure from extant relevant knowledge contributions in terms of them not exhibiting a suitable communication of inherent principles based upon the distinct components of a design theory (e.g., concerning purpose and scope, principles of form and function, etc.; cf. Study 1).

VI Conclusion: Reflections on the Research

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7_6

Overview of Work

1

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Overview of Work

The objective of this research was to answer the research question of how design knowledge for engineering service systems in the digital age can be developed toward a consistent body of design knowledge. In order to address the underlying multifaceted nature of this overarching research question, the overall outline of the dissertation was attuned to the search process that ultimately lead to the emergence of a useful solution (Hevner et al., 2004; Simon, 1996). Against this backdrop, the constituents of this dissertation were comprised of six parts with each of them addressing a distinct task in the context of the overall research objective. Part I motivated this work by shedding light on the proliferation of novel service systems that induce a shift in the anticipation of value creation. Due to digital technology and the ubiquitousness of the Internet, novel innovation opportunities are opened up. In particular, the digitally enabled generativity unleashed in this context triggers unanticipated change and, by that, innovation in service systems. Service systems that are contingent on the according alteration of socio-technical processes can then be conceptualized as digitally enabled service systems. In order to foster positive outcomes, i.e., beneficial resource configurations, in the course of the design of these complex systems, design knowledge is needed that acknowledges the premises underlying digital technology, digitally enabled generativity, and service systems as an abstraction on value creation. In order for this knowledge to address the rapid and pervasive developments in the digital age, a coherent body of design knowledge is needed. By providing prescriptive knowledge in a way that allows for the prescription of a broader class of artifacts, the engineering of service systems with a multitude of digitally enabled peculiarities can be supported. Guided by this research objective, the purpose and scope of the dissertation was outlined, together with prescribing a sub-set of research questions that provide a ground for more fine-grained inquiries. Along these lines, an outlook on the four studies that address this subset is provided in the following.

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Part II provided insights on relevant descriptive theoretical foundations, prior prescriptive knowledge and artifacts that are deemed promising as justificatory knowledge that informs the creation of novel prescriptive knowledge in the further course. In this vein, applicable justificatory knowledge is constituted by knowledge contributions dealing with the nature of innovation in digitally enabled service systems and how these systems can be systematically developed; the nature of digital technology as a driver of digitally enabled generativity and how the idea of resource density is suitable to understand concomitant opportunities for innovation in digitally enabled service systems; and extant design knowledge in the realms at the intersection of IS and service research. Part III dealt with questions of rigor for addressing the research objective by means of explaining which research approach was adopted and how it was applied within the scope of this dissertation. After providing an introduction to design science research as a problem-solving paradigm with the aim of achieving both the purposes of producing scientific and solving real organizational problems, the role of knowledge in the interplay of knowledge consumption and production among Ω and Λ knowledge bases is elaborated on. Moreover, the continuum of designated outcomes of DSR, ranging from the artifact as core outcome in the pragmatic-design school of thought to design theories with different degrees of abstraction in the design-theory school of thought, is illustrated in order to provide a ground for the further development of prescriptive knowledge among this continuum. In this vein, an overview of the distinct research designs applied for answering the sub-set of research questions is provided, together with providing insights on the transition from an artifact-focused perspective to an design-theory focused perspective throughout the research trajectory. Reverting to the overarching research question, insights on how the knowledge contributions that emerge from respective inquiries culminate toward a body of design knowledge are provided. Part IV was mainly concerned with knowledge consumption and production among both, Ω and Λ knowledge bases. In this vein, Study 1 dealt with the development of a taxonomy for the purpose of classifying extant prescriptive knowledge contributions that are deemed relevant for engineering service systems in the digital age. Elaborating on the content and structure of the taxonomy then lead to the demarcation of this extant

Overview of Work

245

body of knowledge, which then allowed for providing insights on inquiries to be considered in the further course. The aim of Study 2 was to identify mechanisms that tend to lead to enhanced resource densities in digitally enabled service systems. These mechanisms acknowledge the notion of digitally enabled generativity and according innovation opportunities through the lens of resource density, which, in turn, can be recognized as a prerequisite to be able to engineer digitally enabled service systems with a beneficial configuration of resources. The development of a method that makes use of these mechanism in an operative manner was at the core of Study 3. The initial design of the method was guided by applicable justificatory knowledge and was formatively evaluated based on suitable evaluation criteria. For the sake of further developing and communicating the prescriptive design knowledge accumulated throughout the inquiries conducted, an expository instantiation was developed in Study 4. On the one hand, this instantiation acknowledged the insights gathered from the formative evaluation of the method and ingrained them it its design. On the other hand, it provided a common ground through which the accumulated knowledge produced up to this could be communicated and disseminated with a truth-like value. Part V predominantly reverted to the overall objective of this dissertation in terms of answering the question of how design knowledge for engineering service systems in the digital age can be developed toward a consistent body of design knowledge. Along these lines, the expository instantiation developed in Study 4 was utilized as linchpin to communicate the prescriptive knowledge accumulated throughout the dissertation along the structural components of a design theory. This emergent design theory allows for specifying principles inherent in the design of a class of artifacts that accomplish the end of engineering digitally enabled service systems, together with prescribing guidelines for the design of future artifacts of the same type. Moreover, by mapping out future inquiries that are promising for further expanding this emergent design theory, a starting point for its further maturation toward a consistent body of design knowledge for engineering service systems in the digital age is defined. Part VI encompasses reflections on the dissertation in terms of summarizing its overall purpose and scope, highlighting theoretical as well as practical contributions, delineating limitations and implications for future research, and, finally, providing concluding statements.

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Theoretical Contributions

Regarding theoretical contributions, this work makes knowledge claims that contribute to a range of knowledge bases. Hence, in the following, statements asserting the originality of knowledge accumulated are provided. In the realms of DSR, six contributions to the knowledge base can be claimed. As described in Table 13, these can be broadly characterized along the continuum spanned between the pragmatic-design camp and the design-theory school of thought. Table 13. Key Contributions Arising from the Research Knowledge Base

Contribution Pragmatic-design camp •

•

•

DSR

•

Taxonomy: model with utility to demarcate extant body of knowledge relevant for engineering service systems in the digital age; allows for prescriptions on future designoriented inquiries Generative mechanisms: method with utility to provide principles of function that foster beneficial configurations of resources within digitally enabled service systems TRIGGER: method with utility to operationalize engineering digitally enabled service systems based on notion of resource density DiDesigner: instantiation with utility to act on the natural world by ingraining design knowledge accumulated throughout the research

Design-theory school of thought •

•

DiDesigner: expository instantiation as means to assist with communication of design knowledge accumulated throughout the research Emergent design theory in conjunction with evaluation framework: Prescription of generalizable guidelines with truth-like value for engineering service systems in the digital age; Prescription of procedures for shaping a consistent body of design knowledge

Theoretical Contributions

247

In the vein of the pragmatic-design paradigm, the artifacts developed throughout the dissertation encompass various forms of utility: the taxonomy demarcates design knowledge, the generative mechanisms permeate design knowledge, TRIGGER operationalizes design knowledge, and the DiDesigner makes use of design knowledge in order to act on its socio-technical environment. From the design-theory perspective, the DiDesigner also deals as means to assist with the communication of the prescriptive knowledge accumulated throughout this research work. The documentation of this design knowledge along the anatomy of a design theory then can be considered as a theory for design and action (Gregor, 2006; Gregor & Jones, 2007). This constitutes a departure in relation to extant knowledge contributions that most often do not address these constituents in a way that allows for generalizable prescriptions on how to engineer service systems in the digital age. By elaborating on how this design theory can further be expanded, its maturation toward a more mature and well-developed body of design knowledge is prescribed with more explanation, more precision, more abstraction, and more testing of beliefs facilitated (Gregor & Hevner, 2013; Nagel, 1979). With this research intentionally being positioned at the intersection of IS and service research, valuable contributions can also be claimed to the knowledge base of SSE. First, its central call for research leading to actionable design knowledge for systematically designing and developing service systems based upon understanding their underlying principles (Böhmann et al., 2014a) is addressed by contributing applicable artifacts developed throughout this research, i.e., the taxonomy, generative mechanisms, TRIGGER, and the DiDesigner as instantiation, to the knowledge base. Second, the call of SSE for theories for design and action (Böhmann et al., 2014a)

is addressed by

communicating and documenting the knowledge accumulated throughout this research by means of the DiDesigner as expository instantiation and the emergent design theory for engineering service systems in the digital age, respectively. The further maturation of this design theory then can culminate into an overarching “Konstruktionslehre” (Böhmann, Leimeister, & Möslein, 2014b) for service systems.

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Moreover, as depicted in Table 14, this research can be positioned along both, the vertically depicted continuum spanned between design-oriented and theory-oriented knowledge bases and the horizontally depicted continuum spanned between ISoriented and service research-oriented knowledge-bases. Hence, beside the key contributions to the knowledge bases of DSR and SSE, contributions can be claimed that deal with various research paths opened up along the continua introduced. An overview of further promising linkages is provided below.

Table 14. Linkages of Contributions to Relevant Research Paths in Literature IS

Service Research Patricio et al. (2018)

Design

Design

Yoo et al. (2010)

Böhmann (2014)(1)

Pragmaticdesign camp

Barrett et al. (2015)

SSE

DSR

• • • •

Taxonomy Generative mechanisms TRIGGER DiDesigner (Instantion)

•

DiDesigner (expository instantiation) Emergent design theory + evaluation framework

• Designtheory school of thought

Ostrom et al. (2015)

Tilson et al. (2010)

IS

Matzner et al. (2018)

Service Research

Theory

Theory

Böhmann (2014)(2)

Theoretical Contributions

249

Research Directions Call for „research leading to actionable knowledge for systematically Böhmann et al. designing, developing and piloting service systems, based upon (2014, p. 74) (1) understanding the underlying principles of service systems.“ Research gap in terms of „little research exists on service systems Böhmann et al. engineering that develops or tests theories for prediction, theories for (2014, p. 77) (2) prediction and explanation or even theories for design and action.“ Barrett et al. (2015, p. 139)

Research opportunity dealing with “how might digital technology embedded in products enable innovation in service systems?”

Ostrom et al. (2015, p. 136)

Call for „research focused on evolving systems engineering approaches for developing services.“

Tilson et al. (2010, p. 9)

Call for “new theoretical lenses to understand the paradoxical nature of change and control in digital infrastructures.”

Yoo et al. (2010, p. 733)

Call for research on “what are the appropriate principles that govern the social context of developments of boundary resources and digital components in doubly distributed innovation networks?”

Patrício et al. (2018, p. 10)

Call for research on „how service design can support organizations in reacting to technology change, namely, by exploring how to create novel product service system solutions to support value cocreation in this technology enabled, networked environment.“

Matzner et al. (2018, p. 14)

Call for „a new grammar and vocabulary for innovation, which is desperately needed to facilitate radically new solutions designs and application schemes.“

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Practical Contributions

The prescriptive knowledge produced throughout this dissertation was considered as important, accessible, and suitable (Rosemann & Vessey, 2008) for engineering service systems in the digital age. With DSR being a problem-solving paradigm, the utility of this knowledge to solve real organizational problems is of particular importance. According implications for practice can be articulated along three main fields of consideration, i.e., industrial applications, industrial standardization, and innovation in living labs.

3.1

Industrial applications

Concerning industrial applications, the prescriptive knowledge accumulated throughout this research may provide valuable insights for the systematic development of digitally enabled offerings in everyday organizational practice. In this context, TRIGGER is attuned to the development of digitally enabled service systems but does not make specific assumptions about how it is to be implemented in settings such as innovation workshops. Accordingly, TRIGGER provides a structured way of thinking, together with defining a set of requirements which have to be addressed by distinct development activities. Yet, in the scope of this research, a set of applicable method building blocks is provided that can deal as benchmark for the implementation of TRIGGER in everyday use. This leads to different perceptions of the utility provided by this artifact among various organizations. Bigger companies with dedicated departments for the development of service offerings can use the metamodel delineated by TRIGGER and combine it with established methods that are exaptated from other application contexts and departments. For instance, parts of commonly used approaches such as the business model canvas introduced by Osterwalder can be used in order to identify relevant actors (key partners), activities (key activities) and information entities (key resources) that are needed to create a draft of the service system to be developed. To the contrary, SMEs seldomly have the

Practical Contributions

251

resources to build new organizational units or create new specialties for engineering novel digitally enabled service systems. Actors within these organizations that are in charge of developing novel digitally enabled solutions might often be laymen in this field. However, beside fostering the exaptation of established methods, TRIGGER can be broken down into its method fragments that permeate combinations of easy to handle development approaches, e.g., from the field of Design Thinking. By that, the complexity inherent in the method building blocks prescribed can be lowered and made accessible for unexperienced development stakeholders. For instance, CVC and VCE can be broken down into a combination of personas, stakeholder maps, and customer journeys that fulfill the same goal when attuned accordingly. The DiDesigner is characterized as a digital tool that triggers innovation. In this role, its utility unfolds in relation to the context in which it is used. With it being capable to create reconfiguration scenarios of digitally enabled service systems that are commonly not anticipated by those who created the idea of the service system in the first place, it can be used as a supplement for TRIGGER. In this vein, a job to be done that is perceived as a valuable starting point for the development of a digitally enabled service system could be identified throughout the early stages of TRIGGER, utilized as input for the DiDesigner, and then further be developed toward a variety of blueprints of digitally enabled service systems with unprecedented resource configurations. Additionally, with the DiDesigner being implemented as a web application, further stakeholders with valuable competencies for the resultant service system can be flexibly involved in the development process, which is especially advantageous in the context of digitally enabled offerings that are dependent on the interplay of a multitude of actors. Hence, the DiDesigner can be used as a kind of development tool in various organizations that deal with the systematic design and development of service systems that are attuned to the opportunities concomitant with digitally enabled generativity. However, and even more important in the digital age, especially among integrated automation providers, there is a trend toward providing industrial cloud solutions in the form of inter-enterprise digital information integration platforms with a multitude of formerly unconsidered actors that gain access to distributed information flows (Wlodarczyk, Rong, & Thorsen, 2009). By that, novel opportunities for developing digitally enabled offerings are unleashed to a special degree, which is why providing

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a common ground for the communication and representation of possible value creation scenarios is of pivotal interest. Along these lines, the DiDesigner can deal as expository means that drives a common understanding of a variety of digitally enabled service systems that are dependent on the integration of resources from the distributed actors encompassed in the realms of a certain industrial cloud. By that, human capabilities can be supported in the course of modelling multidimensional solution alternatives for the digitally enabled service system to be engineered. The body of design knowledge for engineering service systems in the digital age prescribed within the scope of this research constitutes a promising ground for establishing a mindset that is attuned to the affordances opened up in a digitally permeated business environment. In this vein, rather abstract design knowledge for engineering digitally enabled service systems can be ingrained in extant product or service development processes in order to foster a systemic thinking on digitally enabled innovation opportunities. By that, the importance of the physicality of products is deemphasized in favor of acknowledging the role of decoupled information and specialized competences offered by varied audiences as a driver for innovation and the development of according intangible offerings with an information-centric focus. Reverting to the illustrative example mentioned in the beginning, an engineer in a manufacturing company commonly still uses the DUBBEL in his everyday work in order to design tangible product, but could broaden his perception of the development outcome in terms of considering it as a one resource among others in a more complex configuration of resources that interacts with other configurations of resources, i.e., service systems.

3.2

Industrial Standardization

Standardization enables the shaping of a body of knowledge for a certain area of interest. By defining terms and definitions, reference models, methods and procedures, standardization plays a central role in many industries by providing a common ground for the development of certain solutions. Departing from a focus on standardization in areas such as mechanical engineering or software engineering, initial steps toward standardization in the realms of the systematic development of services were grounded

Practical Contributions

253

in the view of service engineering, e.g., DIN PAS 1082 or DIN PAS 1094 (Beverungen et al., 2018). Recent developments in this area advocated the need to provide standards that deal with the engineering of digitally-enabled service offerings from a system perspective. The currently emerging initiative DIN SPEC 33453 dedicatedly addresses this call by incorporating contributions from science and industry in order to be able to provide a well-grounded action guide for a broad range of stakeholders. In this context, distinct knowledge units were carved out of the body of design knowledge for engineering service systems in the digital age prescribed within the scope of this dissertation and supplied to a practice-oriented dissemination. By that, a dedicated practical contribution with broad range may be claimed.

3.3

Living Labs

Recently, living labs emerged as a methodology for interactive co-creation and innovation by providing a platform that allows for direct exchange with the public, customers, users, and other stakeholders. By constructing a virtual spatial context, either with physical material or with computer software, a context for innovation among the users of a living lab is created (Edvardsson, Kristensson, Magnusson, & Sundström, 2012). Thus, living labs invite users to create, prototype, validate, and test new technologies, services, products, and systems in real contexts (Matzner et al., 2018; Nyström, Leminen, Westerlund, & Kortelainen, 2014). In the digital era, digital services become increasingly relevant subjects of living labs, which shifts the focus of consideration towards questions such as how co-creation processes and tools in living labs can be designed to optimally derive knowledge from co-creation in digital and physical spaces with the public (Matzner et al., 2018). In this vein, a practical contribution can be claimed by means of designing a mixed reality innovation sphere that was implemented at a living lab called JOSEPHS (Greve, Martinez, Jonas, Neely, & Möslein, 2016). This initiative combined physical and virtual reality elements with tailored knowledge units extracted from the body of knowledge for engineering digitally enabled service systems developed throughout this dissertation in order to enable users from varied audiences to design distinct aspects of digitally enabled service systems on their own. This is depicted in Figure 26. In this context, the aim was

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Conclusion: Reflections on the Research

to make the context of developing service systems in the digital more tangible, together with fostering an understanding of the premises underlying digital transformation in the public. By that, abstract prescriptive knowledge was translated into actionable tradeoffs for lay users and contributed to a public utilization.

Figure 26. Utilization of Prescriptive Knowledge Units Among a Broader Public

Limitations and Avenues for Future Research

4

255

Limitations and Avenues for Future Research

Along the knowledge moments taking place throughout this dissertation, a variety of knowledge contributions were created that contribute to the shaping of a body of design knowledge for engineering service systems in the digital age. The utility of producing knowledge is enabled by research methods and techniques that are designed for conducting research. By that, research designs can be regard as artifacts that are to be evaluated and further developed in order to increase their utility (Venable & Baskerville, 2012; Venable, vom Brocke, & Winter, 2017). Along these lines, the research designs applied throughout this dissertation are evaluated in terms of limitations and avenues for future research are asserted. An overview is provided in Table 15. The utility of the taxonomy developed is constituted by bringing order to the complex area of research at the intersection of research in the fields of IS and service research in order to be able to identify knowledge contributions that are promising to embody applicable design knowledge for engineering digitally enabled service systems. (1) Guided by the objective of the overall dissertation, the audience of the taxonomy was limited to specialized scholars as well as general scholars in order to demarcate relevant justificatory knowledge and to prescribe future inquiries in the course of knowledge creation. By that, practitioners or a general public that deal with organizational problem were not directly addressed. The taxonomy as such can then be positioned as an artifact that provides the utility for researchers to guide the development of further artifacts that, in turn, address an organizational problem in accordance with the premises of DSR. Thus, a limitation to be pointed out is that the utility of the taxonomy is solely implicitly articulated in terms of providing a ground for the subsequent development of artifacts that are exposed to some realities (Sun & Kantor, 2006). An avenue for future research is constituted by attuning the taxonomy toward practitioners or a general public, together with evaluating it in terms of its utility to bring order to knowledge relevant for engineering digitally enabled service systems on an accessible level of abstraction.

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Table 15. Research Directions for Maturation of Body of Design Knowledge Limitations

Avenues for Future Research

Taxonomy Development

Taxonomy Development

•

Audience limited to specialized and general scholars

•

•

Identification of knowledge contributions based on forward search approach

•

Generative Mechanisms

Adaption toward practitioners and general public and according evaluation Development of search strings based on relevant constructs from emergent design theory

Generative Mechanisms

•

Identification of generative mechanisms based on data gathered from representatives of SMEs

•

Identification of contextual triggers among varied audiences contributing to emergence of generative mechanisms

•

Focus on innovation mechanisms in • accordance with Schumpeterian view

Investigation of adoption and scaling mechanisms from longitudinal perspective

TRIGGER

TRIGGER

•

Focus of evaluation on immediate application context

•

Extension of evaluation toward broader socio-technical system context

•

Generation of solutions is bounded by idiosyncrasies within application situations

•

Incorporation of notion of bounded creativity beside rigor and relevance in further DSR inquiries

DiDesigner

DiDesigner

•

Evaluation based on one artifact representation per evaluation activity

•

Evaluation of different design alternatives in experimental settings

•

Implementation as web application in order to support development of fuzzy and hard to delineate service systems

•

Utilization of recent technologies, e.g., virtual reality, in order to increase immersion and representational power

Emergent Design Theory Based on accumulation of prescriptive knowledge along knowledge moments

Emergent Design Theory Maturation toward full-blown design theory by means of consecutive theory testing and building

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(2) The survey of literature relevant for the overall dissertation has shown that relevant knowledge contributions are rather fragmented and distributed among various fields of research. However, pivotal papers could be identified that were regarded as promising to initiate the emergence of novel research contributions that acknowledge their underlying thoughts. Hence, in alignment with the normative theory of a citing behavior (Baldi, 1998; Stewart, 1983), a sample of objects of interest was created that was solely comprised by contributions citing these papers. A limitation in this context is contingent on the boundaries of the citation network that inhibit the acknowledgement of contributions that are not grounded in a worldview associated with the one postulated by the papers being regarded as pivotal. Accordingly, an avenue for future research could be to surrogate the forward search approach with a search approach that utilizes a query structure that is built on various combinations of the constructs prescribed within the emergent design theory for engineering service systems in the digital age (vom Brocke et al., 2009; Webster & Watson, 2002). With the intent to identify generative mechanisms that bear the potential to lead to enhanced resource densities in digitally enabled service systems, a qualitative explorative approach in the context of a holistic multiple case study was applied. (1) In this vein, data was gathered from interviews with representatives from SMEs among 13 cases. SMEs were deemed as valuable for data collection due to their tendency to differentiate themselves through new value constellations within value networks. Interviewees were comprised of managing directors, senior managers, project managers, and line managers from the respective firms. By that, valuable insights on the emergence of novel service systems could be gathered, albeit from a firm-centric point of view that does not acknowledge the underlying dynamics among the varied audiences incorporated. One approach to overcome according limitations could be addressed by gathering data from these audiences in order to shape the understanding of contextual triggers among the generative mechanisms identified (Koutsikouri & Henfridsson, 2017). (2) The analysis of the data gathered from the interviews lead to generative mechanism that are attuned to enhance resource density in service systems grounded in a perspective that is similar to the Schumpeterian view of innovating (Schumpeter, 1934). This view is promising for prescribing actionable guidelines for

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engineering digitally enabled service systems with enhanced resource densities, but is limited in terms of longitudinal implications. In alignment with Henfridsson and Bygstad (2013), beside elaborating on innovation mechanisms, future research could deal with the role of adoption and scaling mechanisms (Henfridsson & Bygstad, 2013) in the context of digitally enabled service systems. Concerning TRIGGER, its initial design was guided by applicable justificatory knowledge and was formatively evaluated based on suitable evaluation criteria. (1) The main aim of the evaluation trajectory applied was to ensure the fit of the design to address the utility of engineering digitally enabled service systems. Thus, evaluation criteria dealing with the completeness or understandability of the artifact were applied in order to provide evidence on the degree to which the method provides instructions for the goal-driven activity of systematically designing and developing these complex systems. By that, however, the focus knowledge moment taking place in the course of the evaluation activities was limited to the immediate application context of the artifact at the expense of considering its impacts on a wider context. Future research could engage in a extended dynamic perspective in order to foster an improved understanding of change and impact on organizations or society that are triggered by the artifact upon introduction into its immediate application context (Drechsler & Hevner, 2016). (2) Concerning the operationalization of enhancing resource density, evidence from the evaluation suggested that the outcome of according development activities are contingent on the imagination capabilities of the ones who are involved in the design and development of novel digitally enabled service systems. This limitation is due to the inherent necessity of DSR to impose scientific rigor on the design process for artifacts that accomplish some end (Iivari, 2007). The end accomplished, i.e., the design of a novel digitally enabled service system with enhanced resource density, is expected to be a reliable outcome, but also bounded by idiosyncrasies of the situation and the designers ability to address the situation within these bounds (Baskerville, Kaul, Pries-Heje, Storey, & Kristiansen, 2016). A promising avenue for future research in this context is acknowledged by considering the notion of bounded creativity in DSR (Brown & Cagan, 1996). By incorporating bounded creativity into DSR, creativity can be fostered in the application of artifacts but also ingrained in the design of or theorizing on artifacts (Baskerville et al., 2016).

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The development of the DiDesigner contributed to this research in a dual manner. On the one hand, it acknowledged the insights gathered from the formative evaluation of TRIGGER and ingrained them it its design. On the other hand, it provided a common ground through which the accumulated knowledge produced up to this could be communicated and disseminated with a truth-like value. (1) The design of the DiDesigner was attuned to the premises elaborated on in the preceding studies, together with translating abstract design knowledge into actionable tradeoffs by ingraining underlying constructs in artifact versions that were consecutively build. By that, various stakeholders got in touch with the respective design instantiation of the DiDesigner throughout the overall evaluation trajectory (Sonnenberg & vom Brocke, 2012b). Data collection took place among workshops in which the moderator and users interacted with the design to various degrees. However, a limitation in the context of this approach emerges from the dedicated interaction of one stakeholder group with one version of the design. In the context of theorizing on the design of the artifact in the interior as well as exterior mode (Gregor, 2009), this allowed for truth-like statements about the design of the artifact (Iivari, 2007). In order to further strengthen the validation of design decisions, future research could engage in experiments with control groups and different alternatives of constructs, models, methods, and instantiations that are manipulated on a range of devices (Mettler & Winter, 2014). (2) Moreover, the DiDesigner was developed as a means to an end to assist with the communication of the principles underlying the prescriptive knowledge accumulated up to that point. By providing insights on a emergent web application, the communication is bound to the technical limitations of computational simulations (Za, Spagnoletti, Winter, & Mettler, 2018). Thus, in order to foster an understanding of the principles guiding the design of service systems as inherently fuzzy and intangible entities, a more encompassing immersion could lead to a higher degree of representational power. In this vein, a future research avenue could be constituted by assessing the capabilities of virtual reality and similar technological approaches as means to implement expository instantiations (Jung Bae & Seong Leem, 2014). The synthetized overall contribution of this dissertation is the specification of an emergent design theory for artifacts that support the engineering of service systems in the digital age based on the prescriptive knowledge accumulated throughout this

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dissertation. However, in order to mature toward a full-blown theory for design and action (Gregor, 2006) with truth value (Iivari, 2007), future research avenues could deal with expanding this emergent design theory by means of engaging in theory testing and building activities. Thus, following the way mapped out for its further progression leads to the shaping of a consistent body of design knowledge – the declaration of victory and our ultimate goal (Gregor & Hevner, 2013; Nagel, 1979).

Final Considerations

5

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What’s new about digital innovation is a question academics are increasingly paying attention to. Understanding underlying premises, extracting common themes and getting to know which emerging research areas will gain importance in the future are central to manifold research disciplines. The multifaceted nature of the phenomenon leads to the convergence of hitherto bounded schools of thought, thus opening up the opportunity of combining a broad variety of different worldviews and research approaches. Businesses ask themselves what buzz words such as Big Data, Internet of Things, Cyber Physical Systems, Industry 4.0, Smart Factory, and Digital Transformation mean to them. Visions emerge and leave all kinds of firms with the uncertainty of where to pigeon themselves in a range from being hesitant via embracing a pragmatic view to risking too much. Other organizations might know where to go to and which novel business models might emerge, but do not necessarily possess the armamentarium to tread the right path. This work built on the paradigm of design science research in order to solve this real organizational problem via gathering an understanding of underlying premises and providing knowledge for the prospective design of artifacts that are attuned to the nature of innovating in the digital age. Artifacts in which valuable design knowledge is ingrained were built in order to support the engineering of digitally enabled service systems. However, and even more important, it is the knowledge on how to build and use these artifacts that constitutes a promising key for future success. Metaphorically spoken, knowing how to craft and utilize a trowel for constructing a house is far more valuable than solely buying and possessing it. It is then the abstracted knowledge that, when disseminated in an appropriate manner, prescribes a sustainable flow of knowledge gathering among the ones aiming to solve their problems. This dissertation addressed this notion by extracting the knowledge from the artifacts produced and articulating it in a way that opens up the possibility to develop it further in an interplay

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of solving organizational problems and producing scientific knowledge in future inquiries. To the end, the body of knowledge shaped for engineering service systems in the digital age is the body of a dwarf standing on the shoulders of giants. In other words, at least a grain of truth was discovered by building on previous discoveries. Through making this knowledge available for future research and exposing it to further scientific discourse, a step toward a Konstruktionslehre (abstracted and generalized guidelines on how to design something) on service systems in the digital age can be taken. Reverting back to the bearing and machine producer in the beginning, this might help him to understand its product not solely as a means to let a Tesla run smoothly, but to position himself in an a priori unimaginable value constellation with a multitude of resources and actors that will serve him with sustainable success in the digital age.

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Annexes

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 B. S. Höckmayr, Engineering Service Systems in the Digital Age, Markt- und Unternehmensentwicklung Markets and Organisations, https://doi.org/10.1007/978-3-658-26203-7

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Annex A: Knowledge Contributions Ingrained in Research In the following, an overview on work authored or co-authored by the author of this dissertation with relevance for the work is provided. Höckmayr, B. (2015). Enabling Companies to Make Use of Industrial Clouds – Foundations for Evidence-Based Engineering of Service Systems. In Proceedings of the 10th Research Colloquium on Innovation & Value Creation (I+VC). Leipzig, Germany Höckmayr, B., Roth, A., & Möslein, K. M. (2016). Service Systems Engineering Triggered by Digitalization – a Conceptual Framework. Paper presented at the 16th European Academy of Management Conference (EURAM). Paris, France. Höckmayr, B., Genennig, S., Roth, A., & Möslein, K. M. (2016). Service Systems Engineering Triggered by Digitization – Evidence from German Manufacturing SMEs. Paper presented at the 16th European Association for Research on Services Conference (RESER). Naples, Italy. Höckmayr, B. (2016). Initial Design of a Method for Service Systems Engineering in the Context of Digitization. Proceedings of the 11th Research Colloquium on Innovation & Value Creation (I+VC). Linz, Austria. Höckmayr, B., Roth, A., & Möslein, K. M. (2017). Initial Design of a Method for Service Systems Engineering in the Digital Age. Paper Presented at the 17h European Academy of Management Conference (EURAM). Glasgow, United Kingdom. Höckmayr, B., & Roth, A. (2017). Design of a Method For Service Systems Engineering in the Digital Age. In Proceedings of the 38th Internationcal Conference on Information Systems (ICIS). Seoul, South Korea. Roth, A., Höckmayr, B., & Möslein, K. M. (2017). Digitalisierung als Treiber für Faktenbasiertes Service-Systems-Engineering. In M. Bruhn & K. Hardwich (Eds.), Dienstleistungen 4.0 (pp. 185–203). Wiesbaden: Springer Fachmedien Wiesbaden.

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Annex B: Interview Guideline for Multiple Case Study In the following, an excerpt of the interview guideline used for the interviews in Study 2 is provided. Dear interview partner, Thank you very much for having agreed to conduct this interview with us. First of all, I would like to provide you with an understanding of the background of the project we are working on and the questions related to the underlying context. Recent technological developments in the field of sensors, actuators and IT have opened up the opportunity to connect machines and already manufactured products with each other. By that, it is possible to obtain information about their condition at any point of time. This interconnectedness of physical objects and processes has increasingly gained momentum in the digitalized world we live in nowadays. Recent developments aim to combine and centrally store the information generated, e.g., in the context of container, goods and vehicle tracking. It is of particular interest that this information can also be transmitted in real time to various participants across company and process boundaries.

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This makes it possible to react to deviations and inconsistencies in a significantly shorter amount of time. An overview of use case scenarios as elicited by Acatech (2015) is provided in Fig. 1.

Fig. 1: Use Cases for Connected Machinery and Products

In today’s business environment, valuable data is either often not used or its use falls short of expectations. Within the scope of this interview, the aim is to identify use cases from industrial practice, together with assessing their relevance for novel value creation potentials in the digital age. The main objective of this research is to provide you with tools and methods that are attuned to realize according business opportunities. In this context, your organization is regarded as a key resource for gathering insights on relevant use case scenarios. In order to provide a foundation for further scientific processing, we would like to audio tape this interview. Needless to say, the information provided from your behalf is subject to data protection and data privacy law and is analyzed in an anonymous form only. This means that no conclusions can be drawn about you or your company.

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1. Introductory questions about the interviewee i.

What is the name of your position in the company and how is your area of responsibility defined?

2. Introduction to the overall context i.

What does digitization in the manufacturing industry mean to you?

3. Application scenarios in your own company i.

What changes has digitization brought to your business so far?

ii.

Future application scenarios: What are the problems or potentials in your company that can be solved or tackled with the help of digitization in the future?

iii.

How could a concrete solution approach look like from your point of view?

iv.

Besides collecting data, what further prerequisites would need to be met in your company in order to be able to implement the solution?

v.

Desired scenarios: Assuming you are not subject to any technical or organizational limitations, which processes would you like to improve with the help of digitization?

4. Application scenarios along the value chain i.

Future application scenarios: What are the problems or potentials along the value chain that can be solved or tackled with the help of digitization in the future?

ii.

What could a solution approach look like from your point of view?

iii.

Besides collecting data, what further prerequisites would need to be met in your company in order to be able to implement the solution?

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5. Requirements for a cloud solution The interconnectedness of data and applications via platforms is becoming increasingly important. Many companies now use so-called industrial data clouds for the storage, real-time processing and decentralized availability of these data and applications. i.

What services could such a cloud provider provide to you or your customers?

ii.

What requirements do you have for such an industrial data cloud?

6. Wrap-up We discussed the possibilities of improving both internal processes and external applications at the customer on site by providing relevant data. i.

What visions do you have in this context for the next 10 years?

ii.

Did you notice any new aspects during the interview that we did not consider?

Thank you for your time!

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Annex C: Insights on the Development of TRIGGER In the following, an excerpt of an development and evaluation framework for TRIGGER is provided. AGENDA 09:00

WELCOME AND INTRODUCTION ROUND AMONG PARTICIPANTS

09:10

INTRODUCTION GREASE CARTRIDGE EXCHANGE

09:30

GENERAL METHOD INTRODUCTION AND STATUS QUO

10:00

REQUIREMENTS ENGINEERING FOR METHODS

10:30

COFFEE BREAK

10:45

METHOD DEVELOPMENT WORKSHOP II

12:15

LUNCH BREAK

13:00

METHOD DEVELOPMENT WORKSHOP II

14:30

COFFEE BREAK

14:45

DISCUSSION AND EVALUATION

15:00

WRAP UP OF METHOD DEVELOPMENT PART

15:15

PROJECT MANAGEMENT FOR GREASE CARTRIGE EXCHANGE

16:15

ROADMAP AND WRAP UP

17:00

END OF EVENT

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307

WORKSHOP ON METHODS 1. METHOD ENGINEERING • Requirements derived from characteristics of digitally enabled service systems • Requirements derived from service engineering • Requirements derived from characteristics of methods • Requirements derived from firm 2. METHOD CONDUCTION • Stakeholder Mapping • Requirements Engineering • Initial Service Blueprint • Information Pooling • Activity Assessment • Activity Allocation • Resulting Service Blueprint METHOD EVALUATION

REQUIREMENTS FRAMEWORK FOR METHODS FOR ENINGEERING OF DIGITALLY ENABLED SERVICE SYSTEMS

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EVALUATION WORKSHOP SETTING QUESTION •

Was the division into groups meaningful to you? Why?

•

Would the outcomes have been different without a division? How?

•

What did you like better? Working online or offline?

•

What are the advantages or disadvantages of working online?

•

What are the advantages or disadvantages of working offline?

•

What would you have done differently?

•

What was not necessary?

ANSWER

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EVALUATION REQUIREMENTS FROM DIFFERENT ELEMENTS ELEMENT

EXPLANATION

QUALITATIVE COMMENT: What’s good? What’s bad? What’s missing?

SERVICE SYSTEMS

•

Recognition of multitude of stakeholders

•

Recognition of knowledge & Skills as central resource

•

Actors with superior knowledge & skills

•

Actors with inferior knowledge & skills

•

Recognition of technology as the practical

application of knowledge •

Recognition of Information as resource

liquefied by digitization •

Recognition of systems as a configuration of resources

•

Recognition of service as the application of specialized competences (knowledge and

skills)

through

deeds,

processes,

and

performances for the benefit of another

entity or the entity itself

SERVICE ENGINEERING

•

Adaption of methods from engineering and

software development •

Systematic design and development of

•

Development of models, methods and tools

•

Customer orientation

services

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METHODS ENGINEERING

Annexes

•

Fundamental elements

•

Activity

•

Role

•

Specification documentation

•

Metal model

•

Technique

•

Attributes

•

Goal orientation

•

Systematic approach

•

Principles

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In the following, an excerpt of a brochure that translates underlying premises of the knowledge produced in actionable tradeoffs is provided.

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The complete version of the brochure is available online12.

12

http://smartdif.de/Publikationen

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Annex D: Insights on the Development of the DiDesigner In the following, an excerpt of the evaluation framework utilized in the course of the evaluation trajectory for the DiDesigner is provided

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