Cognition and Business Models: From Concept to Innovation 3031515978, 9783031515972

Table of contents :
Preface
Acknowledgments
Contents
List of Figures
List of Tables
1 The Promise of the Cognitive View of Business Modelling
Introduction
Defining the Business Model
Scoping the Cognitive View
Business Models as Mental Representations
Framing Business Models
Beyond the Rational Mind: Cognitive Biases
Emotions and Affect
Learning Theories and Business Modelling
Concluding Comments on the Contexts of Cognition and Business Modelling
References
2 Business Models as Managerial Mental Models
What Are Mental Models (of the Business Model)?
Epistemological Assumptions
One Organization but Multiple Mental Business Models
Are Mental Business Models Accurate?
How Can We Study the Mental Business Model?
Concluding Words on the Challenges of Measuring the Mental Business Model
References
3 The Sharing of (Mental) Business Models
Introduction
Shared Cognition and Mental Models
The Role of Framing
The Role of Cognitive Aids
Are We Really Capturing Shared Cognition?
Concluding Thoughts
References
4 Cognition and Business Model Innovation
Introduction
Innovation Contexts: A Structuring Framework
The BMI Process and Cognition
Metacognition and Knowledge Overconfidence
Concluding Thoughts
References
5 Open Questions on Cognition and Business Modelling
Introduction
Gaps Stemming from Dual Process and Affect Theories
Open Research Questions Identified in Existing Reviews
Creating Research Questions
Theoretical Grounding
Organizational Context
Level of Analysis
Process Stage (Temporal Analysis)
Concluding Thoughts
References
Index

Citation preview

Cognition and Business Models From Concept to Innovation

Kristian J. Sund

Cognition and Business Models

Kristian J. Sund

Cognition and Business Models From Concept to Innovation

Kristian J. Sund Department of Social Sciences and Business Roskilde University Roskilde, Denmark

ISBN 978-3-031-51597-2 ISBN 978-3-031-51598-9 https://doi.org/10.1007/978-3-031-51598-9

(eBook)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 This work is subject to copyright. All rights are solely and exclusively licensed 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. Cover credit: © Harvey Loake This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Preface

Writing this little book has been a real labor of love. I signed my contract with Palgrave just before the Covid-19 pandemic turned academia upside down, and it took longer than I anticipated to complete, as I kept getting interrupted by life events big and small. In the end the book became as much a reflection on the field at the intersection of cognition and business models, as it became a reflection on my own research, and how the various projects I have worked on and papers I have written all fit together. In 2012, while employed at Middlesex University Business School, I spent a short time visiting Copenhagen Business School, and Nicolai J. Foss. During a conversation with Nicolai, he asked me if I would like to contribute a chapter to an upcoming edited volume he was preparing with Tina Saebi (then a post doc at NHH, Norway). The volume was later published by Oxford University Press (OUP) under the title “Business Model Innovation: The organizational dimension”. Nicolai wanted me to write something about the transformation of the postal sector, from a business model perspective. This was an industry I had been studying for about five years at that point, resulting in a book series

v

vi

Preface

edited with a postal consultant, Derek Osborn, called “the Future is in the Post ”. I agreed to write a chapter, on the condition that I could involve two friends from my years at HEC Lausanne and EPFL, Marcel Bogers and Andrei Villarroel. This was no problem, and so we set about interviewing senior managers at three postal operators about their work with business model innovation. This was the first time I studied business models and their innovation in a formal way, and those conversations with managers first opened my eyes to the opportunities for studying business models from a cognitive perspective. Not long after, during a weekend at the end of August 2013, I met at the Solstrand Hotel outside Bergen, Norway, with a group of scholars involved in the OUP book. During that weekend we debated the business model construct, drew parallels to strategy and organization theories, and learned from each other. It was an enriching experience, and in particular I remember walking one afternoon with a fellow academic in the gardens of the hotel, overlooking the fjord, and sharing my skepticism of the construct. He too was grappling with how exactly to separate the business model from the many other constructs of the field of strategy. Then in May 2014 I visited Cass (now Bayes) Business School in London, and during a chance encounter with Charles BadenFuller, he asked me why we should study the business model at all. He too had apparently spent time getting to grips with the construct from a cognitive perspective (as evidenced already in his 2010 Long Range Planning article with Mary S. Morgan, entitled “Business Models as Models”). I answered then (as now), that if managers use and talk about the construct, we have a duty as social scientists to study it as well. Now, a decade later, the concept of business models is more popular than ever, and where I was somewhat skeptical in the beginning of my own journey regarding what business models could bring to the strategy literature, I am now convinced that this concept has enhanced our understanding of how managers think about strategy. For example, academics in strategy will often think about competitive strategy as an almost binary choice between low cost and differentiation positions. But I remember asking a top manager once whether his firm had a low-cost strategy, to which he simply answered: “All firms have to manage their costs”. He did not think about strategy in those terms. When asked how he

Preface

vii

would explain his strategy, he instead brought up elements of his strategic “recipe” that reminded me of elements of a business model. I have also experienced that many managers explicitly use the term “business model”, even when not prompted. It therefore appears to be a construct that has definitively entered the collective consciousness of managers. For this reason, and regardless of whether strategy scholars may have other concepts in their repertoire that could be just as useful, we have to take the business model concept seriously—as a cognitive construct to which managers routinely refer. Business models exist not just in the academic papers of strategy and innovation scholars, but more importantly, in the minds of the managers who are the objects of study of those same scholars. Thus it is, that from the moment I started studying business models, and business model innovation, it became clear to me that there was a need to conceptualize and empirically study the business model as a cognitive construct—a kind of mental map, with cause-effect relationships, of how the firm does business. Far from being fully formally planned and written down, I discovered that business models in firms existed in the minds of the manager, and that different managers could have different models in their minds, even within the same firm. I also discovered that this gave rise to sensemaking, sense-giving, framing activities, and even tensions, as managers would perceive things differently and thus disagree on key decisions regarding business model innovation. Over the past decade, in work carried out with colleagues and with several Ph.D. students, I have come to understand that business models are dynamic, and their change involves a process, that we can study and to some extent generalize from. Similarly, the barriers to business model innovation experienced by managers are somewhat generic and reveal insights about organizing and organizations, as well as about the human mind and social interactions. It is difficult to do justice to the growing literature linking business models and their innovation to theories and concepts of human cognition. Since its founding, I have been one of the series editors of the book series New Horizons in Managerial and Organizational Cognition (Emerald), and in 2018 and 2020 we dedicated volumes to “Cognition and Innovation” and “Business Models and Cognition”, with Stefano

viii

Preface

Brusoni (ETH Zürich) and Marcel Bogers (Eindhoven University of Technology) as guest editors, respectively. In both these volumes we were still early explorers, but publishing relevant to this area appears to be accelerating, as scholars recognize the importance of examining in more detail how managers think about business models, adapt their thoughts, share these thoughts, and how these thoughts can act as both catalyst and barrier in the context of innovation. There are still many gaps, and it is the humble objective of this short book to explore (only) some of what we now know as well as to identify (only) some of the opportunities for further research in the area. I do not know all the answers, but I hope to ask some convincing questions, and open some discussions that can encourage others to join in the exploration of business models from a cognitive perspective. Roskilde, Denmark August 2023

Kristian J. Sund

Acknowledgments

I want to gratefully acknowledge the inspiration and contributions along the way of those who have worked with me on business models over the past decade, including in no particular order, Nicolai J. Foss, Marcel Bogers, Kathrine Egfjord, Henrik Jensen, Andrei Villarroel, Yuliya Snihur, Robert J. Galavan, Annesofie Lindskov, Sergei Mozheiko, Meri Sahramaa. I hope this list continues to grow in the future. This book is dedicated to my family and to the memory of my mother.

ix

Contents

1 The Promise of the Cognitive View of Business Modelling Introduction Defining the Business Model Scoping the Cognitive View Concluding Comments on the Contexts of Cognition and Business Modelling References 2

Business Models as Managerial Mental Models What Are Mental Models (of the Business Model)? Epistemological Assumptions One Organization but Multiple Mental Business Models Are Mental Business Models Accurate? How Can We Study the Mental Business Model? Concluding Words on the Challenges of Measuring the Mental Business Model References

1 1 3 6 16 18 25 26 28 30 32 36 40 41

xi

xii

Contents

3 The Sharing of (Mental) Business Models Introduction Shared Cognition and Mental Models The Role of Framing The Role of Cognitive Aids Are We Really Capturing Shared Cognition? Concluding Thoughts References

47 48 50 53 55 57 61 64

4

Cognition and Business Model Innovation Introduction Innovation Contexts: A Structuring Framework The BMI Process and Cognition Metacognition and Knowledge Overconfidence Concluding Thoughts References

69 70 72 77 81 83 85

5

Open Questions on Cognition and Business Modelling Introduction Gaps Stemming from Dual Process and Affect Theories Open Research Questions Identified in Existing Reviews Creating Research Questions Concluding Thoughts References

Index

91 92 92 93 94 100 100 105

List of Figures

Fig. 2.1 Fig. Fig. Fig. Fig.

2.2 2.3 3.1 3.2

Fig. 3.3

Fig. 4.1

A stylized representation of knowledge related to the business model A simple visual representation of a mental map Sample map reproduced from Egfjord and Sund (2020b) The “whys” and “whats” of shared mental business models The shared mental business model is here defined by the area of overlap in the mental maps of individuals A, B, and C (illustrated by small rectangle D) The shared mental business model is here defined by the sum of the mental maps of individuals A, B, and C (illustrated by large rectangle D) Framework for the study of cognition and innovation (reproduced from Sund et al., 2018b)

33 37 38 52

58

59 75

xiii

List of Tables

Table 1.1 Table 5.1

Business model descriptions (simplified overview) Open research questions at the intersection of cognition and business models explicitly identified in selected literature review articles

5

95

xv

1 The Promise of the Cognitive View of Business Modelling

Abstract The business model construct has become very popular in the strategy and innovation literatures. It has recently been pointed out that a cognitive view of business models, business modelling, and business model innovation, holds much promise in terms of advancing our understanding of both the business model construct, and how such modelling takes place. However, as a newcomer, how would you approach this emergent field? In this chapter, I start by defining the business model, and then scope the cognitive view. This includes a discussion of the business model as a mental representation of a business, how such mental representations are framed and shared, how emotions and biases can affect business modelling, and the role of organizational learning and unlearning in business model innovation.

Introduction As a newcomer to the emerging research field at the intersection of cognition and business models, how could one start both to make sense of the existing literature, and to imagine the many open research questions that exist? This can easily seem like a daunting task, and in my experience be © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9_1

1

2

K. J. Sund

very confusing, particularly for doctoral students new to both the cognition and business model literature. The literature related to managerial and organizational cognition is extensive and diverse both in terms of theories, methods, and empirical findings (Galavan et al., 2018). The same could today be said of the general business model and business model innovation literature. Yet, the field at the intersection of the two is still nascent. The business model construct has become very popular in the strategy and innovation literatures. As has been pointed out many times, the exact definition of a business model has remained the object of some degree of discussion among scholars, some calling it a description (e.g., BadenFuller & Morgan, 2010), some an activity system (e.g., Zott & Amit, 2010), some a template (e.g., Zott & Amit, 2008), and some a framework (e.g., Schneider & Spieth, 2013). What seems to be agreed upon, is that a business model describes how value is created, distributed, and appropriated by the organization (Teece, 2010). This description can take the form of a simple narrative (a recipe), a stylized archetype (a generic business model, or template, such as the “bait-and-hook”), or a more complicated framework of complementary components, such as found in the popular business model canvas (Osterwalder & Pigneur, 2010). Why should anyone studying business models take an interest in theories related to cognition, and what are avenues of potential investigation? These are the questions I will try to address in this chapter, and indeed, in the rest of this book, as I outline the promise of the cognitive view of business modelling. Numerous studies of business models and business model innovation (BMI) have accentuated the cognitive underpinnings of the business model construct or pointed to the role of cognitions in shaping business models and business model change (Sund et al., 2020a). For example, it has been suggested that the business model can be studied as a form of cognitive structure (Doz & Kosonen, 2010), mental map, or schema (Martins et al., 2015), of how the firm creates and appropriates value. Several recent studies have also highlighted how managers’ cognitions and sensemaking influence business model design (Egfjord & Sund, 2020; Sosna et al., 2010; Sund et al., 2021). Finally, process studies of

1 The Promise of the Cognitive View of Business …

3

BMI have highlighted the role of shared logics in enabling such innovation (Bogers et al., 2015; Egfjord & Sund, 2020; Jensen & Sund, 2017), and how the information and knowledge search behaviours of managers affect the type of BMI being pursued (Snihur & Wiklund, 2019). Despite these early research results, recent reviews of the business model literature also emphasize the links between business models and cognition as an area in need of formal conceptualization and further research (Foss & Saebi, 2017, 2018; Martins et al., 2015; Massa et al., 2017). The cognitive underpinnings of business models are thus often mentioned, but far less frequently explicitly studied. This despite the fact that managers decide and act on their subjective cognitions, not on any objective reality (Daft & Weick, 1984; Sund, 2015). In other words, to unfold business model decision-making, one must unfold business model perception and cognition.

Defining the Business Model As already indicated in the introduction, a business model describes how value is created, distributed, and appropriated by the organization (Teece, 2010). To understand the concept of value in the context of business models, we can turn to two sources: the simple economic definition, and what I would call the marketing definition. The first focuses on exchange value, realized at the point of sale. The second focuses on use value, which is subjective and is a value perceived by the individual consumer of a product or service (Bowman & Ambrosini, 2000). Both actually have their foundation in the science of economics. The economic definition of value hinges on the concept of price, which is usually expressed as a monetary amount that a consumer is willing and able to exchange for a product or service, and at which a firm is willing and able to supply this product or service. Market demand and supply for a product will determine the market price at which these exchanges will take place. When an economist puts a value on a product, this market price will often be it. The value appropriated by a firm and its business model can then be quantified as the difference between the market price of the product, and the (market) cost of all inputs used

4

K. J. Sund

to produce this product. For example, if the cost to produce a car is $15,000, and it is sold for $20,000, then the value added (and appropriated) by the car manufacturer is $5,000. This is the value creation principle behind value-added tax (VAT). VAT is collected in a way in which each firm along the value chain in an industry pays a fractional portion of the total VAT that corresponds to the value added by that particular firm. If the car used in my previous example is sold to the final consumer for $20,000+ VAT, the car producer only transfers to the tax authorities the fraction corresponding to its own added value, i.e., VAT on $5,000. The rest is paid by its suppliers upstream. A more detailed analysis is needed when considering distribution and appropriation, since some of the value created could for example, depending on the business model, be shared with distributors, or be appropriated over time in the form of leasing payments. Thus, value created and appropriated may not be the same, and creation and appropriation may occur at different points in time. The use definition of value is central to marketing research, and considers value as a subjective perception, or judgment, by the buyer. Such perceptions are pervasive in the value chain, such that both consumers and firms perceive value in the inputs and outputs they buy, that may differ from the actual cost or price. Economists call the subjective perception of value “utility”, and theorise that consumers are utility maximisers, trying to get the most utility (satisfaction) from their money. The difference between the price of a product, and the utility it generates, or in our case, between the use value and economic value (price), is what economists refer to as a consumer surplus. This surplus exists when the consumer would have been willing to pay more for the product than they did. So-called yield management pricing (as known from for instance the airline or hotel industries), where prices are variable and adapt depending on the demand for the product, is an example of a pricing model that aims to transfer (appropriate) consumer surplus to the producer. Economists traditionally refer to this as price discrimination, which is only possible if competition is imperfect, giving sellers some degree of pricing power. From a business model perspective, this is a pricing policy that could be considered part of the business model.

1 The Promise of the Cognitive View of Business …

5

In other words, if the business model describes how value is created and appropriated, the pricing part is a necessary feature of this model. Although the typical definition of a business model emphasizes the idea of value, the description of a given business model (as employed by both scholars and practitioners) typically goes far beyond pricing. The description of the business model can take the form of a simple narrative (a recipe), a stylized archetype (a generic business model, or template, such as the bait-and-hook), or a more complicated framework of complementary components, such as found in the popular business model canvas. As indicated in Table 1.1, simpler narratives often lack detail. For example, German automaker Volkswagen recently announced it would establish a business model for a unified software stack, which revolves around the Volkswagen Operating System (VW.os). They describe this as “a system of systems: forming a scalable and unified software platform of best-in-class elements developed in-house, combined with solutions from our partners 1 ”. Although such a recipe is not very detailed, it will often be understood by those initiated to it inside the organization, and to key stakeholders outside. Relevant actors inside Volkswagen will be able to fill in the blanks cognitively, such as having a mental picture of what the “platform” is, defining the “elements” of the platform, or providing examples of “partners”. If we study many different businesses, we find patterns emerging among the many business models of these businesses. Similarities emerge, that allow typologies to form. Several books have been published over the years containing such archetypical business models, essentially standardized recipes (e.g., Gassmann et al., 2014). The bait-and-hook is an example, in which the basic product (the bait) is offered cheaply Table 1.1 Business model descriptions (simplified overview) Simple narrative recipe Stylized recipe archetype Framework-based recipe

1

Low level of detail; Understood by the initiated Low-medium level of detail; Understood at least partly also by outsiders Higher level of detail; Understood more widely by all actors

https://cariad.technology/de/en/news/stories/vw-os-software-platform-explained.html.

6

K. J. Sund

on the market but requires a refill or complementary product after a while, which is sold at a higher mark-up. The traditional examples are the razor and the razorblade, or the printer and the toner. The basic product loses its usefulness without the refill, and the objective is to hook the customer with the bait, so additional sales can be generated through the refill. The benefit of such standardized descriptions is that they can be shared with and understood easily by other actors. If an entrepreneur tells a potential investor that they intend to develop a bait-and-hook model, the investor will immediately understand an important part of the value creation and appropriation mechanism of the proposed product or service. Stylized business model archetypes are thus standard recipes that can be communicated and understood with ease. A more detailed description of a business model can be created with a framework containing complementary components such as the business model canvas (Osterwalder & Pigneur, 2010). This canvas suggests that a business model can be described by a pre-defined number of components, such as key activities, resources, and distribution channels. The canvas (and other such frameworks) serves to organize business model thinking and design, and to provide a common language, much like other cognitive aids in strategy do (Gustafsson et al., 2023). It thus supports actors make more rapid and effective decisions, focus attention on what data and issues are relevant (Egfjord & Sund, 2020; Sund, 2013), reduce complexity and uncertainty (Jarzabkowski & Kaplan, 2015; Sund, Galavan, et al., 2016b; Sund et al., 2022), and encourage new ways of thinking (Massa & Hacklin, 2020).

Scoping the Cognitive View The Managerial and Organization Cognition (MOC) Division of the Academy of Management has by now existed in some form for over 30 years. The division’s domain statement (as per 2022/2023) provides a glimpse into the very wide range of topics (and associated theories) that are by now considered part and parcel of management and organizational cognition:

1 The Promise of the Cognitive View of Business …

7

In studying cognition at multiple levels MOC members’ specific topic areas include, but are not restricted to: social construction, culture and cognition, the nature and role of mental models and representations, judgment and decision making, attribution processes, individual differences, non-conscious forms of cognition (e.g. intuition), cognitive institutionalism, emotion, ideology, identity / identification, image, reputation, sense making / meaning making, symbols and artifacts, categorization, knowledge creation and management, individual learning, organizational learning and memory, and communities of practice.

Rather than attempt to be the judge of which of these (or other topics) deserve special treatment, I would simply contend that all of these, and more, represent possible theoretical avenues that can inform research on business models and business model innovation, and that in turn can gain from the study of business modelling (Sund et al., 2018). I will return to this point repeatedly throughout this book.

Business Models as Mental Representations First and foremost, there is an emerging cognitive view on business models, which suggests that the business model serves as a form of mental model, logic, or recipe, of how a business creates and appropriates value. For example, Doz and Kosonen (2010, p. 371) argue that business models stand as cognitive structures providing a theory of how to set boundaries to the firm, of how to create value, and how to organize its internal structure and governance. This view of the business model as a cognitive knowledge structure (or knowledge structure content) is consistent with the more general cognitive view of strategy (Martins et al., 2015). A mental representation of a business model may indeed not be very different than a mental representation of similar constructs, such as a strategy, a market position, a vision, or any other construct representing how the organization generates revenues, and how it relates to other actors, such as competitors, customers, or suppliers. The vast MOC literature concerned with such strategy-related knowledge structures can thus directly inform our study of business models. This literature hinges on the assumptions that such representations really do exist, and that

8

K. J. Sund

managers create these representations to help process information and make decisions (Walsh, 1995). Multiple competing theories and conceptualizations exist of mental representations (Walsh, 1995), that to some extent makes reading the literature confusing. Such representations have been somewhat interchangeably referred to in management literature as schema, cognitive maps, interpretive schemes, causal maps, frames of reference, strategic frames, knowledge structures, dominant logics, world views, etc. In Chapter 2 of this book, I discuss business models as mental representations in much more detail. For now, we will just assume that they exist.

Framing Business Models Any issue can be viewed from a variety of perspectives, or what have been referred to as frames (Sund & Anson, 2021). Snow and Benford (1992, p. 37) consider a frame an “interpretative schema that simplifies and condenses ‘the world out there,’ thus organizing experience and guiding action by rendering events or occurrences meaningful ”. These frames are guides for sensemaking and interpretation, constructed through social interaction (Kaplan, 2008). Sociologists have therefore not surprisingly studied framing for many years, especially in the context of social movements. The emphasis of sociologists has been on public discourse, frame alignment, and collective identity (Benford, 1993). More recently, framing has gained popularity in the management literature as a mechanism to explain the dynamics of competing logics within and between organizations (Guérard et al., 2013; Kaplan, 2008; Pazzaglia et al., 2018). According to framing theory, some actors actively engage in framing activities, trying to share their frame of an issue, and to influence the opinions of other actors. In the context of business models, entrepreneurs and incumbent firms alike have been shown to use framing activities to influence legislators and public opinion. For example, Gurses and Ozcan (2015) provide a rich description of how entrepreneurs in the U.S. pay TV market used framing activities to enter a very regulated market, and how incumbents similarly tried to defend their position through framing. Sund and Anson (2021) discuss how actors in the

1 The Promise of the Cognitive View of Business …

9

postal industry adopted competing frames of the future when faced with digital substitution. There is some degree of similarity of outcome between framing and priming (Chong & Druckman, 2007). In both cases, some interpretations are brought to the forefront, whilst others are repressed. Frames amplify in scope by being actively shared and spread, through being regularly invoked, or by being coupled with emotions (Purdy et al., 2019). This can lead to the institutionalization of a frame at both the organizational and inter-organizational level, as demonstrated by the study of Gurses and Ozcan (2015). They “document how institutional change is the outcome of a long-term process, which is fuelled by entrepreneurs acting collectively to convince private groups and institutional actors to cooperate while battling with resistors of change through framing contests” (p. 1733). Eliciting and studying cognitions and frames can help us examine and compare the perceptions of different managers in a context of business modelling due to environmental change (Egfjord & Sund, 2020; Sund & Anson, 2021). Beyond simply describing the historical actions of an organization in response to change, studying frames allows the researcher to shed light on the logics that guide business model travel, as well as competing logics that were ultimately abandoned (Sund, 2020). In the context of the incumbent innovator, strategies find their roots in the competing frames developed at different management levels and in different teams within the firm. Studying these frames can thus provide insights into why some business model changes were successfully adopted throughout the organization over time, and others abandoned.

Beyond the Rational Mind: Cognitive Biases One of the more ground-breaking and long-term research efforts within cognition was that of Amos Tversky and Daniel Kahneman, for which the latter received the Nobel Memorial Prize in Economic Sciences in 2002 (alone since Tversky had passed away six years earlier). Strategic decision-making takes place under conditions of uncertainty (Huff et al., 2016; Sund et al., 2022), and their work examining the role of cognitive biases and heuristics in such decision-making pushed our understanding

10

K. J. Sund

of human cognition. What is now termed dual processing theory suggests that decision-making is subject to both conscious and nonconscious cognition, or what Kahneman (2011) refers to as “system 1” and “system 2” thinking. On the one hand the brain is capable of making quick, intuitive, and instinctive decisions (system 1), on the other of thinking problems through slowly, analytically and logically (system 2). In order to achieve faster decisions and to conserve energy, the brain is geared toward system 1, and in fact, a lot of our decision-making is nonconscious. In the context of managerial decision-making, superior decision-making performance is associated with using semiautomatic system 1 cognitive processes when faced with well-structured problems, and more deliberative system 2 processes when faced with ill-structured problems (Laureiro-Martínez & Brusoni, 2018). What we colloquially refer to as decisions based on “gut feeling”, is actually system 1 decision-making, based on heuristics, or decision rules. Some of these heuristics result in biases. One of the most documented cognitive biases is the problem of overconfidence. One way this overconfidence bias manifests itself is as overestimation, whereby people are overconfident in the accuracy of their own knowledge and judgments. Evidence thus suggests that we generally and systematically tend to overestimate both our knowledge and abilities (Kahneman, 2011; Kahneman et al., 1982; Klayman et al., 1999). Some degree of confidence is needed in order to function as an individual, but when confidence turns to overconfidence, there are potential negative effects for managerial decision-making. For example, overconfident CEOs and CFOs have been found to lead their organizations into more aggressive corporate policies, bigger investments, and more debt financing (Ben-David et al., 2013; Malmendier & Tate, 2005). There is evidence that overconfidence bias can be considered an individual trait and thus that some people are more overconfident than others (Giacomin et al., 2016; Hansson et al., 2008; Sund, 2016). However, group dynamics also influence overconfidence. Knowledge overconfidence may be encouraged by the professional culture of a business environment, despite the fact that scholars have evidenced a variety of potentially negative effects of overconfidence for the quality of managerial decision-making. An interesting recent study found that return on

1 The Promise of the Cognitive View of Business …

11

equity appears higher for firms with an overconfident CEO, perhaps due to the signals the person sends to investors, although the effect size appears limited (Reyes et al., 2022). More research is needed on this question, and as the authors point out, “the overconfidence-performance link is likely moderated by other factors” (p. 510). Overconfidence has been widely studied in the specific context of entrepreneurship. Here, overconfidence stimulates assessing opportunities positively, leads to more venture creation, and such ventures’ innovativeness, but it also negatively affects ventures’ performance at later stages (Kraft et al., 2022). Overconfident entrepreneurs in general have a tendency for excessive market entry (Camerer & Lovallo, 1999). It has also been suggested that overconfidence is associated with a higher likelihood of over-forecasting new product sales (Markovitch et al., 2015). However, there has been only very limited attention to, and evidence regarding, the link between overconfidence and business model adaptation in existing firms (Kraft et al., 2022).

Emotions and Affect Some decisions are taken under conditions of emotionality (affect). Hodgkinson and Healey (2011) and Hodgkinson et al. (2018) have argued that the early MOC literature was largely focused on methods and theories that explore conscious decision-making under conditions of low affect—i.e., conscious system 2 thinking. It is only in the last two-three decades that the management literature has fully recognized that managers may be subject to not only nonconscious biases, but also emotions when they make decisions (Barsade & Gibson, 2007). Affect is a broad term that covers a variety of feelings people experience, and it has been studied as discrete emotions (e.g., fear, anger, excitement), as moods (e.g., cheerfulness, sadness), and as traits (e.g., a disposition towards being positive or negative). While discrete emotions may come and go rapidly in a particular situation (e.g., temporary anger at upsetting news), moods are more pervasive and long-lasting, while traits have to do with the individual person. Some individuals may, for example, be better than others at regulating their own emotions in a work situation.

12

K. J. Sund

Affect matters to management research, not least because it has been linked to performance, such that, for example, people experiencing positive emotions and moods, will also tend to be more successful at work (Lyubomirsky et al., 2005). Although the vast empirical evidence from the general psychology literature has been somewhat mixed, the tendency is to view positive affect as having a positive effect on decision-making, such that when system 1 thinking is engaged, and a quick answer is needed, people in positive moods more readily respond with an appropriate decision-making strategy. When system 2 thinking is needed, i.e., a deeper and more analytic processing, people who are in a good mood appear to recognize this necessity and have improved processing (Barsade & Gibson, 2007). Of interest to studies of innovation is the finding that chronically happy people score higher on measures of creativity, and that pleasant emotions enhance performance on simple measures of flexible thinking and originality (Lyubomirsky et al., 2005). To complicate matters, in an entrepreneurial and innovation setting, affect may interact with a variety of dimensions of personality and behaviour, such as impulsivity (Wiklund et al., 2018). Moving from individual moods and outcomes to team moods and outcomes, and using an experimental approach, Hoever et al. (2018) demonstrate how negative and positive feedback can affect team creativity, through its effects on information search. Negative feedback may lead teams to search for more information. On the other hand, by stimulating generative processing, positive feedback may indirectly promote team creativity, particularly in informationally homogeneous teams. Affect in teams thus influences the process of creativity, and this could well be the case during business modelling, as with other creative tasks. The role of emotions has been acknowledged in the general innovation literature (Choi et al., 2011). Less is known specifically about affect and business modelling. Beyond creativity itself, there is the question of how affect interacts with the change process often inherent when especially incumbent firms wish to implement business model innovations (BMIs). One aspect is that managers may experience a fear of looking foolish (Bez & Chesbrough, 2020). Schneckenberg et al. (2019, p. 431) furthermore point out that the emotional and affective bonds

1 The Promise of the Cognitive View of Business …

13

to long-established value-creating and value capturing activity configurations risk resulting in escalation of commitment and cognitive inertia of senior managers. The role of emotions could thus help clarify and deepen our understanding of the cognitive barriers to BMI in incumbent firms, including family firms (Rau, 2013). Incumbent firm BMI typically involves multiple groups of actors, including innovation teams, core business middle managers, and top managers (Egfjord & Sund, 2020; Sund et al., 2021). It has been suggested that in situations of positive affect, middle managers will judge change initiatives originating from top management as more legitimate (Huy et al., 2014), but there is also evidence that affective responses become more pronounced over time in a change process, with negative affect typically appearing in later stages of the change process (Balogun et al., 2015). Thus, resistance to business model change may vary across the business model innovation process (Jensen & Sund, 2017). Finally, in their study of innovation failure in Nokia, Vuori and Huy (2016) describe in detail how shared emotions but divergent attention, between top and middle management, actually hampered the innovation process.

Learning Theories and Business Modelling Learning theories deal with the question of how we receive, process, and retain knowledge. Behaviorist learning theories have traditionally focused on conditioning, whereby learned behavior becomes a reflex response to a stimulus, which itself is the result of consequences that follow the behavior through a reward (reinforcement) or a punishment. With his social learning theory, Bandura (1977) added to this that the principal vehicle of learning is observation of the environment, and that stimulus-response relationships are mediated by attention, retention, reproduction, and motivation. For a behavior to be imitated, it has to first grab our attention. Social learning is not necessarily immediate, as behavior may be noticed but not remembered (retention). Even if retained, behavior may not be reproducible, for example due to physical limitations. Finally, the rewards and punishments that follow a behavior may not be sufficient to motivate the individual.

14

K. J. Sund

The memory system is considered in cognitive learning theories an active organized processor of information, and prior knowledge plays an important role in learning. The individual has a limited capacity to hold information in the so-called short term (active) memory. For example, remembering a just-heard phone number requires holding it in short term memory, and is limited to a short period of time. Long term memory has a much greater capacity. These terms should not be confused with the idea of working memory, which denotes memory related to structures and processes for temporarily both storing and manipulating information, related to the concept of working attention. In other words, we focus our attention on a task and can manipulate relevant information in our working memory. Learning theories related to the original work of Swiss psychologist Jean Piaget are often grouped under the term constructivist learning theories. Such theories may refer to active learning, discovery learning, and knowledge building, but all versions promote a learner’s free exploration within a given framework or structure. The learner uses background knowledge and concepts to assist them in their acquisition and assessment of new information. On approaching new information not compatible with the current schema, the learner faces disequilibrium with their previous understanding, and this demands a change in cognitive structure, combining previous and new information to form an improved cognitive schema. A constructivist approach to teaching entrepreneurs has been suggested to be particularly relevant (Honig, 2004). To be successfully implemented, the business model must first be conceived. Business modelling is thus a forward-looking activity with very different learning challenges to the backward-looking gaze of experiential learning (Berends et al., 2016). Recent work has highlighted that managers involved in system dynamic business modelling develop more accurate representations of their business models (Moellers et al., 2019). This can result in a cognitive gap between the representation of those involved in the modelling and those outside the process. Moellers et al. (2019) describe this gap in terms of levels of model dimensionality, with those involved in modelling understanding the complexity, and those outside becoming overwhelmed and treating the model as a black box.

1 The Promise of the Cognitive View of Business …

15

In a study of four BMIs, Berends et al. (2016) highlight that in the context of incumbent BMI, two modes of learning operate iteratively together: cognitive search, and experiential learning. They emphasize that since a business model is both a cognitive representation, but also an objective reality, cognition and organizational action iterate in processes of business model learning. In cognitive search, action follows cognition, while in experiential learning, cognition follows action. While organizational learning can lead to more efficient routines, it also leads to inertia, and barriers to new learning. Past learning compels organizations to reinforce the success formulas embedded in organizational routines, rather than question these. Firms with a strong existing business model will likely find it more difficult, when faced with crisis or large environmental changes, to adjust and unlearn. Starbuck (2017) describes the typical stages of unlearning as (1) a period of inertia during which the firm will try to weather the storm, (2) a period of unlearning as the firm gradually discards old routines to make way for new ones, and (3) a period of rediscovery and regeneration. In a reflection on case firms he studied, Starbuck (2017, p. 36) writes about the passage from the second to the third stage that “the survival of seriously threatened organizations requires mass replacements of top managers. Of the organizations we studied, half survived, and half failed. In every case of survival, some event caused the simultaneous dismissal of almost all of the top managers.” He goes on to reflect that “unlearning makes employees, investors and other stakeholders very sceptical about the competence and truthfulness of the current top managers; stakeholders lose confidence that real strategic changes will occur.” The unlearning of business models is similarly likely to be a tumultuous time for the incumbent organization. Snihur (2018) suggests that when the external threat to the incumbent is a new and different business model of a newcomer in the market, this significant change in the industry impacts organizational identity, and the beliefs that are shared under this identity. For a more detailed recent review of unlearning literature, see for example Sharma and Lenka (2022).

16

K. J. Sund

Concluding Comments on the Contexts of Cognition and Business Modelling Research at the intersection of business models and cognition has only recently emerged, and just started to recognize and explore the multitude of contexts of business modelling. Many opportunities for research thus remain. One context is that of open business models, and open BMI. Open business models transcend organizational boundaries, for example through partnerships with other firms, or through open innovation involving external actors (Sund et al., 2020b). Saebi and Foss (2015) point out that matching the firm’s innovation strategy and business model can be an important antecedent of open innovation performance. However, so could shared cognition. What happens if the mental representations of the business model differ from partner to partner in the open business model? And how do shared representations emerge in the first place in open innovation ecosystems (if they emerge at all)? Such questions have not adequately been answered by existing studies. Furthermore, there may be specific contexts of open innovation that deserve separate study. For example, Saebi and Foss (2015, p. 206) present four distinct open innovation strategies, that we could speculate would lead to very different amounts and depths of interaction between partners. They refer to these as the market-based innovation strategy (in which knowledge is simply bought in from partners), the crowd-based innovation strategy (where knowledge is sourced from a large number of actors), the collaborative innovation strategy (where a deeper integration between partners takes place), and the network-based innovation strategy (akin to an ecosystem, with many partners but some degree of integration as well). We could speculate that in the market-based open innovation strategy, shared cognitions regarding the business model play a lesser role than in a collaborative strategy. One very specific boundary of open innovation is across state and private actors, often termed public–private partnerships. We are in a decade in which the ramifications of an ageing population will be felt much more intensely than previously, in particular in Europe and China. Securing the healthcare and elderly care sectors will likely require the exploration of new business models at the intersection of the public and

1 The Promise of the Cognitive View of Business …

17

private sectors. This is an area rich in questions and scarce in answers (Sund et al., 2020b). Given the need for shared perceptions of goals and business models in such partnerships, how do those actors with a focus on public value reconcile their mental models with those actors supporting an agenda of private value capture? How are varying objectives negotiated and how is the trust necessary for open BMI built? How is innovation (with its inevitable failures) that is embraced by the private sector even conceptualised in the public sector? Such questions are equally important for sustainable business models, where wider objectives are considered than private profit. In fact, sustainable business models and BMI represent a whole separate context for investigation from a cognitive perspective. Two contexts that have been quite clearly distinguished already in the literature specifically addressing BMI and cognition are those of the entrepreneur and the incumbent firm. While the former does not suffer from the cognitive and learning inertia of the latter, the latter often has more resources with which to explore than the former. Business model (and BMI) failure may be caused by different contingencies in these two very different contexts. We need more research to better understand failures in BMI, particularly where the model succeeds in some cases and fails in others. Where the innovation fails, is this to do with differences in firm capabilities, or is it to do with failures in representation and cognition, failures in actioning the representation, or even deliberate misrepresentation of the reality? A summary look at management and entrepreneurship research would suggest that such misrepresentations are actually not uncommon (see for example some of my own discussions in e.g., Sund, 2016, 2023; Sund & Lindskov, 2022; Tatomir et al., 2023), but would in the case of entrepreneurs often be linked to pitching the opportunity and securing investments, while in the incumbent be linked to other considerations (e.g., Egfjord & Sund, 2020). A final direction of research related to context that is worth mentioning is that of industry context (and indeed national/cultural context). Studies of business models and cognition have often used case studies and have been conducted in a wide number of industries, including technology (e.g., Aspara et al., 2013), retailing (e.g., Snihur, 2018), media (e.g., Jensen & Sund, 2017), insurance (Egfjord & Sund,

18

K. J. Sund

2020), banking (Bellini & Castellazzi, 2020; Sund et al., 2021), and the postal industry (e.g., Sund, Bogers et al., 2016a). However, these studies rarely explain how the context affects their conclusions. In other words, specific contextual contingencies are rarely identified. It would be of great value to the study of business models and cognition if these contingencies could be identified and properly studied. Furthermore, larger sample studies based on surveys or archival data are few. As I hope to have demonstrated in this chapter, the opportunities for studying business models and cognition are many, and no doubt the next few years will continue to see a rise in studies trying to do so. In the final chapter in this book I discuss further some of the many open questions for research.

References Aspara, J., Lamberg, J.-A., Laukia, A., & Tikkanen, H. (2013). Corporate business model transformation and inter-organizational cognition: The case of Nokia. Long Range Planning, 46 (6), 459–474. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171. Balogun, J., Bartunek, J. M., & Do, B. (2015). Senior managers’ sensemaking and responses to strategic change. Organization Science, 26 (4), 960–979. Bandura, A. (1977). Social learning theory. Prentice Hall. Barsade, S. G., & Gibson, D. E. (2007). Why does affect matter in organizations? Academy of Management Perspectives, 21(1), 36–59. Bellini, E., & Castellazzi, S. (2020). The metacognition underlying radical business model innovation: Four case studies of individual criticism. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Ben-David, I., Graham, J. R., & Harvey, C. R. (2013). Managerial miscalibration. The Quarterly Journal of Economics, 128(4), 1547–1584. Benford, R. D. (1993). Frame disputes within the nuclear disarmament movement. Social Forces, 71(3), 677–701. Berends, H., Smits, A., Reymen, I., & Podoynitsyna, K. (2016). Learning while (re) configuring: Business model innovation processes in established firms. Strategic Organization, 14 (3), 181–219.

1 The Promise of the Cognitive View of Business …

19

Bez, S. M., & Chesbrough, H. (2020). Barriers in searching for alternative business models: An essay on the fear of looking foolish. In K. J. Sund, R. J. Galavan & M. Bogers (Eds.) Business models and cognition (pp. 187– 202) (New Horizons in Managerial and Organizational Cognition, Vol. 4). Emerald Publishing Limited. Bogers, M., Sund, K. J., & Villarroel, J. A. (2015). The organizational dimension of business model exploration: Evidence from the European postal industry. In. N. J. Foss, & T. Saebi (Eds.), Business model innovation: The organizational dimension. Oxford University Press. Bowman, C., & Ambrosini, V. (2000). Value creation versus value capture: Towards a coherent definition of value in strategy. British Journal of Management, 11(1), 1–15. Camerer, C., & Lovallo, D. (1999). Overconfidence and excess entry: An experimental approach. American Economic Review, 89 (1), 306–318. Choi, J. N., Sung, S. Y., Lee, K., & Cho, D. S. (2011). Balancing cognition and emotion: Innovation implementation as a function of cognitive appraisal and emotional reactions toward innovation. Journal of Organizational Behavior, 32(1), 107–124. Chong, D., & Druckman, J. N. (2007). Framing Theory. Annual Review of Political Science, 10, 103–126. Daft, R. L., & Weick, K. E. (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9 (2), 284–295. Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2– 3), 370–382. Egfjord, K. F.-H., & Sund, K. J. (2020). Do you see what I see? How differing perceptions of the environment can hinder radical business model innovation. Technological Forecasting and Social Change, 150 (1) 119787. Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: How far have we come, and where should we go? Journal of Management, 43(1), 200–227. Foss, N. J., & Saebi, T. (2018). Business models and business model innovation: Between wicked and paradigmatic problems. Long Range Planning, 51(1), 9–21. Galavan, R. J., Sund, K. J., & Hodgkinson, G.P. (Eds.). (2018). Methodological challenges and advances in managerial and organizational cognition. Emerald Publishing Limited Gassmann, O., Frankenberger, K., & Csik, M. (2014). The business model navigator: 55 models that will revolutionise your business. Pearson UK.

20

K. J. Sund

Giacomin, O., Janssen, F., & Shinnar, R. S. (2016). Student entrepreneurial optimism and overconfidence across cultures. International Small Business Journal, 34 (7), 925–947. Guérard, S., Bode, C., & Gustafsson, R. (2013). Turning point mechanisms in a dualistic process model of institutional emergence: The case of the diesel particulate filter in Germany. Organization Studies, 34 (5–6), 781–822. Gurses, K., & Ozcan, P. (2015). Entrepreneurship in regulated markets: Framing contests and collective action to introduce pay TV in the US. Academy of Management Journal, 58(6), 1709–1739. Gustafsson, R., Sund, K. J., & Galavan, R. J. (2023). What are cognitive aids in strategy? In K. J. Sund, R. J. Galavan, & R. Gustafsson (Eds.), Cognitive Aids in strategy. Emerald Group Publishing. Hansson, P., Juslin, P., & Winman, A. (2008). The role of short-term memory capacity and task experience for overconfidence in judgment under uncertainty. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34 (5), 1027. Hodgkinson, G. P., & Healey, M. P. (2011). Psychological foundations of dynamic capabilities: Reflexion and reflection in strategic management. Strategic Management Journal, 32, 1500–1516. Hodgkinson, G. P., Sund, K. J., & Galavan, R. J. (2018). Exploring methods in managerial and organizational cognition: advances, controversies, and contributions. In R. J. Galavan, K. J. Sund, & G. P. Hodgkinson (Eds.), Methodological challenges and advances in managerial and organizational cognition (pp. 1–22). Emerald Publishing Limited. Hoever, I. J., Zhou, J., & van Knippenberg, D. (2018). Different strokes for different teams: The contingent effects of positive and negative feedback on the creativity of informationally homogeneous and diverse teams. Academy of Management Journal, 61(6), 2159–2181. Honig, B. (2004). Entrepreneurship education: Toward a model of contingency-based business planning. Academy of Management Learning & Education, 3(3), 258–273. Huff, A. S., Milliken, F. J., Hodgkinson, G. P., Galavan, R. J., & Sund, K. J. (2016). A conversation on uncertainty in managerial and organizational cognition. In Uncertainty and strategic decision making (pp. 1–31). Emerald Group Publishing Limited. Huy, Q. N., Corley, K. G., & Kraatz, M. S. (2014). From support to mutiny: Shifting legitimacy judgments and emotional reactions impacting the implementation of radical change. Academy of Management Journal, 57 (6), 1650–1680.

1 The Promise of the Cognitive View of Business …

21

Jarzabkowski, P., & Kaplan, S. (2015). Strategy tools-in-use: A framework for understanding “technologies of rationality” in practice. Strategic Management Journal, 36 (4), 537–558. Jensen, H., & Sund, K. J. (2017). The journey of business model innovation in media agencies: Towards a three-stage process model. Journal of Media Business Studies, 14 (4), 282–298. Kahneman, D. (2011). Thinking, fast and slow. Farrar Straus and Giroux. Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press. Kaplan, S. (2008). Framing contests: Strategy making under uncertainty. Organization Science, 19 (5), 729–752. Klayman, J., Soll, J. B., Gonzalez-Vallejo, C., & Barlas, S. (1999). Overconfidence: It depends on how, what, and whom you ask. Organizational Behavior and Human Decision Processes, 79 (3), 216–247. Kraft, P. S., Günther, C., Kammerlander, N. H., & Lampe, J. (2022). Overconfidence and entrepreneurship: A meta-analysis of different types of overconfidence in the entrepreneurial process. Journal of Business Venturing, 37 (4), 106207. Laureiro-Martínez, D., & Brusoni, S. (2018). Cognitive flexibility and adaptive decision-making: Evidence from a laboratory study of expert decision makers. Strategic Management Journal, 39 (4), 1031–1058. Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin, 131(6), 803. Malmendier, U., & Tate, G. (2005). CEO overconfidence and corporate investment. The Journal of Finance, 60 (6), 2661–2700. Markovitch, D. G., Steckel, J. H., Michaut, A., Philip, D., & Tracy, W. M. (2015). Behavioral reasons for new product failure: Does overconfidence induce overforecasts? Journal of Product Innovation Management, 32(5), 825–841. Martins, L. L., Rindova, V. P., & Greenbaum, B. E. (2015). Unlocking the hidden value of concepts: A cognitive approach to business model innovation. Strategic Entrepreneurship Journal, 9 (1), 99–117. Massa, L., & Hacklin, F. (2020). Business model innovation in incumbent firms: Cognition and visual representation. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. Academy of Management Annals, 11(1), 73–104.

22

K. J. Sund

Moellers, T., von der Burg, L., Bansemir, B., Pretzl, M., & Gassmann, O. (2019). System dynamics for corporate business model innovation. Electronic Markets, 29, 387–406. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Wiley. Pazzaglia, F., Farrell, M., Sonpar, K., & Martin de Holan, P. (2018). Keeping up with the Joneses: Industry rivalry, commitment to frames and sensemaking failures. Human Relations, 71(3), 427–455. Purdy, J., Ansari, S., & Gray, B. (2019). Are logics enough? Framing as an alternative tool for understanding institutional meaning making. Journal of Management Inquiry, 28(4), 409–419. Rau, S. B. (2013). Emotions preventing survival of family firms: comments on exploring the emotional nexus in cogent family business archetypes: Towards a predominant business model inclusive of the emotional dimension. Entrepreneurship Research Journal, 3(3), 425–432. Reyes, T., Vassolo, R. S., Kausel, E. E., Torres, D. P., & Zhang, S. (2022). Does overconfidence pay off when things go well? CEO overconfidence, firm performance, and the business cycle. Strategic Organization, 20 (3), 510– 540. Saebi, T., & Foss, N. J. (2015). Business models for open innovation: Matching heterogeneous open innovation strategies with business model dimensions. European Management Journal, 33(3), 201–213. Schneckenberg, D., Velamuri, V., & Comberg, C. (2019). The design logic of new business models: Unveiling cognitive foundations of managerial reasoning. European Management Review, 16 (2), 427–447. Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future research agenda. International Journal of Innovation Management, 17 (1), 1–34. Sharma, S., & Lenka, U. (2022). On the shoulders of giants: Uncovering key themes of organizational unlearning research in mainstream management journals. Review of Managerial Science, 16 (6), 1599–1695. Snihur, Y. (2018). Responding to business model innovation: Organizational unlearning and firm failure. The Learning Organization, 25 (3), 190–198. Snow, D. A., & Benford, R. D. (1992). Master frames and cycles of protest. In A. D. Morris & C. M. Mueller (Eds.), Frontiers in Social Movement Theory (pp. 133–155). Yale University Press. Snihur, Y., & Wiklund, J. (2019). Searching for innovation: Product, process, and business model innovations and search behavior in established firms. Long Range Planning, 52(3), 305–325.

1 The Promise of the Cognitive View of Business …

23

Sosna, M., Trevinyo-Rodríguez, R. N., & Velamuri, S. R. (2010). Business model innovation through trial-and-error learning: The Naturhouse case. Long Range Planning, 43(2–3), 383–407. Starbuck, W. H. (2017). Organizational learning and unlearning. Learning Organization, 24 (1), 30–38. Sund, K. J. (2013). Scanning, perceived uncertainty, and the interpretation of trends: A study of hotel directors’ interpretation of demographic change. International Journal of Hospitality Management, 33, 294–303. Sund, K. J. (2015). Revisiting organizational interpretation and three types of uncertainty. International Journal of Organizational Analysis, 23(4), 588– 605. Sund, K. J. (2016). A test of perceptual accuracy and overconfidence in a strategic issue context. In K. J. Sund, R. Galavan, & A. Huff (Eds.), Uncertainty and strategic decision making (pp. 101–126). Emerald Group Publishing. Sund, K. J. (2020). From cooperation to competition: Changing dominant logics and legitimization in liberalizing industries. In J. D. Rendtorff (Ed.), Handbook of business legitimacy. Springer. Sund, K. J. (2023). Definition and Measurement of Sustainability and CSR: Circumstances of Perceptual Misalignments. Measuring Sustainability and CSR: From Reporting to Decision-Making (pp. 21–26). Springer International Publishing. Sund, K. J., & Anson, J. (2021). The decline of mail: Postal industry decisionmakers’ interpretations in the aftermath of the financial crisis. Entreprises Et Histoire, 105 (4), 65–77. Sund, K. J., Bogers, M., Villarroel, J. A., & Foss, N. (2016a). Managing tensions between new and existing business models. MIT Sloan Management Review, 57 (4), 8. Sund, K. J., Bogers, M. L., & Sahramaa, M. (2021). Managing business model exploration in incumbent firms: A case study of innovation labs in European banks. Journal of Business Research, 128, 11–19. Sund, K. J., Galavan, R. J., & Bogers, M. (Eds.). (2020a). Business Models and Cognition. Emerald Publishing Limited. Sund, K. J., Galavan, R. J., & Bogers, M. (2020b). Exploring the connections between business models and cognition: A commentary. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Publishing Limited. Sund, K., Galavan, R. J., & Brusoni, S. (Eds.). (2018). Cognition and Innovation. Emerald Group Publishing.

24

K. J. Sund

Sund, K. J., Galavan, R. J., & Huff, A. S. (Eds.). (2016b). Uncertainty and Strategic Decision Making. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Huff, A. (2022). Uncertainty in strategy research. In M. A. Griffin, & G. Grote (Eds.), The Oxford handbook of uncertainty management in work organizations (pp. C3.S1–C3.S7). Oxford University Press. Sund, K. J., & Lindskov, A. (2022). Incumbent business model innovation under misperceived hypercompetition. Journal of Business Models, 10 (1), 11– 18. Tatomir, M., Dreyer, J. K., Sund, K. J., & Yu, J. (2023). WARM-GLOW investing and the greenwashing hypothesis. Journal of Cleaner Production, 419, 138229. Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194. Vuori, T. O., & Huy, Q. N. (2016). Distributed attention and shared emotions in the innovation process: How Nokia lost the smartphone battle. Administrative Science Quarterly, 61(1), 9–51. Walsh, J. P. (1995). Managerial and organizational cognition: Notes from a trip down memory lane. Organization Science, 6 (3), 280–321. Wiklund, J., Yu, W., & Patzelt, H. (2018). Impulsivity and entrepreneurial action. Academy of Management Perspectives, 32(3), 379–403. Zott, C., & Amit, R. (2010). Business model design: An activity system perspective. Long Range Planning, 43(2–3), 216–226. Zott, C., & Amit, R. (2008). The fit between product market strategy and business model: Implications for firm performance. Strategic Management Journal, 29 (1), 1–26.

2 Business Models as Managerial Mental Models

Abstract The business model can be viewed as a cognitive construct. This construct exists in the minds of managers, employees, and other actors involved with the organization. One challenge for those studying business models as cognitive constructs, is that scholars have thought up multiple competing theories (and associated terminologies) of what these structures are, how they develop, and how they are shared between individuals. Another is the multiple methods suggested for identifying and describing such structures. In this chapter I introduce some of these various theories and illustrate how these have been used in business model research. I discuss what mental business models are, how they emerge, and what they contain. I also provide some examples of methods that have been used for mapping such models, and finally, provide clues as to opportunities for further research. Keywords Business models · Cognition · Mental models · Schema · Sensemaking · Epistemology · Measurement

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9_2

25

26

K. J. Sund

What Are Mental Models (of the Business Model)? One way to define the business model is to view it as a type of cognitive model at the level of the individual manager, employee, or wider stakeholder (Sund et al., 2020a). A particular challenge for scholars working with this view, or definition, of business models is that cognition scholars have in the past thought up multiple competing theories (and labels) of what such cognitive models are, how they develop over time, how they are shared, and how they can be detected. In this chapter I introduce the reader to some of the various theories of individual managerial cognition that have so far been referred to in the context of business model research and argue that these theories can best be viewed as complementary, answering different research questions, and lending themselves to different research methodologies. But let’s first illustrate the confusion that might exist by considering just a few of these seemingly competing theories. According to personal construct theory, personal cognitive constructs are the dimensions along which an individual makes sense of their world (Kelly, 1955; Wright, 2004). Methodologically, these can be mapped into a so-called repertory grid (Wright, 2008), giving us an idea of how the individual rates different elements or subjects along these dimensions. This provides us with some sort of model of how the individual thinks— a kind of mental model. Mental models are in more general terms considered models that are learned of how the world works, and that help managers solve problems (Kieras & Bovair, 1984), and make inferences, such as if–then predictions (Johnson-Laird, 2001). Thus, mental models connect cognitive constructs into a complete picture, that individuals can use to describe, explain, and predict a particular system (Rouse & Morris, 1986). These mental models have, perhaps confusingly, by some been termed cognitive or mental maps (rather than models). Mental maps have in turn been discussed both in terms of containing submaps of cause-effect relationships, and specific categories (Fiol & Huff, 1992). Schema theory represents a similar approach, suggesting that knowledge structures take the form of schemas (or schemata), that are gradually learned, and are composed of components and their links, which grow

2 Business Models as Managerial Mental Models

27

stronger over time, as the individual gains experience within a domain of knowledge (Fiske & Dyer, 1985; Lurigio & Carroll, 1985). Framing theory in turn considers that an issue can actually be viewed from a variety of perspectives, that are referred to as frames. These frames guide sensemaking and interpretation, and framing activities lead frames to be shared with others, particularly during periods of high environmental change and uncertainty (Sund & Anson, 2021). According to Weick’s (1979, 1995) sensemaking theory, the individual makes retrospective sense of the world, meaning that they act in this world, observe the consequences of this action, and then try to make sense of what they see, by connecting and labeling their lived experience into cognitive cause maps. Individuals “make sense of things by seeing a world on which they already imposed what they believe. People discover their own inventions, which is why sensemaking understood as invention, and interpretation understood as discovery, can be complementary ideas” (Weick, 1995, p. 15). Already, the reader will sense the potential confusion brought about by the variety of labels (schemas, frames, mental models, mental maps, cognitive maps, cause maps…) apparently describing the same or very similar things. Walsh (1995), in his review of these various theories that could collectively be considered information processing theories, attempted to bring some order to this labeling. He suggested the overarching label of “knowledge structure”. However, scholars have since then continued to treat the various labels and theories as distinct, rather than try to unify these. Having stated this, as Bingham and Kahl (2013, p. 15) note: The schema concept is related to a variety of cognitive concepts, including frames, industry recipes, categories, knowledge structures, dominant logics, and interpretive schemes. Importantly, many of these concepts also share definitional underpinnings with the schema concept. For example, several scholars use the term “frame” (Benford & Snow, 2000; Kaplan, 2008; Kaplan & Tripsas, 2008), which relies on and explicitly references Goffman’s original conceptualization of frames as “schemata of interpretation” (1974: 21). Other organizational scholars focus on interpretive schemes, which are defined as “cognitive schemata that map experience of the world” (Bartunek, 1984: 355), or on “knowledge structures,” a term used interchangeably with schema (Walsh, 1995: 285).

28

K. J. Sund

In this chapter, as indeed in the entire work, I will refer to specific theories and associated labels of knowledge structure when citing specific works, even when a unifying label (such as schema) could perhaps be used instead. This is in order to be consistent with the labels used by the various authors whose work I cite. When not citing specific work, I will refer to mental business models or mental maps as generic overarching terms. Since the review of Walsh (1995), work within this area has moved far beyond the information processing view of cognition. Dual process theory suggests that cognition may be both conscious and unconscious (Kahneman, 2011), and work on affect suggests that it can be subject to emotions (Hodgkinson & Healey, 2011; Hodgkinson et al., 2018). Thus, the way a mental map of the business model is evoked by an individual in decision-making, will depend very much on the circumstance, which also dictates what the individual pays attention to (Ocasio, 1997). The mental map could be used in a slow, deliberate, and rational way, or in a rapid, intuitive, and heuristic way, or even in a way laden with emotions. As I hope to have demonstrated, the field of managerial cognition has not developed a single theory of how managers make sense of the world, but multiple theories, each with their own labels for what a mental model is, and this does create confusion. The objective of this chapter is to some extent to disentangle these theories, focusing on what the mental business model is, and how to approach it in research.

Epistemological Assumptions As part and parcel of examining how various cognitive construct theories can and have been used in the business model literature, it may be useful to consider briefly the underlying epistemological assumptions of such theories. Some consider the business model a description (e.g., Baden-Fuller & Morgan, 2010), some an activity system (e.g., Zott & Amit, 2010), some a template (e.g., Zott & Amit, 2008), and some a framework (e.g., Schneider & Spieth, 2013), that describes how value is created, distributed, and appropriated by the organization (Teece, 2010).

2 Business Models as Managerial Mental Models

29

Massa et al., (2017, p. 76) argue that three different perspectives on business models have thus emerged that treat “(1) business models as attributes of real firms having a direct real impact on business operations, (2) business models as cognitive/linguistic schema, and (3) business models as formal conceptual representations/descriptions of how an organization functions”. They go on to state that “Arguably, these are conceptually distinct interpretations of the role of the business model, which point to different phenomena: (1) how firms do business, (2) how the way firms do business is interpreted by organizational members, and (3) how (1) and (2) could be represented by means of formal conceptualizations, such as symbolic, mathematical, or graphical depictions, respectively”. A typology of perspectives on business model innovation is provided by Martins et al., (2015, pp. 101–103) who draw a parallel to perspectives within strategy research. They argue that there is firstly a rational positioning perspective, that “treats business models as purposefully designed systems that reflect rational managerial choices and their operating implications” and changes to these business models as a “result of exogenous shocks that shift the objective interdependencies among firms and therefore require managers to make new design choices that optimize the business model to the new conditions”. Then there is an evolutionary perspective suggesting that “change in business models is generated by external uncertainty, requiring managers to engage in experimentation until they find a system of activities that allows them to compete effectively within their external conditions.” Finally, they define the cognitive perspective of business models as “consistent with the cognitive perspective within strategy research that focuses on managers’ mental representations, emphasizing that each decision maker develops a somewhat unique view of reality”. Scholars who view the business model as an objective attribute of the firm, either implicitly or explicitly approach their study of business models from a positivist and objectivist epistemological stance. The object of study is the de facto business model, or activity system, as established by the particular descriptive method used by the scholar. More often than not, the epistemological stance is implicit, in that it is not clearly formulated. What distinguishes the cognitive view of business models is that in this view, the object of study is the perceived business model, and this is then studied from an interpretivist and subjectivist

30

K. J. Sund

epistemological standpoint. This epistemological stance is unsurprisingly usually made quite explicit in studies using the cognitive view. The study of business models in the cognitive view is concerned with the question of “how the way firms do business is interpreted by organizational members”, to cite again Massa et al. (2017), but I would add to this that other stakeholders too may interpret the business model of a firm, including investors, strategic partners, suppliers, competitors, regulators, and in fact even the wider public (Sund et al., 2020b).

One Organization but Multiple Mental Business Models It is unlikely that all individuals in an organization will hold identical mental models of the business model in their mind. An interesting observation from the managerial and organizational cognition (MOC) literature is that the complexity of mental maps within a domain is linked to job experience and to the scope of a manager’s job, such that a higherlevel manager can be expected to have broader and deeper knowledge (Hodgkinson & Johnson, 1994). We can hypothesize this to be the case concerning a business model as well. In other words, we can expect that a top manager will have a different, and perhaps more complex cognitive representation of the business model, than say a middle manager, or a regular employee. In fact, some employees within larger organizations may not have much knowledge of the business model of the organization at all. Or at least, they will not have framed this knowledge in terms of a business model. This said, they may have deep knowledge of a particular element of the business model, but again without framing this knowledge. Ten years ago, a graduate student and I examined strategy change and communication in a now defunct major retail chain (Sund & Nielsen, 2014).1 Top management wanted to implement a new strategy and devised some initiatives to communicate the new strategy internally. This included communicating on the firm’s intranet and organizing strategy 1

Our work was presented at a conference, but the results were never published.

2 Business Models as Managerial Mental Models

31

days for middle managers. Middle managers were in turn tasked with ensuring that the new strategy trickled down to all employees. What we found was that many employees did not understand and respond to the new strategy. When we investigated why, we discovered something that should perhaps have been obvious to us, but that we only spotted once we had completed detailed interviews with staff across the company. Retail staff in the almost 300 stores did not have the mental models with which to make sense of what management wanted. In fact, the employees we talked to did not even know what a strategy is. They had no prior understanding of the concepts that were being used in the new strategy and could not relate these to their daily activities of stacking shelves and manning the till. For them, words like strategy, KPI , capabilities, differentiation, were all meaningless. Once again it is useful to consider the definition that the business model serves as a form of mental model, logic, or recipe, of how a business creates and appropriates value. Value is created through its activity system. Thus, both value and activities are at the heart of the mental model of the business model. Furthermore, not just the content, but the deeper causal structure of value creation and capture activities are important to the study of mental business models (Furnari, 2015). If we accept that notions of value and activities are at the heart of the business model, we can also surmise that as different employees across a same organization are engaged in different daily activities, their perceptions of what the key activities in the business model are, are likely to be different. We can take this a step further and hypothesize that the mental business model of a given employee emerges out of the daily activities in which this employee engages. The social environment in which the individual acts also plays a role. Thus, if the individual is surrounded daily by other employees performing the same or very similar activities, this will reinforce the mental model. This is compatible with our observation in Egfjord and Sund (2020a) that being exposed to different information environments will lead to noticing different things, in the context of business model innovation. As an employee gains in job experience, and especially if they change role within the organization, their mental model may evolve into something more complex, as they encounter a broader set of activities (and information flows) and gain a better

32

K. J. Sund

appreciation of how different activities within the organization relate to value creation. Similarly, taking on management responsibilities may expose an employee to both new activities and new information. The notion of “business model” is also something managers are more likely to encounter than lower-level employees, just as they are more likely to encounter other concepts of strategy-making.

Are Mental Business Models Accurate? Imagine, as in Fig. 2.1, that we could represent an individual’s complete knowledge as a collection of discrete elements of knowledge. This is represented by the dots in rectangle A. Some of this knowledge would be directly related to the work organization and the conduct of business in that organization, represented by rectangle B. Note that the line between what is related or not is blurry. After all, the same mind is at play in all facets of life. We take with us our knowledge of our surrounding environment and of how to navigate that environment, in all moments of our lives. If the business model concerns more specifically how value is generated through key activities, we could view this individual’s mental map of the business model as a subsection of the whole, illustrated with the smaller rectangle C. Finally, if we were to attempt to map the business model in the way referred to by Massa et al., (2017, p. 76), and define “business models as attributes of real firms having a direct real impact on business operations”, i.e., if we attempt an objective description of how the firm in question operates as it creates value (using for example a business model canvas), we would find, as indicated in rectangle D in Fig. 2.1, discrepancies between the subjective and limited mental model of the individual and what we would define as the “objective” business model, which itself is in fact subjective, since the definition of objective business model would vary from tool to tool (hence again a blurry line). Several observations can be derived from Fig. 2.1. Firstly, as previously noted, the line of demarcation between elements of knowledge of the individual that do and do not pertain directly to organizational life is blurry. Thus, mental maps concerned with the organization may well include elements of knowledge that an outside observer might consider

2 Business Models as Managerial Mental Models

33

Fig. 2.1 A stylized representation of knowledge related to the business model

to lie outside the sphere of organizational life, and that may thus not be shared with other individuals working for the same organization. In Egfjord and Sund (2020a) we show that in the context of business model innovation, some types of job roles are boundary spanning, and may lead to the job holder noticing information (and to interpretations of that information) not noticed by other members of the organization. Secondly, the organizational knowledge of any particular organizational member is going to be incomplete (and linked to their particular job, as previously discussed), as seen by the fact that there are elements outside of A and B (but inside D) not known to the individual. Thirdly, the mental map of the business model of an individual (rectangle C) may be incomplete, at least as assessed by an outside observer who would include elements contained in D that are not present in C. Fourthly, that mental map of the business model of an individual may contain elements we would not normally associate with the business model (those contained

34

K. J. Sund

in C, but not D). For example, a member may wrongly perceive a particular activity to be a key value-generating one. In fact, not only the value associated with a given activity, but also how that activity takes place, who is involved, how that activity fits into the activity system, or even whether the activity takes place at all, could be misperceived. There is in fact ample evidence for widespread managerial misperception in the wider MOC literature (Mezias & Starbuck, 2003; Sund, 2016). Finally, what an outside observer would consider to be an objectively complete and accurate mental map (rectangle D), could include both elements contained in the knowledge of the individual (and perceived by the individual to be related to the business model or not), and elements not contained therein. How could managers promote a more rapid and complex development of mental business models? Two obvious ways immediately come to mind (among many). The first is job rotation. Job rotation is a practice that is used by many organizations as part of career development. An interesting research question is whether job rotation, and associated processes of socialization (Ostroff & Kozlowski, 1992), will lead to a more complex individual mental business model, and to a more rapid and efficient sharing of the model. If employees are deliberately introduced to, and gain experience with, a wider set of activities across the organization, more complex mental models should result. Furthermore, ongoing socialization and job rotation would presumably over time act as an integration mechanism, reducing cognitive differentiation to create convergence in mental business models. A second way for managers to promote the more rapid and complex development of a shared mental business model, is with cognitive aids (Sund et al., 2023). Strategy research and practice is full of frameworks, models, tools, and processes, meant to describe, and guide the strategy work of managers. These are all examples of cognitive aids (Gustafsson et al., 2023). Such aids guide and support cognition. They do this by creating a common set of abstract constructs, and a common language with which to handle these constructs. Cognitive aids support actors make rational decisions under conditions of limited powers of human cognition (Cabantous & Gond, 2011), focus attention on what data and issues are relevant (Egfjord & Sund, 2020a, 2020b; Sund, 2013),

2 Business Models as Managerial Mental Models

35

reduce complexity and uncertainty (Jarzabkowski & Kaplan, 2015; Sund et al., 2016, 2022), encourage new ways of thinking (Wright, 2023), and identify innovation opportunities (Sund et al., 2018, 2020b). The business model canvas (Osterwalder & Pigneur, 2010), the value proposition canvas (Osterwalder et al., 2015), and activity mapping (Armistead & Clark, 1993; Massa & Hacklin, 2020), are all examples of tools (cognitive aids) that are used deliberately for business modelling. When used in the context of workshops, team events, business meetings, and so forth, one might hypothesize that shared mental business models can be shaped and strengthened. In terms of Fig. 2.1, cognitive aids may serve to align C and D, and align these between individuals as well. An interesting set of propositions have been put forward by Shepherd et al., (2023, p. 101) in a recent paper. They suggest that the business model schema2 is shrouded in more uncertainty and is more prone to adaptations in the context of new entrepreneurial ventures. They define “coherence” as “the extent to which a particular knowledge structure accounts for more evidence, is simpler, and is superior ” and in turn define “business-model coherence as the extent to which the entrepreneurial manager’s (or entrepreneurial managers’ shared) cognitive structures, that organize managerial understanding, parsimoniously represent the value creation and value capture factors and mechanisms that account for evidence of an opportunity (such as evidence of markets, technologies, stakeholders’ beliefs, and so on).” They go on to suggest that if new information reveals that the business model lacks coherence, a manager is likely to try to adapt the business model to increase its coherence. They further suggest that experiences with physical aspects of boundary objects can reveal a lack of coherence, and thus trigger changes to the business model, and to the business model schema. This idea of the role of boundary objects can in my view be extended to what I previously referred to as cognitive aids in general. Cognitive aids serve to change the mental model of managers. Whether the exact theoretical mechanism of Shepherd et al. (2023) can be empirically verified, remains to be seen. 2

They employ the terminology of schema in their paper, although the wider term of mental map could perhaps apply to their theorizing.

36

K. J. Sund

How Can We Study the Mental Business Model? An extensive review of methods for measuring and mapping cognition is not my objective, and these can be found instead in edited works such as Huff ’s (1990) Mapping Strategic Thought, Huff and Jenkin’s (2002) Mapping Strategic Knowledge, and Sund, Galavan, and Hodgkinson’s (2018) Methodological Challenges and Advances in Managerial and Organizational Cognition. Instead, I will define in general terms what such mapping aims to achieve and will illustrate how this has been attempted in the business model literature. Mapping the business model is not vey different than working with other mental maps, except that the map relates specifically to value generation and related activities. Mapping within the business model literature has not only been concerned with mapping the business model itself, but with mapping the many perceptions and interpretations surrounding business modelling processes. One could argue that mental maps are always context specific. Maps relate to a particular phenomenon, in a particular context, and may not be generalizable to other contexts. Furthermore, they are in the mind of the individual, and may not be generalizable to other individuals. When researchers attempt to engage with mapping techniques, they create an observable representation of an underlying and unobservable reality. One unique aspect of mental mapping in management and strategy work, is that these relate not just to distances and relationships between constructs, but also to time (Weick, 1992). This is because such maps often recount causality (if this happens now, then that will happen next). What is shown in mental maps could also be considered variations. Sometimes these variations are treated as categories, sometimes as measurements on a spectrum. A simple map could be illustrated as a set of constructs, whether these are related, and whether cause-effect relationships exist (typically illustrated by an arrow). An example is found in Fig. 2.2. In practice, two approaches could be taken to establish such a map. The first is an inductive approach in which the researcher for example lets the individual studied talk and uses the data to code key constructs and how these link to each other. Another could be a more

2 Business Models as Managerial Mental Models

37

Fig. 2.2 A simple visual representation of a mental map

deductive approach, in which the researcher uses a framework such as the business model canvas to either guide the coding of what the individual is saying, or to guide actual interview questions. Huff (1990) specifies a typology with five types of mental maps, from simple to more complex. The first (1) is what she refers to as the map that assesses attention, association, and importance of concepts. Here the objective is to draw out what managers pay attention to, the content of thoughts about a topic, and the placement of concepts compared to related higher-level concepts. For example, the researcher might conduct word counts on raw data like interview transcripts, annual reports, or other texts. The objective is to look for words related to specific concepts, and by comparing the frequencies of specific words, and concepts, to other respondents, the relative importance can be assessed. For example, Frankenberger and Sauer (2019) studied four corporate spin-offs to find out what top management in these spin-offs paid attention to and how this linked to business model design. They conducted a series of interviews, extracting keywords that referred to attention targets based on frequency and salience. From this data they developed first-order concepts that aggregated into second-order themes, which then represented the attention targets. They thus identified seven attention targets, five of which were external and two of which were internal. The second type of map (2) is that which shows dimensions of categories or taxonomies. Numerous “generic” categories have been found in studies of management psychology, such as the “threat vs. opportunity” categorization, “positive vs. negative” categorization, and many others (e.g., Sund, 2015). Within the business model literature, an example of its use is found in Egfjord and Sund (2020a, 2020b). We argue that

38

K. J. Sund

differences in strategic issue identification and interpretation can help to explain the cognitive barriers found in studies of radical business model innovation in incumbent firms. Our method involved a Delphi approach to inductively uncover environmental trends perceived by managers, who were subsequently asked to rank these using Likert-type scales. The end result was a map illustrating perceptions of three groups of individuals, and where these perceptions overlapped. The map is reproduced in Fig. 2.3. The third type in Huff ’s (1990) typology (3) is the map showing influence, causality, and system dynamics. Here the objective is not just to uncover concepts or their importance, but how concepts are linked in cause and effect. As Huff points out, these are probably the most popular types of maps that organizational and strategy researchers like

Fig. 2.3 Sample map reproduced from Egfjord and Sund (2020b)

2 Business Models as Managerial Mental Models

39

to use, since they can be used to illustrate theory. An example can be found in Sund et al. (2021) study of business model innovation in incumbent firms, in which we seek to identify organizational barriers and their management. Based again on interview data, we searched for emerging themes, connecting these in a thematic map based on the coding, and including a simple analysis of directions of causality. This yielded a map similar in style to Fig. 2.2, but much greater in size, with five main themes connected through seventeen subthemes. An example of a more deductive method of mapping of this type is found in Jensen and Sund (2017), in which a process of business model innovation in media agencies is described by first interviewing managers with questions directly derived from the business model canvas, then coding the answers according to that same framework, and then according to stage in time. The result is a map in the form of a description of whether each of the nine components of the business model canvas played a primary, secondary, or neutral role in each of the three business model innovation stages identified (awareness stage, exploration stage, exploitation stage). Although we did not, we could have illustrated this with a heat map evolving over time. A fourth type of map (4) attempts to illustrate lines of reasoning or logic. Here the objective is to illustrate how a person makes sense of conclusions of actions. One could argue that this type of map is compatible with Weick’s (1995)sensemaking theory that individuals act and then make sense of their actions. The objective for the researcher with this type of map is thus to identify and document the logic behind a decision. An example are co-called cause (or causal) maps. Finally, the fifth type (5) is the map that specifies a schema or a frame. This is arguably the most difficult to achieve, and often results in a focus on language and words. In practice, a schema or frame is usually presented by the researcher in the form of either a descriptive table (e.g., Snihur, Thomas, & Burgelman, 2018; Sund & Anson, 2021), or a more complex map of the type found in Fig. 2.2, mapping causal relationships (e.g., Hodgkinson & Maule, 2002; Narayan et al., 2020).

40

K. J. Sund

Concluding Words on the Challenges of Measuring the Mental Business Model One difficulty of capturing mental business models is that the methods for doing so mostly deal with post hoc data collected outside of the “live” context of business modelling. In other words, the researcher may use data captured in an interview setting or by studying document text, that is actually an ex-post rationalization of the logic of the business model. What is captured may not be a very accurate representation of the mental map actually employed by the individual at the time of conducting their work. Furthermore, when using secondary sources such as annual reports, meeting minutes, company presentations, websites and other such sources, the data captured typically does not represent the mental model of a single individual. Instead, these are curated texts typically edited over time by any number of individuals, and presenting some stylized “ideal” of the business model. A similar issue can appear in an interview or survey setting, in which the individual may state what they believe to be the “correct” thing to state in the given interview context. They may hold back information or make up information, consciously, or unconsciously. They may also be influenced by the researcher, or context in which they find themselves. These are all classical problems of interviews, and they affect work on business models as well. A further problem is that unconscious implicit biases that affect decision-making may not be accurately captured (Sund et al., 2020b). Managerial and organizational cognition literature has over the past two decades seen interesting developments in two different directions, emphasizing the importance of (1) unconscious cognition and (2) emotions (Galavan et al., 2018). This means that while we may capture the conscious mental business model, how this model is actually used in decision-making may be subject to biases that we cannot account for. Furthermore, emotions may in some instances play a more important role than conscious rational cognition in business modelling (Rau, 2013). For example, Bez and Chesbrough (2020) discuss how the fear of looking foolish may limit managers’ inclination to share technology and engage in open innovation business modelling.

2 Business Models as Managerial Mental Models

41

Methodologically, there are a number of interesting newer advances, including those related to neuroscience, and those resulting from increased data processing capabilities, such as agent-based modeling (Hodgkinson et al., 2018). These are beyond the scope of this chapter, but it is worth noting that the field of managerial and organizational cognition is advancing rapidly, and new opportunities for the study of business models continue to arise out of these advances. Perhaps in a not too distant future we may see more research capturing not just conscious mental business models, but also the emotions and heuristics that are at play during their use.

References Armistead, C. G., & Clark, G. (1993). Resource activity mapping: The value chain in service operations strategy. The Service Industries Journal, 13(4), 221–239. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171. Bartunek, J. M. (1984). Changing interpretive schemes and organizational restructuring: The example of a religious order. Administrative Science Quarterly, 355–372. Benford, R. D., & Snow, D. A. (2000). Framing processes and social movements: An overview and assessment. In K. Cook & J. Hagan (Eds.), Annual review of sociology, 26 (pp. 611–639). Annual Reviews. Bez, S. M., & Chesbrough, H. (2020). Barriers in searching for alternative business models: An essay on the fear of looking foolish. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition (New Horizons in Managerial and Organizational Cognition, Vol. 4, pp. 187–202), Emerald Publishing Limited. Bingham, C. B., & Kahl, S. J. (2013). The process of schema emergence: Assimilation, deconstruction, unitization and the plurality of analogies. Academy of Management Journal, 56 (1), 14–34. Cabantous, L., & Gond, J. P. (2011). Rational decision making as performative praxis: Explaining rationality’s Éternel Retour. Organization Science, 22(3), 573–586.

42

K. J. Sund

Egfjord, K.F.-H., & Sund, K. J. (2020a). Do you see what I see? How differing perceptions of the environment can hinder radical business model innovation. Technological Forecasting and Social Change, 150 (1), 119787. Egfjord, K. F. H., & Sund, K. J. (2020b). A modified Delphi method to elicit and compare perceptions of industry trends. MethodsX, 7 , 101081. Fiol, C. M., & Huff, A. S. (1992). Maps for managers. Where are we? Where do we go from Here? Journal of Management Studies, 29, 267–285. Fiske, S. T., & Dyer, L. M. (1985). Structure and development of social schemata: Evidence from positive and negative transfer effects. Journal of Personality and Social Psychology, 48(4), 839. Frankenberger, K., & Sauer, R. (2019). Cognitive antecedents of business models: Exploring the link between attention and business model design over time. Long Range Planning, 52(3), 283–304. Furnari, S. (2015). A cognitive mapping approach to business models: representing causal structures and mechanisms. In C. Baden-Fuller & V. Mangematin (Eds.), Business models and modelling. Emerald Group Publishing. Galavan, R. J., Sund, K. J., & Hodgkinson, G. P. (eds.). (2018). Methodological challenges and advances in managerial and organizational cognition. Emerald Publishing Limited. Goffman, E. (1974). Frame analysis. Harvard University Press. Gustafsson, R., Sund, K. J., & Galavan, R. (2023). What are cognitive aids in strategy? In K. J. Sund, R. Galavan & R. Gustafsson (Eds.), Cognitive aids in strategy. Emerald Group Publishing. Hodgkinson, G. P., & Healey, M. P. (2011). Psychological foundations of dynamic capabilities: Reflexion and reflection in strategic management. Strategic Management Journal, 32, 1500–1516. Hodgkinson, G. P., & Johnson, G. (1994). Exploring the mental models of competitive strategists: The case for a processual approach. Journal of Management Studies, 31(4), 525–552. Hodgkinson, G. P., & Maule, A. J. (2002). The individual in the stategy process: Insights from behavioural decision research and cognitive mapping. In A. S. Huff & M. Jenkins (Eds.), Mapping strategic knowledge. Sage. Hodgkinson, G. P., Sund, K. J., & Galavan, R. J. (2018). Exploring methods in managerial and organizational cognition: Advances, controversies, and contributions. In Robert J. Galavan, Kristian J. Sund & Gerard P. Hodgkinson (Eds.), Methodological challenges and advances in managerial and organizational cognition. Emerald Publishing Limited, pp.1–22 Huff, A. S. (ed.). (1990). Mapping strategic thought. Wiley. Huff, A. S., & Jenkins, M. (Eds.) (2002). Mapping strategic knowledge. Sage.

2 Business Models as Managerial Mental Models

43

Jarzabkowski, P., & Kaplan, S. (2015). Strategy tools-in-use: A framework for understanding “technologies of rationality” in practice. Strategic Management Journal, 36 (4), 537–558. Jensen, H., & Sund, K. J. (2017). The journey of business model innovation in media agencies: Towards a three-stage process model. Journal of Media Business Studies, 14 (4), 282–298. Johnson-Laird, P. N. (2001). Mental models and deduction. Trends in Cognitive Sciences, 5 (10), 434–442. Kahneman, D. (2011). Thinking, fast and slow. Farrar Straus and Giroux. Kaplan, S. (2008). Framing contests: Strategy making der uncertainty. Organization Science, 19, 729–752. Kaplan, S., & Tripsas, M. (2008). Thinking about technology: Applying a cognitive lens to technical change. Research Policy, 37 , 790–805. Kelly, G. (1955). The psychology of personal constructs. Norton. Kieras, D. E., & Bovair, S. (1984). The role of a mental model in learning to operate a device. Cognitive Science, 8(3), 255–273. Lurigio, A. J., & Carroll, J. S. (1985). Probation officers’ schemata of offenders: Content, development, and impact on treatment decisions. Journal of Personality and Social Psychology, 48(5), 1112. Martins, L. L., Rindova, V. P., & Greenbaum, B. E. (2015). Unlocking the hidden value of concepts: A cognitive approach to business model innovation. Strategic Entrepreneurship Journal, 9 (1), 99–117. Massa, L., & Hacklin, F. (2020). Business model innovation in incumbent firms: Cognition and visual representation. In K. J. Sund, R. J. Galavan & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. Academy of Management Annals, 11(1), 73–104. Mezias, J. M., & Starbuck, W. H. (2003). Studying the accuracy of managers’ perceptions: A research odyssey. British Journal of Management, 14 (1), 3–17. Narayan, S., Sidhu, J. S., Baden-Fuller, C., & Volberda, H. W. (2020). Examining CEOs’ business model schemas: A cognitive mapping of differences between industry insiders and outsiders. In K. J. Sund, R. J. Galavan & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Ocasio, W. (1997). Towards an attention-based view of the firm. Strategic Management Journal, 18(S1), 187–206. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. John Wiley & Sons.

44

K. J. Sund

Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2015). Value proposition design: How to create products and services customers want. John Wiley & Sons. Ostroff, C., & Kozlowski, S. W. J. (1992). Organizational socialization as a learning process: The role of information acquisition. Personnel Psychology, 45, 849–874. Podoynitsyna, K., Snihur, Y., Thomas, L.D.W., & Grégoire, D. (2020). Creating meta-narratives: How analogies and metaphors support business model innovation. In K. J. Sund, R. J. Galavan & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Rau, S. B. (2013). Emotions preventing survival of family firms: Comments on exploring the emotional nexus in cogent family business archetypes: Towards a predominant business model inclusive of the emotional dimension. Entrepreneurship Research Journal, 3(3), 425–432. Rouse, W. B., & Morris, N. M. (1986). On looking into the black box: Prospects and limits in the search for mental models. Psychological Bulletin, 100 (3), 349–363. Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future research agenda. International Journal of Innovation Management, 17 (1), 1–34. Shepherd, D. A., Seyb, S. K., & George, G. (2023). Grounding business models: Cognition, boundary objects, and business model change. Academy of Management Review, 48(1), 100–122. Snihur, Y., Thomas, L. D. W., & Burgelman, R. A. (2018). The performative power of words: How business model innovators use framing for strategic advantage. In Kristian J. Sund, Robert J. Galavan & Stefano Brusoni (Eds)., Cognition and innovation. Emerald Publishing. Sund, K. J. (2013). Scanning, perceived uncertainty, and the interpretation of trends: A study of hotel directors’ interpretation of demographic change. International Journal of Hospitality Management, 33, 294–303. Sund, K. J. (2015). Revisiting organizational interpretation and three types of uncertainty. International Journal of Organizational Analysis, 23(4), 588– 660. Sund, K. J. (2016). A test of perceptual accuracy and overconfidence in a strategic issue context. In K. J. Sund, R. Galavan & A. Huff (Eds.), Uncertainty and strategic decision making (pp. 101–126). Emerald Group Publishing.

2 Business Models as Managerial Mental Models

45

Sund, K. J., & Anson, J. (2021). The decline of mail: Postal industry decisionmakers’ interpretations in the aftermath of the financial crisis. Entreprises Et Histoire, 105, 65–77. Sund, K. J., Bogers, M. L., & Sahramaa, M. (2021). Managing business model exploration in incumbent firms: A case study of innovation labs in European banks. Journal of Business Research, 128, 11–19. Sund, K. J., Galavan, R. J., & Bogers, M. (2020a). Business models and cognition. Emerald Publishing Limited. Sund, K. J., Galavan, R. J., & Bogers, M. (2020b). Exploring the connections between business models and cognition: A commentary. In K. J. Sund, R. J. Galavan, & M. Bogers. Business models and cognition. Emerald Publishing Limited. Sund, K., Galavan, R. J., & Brusoni, S. (Eds.). (2018). Cognition and innovation. Emerald Group Publishing. Sund, K. J., Galavan, R., & Gustafsson, R. (Eds.). (2023). Cognitive aids in strategy. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Huff, A. S. (Eds.). (2016). Uncertainty and strategic decision making. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Huff, A. (2022). Uncertainty in strategy research. In M. A. Griffin & G. Grote (Eds.), The Oxford handbook of uncertainty management in work organizations (p. C3.S1–C3.S7). Oxford University Press. Sund, K. J., & Nielsen, C. (2014). If it makes sense for me, it makes sense for you! Trickle-down organizational sensemaking. Paper presented at Dansk Ledelsesakademis årskonference 2014, Roskilde, Denmark. Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194. Walsh, J. P. (1995). Managerial and organizational cognition: Notes from a trip down memory lane. Organization Science, 6 , 280–321. Weick, K. E. (1979). The social psychology of organizing (2nd ed.). AddisonWesley. Weick, K. E. (1992). Cartographic methods in organizations. In A. S. Huff (Ed.), Mapping strategic thought. Wiley. Weick, K. E. (1995). Sensemaking in organizations. Sage. Wright, R. P. (2004). Mapping cognitions to better understand attitudinal and behavioral responses in appraisal research. Journal of Organizational Behavior, 25 (3), 339–374.

46

K. J. Sund

Wright, R. P. (2008). Eliciting cognitions of strategizing using advanced repertory grids in a world constructed and reconstructed. Organizational Research Methods, 11(4), 753–769. Wright, R. (2023). Opening up alternatives for managers stuck with complexity. In K. J. Sund, R. J. Galavan, & R. Gustafsson (Eds.). Cognitive aids in strategy. Emerald Group Publishing. Zott, C., & Amit, R. (2008). The fit between product market strategy and business model: Implications for firm performance. Strategic Management Journal, 29 (1), 1–26. Zott, C., & Amit, R. (2010). Business model design: An activity system perspective. Long Range Planning, 43(2–3), 216–226.

3 The Sharing of (Mental) Business Models

Abstract Cognition and emotions can be shared between individuals. Thus, the business model as a cognitive construct too can be shared. This construct exists in the minds of actors involved with the organization and is shaped, shared, and adapted over time. In this chapter I discuss how this sharing between individuals takes place. I reflect on some of the managerial and organizational cognition literature related to social cognition and explore how this literature has been used in studies on cognition and business models. I place particular emphasis on the means by which sharing takes place, including linguistic means such as framing, and the role of cognitive aids and boundary objects. Finally, I remain critical of the extent to which mental business models are really shared in practice, and the extent to which our methods accurately capture the shared elements of the mental business model. Keywords Business models · Cognition · Emotions · Shared cognition · Framing · Cognitive aids

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9_3

47

48

K. J. Sund

Introduction As discussed in the previous chapter, the business model can be considered a mental model (Baden-Fuller & Morgan, 2010; Furnari, 2015; Sund et al., 2020). In this chapter I will deal with this mental business model at the team and organizational cognition levels. Within the general mental model literature, it is often assumed that such models can indeed exist at the team level (Klimoski & Mohammed, 1994). It is also assumed that when such models are shared and aligned among team members, this will lead to superior performance (see e.g., the discussion of Mohamed et al., 2000). Similarly, the business model appears to regularly be treated in the business model literature as a shared mental model within the organization. Such a model would be the result of shared sensemaking processes (Daft & Weick, 1984; Sund, 2013, 2015; Weick, 1995). However, managers throughout the organization may not automatically fully share this mental business model. In Egfjord and Sund (2020) we report that members of the core business and the innovation team within an incumbent have different perceptions of environmental changes, due to exposures to different information environments. The mental business model of members of different teams within the incumbent are shaped by such differences in information and are thus not the same. Different mental models regarding the environment in turn lead to different views on what the business model is and should be (Bogers et al., 2015; Martins et al., 2015; Zott et al., 2011). Within the incumbent, it is mainly top management, as well as innovation teams within the organization, who actively work on business model designs and innovation, often employing standardized frameworks and visualization tools (Täuscher & Abdelkafi, 2017). They are therefore the natural informants for studies on (mental) business models. There is an interesting line of research developing on the exact role of cognitive aids, such as frameworks, visual tools, and innovation methods in shaping shared business model cognitions (Gustafsson et al., 2023; Massa & Hacklin, 2020). For example, Henike and Hölzle (2020) document that such frameworks have a significant effect on entrepreneurs’ cognition, stabilizing the entrepreneurs’ mental models. One could

3 The Sharing of (Mental) Business Models

49

hypothesize that formal business model frameworks and business model development methods help entrepreneurs test their own presumptions and hypotheses, providing useful tools for accelerating learning (Ladd, 2020). These findings in the entrepreneurial context may to some extent be transferable to the incumbent context as well. The mental business model can also be shared outside the firm, for example with key stakeholders (Aspara et al., 2013). Wallnöfer and Hacklin (2013) suggest that the business model serves as a narrative device when new ventures pitch to business angels, who use this pitched business model in their opportunity interpretation. Similarly, within one organization, Podoynitsyna et al. (2020) show how analogies and metaphors were used as narrative tools by Salesforce to construct a strong organizational identity. Storbacka and Nenonen (2011) suggest that market actors’ mental representations of the business model are shared even more widely across organizational boundaries within the marketplace and can be deliberately manipulated by individual actors. Kim and Kim (2023) document how industry-level recipes can influence firm-level business model innovation. Furthermore, Snihur et al. (2018) examine how framing can constitute a strategic process that enables business model innovators to shape new ecosystems. On the other hand, when there is incongruence with existing schemas, innovation originating outside the firm leads managers to search for information on opportunities or threats (Greve & Taylor, 2000). There is thus a twoway flow of information and framing activities across organizational boundaries regarding the business model. In this chapter, I will first define what is meant by shared cognition and a shared mental business model, and then explore some of the ways that sharing of this business model takes place. I will then somewhat critically discuss how we capture shared mental business models in the business model literature.

50

K. J. Sund

Shared Cognition and Mental Models Why study the mental business model at a group or team level at all? One simple answer is that management researchers have for long now recognized that important decisions in the organization are influenced by, and taken by, groups of people, usually working as a team, rather than by single individuals. For instance, this is the premise of research into top management teams and the associated upper echelons theory (e.g., Hambrick & Mason, 1984). A fundamental assumption behind the idea of the shared mental business model is that the information processing of the group is conceptually related to the information processing of the individual (Klimoski & Mohammed, 1994). In other words, it is assumed that we can use individual-level cognition theories to inform our study of cognition and decision-making at the team and even organizational level. Although I may use the term “organizational cognition” (just like many others do), I do not mean to imply that organizations “think”. Rather, the concept of cognition at the team and organizational level is a recognition of the facts that: (a) cognition in organizations is mostly a social phenomenon since we interact with others to construct organizational “reality” (Levine et al., 1993); (b) we acquire and process information in the organization within an organizational social structure; (c) cognition in organizations takes place in affective contexts created by the group (i.e., there is an emotional environment in which cognition takes place); and (d) unconscious assumptions, beliefs, and biases are at play at the team level (as evidenced by the burgeoning literature on organizational culture). The organizational cognition literature considers clearly that a shared mental model is more than just a metaphor, is in fact “real”, and can be measured by researchers. Klimoski and Mohammed’s (1994, pp. 425– 426) list of properties of shared mental models is useful for examining the nature of such models. They suggest that a shared mental model: (a) is a hypothetical construct that need not be identified as such by individuals affected but can be captured by the researcher. (b) is a characteristic of a group that is not simply the sum of individual mental models.

3 The Sharing of (Mental) Business Models

51

(c) reflects the categorizations and simplifications of individuals in a group. (d) reflects organized knowledge, such as concepts stored in the memory of individuals. (e) may not be strictly context-specific, but instead contain more general representations of situations, tasks, and relationships. (f ) reflects internalized beliefs, assumptions, and perceptions, that truly influence behavior. (g) operates in a way in which the individual is aware of its existence, i.e., is aware that others in the group share elements of thought with that individual. Figure 3.1 summarizes some of the reasons why shared mental business models may be sought by members of the organization, how these are created through interactions, and what some of the outcomes are (loosely inspired by Thompson & Fine, 1999, p. 296). It is a common assumption that shared mental models are positive for the organization, in that they act to enhance team performance in various ways (Cannon-Bowers & Salas, 2001). A shared mental business model could guide both collective sensemaking and collective sense-giving. A shared mental business model could for example allow different members of an organization to align their interpretations of information (Egfjord & Sund, 2020), such as interpreting whether a given environmental change should be seen as a threat or an opportunity to the existing business model (Sund, 2013, 2015). It also allows for collective perceived uncertainty reduction, and more rapid coordination and alignment of actions, without the need for communication. A shared mental business model could thus allow members to reach a consensus and make operational decisions without consulting each other. It could allow members to prioritize activities in a similar manner, again without having to consult each other. Or it could allow members to “sell” the business model to external stakeholders in a consistent manner. As Cannon-Bowers and Salas (2001, p. 196) point out, in general, “the concept of shared cognition can help us to explain what separates effective from ineffective teams by suggesting that in effective teams, members have similar or compatible knowledge, and that they use this knowledge to guide their (coordinated) behavior ”.

52

K. J. Sund

Fig. 3.1 The “whys” and “whats” of shared mental business models

The shared mental business model emerges as team members share in strategic decision-making, share information and interpretations regarding the external environment, engage in collective business model design activities, and in general engage in shared work practices. It may be worth noting at this point that business model experimentation may be a purely mental exercise, or may be a real experiment, made sense of later. In other words, a shared mental business model may emerge as a group of people engage in hypothetical business modelling (for example when using cognitive aids, something I discussed briefly in Chapter 1 and will return to later in this chapter), or as they retrospectively make sense of actual changes made to the (objective) business model. The literature on shared cognition in organizations in general considers that what is shared are things like task-related knowledge, knowledge of others (i.e., teammates), identity, and attitudes and beliefs. In the context of business model studies, several further elements have either been implicitly assumed, or explicitly examined, as being shared. This has included interpretations of the environment (e.g., Egfjord &

3 The Sharing of (Mental) Business Models

53

Sund, 2020; Massa & Hacklin, 2020), perceptions of key activities and resources (e.g., Sund et al., 2021), and value propositions (e.g., Narayan et al., 2020).

The Role of Framing As discussed in Chapter 1, any issue can be framed in multiple ways (Sund & Anson, 2021). As a reminder, Snow and Benford (1992, p. 37) consider a frame an “interpretative schema that simplifies and condenses ‘the world out there,’ thus organizing experience and guiding action by rendering events or occurrences meaningful ”. Frames are guides for sensemaking and interpretation, and critically, these are constructed through social interaction (Kaplan, 2008). Thus, it could make sense to employ framing theory when studying the development of shared mental business models. Framing theory has gained popularity in management literature, both as a way to study grand narratives (see e.g., the discussion of the emergence of Covid-19 narratives of Schwoon et al., 2022), but also as a way to explain the dynamics of competing logics within and between organizations, that may in fact continue over longer periods of time (Guérard et al., 2013; Kaplan, 2008; Pazzaglia et al., 2018; Sund & Anson, 2021). Whether or not they themselves entirely believe in the objective truth of a frame, some actors actively engage in framing activities, trying to share their frame of an issue, and hoping that other actors will adopt the frame as their own. In fact, frames amplify in scope by being actively shared and spread, being regularly invoked, or being coupled with emotions (Purdy et al., 2019). In the context of business models, entrepreneurs and incumbent firms alike have been shown to employ deliberate framing activities. For example, Gurses and Ozcan (2015) provide a rich description of how entrepreneurs in the pay TV market in the United States used framing activities to enter a market, and how incumbents similarly tried to defend their position through framing. Frames can end up being dominant at both the organizational and interorganizational level, as demonstrated by their study. They “document how institutional change is the outcome of a long-term process, which is fueled by

54

K. J. Sund

entrepreneurs acting collectively to convince private groups and institutional actors to cooperate while battling with resistors of change through framing contests” (p. 1733). In the incumbent setting, in Sund and Anson (2021) we discuss how actors in the postal industry adopted competing frames of the future when faced with digital substitution. The postal sector has faced many environmental changes over the past decades, including a full liberalization of the European postal space, waves of technological substitution, and even privatization (for discussions see e.g., Bogers et al., 2015; Jaag, 2014; Sund, 2020; Sund & Osborn, 2010; Sund et al., 2014). We document how at least three separate frames emerged by the early 2010s to describe the problems facing the sector, and the opportunities available to postal operators. According to the first frame (“paper has a future”), paper was viewed as a superior and more valuable means of communication than electronic communication. In the second frame (“diversify the trusted brand”), paper communication was viewed as largely something of the past, but the postal brand was seen as valuable, and allowing diversification opportunities (for examples of such opportunities, see e.g., Sund, 2011). In the third and final frame (“digitalize and differentiate with open innovation”) both paper and the postal brand were seen as having lost their value. Obviously, with the concept of value being at the heart of the business model, these three competing frames would lead to different opportunity assessments of possible future business models, and this can to some extent explain why postal operators indeed appear in subsequent years to have pursued quite diverse business opportunities (Sund & Anson, 2021). Eliciting and studying frames can thus help us examine and compare the perceptions of different managers in a context of business modelling due to environmental change (Egfjord & Sund, 2020; Sund & Anson, 2021). Beyond simply describing the historical actions of an organization in response to change, studying frames allows the researcher to analyze the logics that guide business model travel. Such travel can be a mechanism for mental business model sharing, and thus help us understand how the mental business model comes to be shared both inside the organization, and across organizational boundaries. In the context of the incumbent innovator, strategies find their roots in the competing

3 The Sharing of (Mental) Business Models

55

frames developed at different management levels and in different teams within the firm. Studying these frames can provide insights into why some business model changes were successfully adopted throughout the organization over time, and others abandoned.

The Role of Cognitive Aids A relatively minor strand of research has over the years examined the role of things like tools, arts, play, and frameworks in the collective shaping and sharing of cognition and mental maps. In a recently edited volume, we refer to these collectively as cognitive aids (Sund et al., 2023). We define a cognitive aid (in strategy): … in a broad sense as a physical or conceptual artefact purposefully used as a sensory input to influence a cognitive state or process in the context of strategy. Such aids include structured strategy simulations or games, visual tools used in strategy work such as conceptual models, drawings, images, or frameworks, and physical and sensory artefacts such as clay, Lego bricks, sound, smell, or physical presence, to guide and support the cognition of managers engaging in strategy work and strategic decisionmaking. Cognitive aids are often employed in a social context that is deliberately designed. Such a context could be a class, a meeting, or a workshop, and it could be interactive or not. Often one or more persons act as facilitators, thereby influencing the use of the aid, and how it is made sense of cognitively. (Gustafsson et al., 2023, p. 2)

As described in Gustafsson et al. (2023), cognitive aids support actors to make rational decisions under conditions of limited powers of human cognition (Cabantous & Gond, 2011), and focus their attention on what data and issues are relevant (Egfjord & Sund, 2020; Sund, 2013). They help reduce complexity and uncertainty (Jarzabkowski & Kaplan, 2015; Sund et al., 2016b, 2022), and identify innovation opportunities (Sund et al., 2018, 2020). I would thus clearly define a tool such as the business model canvas (Osterwalder & Pigneur, 2010) as a cognitive aid to business modelling. The authors themselves in fact refer to the canvas as both “a shared language for describing, visualizing, assessing, and changing

56

K. J. Sund

business models” (p. 12), and as “a concept that allows you to describe and think through the business model of your organization” (p. 15). Since the canvas is designed to allow the user to “think through the business model ” it indeed fits my definition of a cognitive aid to business modelling. Other examples of cognitive aids to business modelling could include the many models and frameworks directly dealing with business models, proposed by scholars and practitioners over the years (for an overview of visual aids, see e.g., Täuscher & Abdelkafi, 2017). However, there are also very many more general strategy and management tools that could be applied to business modelling (see e.g., Munir et al., 2022). Where there is a big research gap is in theorizing and empirically verifying how exactly such tools aid cognition. One possibility is that the cognitive aid introduces a heuristic to managers. Gigerenzer and Gaissmaier (2011, p. 454) define a heuristic as “a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods.” This is indeed what cognitive aids to business modelling appear to invite the user to do. They invite users to suspend consideration of information other than that which relates directly to value creation and appropriation, as well as surrounding concepts. For example, the business model canvas focusses attention on nine elements, or building blocks. Furthermore, a tool like the business model canvas introduces imagery to help visualize these business model elements. Used in a social setting, cognitive aids in general provide a context for teams to identify and argue contentious or critical issues (Jacobs & Heracleous, 2005). Cognitive aids can enable individuals to explain and simplify, focus attention, enhance perceptual processing and memorizing, attend to what others are saying, and be more receptive to learn (Dehaene, 2021; Gustafsson et al., 2023). Cognitive aids can thus play a key role in the shaping and sharing of mental business models—yet this is an area of research that remains underexplored.

3 The Sharing of (Mental) Business Models

57

Are We Really Capturing Shared Cognition? An interesting and somewhat critical1 question, is whether the studies purporting to capture business models as perceived at a team or organizational level are truly doing so. One potential pitfall is the source of data. A prime example of data that may not yield a valid representation of a shared mental model or map is archival data. This includes things like memos, meeting minutes, press releases, or annual reports. In the words of Johnson and Johnson (2002, p. 233), such data “may tell us a lot about what a company wants the outside world to think it is thinking, but little about what individual managers are actually thinking about issues that are likely to predict future actions of the company and individuals in it ”—or by extension little about what aspects of thinking are shared. However, data elicited directly from respondents too can be prone to weaknesses, including being influenced by respondents’ need for social desirability, i.e., giving the answers they think the interviewer wants to hear. Beyond data issues, there is the fundamental question of how we empirically define a shared mental business model. For example, do our methodologies sometimes add constructs together and refer to these as shared, even if some members of the organization do not hold all these constructs in their mind? And is this a problem? Consider a hypothetical research setting, and Figs. 3.2 and 3.3. We have three individuals (A, B, and C) representing an organization. Assume that we extract from each individual their personal mental representation (as a recipe, causal map, structured framework, or however else we decide to do it) of the organization’s business model. Assume furthermore, as is highly likely in this type of research, that each individual actually provides somewhat different data, indicating possible differences in their underlying mental map, and thus in their personal mental business model. This is illustrated in Figs. 3.2 and 3.3 with rectangles A, B, and C, each containing constructs (the dots) that have emerged from our data, and that may either be unique to that individual or may be shared with either one or two of the other individuals. What we see is that only two constructs are shared by all three individuals, contained in the central small rectangle 1

Indeed self-critical, as I am myself guilty of the sins to which I point in this section.

58

K. J. Sund

D in Fig. 3.2. The question is how we define “shared mental business model” and decide to treat the data. A first option could be to consider only constructs that are shared by all three individuals to be representative of the shared mental business model of this group of individuals. This is illustrated by rectangle D in Fig. 3.2. The advantage of this option is that we stay strictly true to a definition of the shared mental business model as containing only those elements which these individuals indeed have cognitively in common when they think of the business model. The problem is that the shared mental business model revealed in this way becomes quite data poor. When decisions are made by these individuals as a collective, based on the mental representations of the business model, they are likely to bring into play elements beyond rectangle D. Regardless of the approach taken to decision-making, individuals are likely to exchange information, interpretations, opinions, and even emotions, and thus rectangle D may be meaningless as an indicator, especially if what interests the researcher are decision processes surrounding business modelling.

Fig. 3.2 The shared mental business model is here defined by the area of overlap in the mental maps of individuals A, B, and C (illustrated by small rectangle D)

3 The Sharing of (Mental) Business Models

59

Fig. 3.3 The shared mental business model is here defined by the sum of the mental maps of individuals A, B, and C (illustrated by large rectangle D)

A second option would be to consider rectangle D in the other figure, Fig. 3.3, to be the shared mental business model, i.e., the sum of what all three individuals have revealed in the data collection. The assumption here would be that what informs, and guides team actions is not the knowledge held by one individual, or narrowly shared by everyone, but rather the total collective knowledge. We are then implicitly assuming that this collective knowledge comes into play during collective decision-making involving the business model (the contrary of the first option). Yet, this approach contradicts with the definition of Klimoski and Mohammed (1994, pp. 425–426) discussed earlier in this chapter. In particular, it contradicts their suggestion that a shared mental model is a characteristic of a group that is not simply the sum of individual mental models. In fact, the mental model literature would suggest that the shared mental business model would be something in between the two options above. A third option would therefore be for the researcher to use their judgment to decide what constitutes elements of the shared mental business model, despite the obvious problems with such an approach. For

60

K. J. Sund

example, the researcher may consider that any element shared by at least two of the individuals should be considered part of the collective shared mental business model. This means including all elements contained in the four different overlap rectangles in Figs. 3.2 and 3.3. What would be excluded would be elements held in the mental business model of only one individual. However, this is only one possible approach, and the researcher could use their own judgment to define a different approach. My point here is merely that no matter what approach is taken, it leaves room for doubt and criticism regarding validity. As already touched on in Chapters 1 and 2 of this book, Massa et al. (2017) point to the issue of construct validity of the business model construct, due to some of the literature being unclear about whether they treat the business model as “(1) attributes of real firms variously influencing their performance in markets, (2) cognitive schemas (and linguistic schemas as observable manifestations), and (3) formal (scaled-down) conceptual representations of organizational activities” (p. 88). What I point out here, is that even if we clearly define our epistemological approach and define our object of study as the cognitive schema, we have a high risk of encountering problems of construct validity as soon as we move from the individual mental business model, to the collective, shared mental business model. The above discussion is only complicated further by the fact that within an organization there can be many teams. I have discussed the problems of moving from individual mental model to team mental business model. Similar problems arise when we try to move from team to organizational levels of analysis. How do we best define the organizational level shared mental business model? Is it the sum of team level models? Is it the overlap of the models of different teams, or of all individuals in the organization? Is it best simply to let key decision-makers, such as a CEO, describe their (individual) model and then use this as a proxy for the organizational level model? There is no clear answer to these questions, and indeed, a careful reading of studies that have documented the mental business model at the team or organizational levels reveal different methodological choices. Another interesting question is whether what we would define as elements in common, are actively shared between members (as opposed to just passively). Are members aware that these elements are held in

3 The Sharing of (Mental) Business Models

61

common in their mental business models, and what would be the implications of awareness or non-awareness? For example, if a shared mental model leads to coordinated action, as discussed earlier in this chapter, would non-awareness of the fact that the business model is shared lead the individual member to be uncertain as to whether other members would agree to a particular action? Is it necessary for the benefits of shared cognition to materialize, that members be consciously aware of the shared cognition, or is it enough that members simply think the same way? To my knowledge this has not been explored in the business model literature. To sum up, the critical reader of the business model literature will in fact note three common weaknesses in business model studies adopting the cognitive perspective: (1) a lack of careful consideration of the epistemological approach (although in fairness this is becoming the least common one, as the problem has been highlighted multiple times in the literature), (2) a lack of clear and explicit definition of how the shared mental business model is delimited (as discussed above in reference to Figs. 3.2 and 3.3), and (3) a lack of consideration of whether organizational members are aware of the sharing, and the consequences of this. The latter two have to the best of my knowledge not been discussed before in the business model literature, and represent both a major weakness, but also opportunity for future research. Aside from this are a number of methodological advances in the MOC literature that also represent opportunities to improve the measurement of mental business models, some of which have been discussed in previous chapters, and some of which have been discussed elsewhere (see e.g., Galavan et al., 2018).

Concluding Thoughts I started this chapter with a discussion of some of the benefits to shared mental models that have been highlighted in the cognition literature. I especially emphasized how this literature sees shared mental models as something that leads to superior team performance. However, can we extend this assumption to the particular type of mental model that is

62

K. J. Sund

the mental business model? It may not be so obvious. In Chapter 2, I discussed a study I carried out with a graduate student years back, that led us to the realization that within a larger organization, employees at different levels of hierarchy and across different organizational units had very different perceptions of the strategy of that organization. There was a lack of alignment in perceptions of what the strategy was, but this was actually not surprising, as different employees across a same organization are engaged in very different daily activities. Taking this a step further, as I did in Chapter 2, we should perhaps expect that especially in larger organizations, different employees will have different views on the elements that constitute the mental business models. So what? Is this necessarily a problem? As discussed earlier in this chapter, key elements of the mental business model include interpretations of the environment (e.g., Egfjord & Sund, 2020; Massa & Hacklin, 2020), perceptions of key activities and resources (e.g., Sund et al., 2021), and value propositions (e.g., Narayan et al., 2020). We also recognize that the model can take the form of a simple narrative (a recipe), or a more complicated framework of complementary components, such as found in tools like the business model canvas. Either way, the content of the mental business model is relatively abstract and is intimately linked to the strategy of the firm. When studied as a simple narrative, it may be to be expected that different employees, working in the same firm with the same objective business model, but at different levels of the hierarchy, or working in different functional roles, or different departments, may have large differences in their mental business model (as in fact illustrated in Figs. 3.2 and 3.3). As these people are involved in distinct daily activities, involving distinct resources, and adding value in distinct ways, it would not be surprising that they have distinct views on the business model as well. However, contrary to the very task-oriented types of mental models discussed in the literature that suggests that alignment of mental models is performanceenhancing, if the mental business model is abstract and somewhat distant from the daily activities of the employee, misalignment may not have as big an effect as we might imagine. Of course, if the researcher engages the employees with cognitive aids (such as a more deductive framework), one could imagine that alignment occurs more naturally, as employees

3 The Sharing of (Mental) Business Models

63

are brought into a sensemaking process that creates a shared definition and shared language. Regardless, my point here is simply that since the business model construct is of a more abstract nature, alignment may be less of an issue. So, when is alignment (i.e., a truly shared mental business model) of value? The answer may be that alignment becomes important in at least three hypothetical types of circumstances. The first is where multiple, but conflicting shared mental business models emerge in the organization. Literature on organizational culture provides us with a clue as to what could happen. In larger organizations, it is possible for sub-cultures to emerge alongside the dominant culture (Rose, 1988). Such subcultures can be enhancing with regards to the dominant culture, and thus compatible with and in fact supportive of the dominant culture. They can also be orthogonal, meaning that they co-exist without affecting the dominant culture. Or they can be counter-cultures, that challenge the dominant culture. Analogously, one could imagine a situation in which a group within the firm develops their own shared mental business model, which counters the dominant one. In other words, a particular group (for example a functional team, a branch office, or a team) develops their own idea of what the business model is, or should be, that goes against the rest of the organization. For example, the marketing team believes that the firm’s product adds value in one way, while the rest of the organization believes it adds value in a different way. In this circumstance, a misalignment in the shared mental business model of different groups of individuals in the organization may lead on the one hand to performance problems, and on the other even to potential tensions and conflicts between groups. The second circumstance is when efforts are made to change the business model. Ongoing business model innovation is a necessity and can be approached in a variety of ways (Saebi & Foss, 2015). One could speculate that a shared mental business model may have more or less value depending on the type and degree of innovation that is sought. The third circumstance is when efforts are made to introduce entirely new business models that are to exist alongside the existing business model. This circumstance is unique, since it introduces the possibility that the new business model could be neutral or complementary with regards to the

64

K. J. Sund

existing model but could also substitute the existing model (Bogers et al., 2015; Kim & Min, 2015; Sund et al., 2016a). The last two circumstances are those that arise during incumbent business model innovation and are the subject of Chapter 4.

References Aspara, J., Lamberg, J.-A., Laukia, A., & Tikkanen, H. (2013). Corporate business model transformation and inter-organizational cognition: The case of Nokia. Long Range Planning, 46 (6), 459–474. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171. Bogers, M., Sund, K. J., & Villarroel, J. A. (2015). The organizational dimension of business model exploration: Evidence from the European postal industry. In N. J. Foss & T. Saebi (Eds.), Business model innovation: The organizational dimension. Oxford University Press. Cabantous, L., & Gond, J. P. (2011). Rational decision making as performative praxis: Explaining rationality’s Éternel Retour. Organization Science, 22(3), 573–586. Cannon-Bowers, J. A., & Salas, E. (2001). Reflections on shared cognition. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 22(2), 195–202. Daft, R. L., & Weick, K. E. (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9 (2), 284–295. Dehaene, S. (2021). How we learn: Why brains learn better than any machine… for now. Penguin. Egfjord, K.F.-H., & Sund, K. J. (2020). Do you see what I see? How differing perceptions of the environment can hinder radical business model innovation. Technological Forecasting and Social Change, 150 (1), 119787. Furnari, S. (2015). A cognitive mapping approach to business models: Representing causal structures and mechanisms. In C. Baden-Fuller & V. Mangematin (Eds.), Business models and modelling. Emerald Group Publishing. Galavan, R. J., Sund, K. J., & Hodgkinson, G. P. (Eds.). (2018). Methodological challenges and advances in managerial and organizational cognition. Emerald Group Publishing.

3 The Sharing of (Mental) Business Models

65

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482. Greve, H. R., & Taylor, A. (2000). Innovations as catalysts for organizational change: Shifts in organizational cognition and search. Administrative Science Quarterly, 45 (1), 54–80. Guérard, S., Bode, C., & Gustafsson, R. (2013). Turning point mechanisms in a dualistic process model of institutional emergence: The case of the diesel particulate filter in Germany. Organization Studies, 34 (5–6), 781–822. Gurses, K., & Ozcan, P. (2015). Entrepreneurship in regulated markets: Framing contests and collective action to introduce pay TV in the US. Academy of Management Journal, 58(6), 1709–1739. Gustafsson, R., Sund, K. J., & Galavan, R. (2023). What are cognitive aids in strategy? In K. J. Sund, R. Galavan, & R. Gustafsson (Eds.), Cognitive aids in strategy. Emerald Group Publishing. Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. The Academy of Management Review, 9 (2), 193–206. Henike, T., & Hölzle, K. (2020). What bounds entrepreneurial business modelling? The impacts of visual framing effects and cognitive dispositions. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Jaag, C. (2014). Postal-sector policy: From monopoly to regulated competition and beyond. Utilities Policy, 31, 266–277. Jacobs, C. D., & Heracleous, L. T. (2005). Answers for questions to come: Reflective dialogue as an enabler of strategic innovation. Journal of Organizational Change Management, 18(4), 338–352. Jarzabkowski, P., & Kaplan, S. (2015). Strategy tools-in-use: A framework for understanding “technologies of rationality” in practice. Strategic Management Journal, 36 (4), 537–558. Johnson, P., & Johnson, G. (2002). Facilitating group cognitive mapping of core competencies. In A. S. Huff & M. Jenkins (Eds.), Mapping strategic knowledge. Sage. Kaplan, S. (2008). Framing contests: Strategy making under uncertainty. Organization Science, 19 (5), 729–752. Kim, J.-S., & Kim, J. (2023). How industry recipe and boundary belief influence similar modular business model innovations. Journal of Open Innovation: Technology, Market, and Complexity, 9 (3), 100101.

66

K. J. Sund

Kim, S. K., & Min, S. (2015). Business model innovation performance: When does adding a new business model benefit an incumbent? Strategic Entrepreneurship Journal, 9 (1), 34–57. Klimoski, R., & Mohammed, S. (1994). Team mental model—Construct or metaphor. Journal of Management, 20 (2), 403–437. Ladd, T. (2020). Science and swagger for success: The interactions of hypothesis testing and self-efficacy to influence business model performance. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Levine, J. M., Resnick, L. B., & Higgins, E. T. (1993). Social foundations of cognition. Annual Review of Psychology, 44, 585–612. Martins, L. L., Rindova, V. P., & Greenbaum, B. E. (2015). Unlocking the hidden value of concepts: A cognitive approach to business model innovation. Strategic Entrepreneurship Journal, 9 (1), 99–117. Massa, L., & Hacklin, F. (2020). Business model innovation in incumbent firms: Cognition and visual representation. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. Academy of Management Annals, 11(1), 73–104. Mohammed, S., Klimoski, R., & Rentsch, J. R. (2000). The measurement of team mental models: We have no shared schema. Organizational Research Methods, 3(2), 123–165. Munir, H., Bengtsson, L., & Åkesson, E. (2022). Management tools for business model innovation—A review. In R. Agarwal, E. Patterson, S. Pugalia, & R. Green (Eds.), Innovation. Taylor & Francis. Narayan, S., Sidhu, J. S., Baden-Fuller, C., & Volberda, H. W. (2020). Examining CEOs’ business model schemas: A cognitive mapping of differences between industry insiders and outsiders. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Wiley. Pazzaglia, F., Farrell, M., Sonpar, K., & Martin de Holan, P. (2018). Keeping up with the Joneses: Industry rivalry, commitment to frames and sensemaking failures. Human Relations, 71(3), 427–455. Podoynitsyna, K., Snihur, Y., Thomas, L. D. W., & Grégoire, D. (2020). Creating meta-narratives: How analogies and metaphors support business model innovation. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing.

3 The Sharing of (Mental) Business Models

67

Purdy, J., Ansari, S., & Gray, B. (2019). Are logics enough? Framing as an alternative tool for understanding institutional meaning making. Journal of Management Inquiry, 28(4), 409–419. Rose, R. A. (1988). Organizations as multiple cultures: A rules theory analysis. Human Relations, 41(2), 139–170. Saebi, T., & Foss, N. J. (2015). Business models for open innovation: Matching heterogeneous open innovation strategies with business model dimensions. European Management Journal, 33(3), 201–213. Schwoon, B., Schoeneborn, D., & Scherer, A. G. (2022). Enacting a grand challenge for business and society: Theorizing issue maturation in the mediabased public discourse on COVID-19 in three national contexts. Business & Society. https://doi.org/10.1177/00076503221110486 Snihur, Y., & Wiklund, J. (2019). Searching for innovation: Product, process, and business model innovations and search behavior in established firms. Long Range Planning, 52(3), 305–325. Snihur, Y., Thomas, L. D. W., & Burgelman, R. A. (2018). The performative power of words: How business model innovators use framing for strategic advantage. In K. J. Sund, R. J. Galavan, & S. Brusoni (Eds.), Cognition and innovation. Emerald Group Publishing. Snow, D. A., & Benford, R. D. (1992). Master frames and cycles of protest. In A. D. Morris & C. M. Mueller (Eds.), Frontiers in social movement theory (pp. 133–155). Yale University Press. Storbacka, K., & Nenonen, S. (2011). Scripting markets: From value propositions to market propositions. Industrial Marketing Management, 40 (2), 255–266. Sund, K. J. (2020). From cooperation to competition: Changing dominant logics and legitimization in liberalizing industries. In J. Rendtorff (Ed.), Handbook of business legitimacy. Springer. Sund, K. J. (2011). Transformation and diversification in the context of regulated industries: The case of Poste Italiane and PosteMobile. International Journal of Management Education, 9 (4), 77–85. Sund, K. J. (2013). Scanning, perceived uncertainty, and the interpretation of trends: A study of hotel directors’ interpretation of demographic change. International Journal of Hospitality Management, 33, 294–303. Sund, K. J. (2015). Revisiting organizational interpretation and three types of uncertainty. International Journal of Organizational Analysis, 23(4), 588– 660.

68

K. J. Sund

Sund, K. J., & Anson, J. (2021). The decline of mail: Postal industry decisionmakers’ interpretations in the aftermath of the financial crisis. Entreprises et Histoire, 105, 65–77. Sund, K. J., & Osborn, D. (2010). The future is in the post: Perspectives on strategy in the postal industry. Libri Publishing. Sund, K. J., Bogers, M. L., & Sahramaa, M. (2021). Managing business model exploration in incumbent firms: A case study of innovation labs in European banks. Journal of Business Research, 128, 11–19. Sund, K. J., Bogers, M., Villarroel, J. A., & Foss, N. (2016a). Managing tensions between new and existing business models. MIT Sloan Management Review, 57 (4), 8. Sund, K. J., Galavan, R. J., & Huff, A. S. (Eds.). (2016b). Uncertainty and strategic decision making. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Bogers, M. (Eds.). (2020). Business models and cognition. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Brusoni, S. (Eds.). (2018). Cognition and innovation. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Huff, A. (2022). Uncertainty in strategy research. In M. A. Griffin & G. Grote (Eds.), The Oxford handbook of uncertainty management in work organizations (pp. C3.S1–C3.S7). Oxford University Press. Sund, K. J., Galavan, R., & Gustafsson, R. (Eds.). (2023). Cognitive aids in strategy. Emerald Group Publishing. Sund, K. J., Villarroel, J. A., & Bogers, M. (2014). Organizational aspects of business model innovation: The case of the European postal industry. In Academy of management proceedings (Vol. 2014, No. 1, p. 11099). Academy of Management. Täuscher, K., & Abdelkafi, N. (2017). Visual tools for business model innovation: Recommendations from a cognitive perspective. Creativity and Innovation Management, 26 (2), 160–174. Thompson, L., & Fine, G. A. (1999). Socially shared cognition, affect, and behavior: A review and integration. Personality and Social Psychology Review, 3(4), 278–302. Wallnöfer, M., & Hacklin, F. (2013). The business model in entrepreneurial marketing: A communication perspective on business angels’ opportunity interpretation. Industrial Marketing Management, 42(5), 755–764. Weick, K. E. (1995). Sensemaking in organizations. Sage. Zott, C., Amit, R., & Massa, L. (2011). The business model: Recent developments and future research. Journal of Management, 37 (4), 1019–1042.

4 Cognition and Business Model Innovation

Abstract The use of cognition theories in the study of business model innovation has gained in popularity in the last decade, and especially in the last five years or so. This is not least the case because earlier studies of both business model innovation, and strategic change more broadly, identified that dominant logic, culture, identity, and other cognitionrelated phenomena can constitute both enablers and barriers to such innovation. In this chapter I reflect on just some of the literature that has emerged that connects theories of cognition to the context of business model innovation, focusing mainly on incumbent firms, but touching also on the start-up. I propose a framework for thinking about how to link cognition and innovation in general terms, emphasize the promise of a process view of business model innovation and cognition, and point to both some of the weaknesses in the existing literature, and some of the opportunities that exist for future research. Keywords Business model innovation · Cognition · Framework · Process · Dual processing · Overconfidence

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9_4

69

70

K. J. Sund

Introduction In this chapter I will deal in more detail with the shaping and re-shaping of the business model, in other words business model innovation (BMI), from a cognitive perspective. As a reminder, the business model has by some been called a description (e.g., Baden-Fuller & Morgan, 2010), some an activity system (e.g., Zott & Amit, 2010), some a template (e.g., Zott & Amit, 2008), and some a framework (e.g., Schneider & Spieth, 2013). This description, system, or template, describes how value is created, distributed, and appropriated by the organization (Teece, 2010). The description can thus take the form of a simple narrative (a recipe), a more stylized archetype (a generic business model, or template), or a more complicated framework of complementary components (e.g., the business model canvas of Osterwalder & Pigneur, 2010). From the cognitive perspective the business model is commonly treated as a mental model or schema, that defines the logic of how the business creates value. This schema is malleable, and can thus change over time (Shepherd et al., 2023). A business model innovation could thus from a cognitive perspective be defined as a change in the logic of how the business creates and captures value, and business modelling could be defined as the “search for new logics of the firm and new ways to create and capture value for its stakeholders” (Casadesus-Masanell & Zhu, 2013, p. 464). Distinctions can be made between the contexts of incremental and radical BMI, and between the contexts of the entrepreneurial start-up and the existing incumbent (Sund et al., 2018a, 2018b). The start-up often uses more radical forms of BMI as a way of creating a new market or entering an existing market with a new product or service, sometimes resulting in what has been termed “disruption” (Amit & Zott, 2001). Once established, start-up firms in industries experiencing high growth can use incremental BMI to scale-up their activities. Conversely, incumbents in mature industries may focus more on incremental improvements in production or distribution to optimize the established business model. This observation is consistent with the traditional view on competitive strategy and the industry life cycle (Porter, 1980). Alternatively (especially if facing a declining market for its core products and services), the incumbent may attempt to discover and implement (to the firm, or to

4 Cognition and Business Model Innovation

71

the whole industry) entirely new business models in an attempt to defend its position, to diversify its portfolio of activities, or to leverage new technologies (Bogers et al., 2015; Egfjord & Sund, 2020; Sund et al., 2020b). Of course, there could also be exceptional competitive or environmental circumstances in which the firm struggles to pursue BMI at all, such as in the case of a highly regulated government monopoly, or in a situation of hypercompetition (see e.g., Lindskov et al., 2021, 2023; Sund & Lindskov, 2022). The business model literature is only now starting to reach maturity (Foss & Saebi, 2018), and quite a few studies of business models and business model innovation (BMI) have in very recent years accentuated the cognitive underpinnings of the business model construct or pointed to the role of cognitions in shaping business models and business model change (Sund et al., 2020a). A number of recent studies have specifically highlighted how managers’ cognitions and sensemaking influence business model design (Egfjord & Sund, 2020; Sosna et al., 2010; Sund et al., 2021). Additionally, process studies of BMI have highlighted the role of shared logics in enabling such innovation (Bogers et al., 2015; Egfjord & Sund, 2020), and how the information and knowledge search behaviour of managers affects the type of BMI being pursued (Snihur & Wiklund, 2019). A shared mental business model directs the way executives perceive new ideas for business models in incumbent firms (Bogers et al., 2015; Sund et al., 2016). Yet, Daood et al. (2020) suggest that a strong shared schema of the current business model may in fact be detrimental to radical BMI, and in Bogers, Sund, and Villarroel (2015) we demonstrate how a strong dominant logic around the existing business model prevented radical BMI in incumbent firms in the postal sector. We report a similar view in Egfjord and Sund (2020) and in Sund et al. (2021). Others have suggested that when there is incongruence with existing schemas, general innovations originating outside the firm lead managers to search for information on opportunities or threats (Greve & Taylor, 2000). This is consistent with the information processing view on strategic issue interpretation (Sund, 2013, 2015). BMI is thus largely about schema change (Martins et al., 2015). It is further thought that a strong organizational identity can act as a barrier in this context

72

K. J. Sund

(Snihur, 2018). Yet, efforts at better understanding such barriers have often looked at the innovation process from an objectivist perspective, not at issues of managerial and organizational cognition. Combining the two, i.e., differentiating stages in the cognition process while studying the cognitions of managers, can provide interesting insights.

Innovation Contexts: A Structuring Framework There are of course any number of ways that one could categorize BMI, and thus define different contexts for its study. One could be scope. Another could be sector. Yet another could be stage in the innovation process. For example, starting with scope, in Sund et al. (2021) we refer to incremental and radical BMI. Kim et al. (2020) refer to incremental, radical, disruptive, and breakthrough BMI. Finally, Foss and Saebi (2018) when discussing the scope of a BMI take a configurational view and differentiate between modular and architectural changes (rather than the more “generic” incremental and radical) and point out that a business model could be novel to only one firm, or to an entire industry. They thus suggest four specific types of BMI that they call evolutionary, adaptive, focused, and complex BMI. Studies of BMI and cognition have in some cases focussed on the organizational level of analysis, in some cases the team level of analysis, and in some cases the individual level of analysis. By this, I mean that although changes to the business model are obviously the object of study, theories of organizational, team, or individual cognition are employed. Authors of studies often also move (either implicitly or explicitly) between levels. These levels are intuitively connected, but how exactly we move conceptually and empirically between these levels is a critical question, that has in fact spurred a whole movement on “micro-foundations” outside of the business model literature (see e.g., Felin et al., 2015; Foss & Pedersen, 2016). Bringing this discussion into the business model literature would be a good step forward. The problems associated with moving between levels of analysis can easily be illustrated with an example. When studying how dominant

4 Cognition and Business Model Innovation

73

logic at the organizational level constitutes a barrier to BMI, one might use data created by interviewing individual informants, but how exactly do we move from the individual cognitions of these informants to making conclusions about an organization as a whole? This requires a theory, or at least a series of explicit assumptions, regarding the link between levels of analysis, where the individual acts as a microfoundation for the social. In Sund et al. (2018b), we propose a framework to think about the study of cognition and innovation in general, that incorporates the study of BMI. Looking at the wider innovation literature (not just the BMI literature), there is by now a rich (although still fairly limited in the number of empirical studies) body of literature studying innovation through cognitive lenses. A careful reading of this literature reveals a number of dimensions along which such studies have differentiated themselves: • Firstly, as mentioned earlier, some studies focus on start-ups, and some on established (incumbent) firms. Some study both, for example within the context of an ecosystem. • Secondly, some study product innovation, some service innovation, some process innovation, some business model innovation, and some a combination. Each of these could further be broken into incremental and radical innovation. • Thirdly, some study cognition and innovation at the organizational level, some at the team level, and some at the individual level. Some try to bridge levels or organizations. • Fourthly, some study innovation at a particular stage of the innovation process, while some study multiple stages. • Fifthly, some study conscious cognition, while some touch on more non-conscious themes like heuristics or biases. • Sixthly, some studies consider cognition independently from emotions, while some recognize that cognition can also be emotion-laden (Galavan et al., 2018; Hodgkinson et al., 2018). Starting with the last point, illustrated at the bottom of Fig. 4.1, dual processing theory tells us that cognition is not just about conscious,

74

K. J. Sund

rational decision-making. Instead, cognition takes place under conditions of uncertainty (Huff et al., 2016; Sund et al., 2022), and the brain has evolved to incorporate particular mechanisms for dealing with these. Decision-making thus involves both conscious and nonconscious cognition, or what Kahneman (2011) refers to as “system 1” and “system 2” thinking. The brain can make quick and instinctive decisions (system 1), but also think problems through slowly, analytically, and logically (system 2). Being geared towards system 1, our brain tends to make fast decisions and conserve energy, which is why a lot of our decision-making is nonconscious. A typical evolutionary explanation for this, given in popular science, is that prehistorical man would commonly face natural dangers that required a quick fight or flight reaction, leaving no time for slow, deliberate decisions. In the context of modern-day managerial decision-making, system 1 cognitive processes are useful when faced with well-structured problems, while more deliberative system 2 processes are useful when faced with ill-structured problems (Laureiro-Martinez & Brusoni, 2018). What we call “gut feeling”, is in fact system 1 decisionmaking, based on heuristics, or decision rules, some of which may result in biases. Some decisions are taken under conditions of emotionality (affect). For example, Hodgkinson and Healey (2011) and Hodgkinson et al. (2018) have argued that only recently has the MOC literature fully recognized that managers may be subject to emotions when they make decisions (Barsade & Gibson, 2007). Affect is a broad term that covers a variety of feelings people experience. Discrete emotions may come and go rapidly in a particular situation (e.g., temporary shock at news), while moods are more long-lasting, and emotive traits have to do with the individual person. Some individuals may thus be better at regulating their own emotions. In the innovation literature, it has been suggested that it can be a combination of cognition and emotion that leads groups to adopt or not process innovations in large firms (Choi et al., 2011). A more detailed discussion of both dual processing theory, and the role of emotions, is found in Chapter 1 in this book. As we argue in Sund et al. (2018b) for the study of innovation in general, combining the ideas of cognitive dual-processing theory with various categorizations of innovation, provides us with a robust

4 Cognition and Business Model Innovation

75

Process

Innovation Type

Organizational Level

Team (Socio-Cognitive) Level

Hot Cognition (emotion-laden)

Individual Level

Cold Cognition (emotion-independent) NonConsciou

Conscious

Fig. 4.1 Framework for the study of cognition and innovation (reproduced from Sund et al., 2018b)

structure or framework for exploring the many contexts and research questions that could be found at the intersection of cognition and BMI. For example, one might wish to study how conscious, cold (emotionindependent) cognition affects the implementation (exploitation) stage of a new business model. In such a case, multiple theories of cognition could provide relevant insights, an example of which is found in Snihur et al.’s (2018) study in which they examine how framing can constitute

76

K. J. Sund

a strategic process that enables business model innovators to shape new ecosystems. So far very few studies have empirically tried to include dual processes in a single study, although very recently Shepherd et al. (2023) have at least theorized in that direction. As discussed earlier, socio-cognitive processes occur at the group or team level within the organization, in which case theoretical development may need to consider just how individual-level cognition constructs affect team processes, and how team processes result in organizational-level outcomes. In other words, how do we move between levels? Finally, it is worth paying particular attention to process. The links between cognition and BMI may very well be contingent on the stage of BMI. Indeed, several BMI studies have suggested that things like the strength of the barrier constituted by a dominant logic, will vary along the BMI process (Bogers et al., 2015; Jensen & Sund, 2017; Sosna et al., 2010; Sund et al., 2021). A given study could focus on a single process stage or could take the temporal element into consideration and study BMI across multiple stages. What is illustrated in Fig. 4.1, is thus that empirical observations of cognition at the individual level may not directly translate into effects at the organizational level; that empirical observations derived from the study of one type of innovation (say service innovation) may not hold true for another type (say business model innovation); that conclusions regarding the role of cognition in one stage of innovation may not be generalizable to other stages; that empirical data on cold cognition may not account for situations when cognition is hot; and that non-conscious cognitions may not be picked up in a given study. Figure 4.1 thus allows the researcher to situate the context of their particular study and think about how this context affects the limitations and generalizability of their findings. Beyond this, it should again be noted that empirical observations gathered in the start-up context may not be relevant for the incumbent context and vice-versa.

4 Cognition and Business Model Innovation

77

The BMI Process and Cognition In this section I focus on contexts of incumbent BMI, but some of the discussion may extend to the entrepreneurial start-up as well. The process of BMI is typically hypothesized to involve several stages. For example, in Bogers et al. (2015) we inductively identify two stages of exploration and exploitation. In later work (Jensen & Sund, 2017) we find that these two stages are actually preceded by a first awareness stage. We find that the BMI process starts with managers becoming aware of the need to explore new business models (awareness stage), which are then searched for (exploration stage), before being gradually implemented and perfected (exploitation stage). It should be noted that many other stage definitions have been proposed over the years, and it can be easy to get confused as a reader (for a recent review see Andreini et al., 2022). For example, one framework that has received some attention is the I4 framework deductively proposed by Frankenberger et al. (2013), based on their reading of the general innovation literature, and in which they include four stages: initiation, ideation, integration, and implementation. They thus assume that BMI follows a similar process structure to any other form of innovation. Other work has suggested only two stages. Frankenberger and Sauer (2019), departing from their earlier I4 framework, define what they call a “design stage” followed by a “growth stage” and illustrate with four case studies of corporate spin-offs (interviewing the top management of those spin-offs) how top management attention could differ across these two stages. They partially credit Brea-Solís et al. (2015) for coming up with these two stages in a case study of Walmart. Somewhat confusingly, that study in turn explicitly refers to three (not two) stages of the development of Walmart, with the authors writing “our analysis has shown three distinct stages in the evolution of Walmart. In the first one, Walmart was under the management of a visionary leader (Sam Walton) who implemented several choices that sought to achieve cost leadership. The second stage was characterized by a large-scale deployment of the original business concept. The final stage corresponds to the downside of success. Walmart’s human resource practices were criticized, which prompted higher salaries and benefits to employees” (p. 29). These three stages in turn do not seem to match

78

K. J. Sund

those of Jensen and Sund (2017). The reason is perhaps that the Walmart case actually describes the transition from start-up to incumbent, rather than the stages of incumbent BMI, like Jensen and Sund (2017). Sosna et al. (2010), just like Bogers et al. (2015) report finding two distinct stages of exploration and exploitation in incumbent BMI. A key insight from the short discussion above is that while process studies show a great deal of promise, findings are a mixed bag, and further research should seek to verify exactly how many stages there are in the process, and exactly how these stages differ from each other. There appears furthermore to be a need to differentiate more clearly in the literature between the context of start-up and incumbent. Finally, there is a need to more clearly justify how stages are defined in each process study, especially whether this is done inductively based on data derived from the study itself (as it should perhaps ideally be done), or deductively based on earlier studies. Either way, for now I invite the reader to simply accept that there are multiple stages to the BMI process. A critical question for BMI research, especially for strategy researchers, is why some firms are successful at moving through these stages of innovation, while others fail. In later work, Teece (2018, 2020) proposes three underlying process-related capabilities of sensing, seizing, and reconfiguring, that he calls dynamic capabilities for BMI, and that can be directly related to the three stages of Jensen and Sund (2017). Commenting on sensing he writes that “setting up an early-stage business model […] depends as much on art and intuition as on science and analysis” (Teece, 2018, p. 43). This is to some extent confirmed by Schneckenberg et al. (2019) who find that both problem sensing and intuitional insights help form new business model design logics. In very general terms, sensemaking and learning capabilities seem important for BMI at this stage as well (Berends et al., 2016; Loon et al., 2020). In the context of incumbent BMI, the stage of business model exploration appears particularly sensitive to competing logics between top management, middle management who are mainly involved with the operations of the current business model, and innovators trying to explore and implement new business models (Bogers et al., 2015; Egfjord & Sund, 2020; Sund et al., 2021). Several studies have documented that such business model exploration may even result in tensions

4 Cognition and Business Model Innovation

79

(Chesbrough, 2010; Egfjord & Sund, 2020; Kim & Min, 2015; Snihur & Tarzijan, 2018; Sund et al., 2016, 2021), at least some of which may be assumed to be due to cognitive differentiation, i.e., differences in mental models (see e.g., Sund et al., 2023). According to Jensen and Sund (2017, p. 286), “for the organisation, there is an element of both unlearning and new learning, as business logic changes and transforms during the BMI process […] The role of leadership moves from sense-making in the awareness stage to sense-giving in the business model exploration stage.” In our study of four European banks, and their attempts at developing new business models in response to digitalization trends (Sund et al., 2021), we identified perceived organizational barriers to BMI during the business model exploration stage. Confirming our earlier findings from the postal sector, it seemed that these banks experimented with various organizational design choices for their innovation labs, perhaps finding it somewhat difficult to fit the innovation lab into the existing organization. The tension was how to ensure on the one hand that employees in these labs had sufficient autonomy and distance to the core organization to allow them to experiment and be creative, while on the other keeping them sufficiently integrated with the core business to allow good ideas to actually be adopted by the core. One issue these labs encountered was that “while efforts are attempted by these banks at more radical digital BMI, in the end, most efforts end up focusing on process and product innovation, based on existing “analogue” processes and products” (Sund et al., 2021, p. 14). We saw the same thing in the insurance sector in Egfjord and Sund (2020), namely that business model innovators found it easier to sell very incremental changes to process and product to the core business. In Sund et al. (2021) we thus found that perceived barriers to BMI in the exploration stage revolved around five main themes: (1) The problem of balancing incremental and radical innovation, and in particular how these organizations tended to end up making incremental rather than radical BMI; (2) The problem of securing top management team support; (3) Integration mechanisms and the tensions that emerge between an innovation lab and managers from the core business; (4) Issues of control linked to the innovation process; and (5) Issues related to limited resources and capabilities for BMI. These overarching themes

80

K. J. Sund

were linked themselves to several organizational issues. I will not reproduce all of these as they can be found in the original article, but a few stand out. One thing we documented was how top management attention and focus tends to be on alignment to the existing core business, which favors incremental, rather than radical innovation. We also saw high degrees of centralization and control, whereby in these banks decision-making centralization tended again to favor safer “quick win” innovations (something we also saw in Egfjord & Sund, 2020). Goal incompatibility was another problem, whereby radical BMI goals were not perceived to be compatible with core business goals by lab managers themselves. They experienced resistance from core business, linked both to scarce resources, and to the use (or non-use) of integration mechanisms. Resource and capability constraints would again tend to favor smaller and cheaper incremental innovations, rather than radical long shots. During the final stage of business model exploitation, the cognitive focus of innovators and managers moves away from experimentation and towards the successful implementation and optimization of the new business model (Jensen & Sund, 2017). At this stage the perceived uncertainty surrounding the new business model lowers (Bogers, Sund, & Villarroel, 2015), but a new set of dilemmas emerge when BMI takes place in an incumbent context. Managing a multi-business model organization implies handling multiple business logics, that may be complementary, neutral, or even substitutes in the marketplace (Mozheiko & Sund, 2024; Sund et al., 2016, 2021). This leads to organizational complexity (Snihur & Tarzijan, 2018). Kim and Min (2015) point out the importance of complementary assets in determining how best to design the organization after adding a new business model to the incumbent firm, while we in our forthcoming study of Danish windowmaker Velux’s Chinese business unit, suggest that respecting the dominant corporate culture and vision, allows local managers more room to experiment in the context of the incumbent multinational (Mozheiko & Sund, 2024). As we write in Sund et al., (2021, p. 12), “balancing the exploration of new business models and the exploitation of existing business models leads to a need to carefully design the organization. Such design can be thought of in terms of the optimal degree of differentiation of activities (for

4 Cognition and Business Model Innovation

81

example, giving both cognitive, resource, and capability freedom to innovation labs and innovative employees), and integration mechanisms (both vertical and horizontal).”

Metacognition and Knowledge Overconfidence An interesting observation (when discussing the context of the BMI process) is reported by Bellini and Castellazzi (2020), who suggest that successful radical business model innovators can leverage the perception and control of own cognition, i.e., possess what they call meta-cognition (cognition about cognition). To some extent this insight is both compatible with and complementary to my own findings outlined in the paragraphs above. For example, in our study of bank innovation labs (Sund et al., 2021), we report on barriers to business model exploration as perceived by lab managers, but we do not explicitly question whether these perceptions are actually justified. Do innovation managers misperceive barriers to innovation? Are they prone to unconscious biases (Kahneman, 2011)? What are the implications if they do misperceive the barriers? And could they overcome these misperceptions by exercising meta-cognition? Managerial misperceptions in general are a common phenomenon (see discussions in e.g., Mezias & Starbuck, 2003; Starbuck & Mezias, 1996; Sund, 2016; Sund & Lindskov, 2022; Sutcliffe, 1994). At least some of these misperceptions coincide with what is referred to as knowledge overconfidence. In fact, in Sund (2016, p. 121) I conclude firstly “that executives as a group have inaccurate perceptions, and secondly that many exhibit overconfidence, in the context of specific environmental issue interpretation”. Numerous studies report this systematic overconfidence bias, whereby individuals overestimate the accuracy of their own perceptions (e.g., Kahneman, 2011; Kahneman et al., 1982; Klayman et al., 1999). We can consider for a moment the problem of misperceptions and knowledge overconfidence (or overconfidence bias) in the BMI process. In Sund and Lindskov (2022) we conduct a thought experiment to consider the implications for BMI of managers misperceiving the degree

82

K. J. Sund

of competition in the environment. We suggest that managers who perceive their competitive environment to be hypercompetitive, when it is not, or who perceive their environment to be normally competitive, when in fact it is hypercompetitive, may misbalance incremental versus radical BMI. Incidentally, in a separate strand of very recent research, we question in general the existence of hypercompetition, concluding that the phenomenon is limited in time, space, and sector (Lindskov et al., 2021, 2023). Regardless, the general take-away from the thought experiment in Sund and Lindskov (2022) is that misperceptions may lead to suboptimal decision-making in the BMI context. Let us consider another thought experiment. Let us imagine that an innovation lab manager misperceives organizational barriers to radical BMI during the exploration stage as outlined earlier in this chapter but is confident that they have identified these barriers accurately (which they have not). For one, if I as a researcher rely solely on a single manager to provide me with an objective observation of organizational reality, I risk identifying obstacles that do not exist, and missing ones that do. Misperceptions thus create a problem with managers as research informants (Mezias & Starbuck, 2003; Sund, 2016), unless we clearly subscribe to the epistemology that subjective perceptions are subjective perceptions, and nothing more. But for the innovation process itself, the implications could be even more interesting. For instance, the BMI process may be stalled simply because a key manager perceives there to be barriers that do not actually exist. An example could be an innovation manager who kills a good idea because they perceive resource constraints preventing its further development. If these constraints are not actually there, this results in a missed innovation opportunity. In forthcoming work (presented in Sund & Rydén, 2022) we illustrate with experiments on university students how simple techniques of dialectical bootstrapping can reduce knowledge overconfidence (see also, e.g., Herzog & Hertwig, 2009; Sund, 2016). We taught students how to question their initial interpretations, by thinking about “what could be an argument against my initial answer” and were able to document how knowledge overconfidence was reduced as a consequence of forcing oneself to think rationally about why one might be wrong (essentially forcing cognition into the cold-conscious quadrant in Fig. 4.1). This is

4 Cognition and Business Model Innovation

83

essentially a form of meta-cognition experiment in the terminology of Bellini and Castellazzi (2020). Could the type of meta-cognition exercise we used on students be useful in getting innovation managers to question their own perceptions of organizational barriers to BMI? More broadly, in Sund et al., (2021, p. 18) we suggest there is a gap in our understanding of the roles of business model visualization tools and suggest these could be used as integration mechanisms. Beyond this, they could perhaps be used as tools to reduce misperceptions and overconfidence in barriers to BMI. In Sund et al. (2023a, 2023b) we explore the roles of cognitive aids in strategy in general (see in particular the discussion in Gustafsson et al., 2023). One might imagine that specific tools could be developed to help managers think about what organizational barriers are relevant or not and how to attend to these in a systematic fashion, as a way to facilitate radical BMI in the incumbent firm.

Concluding Thoughts The intention in this chapter has not been to provide an exhaustive overview of BMI literature that engages with the cognitive perspective, or theories related to cognition. Instead, I have provided a teaser of what types of questions have been asked in the BMI literature that relate to cognition and provided a framework for how to structure the emerging literature, and how to think about that literature in a systematic way. I had a particular focus on the incumbent BMI process, as this is the literature to which I have myself contributed. From Fig. 4.1 it becomes clear how different studies might relate to each other, but also that there are indeed many different contexts in which to study cognition and BMI. A key insight is that no single study provides the theory of cognition and BMI, because no such unifying theory of cognition actually exists, especially at a more micro level. Instead, what we have is a collection of theories (discussed in previous chapters of this book), that collectively can help us understand, measure, explain, and predict how management thinking impacts BMI, and how such thinking can emerge at both individual and team levels of analysis, and result in organizational level outcomes.

84

K. J. Sund

To reiterate what I wrote in an earlier section, empirical observations of cognition at the individual level may not directly translate into effects at the organizational level. Empirical observations derived from the study of one type of innovation may not hold true for another type. What is true for start-ups may not be true for incumbent firms. Conclusions regarding the role of cognition in one stage of the BMI process may not be generalizable to other stages. Empirical data on cold cognition may not account for situations when cognition is hot. Non-conscious cognitions may not be picked up at all. These points emerge from Fig. 4.1, allowing the researcher to situate the context of their particular study and think about how this context affects the limitations and generalizability of their findings. A final comment is that the two big developments that I see in the literature are firstly a movement away from simpler sensemakingstyle studies focused on questions of cold rational cognition, towards studies recognizing the roles of emotions and unconscious cognition, and secondly a movement towards recognizing the temporal and process nature of BMI. The cost of these movements is generalizability of findings (Andreini et al. 2022). Not surprisingly, inductive, and qualitative case methods lend themselves particularly well to digging into the different contexts illustrated in Fig. 4.1 (for example, studying the role of emotions in the BMI awareness stage at the team level). Thus, we should not be surprised that more empirical studies of cognition and BMI have adopted such methods (Wirtz et al., 2016). These have over the past 10–15 years documented in much more detail the cognitive microfoundations of BMI, and already at this point in time given us a rich set of analytical descriptions of successful and unsuccessful cases of BMI, to which my own research has contributed. The next big challenge will be how to move beyond these rich, context-specific descriptions, towards generalizable theory. One intermediary step could be to identify the generalizable stylized facts of cognition and BMI, but perhaps even this would defeat the very purpose of recognizing the diversity of contexts, and of cognition itself. The cognitive perspective on BMI continues in my opinion to hold enormous promise and opportunity for research, and we are far from having documented fully the various contexts outlined in Fig. 4.1, something I will reflect on further in Chapter 5 of this book.

4 Cognition and Business Model Innovation

85

References Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22(6–7), 493–520. Andreini, D., Bettinelli, C., Foss, N. J., & Mismetti, M. (2022). Business model innovation: A review of the process-based literature. Journal of Management and Governance, 26 (4), 1089–1121. Baden-Fuller, C., & Morgan, M. S. (2010). Business models as models. Long Range Planning, 43(2–3), 156–171. Barsade, S. G., & Gibson, D. E. (2007). Why does affect matter in organizations? Academy of Management Perspectives, 21(1), 36–59. Bellini, E., & Castellazzi, S. (2020). The metacognition underlying radical business model innovation: Four case studies of individual criticism. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Berends, H., Smits, A., Reymen, I., & Podoynitsyna, K. (2016). Learning while (re) configuring: Business model innovation processes in established firms. Strategic Organization, 14 (3), 181–219. Bogers, M., Sund, K. J., & Villarroel, J. A. (2015). The organizational dimension of business model exploration: Evidence from the European Postal Industry. In. N. J. Foss, & T. Saebi (Eds.), Business model innovation: The organizational dimension. Oxford University Press. Brea-Solís, H., Casadesus-Masanell, R., & Grifell-Tatjé, E. (2015). Business model evaluation: Quantifying W Almart’s sources of advantage. Strategic Entrepreneurship Journal, 9 (1), 12–33. Casadesus-Masanell, R., & Zhu, F. (2013). Business model innovation and competitive imitation: The case of sponsor-based business models. Strategic Management Journal, 34 (4), 464–482. Chesbrough, H. (2010). Business model innovation: Opportunities and barriers. Long Range Planning, 43(2–3), 354–363. Choi, J. N., Sung, S. Y., Lee, K., & Cho, D. S. (2011). Balancing cognition and emotion: Innovation implementation as a function of cognitive appraisal and emotional reactions toward innovation. Journal of Organizational Behavior, 32(1), 107–124.

86

K. J. Sund

Daood, A., Calluso, C., & Giustiniano, L. (2020). Unveiling the dark side of business models: A novel framework for managerial cognition and decisionmaking. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Group Publishing. Egfjord, K.F.-H., & Sund, K. J. (2020). Do you see what I see? How differing perceptions of the environment can hinder radical business model innovation. Technological Forecasting and Social Change, 150 (1), 119787. Felin, T., Foss, N. J., & Ployhart, R. E. (2015). The microfoundations movement in strategy and organization theory. Academy of Management Annals, 9 (1), 575–632. Foss, N. J., & Pedersen, T. (2016). Microfoundations in strategy research. Strategic Management Journal, 37 (13), E22–E34. Foss, N. J., & Saebi, T. (2018). Business models and business model innovation: Between wicked and paradigmatic problems. Long Range Planning, 51(1), 9–21. Frankenberger, K., & Sauer, R. (2019). Cognitive antecedents of business models: Exploring the link between attention and business model design over time. Long Range Planning, 52(3), 283–304. Frankenberger, K., Weiblen, T., Csik, M., & Gassmann, O. (2013). The 4Iframework of business model innovation: A structured view on process phases and challenges. International Journal of Product Development, 18(3– 4), 249–273. Galavan, R.J., Sund, K.J., & Hodgkinson, G.P. (eds.) (2018). Methodological challenges and advances in managerial and organizational cognition. Emerald Publishing Limited Greve, H. R., & Taylor, A. (2000). Innovations as catalysts for organizational change: Shifts in organizational cognition and search. Administrative Science Quarterly, 45 (1), 54–80. Gustafsson, R., Sund, K. J., & Galavan, R. (2023). What are cognitive aids in strategy? In K. J. Sund, R. Galavan, & R. Gustafsson (Eds.). Cognitive aids in strategy. Emerald Group Publishing. Herzog, S. M., & Hertwig, R. (2009). The wisdom of many in one mind: Improving individual judgments with dialectical bootstrapping. Psychological Science, 20 (2), 231–237. Hodgkinson, G. P., & Healey, M. P. (2011). Psychological foundations of dynamic capabilities: Reflexion and reflection in strategic management. Strategic Management Journal, 32, 1500–1516. Hodgkinson, G. P., Sund, K. J., & Galavan, R. J. (2018). Exploring methods in managerial and organizational cognition: Advances, controversies, and

4 Cognition and Business Model Innovation

87

contributions. In Robert J. Galavan, Kristian J. Sund, & Gerard P. Hodgkinson (Eds.), Methodological challenges and advances in managerial and organizational cognition (pp. 1–22). Emerald Publishing Limited. Huff, A. S., Milliken, F. J., Hodgkinson, G. P., Galavan, R. J., & Sund, K. J. (2016). A conversation on uncertainty in managerial and organizational cognition. In Uncertainty and strategic decision making (pp. 1–31). Emerald Group Publishing Limited. Jensen, H., & Sund, K. J. (2017). The journey of business model innovation in media agencies: Towards a three-stage process model. Journal of Media Business Studies, 14 (4), 282–298. Kahneman, D. (2011). Thinking, fast and slow. Farrar Straus and Giroux. Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press. Kim, I. H. S., Ku, T. Y. D., & Lee, B. Y. M. (2020). Business model schema: Business model innovation tool based on direct causal mechanisms of profit. Technology Analysis & Strategic Management, 32(4), 379–396. Kim, S. K., & Min, S. (2015). Business model innovation performance: When does adding a new business model benefit an incumbent? Strategic Entrepreneurship Journal, 9 (1), 34–57. Klayman, J., Soll, J. B., Gonzalez-Vallejo, C., & Barlas, S. (1999). Overconfidence: It depends on how, what, and whom you ask. Organizational Behavior and Human Decision Processes, 79 (3), 216–247. Laureiro-Martínez, D., & Brusoni, S. (2018). Cognitive flexibility and adaptive decision-making: Evidence from a laboratory study of expert decision makers. Strategic Management Journal, 39 (4), 1031–1058. Lindskov, A., Sund, K. J., & Dreyer, J. K. (2021). The search for hypercompetition: Evidence from a nordic market study. Industry and Innovation, 28(9), 1099–1128. Lindskov, A., Sund, K. J., Dreyer, J. K., & Yu, J. (2023). The regional and temporal nature of hypercompetition. Long Range Planning, 56 (4), 102328. Loon, M., Otaye-Ebede, L., & Stewart, J. (2020). Thriving in the new normal: The HR microfoundations of capabilities for business model innovation. An integrated literature review. Journal of Management Studies, 57 (3), 698–726. Martins, L. L., Rindova, V. P., & Greenbaum, B. E. (2015). Unlocking the hidden value of concepts: A cognitive approach to business model innovation. Strategic Entrepreneurship Journal, 9 (1), 99–117. Mezias, J. M., & Starbuck, W. H. (2003). Studying the accuracy of managers’ perceptions: A research odyssey. British Journal of Management, 14 (1), 3–17.

88

K. J. Sund

Mozheiko, S., & Sund, K. J. (2024). Managing the dual business model tradeoff in multinational corporations. Journal of Business Models. Forthcoming. Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. John Wiley & Sons. Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. The Free Press. Schneckenberg, D., Velamuri, V., & Comberg, C. (2019). The design logic of new business models: Unveiling cognitive foundations of managerial reasoning. European Management Review, 16 (2), 427–447. Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future research agenda. International Journal of Innovation Management, 17 (1), 1–34. Shepherd, D. A., Seyb, S. K., & George, G. (2023). Grounding business models: Cognition, boundary objects, and business model change. Academy of Management Review, 48(1), 100–122. Snihur, Y. (2018). Responding to business model innovation: Organizational unlearning and firm failure. The Learning Organization, 25 (3), 190–198. Snihur, Y., & Tarzijan, J. (2018). Managing complexity in a multi-businessmodel organization. Long Range Planning, 51(1), 50–63. Snihur, Y., Thomas, L. D. W., & Burgelman, R. A. (2018). The performative power of words: How business model innovators use framing for strategic advantage. In Kristian J. Sund, Robert J. Galavan, & Stefano Brusoni (Eds.), Cognition and Innovation. Emerald Publishing. Snihur, Y., & Wiklund, J. (2019). Searching for innovation: Product, process, and business model innovations and search behavior in established firms. Long Range Planning, 52(3), 305–325. Sosna, M., Trevinyo-Rodríguez, R. N., & Velamuri, S. R. (2010). Business model innovation through trial-and-error learning: The Naturhouse case. Long Range Planning, 43(2–3), 383–407. Starbuck, W. H., & Mezias, J. M. (1996). Opening Pandora’s box: Studying the accuracy of managers’ perceptions. Journal of Organizational Behavior, 17 (2), 99–117. Sund, K. J. (2013). Scanning, perceived uncertainty, and the interpretation of trends: A study of hotel directors’ interpretation of demographic change. International Journal of Hospitality Management, 33(June), 294–303. Sund, K. J. (2015). Revisiting organizational interpretation and three types of uncertainty. International Journal of Organizational Analysis, 23(4), 588– 660.

4 Cognition and Business Model Innovation

89

Sund, K. J. (2016). A test of perceptual accuracy and overconfidence in a strategic issue context. In K. J. Sund, R. Galavan, & A. Huff (Eds.), Uncertainty and strategic decision making (pp. 101–126). Emerald Group Publishing. Sund, K. J., Bogers, M. L., & Sahramaa, M. (2021). Managing business model exploration in incumbent firms: A case study of innovation labs in European banks. Journal of Business Research, 128(May), 11–19. Sund, K. J., Bogers, M., Villarroel, J. A., & Foss, N. (2016). Managing tensions between new and existing business models. MIT Sloan Management Review, 57 (4), 8. Sund, K. J., Foss, N. J., & Burgelman, R. A. (2023). Why do we fight? Internal conflict and incumbent business model innovation. 83rd Academy of Management Meeting. Sund, K. J., Galavan, R. J., & Bogers, M. (Eds.). (2020a). Business models and cognition. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Bogers, M. (2020b). Exploring the connections between business models and cognition: A commentary. In K. J. Sund, R. J. Galavan, & M. Bogers. Business models and cognition. Emerald Publishing Limited. Sund, K. J., Galavan, R. J., & Brusoni, S. (Eds.). (2018a). Cognition and innovation. Emerald Group Publishing. Sund, K., Galavan, R. J., & Brusoni, S. (2018b). Cognition and innovation: A framework and invitation to explore. In K. J. Sund, R. J. Galavan, & S. Brusoni. Cognition and innovation. Emerald Group Publishing. Sund, K. J., Galavan, R., & Gustafsson, R. (Eds.). (2023). Cognitive aids in strategy. Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Huff, A. (2022). Uncertainty in strategy research. In M. A. Griffin, & G. Grote (Eds.), The Oxford handbook of uncertainty management in work organizations (pp. C3.S1–C3.S7). Oxford University Press. Sund, K. J., & Lindskov, A. (2022). Incumbent business model innovation under misperceived hypercompetition. Journal of Business Models, 10 (1), 11– 18. Sund, K.J., & Rydén, P. (2022). A dialectic method for reducing knowledge overconfidence in students. 26th Biennial Nordic Academy of Management Conference, Örebro, Sweden. Sutcliffe, K. M. (1994). What executives notice: Accurate perceptions in top management teams. Academy of Management Journal, 37 (5), 1360–1378.

90

K. J. Sund

Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), 172–194. Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. Teece, D. J. (2020). Fundamental issues in strategy: Time to reassess? Strategic Management Review, 1(1), 103–144. Wirtz, B., Göttel, V., & Daiser, P. (2016). Business model innovation: Development, concept and future research directions. Journal of Business Models, 4 (1), 1–28. Zott, C., & Amit, R. (2010). Business model design: An activity system perspective. Long Range Planning, 43(2–3), 216–226. Zott, C., & Amit, R. (2008). The fit between product market strategy and business model: Implications for firm performance. Strategic Management Journal, 29 (1), 1–26.

5 Open Questions on Cognition and Business Modelling

Abstract The cognitive turn in business model research has been lauded as holding great promise. The business model can thus be approached as a cognitive construct, a kind of mental map or model of how the business creates and appropriates value. This construct exists in the minds of internal and external stakeholders of the organization and is shaped, shared, and adapted over time. In some incumbent firms, multiple business models may emerge and co-exist, leading to a particular set of challenges to the host organization. Over the past decade, in an effort to document all this, the emergent literature on cognition and business models has seemingly moved in many different directions. This can lead to some degree of confusion for the reader new to this field, especially as for every research question answered, several new ones seem to appear. In this chapter, I conclude this book by very briefly discussing the main existing directions of research and propose a way to structure the identification of open research questions. Keywords Business models · Business model innovation · Cognition · Research gaps · Research questions · Research design

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9_5

91

92

K. J. Sund

Introduction I can start this final chapter with the same observations with which I started the first. “As a newcomer to the emerging research field at the intersection of cognition and business models, how could one start to imagine the many open research questions that exist? This can easily seem like a daunting task, and in my experience be very confusing, particularly for doctoral students new to both the cognition and business model literature. The literature related to managerial and organizational cognition (MOC) is extensive and diverse both in terms of theories, methods, and empirical findings (Galavan et al., 2018). The same could today be said of the general business model and business model innovation literature. Yet the field at the intersection of the two is still nascent.” In this concluding chapter, I will sum up a few of the directions taken by scholars over the past few years, and what the research gaps are, providing a framework with which to identify such gaps in a systematic way.

Gaps Stemming from Dual Process and Affect Theories Whilst research on the cognitive dimensions of business models and business model innovation (BMI) has been increasing, there are in fact numerous gaps in our knowledge. To illustrate these, it may be useful to consider for example the overviews of theoretical and methodological MOC advances presented in Hodgkinson, Galavan, and Sund (2018). Dual processing theory suggests that decision making can be the result of both conscious reasoning and nonconscious intuition (Kahneman, 2011). Furthermore, cognition can be “cold” and rational, or it can be “hot” and emotional (Hodgkinson & Healey, 2011; Hodgkinson et al., 2018). Existing BMI research has almost exclusively been concerned with conscious, cold, and rational cognition, inspired by classical interpretative theory and the idea of mental mapping (Huff, 1990; Sund, 2013, 2015). Within these studies, a variety of theories have been leaned on, including mental model theory, schema theory, and sensemaking.

5 Open Questions on Cognition and Business Modelling

93

The role of emotions thus remains largely unexplored, although they have been acknowledged in the general innovation literature (e.g., Choi et al., 2011). Schneckenberg et al., (2019, p.431) point out that “in the case of business models, the emotional and affective bondages to long-established value-creating and value capturing activity configurations risks resulting in escalation of commitment and cognitive inertia of senior managers”. Exploring further this role of emotions could help clarify and deepen our understanding of the cognitive barriers to BMI in incumbent firms, and there are early indications that this may be particularly relevant in the study of family firm BMI (Rau, 2013). Similarly, the role of nonconscious cognitive biases during both entrepreneurial and incumbent BMI remains underexplored. For example, what exactly is the role of heuristics in business modelling? Does a strong heuristic act as a constraint on creativity, and thus limit available options during business modelling? How does overconfidence and the problem of positive illusions affect business model exploration (Sund, 2016)? Such questions remain largely unexplored in the business model literature and could open a path for fresh exploration.

Open Research Questions Identified in Existing Reviews How do we create some structure to the question of open research questions? A traditional way is to conduct a literature review to examine what roads existing studies have taken, and to use these as points of departure from which to suggest unanswered questions. This traditional approach tends, however, to result in either very incremental suggestions for further research, or very generic ones. Several such literature review articles on both business models and business model innovation have been published in important journals over the past decade (unfortunately none of which focus exclusively on a cognitive perspective), and a reading of these gives us a list of research questions identified therein. A majority of these research questions do not explicitly make reference to cognitive theory or a cognitive perspective on business models. However, some do. Thus, Table 5.1 contains an overview of open research questions as I have

94

K. J. Sund

identified them in some of the main literature review articles published over the past decade or so. The list of articles is not exhaustive, and I include a few articles that, although more conceptual pieces than review articles per se, are nevertheless highly cited and explicitly mention opportunities for further research at the intersection of cognition and business models. Table 5.1 is not meant to be complete, but to provide a small overview with which I can make an important point. A careful reading of Table 5.1 indicates that although many reviews emphasize the “cognitive agenda” (Spieth et al., 2014, p. 243) as being both emergent and important, few present specific suggestions for further research in this area. The few suggested research questions are in fact wider research gaps, rather than specific questions. They are thus quite general. Only a few indicate what the relevant theory of cognition might be, such as the interpretative view (Baden-Fuller & Haefliger, 2013), sensemaking theory (Spieth et al., 2014), judgment (Foss & Saebi, 2018), schema theory (Massa et al., 2017), or framing theory (Spieth et al., 2014). A more targeted literature review article on cognition and business models (which I have not seen yet in the literature) would provide better answers, but for now, the reader needs to look elsewhere to identify more specific directions for research.

Creating Research Questions How else do we create some structure to the identification of open research questions? One important factor, as indicated above, is the grounding of such questions in theories of cognition. In chapter 1 in this book, I provided an overview of some of the cognition theories that have started to be explored in business model research. A second factor to consider is the organizational context studied. The context of a startup is for example very different to that of an incumbent firm. A third is the level of analysis, and how a particular study moves between levels. This was discussed in Chapters 2 and 3, for the individual and sociocognitive levels respectively, but was also a focus in Chapter 4, in which I presented a framework for thinking about contexts. A fourth and final factor to consider is time, i.e., the importance of process. As indicated in

Baden-Fuller and Mangematin (2013)

(continued)

Research to explore how multiple BMI processes may interact dynamically over time, viewing “the BM as a dynamic bundle of qualities (Langley et al., 2013) and all the observed elements and actors of BM as momentary instantiations of processes” (p.1107) When are feedback loops adjustive and when are they generative for BMI? What are the feedback loops that generate incremental BMI processes, and which loops contribute to disruptive ones? How can multiple actors’ interactions be depicted in BMI processes? Research “to recognize where rational decisionmaking deserves its rightful place, and where other, possibly finer forms of deliberation and perception should guide managerial action.” An essay that explores “how business models can be seen as a set of cognitive configurations that can be manipulable in the minds of managers (and academics).” (p.418) Are there different requirements of cognitive capacity for different business models? How are perceived cause-effect configurations linked to behavior and key strategic decisions? Does a not-for-profit business model require managers to adopt novel cognitive frames? In the minds of observers and key actors, are there perceived status ordering among business models?

Andreini et al., (2022)

Baden-Fuller and Haefliger (2013)

Identified open research questions (examples)

Review article

Table 5.1 Open research questions at the intersection of cognition and business models explicitly identified in selected literature review articles

5 Open Questions on Cognition and Business Modelling

95

“Which borrowed constructs from various research domains could improve the BM concept?” (p.490) (Cognition not explicitly mentioned) Cognition is seen as a research gap and as a potential moderator variable for business model innovation in general terms. “The role of cognition in managerial decisions related to BM change and innovation is increasingly in focus in the literature.” (p.213) “What is the role of entrepreneurial “vision”, “imagination” and “judgment” in the design of BM and BMI?” (p.18) “Role of managerial cognition/characteristic of top management team in BMI?” (p.18) Although this is a book, the authors provide brief reviews and comments on many different theoretical perspectives that have been and could be applied to business model innovation research, highlighting in general terms that cognitive theories hold high promise Not mentioned explicitly in this review on sustainable business model innovation Not mentioned explicitly “Are certain cognitive/linguistic schema more likely to allow managers to overcome radical technological change?” (p.95) “How do cognitive schema and narratives of entrepreneurs versus intrapreneurs help them craft demand-side business models?” (p.96)

Budler et al., (2021)

Klang et al., (2014) Massa et al., (2017)

Geissdoerfer et al., (2018)

Gassmann et al., (2016)

Foss and Saebi (2018)

Foss and Saebi (2017)

Identified open research questions (examples)

Review article

Table 5.1 (continued)

96 K. J. Sund

“What determines the process and elements of business model innovation in specific contexts?” (p.23, not explicitly mentioning cognition) “Another promising aspect for future research on business model innovation is the cognitive agenda, which is linked to microfoundational sources of dynamic capabilities and the field of behavioral strategy. This aspect comprises, for example, the relationship between cognition and business model innovation, and the combination of analytic and intuitive management skills for sensing and opportunity recognition of the firm. Interdependencies between specific leadership styles, cognitive modes and business model innovation are equally interesting Opportunity recognition and processes of sense making versus cognitive biases—such as escalation of commitment, bounded rationality and path dependencies of decision making—will almost certainly have an impact on processes of business model innovation. And finally questions on strategic agility and entrepreneurial/intrapreneurial actions arise: Which capabilities, enabling factors and conditions allow decision makers to experiment with and enact new business models in organizations? What are methods for reframing dominant logic in business model innovation and counteracting not-invented here syndrome?” (p.243) “Future research on BMI should reduce its efforts to produce further case study-based investigations and rather head towards well-founded conceptual articles that stabilize and consolidate basic research as well as confirmatory quantitative empirical investigations, especially large-scale quantitative multivariate methods that allow generalization and disconfirmation of misleading concepts and conclusion.” (p.17) “Scholars need to develop the theoretical foundations of the business model and shed light on its conceptual distinction from other related concepts such as new organizational forms, ecosystems, activity systems, and value chains or value networks.” (p.1038) How can the cognitive inability of managers to understand the value potential of a new business model be overcome?

Schneider and Spieth (2013)

Zott et al., (2011)

Wirtz et al., (2016)

Spieth et al., (2014)

Identified open research questions (examples)

Review article

5 Open Questions on Cognition and Business Modelling

97

98

K. J. Sund

Table 5.1, several review article authors have emphasized the importance of process (Andreini et al., 2022; Spieth et al., 2014), as have numerous studies of business model innovation (e.g., Jensen & Sund, 2017). This was the subject of a longer discussion in Chapter 4 in this book.

Theoretical Grounding Beyond the simple observation that the business model can be studied as a cognitive construct, recipe, or mental model, the shaping, sharing, and changing of that model can be explained by a variety of different theories of cognition, depending on the research question asked and empirical setting observed. Such theories include interpretation theory, sensemaking, mental models and mapping of these, schema theory, framing theory, the attention-based view, dual processing theory, theories related to cognitive bias, emotions, intuition, heuristics, identity theory, theories of organizational culture, theories of traits and personality, learning theories, or memory theories. As discussed in earlier chapters, a number of these theories have already been introduced to the business model and business model innovation literature, but there remain many opportunities to further study business models and their change through the lenses of the various theories mentioned above.

Organizational Context The study of business models and of business model innovation will to a large extent be influenced by the context. Here there are many open research questions. So far, studies have tended to differentiate simply between the entrepreneurial start-up context, and the incumbent context. This has already been discussed in earlier chapters. However, there are opportunities for further refining and contextualizing the study of business models. One example of an unexplored set of research questions is how the shaping and sharing of mental business models take place across both the organizational and industry life cycles. The organizational life cycle model holds that as organizations grow over time, they go through life cycle stages that present the organization with particular

5 Open Questions on Cognition and Business Modelling

99

challenges (Greiner, 1972). For example, the focus of top management changes across these stages (Smith et al., 1985). The exact number of stages has been open to some debate, with Greiner (1972) identifying 5 stages (for a discussion see e.g., Lester et al., 2003). Life cycle stage was nonetheless in the 1980s and 1990s seen as an important contingency variable (Dodge & Robbins, 1992), that seems to have lost some of its appeal. Despite this, instead of treating incumbents under a common label, it might be useful to study the life cycle stage as a contingency variable in studies of incumbent business modelling. Similarly, the wider industry may be at different stages of a life cycle (Porter, 1980). Thus, business modelling in a declining industry may be very different to business modelling in a growing industry. There may be other ways too of defining organizational context, including studying the specific contexts of family businesses, non-profit organizations, public sector organizations, and so forth. My point here is merely that by considering carefully the possible organizational contexts within which cognition and business model theory can be combined, one can identify very many open research questions.

Level of Analysis I discussed level of analysis extensively in previous chapters, so here I will simply reiterate that cognition, the business model, and business modelling can be studied at multiple levels of analysis: individual, team, organizational, inter-organizational, and even institutional. Open research questions can be identified not only at each level of analysis, but also regarding the connections between levels.

Process Stage (Temporal Analysis) Finally, studies of cognition and business models can be conducted at a single point in time, i.e., using cross-sectional theory and analysis, or as a process in time, i.e., using longitudinal data. Some research questions and organizational contexts will lend themselves more naturally to

100

K. J. Sund

a cross-sectional study, while others will lend themselves more naturally to a longitudinal study.

Concluding Thoughts This short chapter does obviously not do justice to the very many open questions that exist regarding cognition and business models (see also e.g., the discussions in Sund et al., 2020b; Sund et al., 2018b). The first decade or so of research into this field has resulted in a growing number of studies adopting a variety of theories of cognition (see e.g., the contributions in Sund et al., 2020a; Sund et al., 2018a). However, these studies have also opened space for even more research questions. Considering the numerous topics and associated theories of the cognition space, as well as the great diversity of organizational contexts within which the business modelling phenomenon can be studied, there is ample opportunity for researchers to come up with creative research questions. Some scholars have recently started to call for a stop to small-n inductive studies, in favor of large-n confirmatory, deductive studies (Wirtz et al., 2016), but the truth is that there is still ample space for more exploratory work, as well as work to replicate, extend, and consolidate existing studies. In 2013, Baden-Fuller and Mangematin (2013, p.419) wrote that “most challenging and promising is the cognitive agenda” on business models. Ten years later, the emergent field at the intersection of cognition and business models continues to hold great promise, and I would venture so far as to assert that the cognitive view of business modelling is likely to become the dominant one over the next decade.

References Andreini, D., Bettinelli, C., Foss, N. J., & Mismetti, M. (2022). Business model innovation: A review of the process-based literature. Journal of Management and Governance, 26 (4), 1089–1121.

5 Open Questions on Cognition and Business Modelling

101

Baden-Fuller, C., & Haefliger, S. (2013). Business models and technological innovation. Long Range Planning, 46 (6), 419–426. Baden-Fuller, C., & Mangematin, V. (2013). Business models: A challenging agenda. Strategic Organization, 11(4), 418–427. Budler, M., Župiˇc, I., & Trkman, P. (2021). The development of business model research: A bibliometric review. Journal of Business Research, 135, 480–495. Choi, J. N., Sung, S. Y., Lee, K., & Cho, D. S. (2011). Balancing cognition and emotion: Innovation implementation as a function of cognitive appraisal and emotional reactions toward innovation. Journal of Organizational Behavior, 32(1), 107–124. Dodge, H. R., & Robbins, J. E. (1992). An empirical investigation of the organizational life cycle. Journal of Small Business Management, 30 (1), 27. Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: How far have we come, and where should we go? Journal of Management, 43(1), 200–227. Foss, N. J., & Saebi, T. (2018). Business models and business model innovation: Between wicked and paradigmatic problems. Long Range Planning, 51(1), 9–21. Galavan, R.J., Sund, K.J., & Hodgkinson, G.P. (Eds.). (2018). Methodological Challenges and Advances in Managerial and Organizational Cognition. Emerald Publishing Limited Gassmann, O., Frankenberger, K., & Sauer, R. (2016). Exploring the field of business model innovation: New theoretical perspectives. Springer. Geissdoerfer, M., Vladimirova, D., & Evans, S. (2018). Sustainable business model innovation: A review. Journal of Cleaner Production, 198, 401–416. Greiner, L. E. (1972). Evolution and revolution as organizations grow. Harvard Business Review, 50 (4), 37–46. Hodgkinson, G. P., & Healey, M. P. (2011). Psychological foundations of dynamic capabilities: Reflexion and reflection in strategic management. Strategic Management Journal, 32, 1500–1516. Hodgkinson, G. P., Sund, K. J., & Galavan, R. J. (2018). Exploring methods in managerial and organizational Cognition: Advances, controversies, and contributions. In R. J. Galavan, K. J. Sund, & G. P. Hodgkinson (Eds.), Methodological challenges and advances in managerial and organizational cognition (pp. 1–22). Emerald Publishing Limited. Huff, A.S. (Ed.) (1990). Mapping strategic thought. Wiley.

102

K. J. Sund

Jensen, H., & Sund, K. J. (2017). The journey of business model innovation in media agencies: Towards a three-stage process model. Journal of Media Business Studies, 14 (4), 282–298. Kahneman, D. (2011). Thinking, fast and slow. Farrar Straus and Giroux. Klang, D., Wallnöfer, M., & Hacklin, F. (2014). The business model paradox: A systematic review and exploration of antecedents. International Journal of Management Reviews, 16 (4), 454–478. Langley, A., Smallman, C., Tsoukas, H., & Van de Ven, A. H. (2013). Process studies of change in organization and management: Unveiling temporality, activity, and flow. Academy of Management Journal, 56 , 1–13. Lester, D. L., Parnell, J. A., & Carraher, S. (2003). Organizational life cycle: A five-stage empirical scale. International Journal of Organizational Analysis, 11(4), 339–354. Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. Academy of Management Annals, 11(1), 73–104. Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. Free Press. Rau, S. B. (2013). Emotions preventing survival of family firms: Comments on exploring the emotional nexus in cogent family business archetypes: Towards a predominant business model Inclusive of the emotional dimension. Entrepreneurship Research Journal, 3(3), 425–432. Schneckenberg, D., Velamuri, V., & Comberg, C. (2019). The design logic of new business models: Unveiling cognitive foundations of managerial reasoning. European Management Review, 16 (2), 427–447. Schneider, S., & Spieth, P. (2013). Business model innovation: Towards an integrated future research agenda. International Journal of Innovation Management, 17 (1), 1–34. Smith, K. G., Mitchell, T. R., & Summer, C. E. (1985). Top level management priorities in different stages of the organizational life cycle. Academy of Management Journal, 28(4), 799–820. Spieth, P., Schneckenberg, D., & Ricart, J. E. (2014). Business model innovation–state of the art and future challenges for the field. R&D Management, 44 (3), 237–247. Sund, K. J. (2013). Scanning, perceived uncertainty, and the interpretation of trends: A study of hotel directors’ interpretation of demographic change. International Journal of Hospitality Management, 33, 294–303. Sund, K. J. (2015). Revisiting organizational interpretation and three types of uncertainty. International Journal of Organizational Analysis, 23(4), 588– 660.

5 Open Questions on Cognition and Business Modelling

103

Sund, K. J. (2016). A test of perceptual accuracy and overconfidence in a strategic issue context. In K. J. Sund, R. Galavan, & A. Huff (Eds.), Uncertainty and strategic decision making (pp. 101–126). Emerald Group Publishing. Sund, K. J., Galavan, R. J., & Bogers, M. (Eds.). (2020a). Business models and cognition. Emerald Publishing Limited. Sund, K. J., Galavan, R. J., & Bogers, M. (2020b). Exploring the connections between business models and cognition: A commentary. In K. J. Sund, R. J. Galavan, & M. Bogers (Eds.), Business models and cognition. Emerald Publishing Limited. Sund, K. J., Galavan, R. J., & Brusoni, S. (Eds.). (2018a). Cognition and innovation. Emerald Group Publishing. Sund, K., Galavan, R. J., & Brusoni, S. (2018b). Cognition and innovation: A framework and invitation to explore. In K. J. Sund, R. J. Galavan, & S. Brusoni. Cognition and Innovation. Emerald Group Publishing. Wirtz, B., Göttel, V., & Daiser, P. (2016). Business model innovation: Development, concept and future research directions. Journal of Business Models, 4 (1), 1–28. Zott, C., Amit, R., & Massa, L. (2011). The business model: Recent developments and future research. Journal of Management, 37 (4), 1019–1042.

Index

A

activity 2, 13, 14, 29, 31, 34, 35, 70, 97

framework 2, 5, 6, 14, 28, 37, 39, 48, 57, 62, 72, 73, 75, 77, 83, 92, 94 framing. See frames

B

bias 9, 10, 81, 98

I

intuition 7, 78, 92, 98 C

cognitive aids 6, 34, 35, 48, 52, 55, 56, 62, 83

K

knowledge 3, 7, 10, 13, 14, 16, 28, 30, 32, 34, 36, 51, 52, 59, 61, 71, 81, 82, 92

E

emotions 9, 11, 12, 28, 40, 41, 50, 58, 74, 84, 93, 98

L

logic 7, 31, 39, 40, 70, 71, 73, 76, 78, 97 F

frames 8, 9, 27, 54, 95

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. J. Sund, Cognition and Business Models, https://doi.org/10.1007/978-3-031-51598-9

105

106

Index

M

S

mapping 25, 35, 36, 39, 98 mental map vii, 2, 30, 32–34, 36, 40, 57, 92

schema 2, 8, 14, 26, 28, 35, 39, 53, 60, 70, 71, 92, 94, 96, 98 sensemaking vii, 2, 8, 27, 39, 48, 51, 53, 63, 71, 78, 84, 92, 94, 98 strategy vi, 1, 6, 7, 12, 16, 29–31, 34, 36, 38, 55, 56, 62, 70, 78, 83, 97

N

nonconscious 10, 11, 74, 92, 93 O

organizational learning 7, 15 P

U

process vii, 2, 8, 9, 12–14, 28, 39, 41, 48, 50, 55, 56, 63, 69, 71, 72, 74, 76, 77, 79, 81, 82, 84

uncertainty 6, 9, 27, 35, 51, 55, 74, 80 unlearning 15, 79