Understanding Supply Chain Digitalization Through Actor-Network Theory: The Interplay Between Blockchain, Accounting and Management Control 3031309871, 9783031309878

Table of contents :
Foreword
Preface
Acknowledgements
Contents
Abbreviations and Acronyms
Chapter 1: Information Technologies for Business Management: From Big Data to Blockchain, a Literature Overview
1.1 Introduction
1.2 What Is Big Data?
1.3 BD and Management Issues
1.3.1 BD in Management Accounting and Control Activities
1.4 What Is Blockchain?
1.5 Blockchain and Management Accounting Issues
1.6 Literature Shortcomings and Research´s Objectives
1.7 Conclusion
References
Chapter 2: Theoretical Framework: The Actor-Network Theory (ANT)
2.1 Introduction
2.2 Conceptualizing Technology in Management Research: Why ANT?
2.3 What Is Ant? A Historical Background
2.3.1 Power
2.3.2 Actors
2.3.3 Actor-Network
2.3.4 Control
2.4 The Sociology of Translation
2.5 Latour´s Five Sources of Uncertainty
2.6 ANT in Management Accounting and Control Studies
2.6.1 ANT in Business Information Technologies Studies
2.7 Research Questions Development
2.8 Conclusion
References
Chapter 3: Research Methodology
3.1 Introduction
3.2 The Paradigm Concept
3.2.1 Ontology
3.2.2 Epistemology
3.2.3 Methodology
3.3 Historical Approaches to Social Studies
3.3.1 Positivism
3.3.2 Postpositivism
3.3.3 Interpretivism
3.4 The Case Study Method
3.4.1 Triangulation
3.5 Case Selection and Data Collection
3.6 Conclusion
References
Chapter 4: Unboxing the Network: The Empirical Case Study
4.1 Introduction
4.2 Background
4.3 The First Source of Uncertainty: The Nature of Groups
4.4 The Second Source of Uncertainty: The Nature of Actions
4.4.1 The Role of Management Control Activities in Network Creation
4.5 The Third Source of Uncertainty: The Nature of Objects
4.5.1 The Accounting Objects
4.5.2 The Blockchain Objects
4.6 The Fourth Source of Uncertainty: Matter of Facts Vs. Matter of Concerns
4.7 The Fifth Source of Uncertainty: The Nature of the Study Itself
4.8 Discussion
4.9 Conclusion
References
Chapter 5: Conclusion, Managerial Implications and Limitations
References
Annex 1: Draft of the Questions Made During the Semi-Structured Interviews

Citation preview

SIDREA Series in Accounting and Business Administration

Gianluca Vitale

Understanding Supply Chain Digitalization Through Actor-Network Theory The Interplay Between Blockchain, Accounting and Management Control

SIDREA Series in Accounting and Business Administration Series Editors Stefano Marasca, Università Politecnica delle Marche, Ancona, Italy Anna Maria Fellegara, Università Cattolica del Sacro Cuore, Piacenza, Italy Riccardo Mussari, Università di Siena, Siena, Italy Editorial Board Members Stefano Adamo, University of Lecce, Leece, Italy Luca Bartocci, University of Perugia, Perugia, Italy Adele Caldarelli, University of Naples Federico II, Naples, Italy Bettina Campedelli, University of Verona, Verona, Italy Nicola Castellano, University of Pisa, Pisa, Italy Denita Cepiku, University of Rome Tor Vergata, Rome, Italy Lino Cinquini , Sant’Anna School of Advanced Studies, Pisa, Italy Maria Serena Chiucchi, Marche Polytechnic University, Ancona, Italy Vittorio Dell’Atti, University of Bari Aldo Moro, Bari, Italy Francesco De Luca , University of Chieti-Pescara, Pescara, Italy Anna Maria Fellegara, Catholic University of the Sacred Heart, Piacenza, Italy Raffaele Fiorentino, University of Naples Parthenope, Naples, Italy Francesco Giunta, University of Florence, Florence, Italy Alberto Incollingo , University of Campania “Luigi Vanvitelli”, Caserta, Italy Giovanni Liberatore, University of Florence, Florence, Italy Andrea Lionzo , Catholic University of the Sacred Heart, Milano, Italy Rosa Lombardi, University of Rome, Sapienza, Roma, Italy Davide Maggi, Amedeo Avogadro University of Eastern Piedmont, Novara, Italy Daniela Mancini , University of Teramo, Teramo, Italy Francesca Manes Rossi, University of Naples Federico II, Naples, Italy Luciano Marchi, University of Pisa, Pisa, Italy Riccardo Mussari, University of Siena, Siena, Italy Marco Maria Mattei, University of Bologna, Forlì, Italy Antonella Paolini, University of Macerata, Macerata, Italy Mauro Paoloni, University of Rome Tor Vergata, Rome, Italy Paola Paoloni, University of Rome Tor Vergata, Rome, Italy, Sapienza University of Rome, Rome, Italy Marcantonio Ruisi, University of Palermo, Palermo, Italy Claudio Teodori, University of Brescia, Brescia, Italy Simone Terzani, University of Perugia, Perugia, Italy Stefania Veltri, University of Calabria, Rende, Italy

This is the official book series of SIDREA - the Italian Society of Accounting and Business Administration. This book series is provided with a wide Scientific Committee composed of Academics by SIDREA. It publishes contributions (monographs, edited volumes and proceedings) as a result of the double blind review process by the SIDREA’s thematic research groups, operating at the national and international levels. Particularly, the series aims to disseminate specialized findings on several topics – classical and cutting-edge alike – that are currently being discussed by the accounting and business administration communities. The series authors are respected researchers and professors in the fields of business valuation; governance and internal control; financial accounting; public accounting; management control; gender; turnaround predictive models; non-financial disclosure; intellectual capital, smart technologies, and digitalization; and university governance and performance measurement.

Gianluca Vitale

Understanding Supply Chain Digitalization Through Actor-Network Theory The Interplay Between Blockchain, Accounting and Management Control

Gianluca Vitale Department of Business and Law University of Siena Siena, Italy

ISSN 2662-9879 ISSN 2662-9887 (electronic) SIDREA Series in Accounting and Business Administration ISBN 978-3-031-30987-8 ISBN 978-3-031-30988-5 (eBook) https://doi.org/10.1007/978-3-031-30988-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To Loredana, for sharing every sacrifice that life put ahead. Without her, this monograph would have never been written.

Foreword

Starting from the calls of different authors in the literature to investigate the issues of big data and blockchain applications in business management, this study aims to investigate the case of the first blockchain application in Europe in an agro-food supply chain. In particular, given the lack of empirical evidence on the impact of these new technologies on accounting and management control, this research work is among the first on this topic providing preliminary empirical results. Combining the actor-network theory perspectives of Callon (1986) [The sociology of translation] and Latour (2005) [The five sources of uncertainty] and through the methodology of the single case study, this research work offers important empirical evidence and managerial implications. The study shows how, contrary to the theoretical assumptions proposed in the literature, the traditional accounting and control activities improved the blockchain and fostered its correct implementation within the network. Accounting is the information base on which the technology is customized and built. Moreover, accounting and management control activities remedy some of blockchain’s intrinsic defects, thus representing the engine of this technology. The blockchain, for its part, proves to be a “superstructure” of the traditional accounting system that, by expanding the visual space for calculations, extends the monitoring activities within the supply chain, allowing the action at distance, improving interorganizational controls and putting order within the network. Finally, “unboxing” the whole path of blockchain adoption and the related network creation process allowed the author to present several managerial solutions that are useful for the effective implementation of the blockchain and for overcoming the barriers to its adoption. University of Siena, Siena, Italy

Gianluca Vitale

vii

Preface

Information technologies are acquiring an increasingly leading role in business management. Although these technologies have been used in companies since the 1960s, it is only recently that they are undergoing rapid and growing evolution, responding to an increasingly wide range of business needs and functions. In the last decade, in particular, there has been much talk about big data (BD) technologies and their potential in revolutionizing business management (McAfee and Brynjolfsson, 2012). By virtue of this debate, many academics have begun to study the phenomenon from different perspectives focusing on the different business contexts in which BD could have a significant impact. Even more recently, especially in the last two years of this decade, a particular BD-based technology is gaining the attention of both practitioners and academics: the blockchain. This technology, born in the 1990s, has found, in recent years, effective use in the world of virtual finance and bitcoins. Little by little, this technology, which is characterized by guaranteeing the immutability of the data and the impossibility of tampering with them, has also found use in other more operational contexts such as the supply chains (Kshetri, 2018). This, therefore, has diverted the attention of scholars to the effects that the blockchain could have on several corporate functions such as accounting, control and supply chain management. Despite the great debate that exists in the literature about the potential that BD applications (including blockchain) can have in the different fields of business management, there is still very little empirical evidence in this regard. About this, many authors in the literature underline the need to conduct new studies that lead to empirical results on the application of current BD technologies (such as blockchain) in different business areas (Arnaboldi et al., 2017; Lombardi et al., 2022; Lombardi and Secundo, 2021; Maffei et al., 2021; Mancini et al., 2021; Quattrone, 2016; Rikhardsson and Yigitbasioglu, 2018; Saberi et al., 2019; Secinaro et al., 2022; Shyshkova, 2018; Vitale et al., 2020). Given these premises, this research aimed at investigating one of the earliest blockchain applications in Europe to find preliminary empirical results regarding the use of this technology. More specifically, this study investigates the implementation of blockchain within an agro-food supply chain focusing on the interplay dynamics ix

x

Preface

that occurred between this technology and traditional accounting and control systems throughout the installation process and after its acceptance and spread within the supply chain. Therefore, by relying on actor-network theory (ANT) (Callon, 1986a, 1986b; Callon and Latour, 1981; Latour, 1995, 2005) and the case of the first European application of blockchain in the food supply chain, this research work has a twofold purpose. On one hand, it will provide first empirical evidence on the barriers and managerial solutions that are necessary for the adequate adoption of the blockchain. On the other hand, it will also give equally preliminary results regarding how traditional accounting systems and blockchain affect each other, also underlying the effects that one has on the other and vice versa. In this sense, given the preliminary nature of the results, this study should be considered as one of the pioneers on the topics: blockchain and business management and, more specifically, blockchain and accounting. Against this background, this study represents a practical example for managers and professionals on how to implement blockchain technology within companies. Furthermore, practitioners can find out how traditional management accounting and control mechanisms can overcome the barriers to blockchain adoption. The monograph is structured as follows. The first chapter presents a review of the literature concerning the definition of BD and blockchain and their applications in business management. In this chapter, a particular focus is devoted to the applications of these technologies in the area of accounting and management control since these topics represent the key elements of this research. In the second chapter, space is given to the theory and explanation of those theoretical assumptions that will be used in the empirical chapter to interpret the case study results. The methodology is outlined in the third chapter. In particular, there is an examination of historical approaches to social research. The discussion of these topics is functional to the explanation of the choice of the research methodology adopted (the case study) which is then discussed in the concluding part of the chapter. In the fourth chapter, the case study is examined and discussed through the theoretical assumptions proposed in the second chapter. In particular, by combining the frameworks of the sociology of translation (Callon, 1986a) and the sources of uncertainty (Latour, 2005), the path through which the blockchain was implemented and the related network built is “unboxed” to highlight the role that traditional accounting and control systems have played in this path is analysed. Finally, the conclusion section presents the contribution of this research against the literature background as well as the managerial implications that emerged from the case study and the research limitations. Siena, Italy

Gianluca Vitale

Acknowledgements

I am grateful to Prof. Rosa Lombardi and Prof. Patrizia Pastore for the precious support they gave me in the publication steps of this research work. I would like to thank the two anonymous reviewers for their valuable suggestions that significantly improved the scientific rigour, clarity and readability of this monograph. Many thanks to Prof. Roberto Di Pietra for his strategical advice that effectively supported the publication of this monograph. Moreover, special thanks go to Prof. Pasquale Ruggiero for his valuable advice on the theoretical assumptions underlying this work. Finally, I am extremely thankful to Prof. Angelo Riccaboni for the support in the case study development, for his daily guidance in my research activities and for all his professional teachings. He decisively contributed to shaping the researcher I am, and I will always be grateful to him.

xi

Contents

1

2

3

Information Technologies for Business Management: From Big Data to Blockchain, a Literature Overview . . . . . . . . . . . 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 What Is Big Data? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 BD and Management Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 BD in Management Accounting and Control Activities . . 1.4 What Is Blockchain? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Blockchain and Management Accounting Issues . . . . . . . . . . . . 1.6 Literature Shortcomings and Research’s Objectives . . . . . . . . . . 1.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 2 4 5 7 10 13 18 18 23 23

Theoretical Framework: The Actor-Network Theory (ANT) . . . . . 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Conceptualizing Technology in Management Research: Why ANT? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 What Is Ant? A Historical Background . . . . . . . . . . . . . . . . . . . 2.3.1 Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Actors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Actor-Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 The Sociology of Translation . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Latour’s Five Sources of Uncertainty . . . . . . . . . . . . . . . . . . . . 2.6 ANT in Management Accounting and Control Studies . . . . . . . . 2.6.1 ANT in Business Information Technologies Studies . . . . 2.7 Research Questions Development . . . . . . . . . . . . . . . . . . . . . . . 2.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24 26 27 28 29 30 30 33 36 37 39 41 42

Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

47 47 xiii

xiv

Contents

3.2

The Paradigm Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Epistemology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Historical Approaches to Social Studies . . . . . . . . . . . . . . . . . . . 3.3.1 Positivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Postpositivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.3 Interpretivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 The Case Study Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 Triangulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Case Selection and Data Collection . . . . . . . . . . . . . . . . . . . . . . 3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

48 50 50 51 52 52 53 54 56 60 62 65 67

Unboxing the Network: The Empirical Case Study . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 The First Source of Uncertainty: The Nature of Groups . . . . . . . 4.4 The Second Source of Uncertainty: The Nature of Actions . . . . . 4.4.1 The Role of Management Control Activities in Network Creation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 The Third Source of Uncertainty: The Nature of Objects . . . . . . . 4.5.1 The Accounting Objects . . . . . . . . . . . . . . . . . . . . . . . . 4.5.2 The Blockchain Objects . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 The Fourth Source of Uncertainty: Matter of Facts Vs. Matter of Concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 The Fifth Source of Uncertainty: The Nature of the Study Itself . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71 71 71 73 79

95 96 100 101

Conclusion, Managerial Implications and Limitations . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

105 107

Annex 1: Draft of the Questions Made During the Semi-Structured Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

109

4

5

82 86 87 90 92

Abbreviations and Acronyms

ABC ANT BD BDA BI&A BPM BSC DLT ERP IoT IS IT OLAP OPP SAP SMEs

Activity-based costing Actor-network theory Big data Big data analytics Business intelligence and analytics Business performance management Balanced scorecard Distributed ledger Enterprise resource planning Internet of Things Information systems Information technologies On-line analytical processing Obligatory passage point Systems, Applications and Products in Data Processing Small and medium enterprises

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Chapter 1

Information Technologies for Business Management: From Big Data to Blockchain, a Literature Overview

1.1

Introduction

Information is a vital element for business management. It is the “lifeblood of accounting” (Rainer & Cegielski, 2013: p. 61) as well as the main source of support for managerial decision-making processes (March & Hevner, 2007). In particular, support for decision-making processes is greater the higher the quality, accuracy and timeliness of information (March & Hevner, 2007). Information is the meaning that is extracted from data that, in turn, constitute the elementary description of events or activities that have been recorded (Rainer & Cegielski, 2013: p. 10). In other words, data can be compared to a raw material that acquires value only when it is transformed into a final output, or information (Marchi, 2003: pp. 5–6). For this reason, over the years, technologies have been more and more used for the collection and archiving of companies’ data as well as for their organization so that, from them, information can be extracted. Already in the 1950s, academics began to talk about data processing systems and business intelligence (Chen et al., 2012). In this regard, the Italian business literature has a great tradition of studies concerning the application of information systems (IS) in business management from which a great variety of definitions of IS derives. Without claiming to be exhaustive, following the precepts of Amaduzzi (1973), Camussone (1998) and De Marco (1992), IS can be understood as the set of equipment, software and procedures aimed at systematically detecting economic phenomena concerning the company and to produce key information that supports business decisions and management. Over the years, IS and, more in general, information technologies (IT) have evolved rapidly. Despite this, the notions of IS, introduced by the aforementioned authors, remain effective. Indeed, Chen et al. (2012), referring to the most modern Business Intelligence & Analytics (BI&A) systems, define them as the techniques, technologies, systems, practices, methodologies and applications that analyse critical business data to help an enterprise better understanding its business and in making timely decisions. This © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5_1

1

2

1 Information Technologies for Business Management: From Big Data. . .

definition seems to follow the notions of the authors belonging to the Italian business administration tradition, remarking the emphasis on the primary aims of the IS of allowing better and more informed management of companies and supporting decision-making processes (see Amaduzzi, 1973; De Marco, 1992). Although the aims of IS have not significantly changed over time, the IT used in business management has undergone a rapid evolution that Chen et al. (2012) outline in three phases: BI&A 1.0. The first applications of BI&A were based on data management and warehousing. The first BI&A technologies were based on structured enterprisespecific data collected by companies for mainly internal management purposes. This category of BI&A includes the most traditional business information systems such as online analytical processing (OLAP) and business performance management (BPM). BI&A 2.0. With the advent of the Internet, in the 2000s, it took note of the second phase of the evolution of BI&A. The availability of the Internet has opened up the possibility of gathering numerous new data relating to the market and the choices of consumers, extending the use of BI&A also to functions and marketing activities. In this case, therefore, the data collected and processed by the BI&As are no longer just internal but also external. BI&A 3.0. The most recent evolutionary phase of BI&A matches the advent of the Internet of Things (IoT) applications which allow collecting higher volume and variety of context-related data, also allowing the development of forecast scenarios for ever-better support to business management and decisions-making. This last partition includes the recent applications of big data (BD) and big data analytics (BDA) which, based on IoT infrastructures, are progressively revolutionizing business management due to their capacity to collect, analyse and immediately make visible a vast and varied amount of data, thus increasing rationality and timeliness in managerial decisions. Because of their functionality and their usefulness in the managerial field, BD is receiving great attention from both practitioners and business management scholars. In light of this, in the continuation of this chapter, the BD solutions will be discussed and analysed with a particular focus on their application in business management.

1.2

What Is Big Data?

Although the topic of big data is widely studied in the literature, there is no precise, unitary and universally recognized definition. Gandomi and Haider (2015) underline how professionals have a different understanding of BD, distinguishing between what is and what it does. Although there is no shared definition of BD, it is generally defined as the amounts of data that are characterized by their speed, volume and

1.2

What Is Big Data?

3

variety (Laney, 2001). Thus, the framework of the 3 v was introduced by Laney (2001) who, in defining BD, states: Big data are high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

From this definition, a key concept emerges namely that BD needs processing solutions so that useful information can be extracted from them to support decisionmaking. In this regard, Gandomi and Haider (2015) argue that, compared to the past, BD is unstructured and therefore needs appropriate methodologies, processes and technologies so that they can be processed and transformed into information. Such processes, methods and technologies of BD collection and analysis are terminologically enclosed in the generic name of big data analytics (BDA). These reflections are in line with another definition of BD provided by the TechAmerica Foundation’s Federal Big Data Commission (2012), according to which: Big data is a term that describes large volumes of high velocity, complex and variable data that require advanced techniques and technologies to enable the capture, storage, distribution, management, and analysis of the information.

This definition appears as one of the most complete in literature and adds the criterion of complexity. To the latter, then, other authors added two further features. In particular, Dijcks (2012) introduced the V of “Value,” while Schroeck et al. (2012) add the V of “Veracity”. To summarize, what distinguishes BD from simple data is the presence of “5 V’s”: huge Volume, high Velocity, high Variety, low Veracity and high Value (Sen et al., 2016; Jin et al., 2015). More in details: • Volume refers to the huge amount of information and data stored and registered. • Velocity is the frequency of data generation. • Variety is about the different sources or fields of information that make the data hybrid. • Value refers to potential business benefits extractable from BD. • Veracity is inherent to the unreliability of some data which requires that they must be integrated with some others to avoid distorted or incorrect analysis (Wamba et al., 2015; Sen et al., 2016). Regarding the feature of complexity, it was promptly explained by Ward and Barker (2013), which consider it inherent in the structure, behaviour and permutation of datasets. Given these characteristics, the potential benefits that BD can have in the managerial context are evident. Rapidity and heterogeneity of data can allow an increase in timeliness and rationality of decisions, thus inducing better company performance (McAfee & Brynjolfsson, 2012). On the other hand, the complexity of the BD means that there are barriers to their adoption and that, therefore, the pioneering companies in the use of these IT solutions have been the large ones, since they have the necessary human and economic resources to deal with such innovation (Akter et al., 2016). From these first lines, it emerges how, in the field of business studies, the literature is divided between those who expose the benefits and potentials

4

1 Information Technologies for Business Management: From Big Data. . .

deriving from the BD adoption and those who, conversely, dwell on the barriers and difficulties of use inherent in this innovation. In light of these considerations, in the following lines, a brief literature overview will be presented about the methods of employment, the effects and the barriers related to the involvement of BD in business management.

1.3

BD and Management Issues

Nothing better explains the link between BD and business management as the opening sentence of McAfee and Brynjolfsson (2012): “You can’t manage what you don’t measure”. In this regard, the large amount of data that, in recent years, are characterizing companies’ management practices extend the debate on how the availability of such information intersects with the management of data and its interpretation, to transform simple data into information, and information into new knowledge supporting managerial decision-making (Janssen et al., 2017). According to Liu (2014) companies that adopt BDA technologies, i.e. those technologies designed to economically extract value from BD, are distinguished by higher performance than those who, instead, do not adopt these innovations. In line with Liu (2014), several authors in the literature highlighted the potential benefits of BD on business management. Côrte-Real et al. (2017) underline the potential of BDA to guarantee an important competitive advantage to companies that invest and appropriately use this new kind of technology. Sen et al. (2016) highlight that BD could represent a key driver in ensuring an improvement of flexibility, productivity and a better ability to meet customer needs, while Frizzo-Barker et al. (2016) underlined that companies can gain significant ground by using BD and related technologies since the latter allow them to differentiate themselves on markets. Beyond the implications of BD on the competitive advantage of companies, a large number of studies focus on the effects of these technologies on decisionmaking processes. The possibility of extracting detailed information on the company’s internal and external context means that BD can significantly support managers in their decisions increasing their timeliness and rationality. On these aspects Mcafee and Brynjolfsson (2012) argue that the use of big data enables managers to decide based on evidence rather than intuition and this has the potential to revolutionize management. Following this line of thinking, Sivarajah et al. (2017) report that more and more companies are using BD to enhance top management decisions, while Vajjhala and Ramollari (2016) state that BDA could help managers in having access to knowledge that was not previously available. Despite the positive aspects exposed by numerous authors in the literature related to BD adoption, several critical issues also emerge. Indeed, for these innovations to be effective and useful for business management, companies need to provide themselves with adequate organizational resources capable of realizing the potentials connected with BD (Manyika et al., 2011; Morabito, 2015). In other words, the challenge for companies is to be able to collect,

1.3

BD and Management Issues

5

interpret, store, extract, analyse and use data at the right time. In this regard, Wamba et al. (2017) pointed out that in some cases investments in BD and IT did not lead to the desired results due to the lack of dynamic capabilities or the inability to extract the appropriate data. Furthermore, Bhimani and Willcocks (2014) argued that investments in technologies such as BD can increase cost structures complexities. In the context of the barriers that companies can face in approaching BD, Russom (2011) conducts an investigation administering an ad hoc questionnaire to about 325 companies. He found that the main problems that companies face in dealing with BD concern: (i) inadequacy of skills and lack of specialized personnel in staffing, (ii) difficulties in managing the large amount of data produced, (iii) investment costs and extra operating costs to be incurred and (iv) lack of external support (e.g. cooperation with research and training institutes, extension services support, etc.). In line with Russom (2011), Coleman et al. (2016) highlight several barriers in approaching BD. After confirming the issues of lack or inadequacy of cognitive, technical and organizational resources, the authors argue that further obstacles to the adoption of BD concern an intrinsic conservatism which often affect corporate culture, especially in small and medium enterprises (SMEs), the lack of adequate management and organizational models and the shortage of in-house data analytic expertise (Coleman et al., 2016). From the literature review, it emerges how the BD, on its own, cannot revolutionize the way companies are managed, but, for this purpose, they still need the human and managerial component. Specifically, it is necessary to acquire appropriate expertise as well as to develop strong managerial skills to overcome the barriers to adoption, effectively use this technology and extract economic value by supporting the various business functions. Among the business functions that could most benefit from BD applications, there is undoubtedly the accounting and control function. As mentioned at the beginning of this chapter, data and information constitute the “lifeblood of accounting” (Rainer & Cegielski, 2013: p. 61). Therefore, the possibility of obtaining data and management information in a more timely and precise manner can certainly have an impact on the accounting and control systems. Therefore, in the next lines, particular attention will be paid to the theme of the role of BD in the context of accounting and control activities.

1.3.1

BD in Management Accounting and Control Activities

Information is central in business management activities. In fact, according to Simon (1954), accounting information serves three different functions: scorecard, attentiondirecting and decision-making. Regarding this last aspect, Emmanuel et al. (1992 p.1) consider decision-making as complementary to control, thus emphasizing the role of accounting information for management control. Reading along the lines of the body of previous studies, management control can be defined as the organic set of tools, processes, roles and informal solutions aimed to ensure that the behaviour and actions of business actors are consistent with the organization’s objectives and strategies (Abernethy & Brownell, 1997; Merchant & Riccaboni, 2001; Otley, 1980;

6

1 Information Technologies for Business Management: From Big Data. . .

Ouchi, 1979). Management control can thus be understood as a “package” that encompasses formal as well as informal controls (Malmi & Brown, 2008). Over the years, accounting systems have become consolidated as social institutions (Wysocki, 2011; Quattrone, 2015), aimed at the truthful and correct representation of corporate facts, as well as mechanisms that facilitate communication and interaction between economic players (Olson, 1965; Williamson, 1975). Despite this, according to Lampland (2010), the accounting numbers are tools in which the question of the accuracy, precision and objectivity of data emerges in a central way. Such data can be imperfect or even false (Lampland, 2010), and such defects can lead accounting systems to function imperfectly (Dambrin & Robson, 2011). To mitigate this lack, scholars and practitioners seek greater rationality of data with innovations such as big data (Mcafee & Brynjolfsson, 2012) as these give access to previously unknown information (Arnaboldi et al., 2017). These premises were necessary to introduce the role of IT, and in particular of BD, within the accounting and control systems. As above stated, if accounting information has among their main functions that of supporting decision-making and, therefore, management control but, at the same time, they could be imperfect, the use of IT can become crucial in ensuring an improvement in management activities. In particular BD solutions, being able to facilitate the creation and transfer of company information flows, can represent a turning point in carrying out business management activities. For these reasons, over the years, numerous scholars have focused on the effects of IT and, more recently, of BD on the dynamics of management accounting and control. Accordingly, access to a wider range of information, as allowed by recent IT developments, may have a significant impact on programming and management control practices (Teittinen et al., 2013). About this, Warren Jr et al. (2015) argue that the introduction of BDA technologies, in addition to improving the quality of accounting data, can also increase the effectiveness of planning practices such as budgeting processes. The availability of rational and more precise information compared to the past allows a better predictive analysis (FrizzoBarker et al., 2016) able, in turn, to support the strategic planning (Warren Jr et al., 2015). In addition to the planning function, the introduction of BDA technologies into companies can also have an impact on the more strictly accounting and management control dynamics (Vasarhelyi et al., 2015). In this regard, Warren Jr et al. (2015) highlighted the effectiveness of BD both in accounting processes, such as updating the values of the historical balance sheet to the principles of fair value, and in supply chain control mechanisms. Still in terms of accounting, Vasarhelyi et al. (2015) show how BD can affect the measurement methods of some accounting items such as the valuation of inventories, the determination of tangible and intangible assets or the calculation of the depreciation. Vitale et al. (2020) found that BD affects differently the formal and informal dimensions of control, representing a driver of stability for the former and a driver of change for the latter. Despite the potential and the opportunities for improvement outlined by the various authors in literature, Quattrone (2015, 2016) argues that these technologies will never be able to guarantee the perfect information or the absolute rationality of decision-making processes, and this implies the persistence of a central role of the accounting institution within organizations. In literature, therefore, it seems to persist

1.4

What Is Blockchain?

7

a sort of uncertainty about the real capabilities of the new IT and about the role that traditional accounting systems will play in the future. Indeed, the research field regarding the impact of BD on management dynamics is still in its infancy (Arnaboldi et al., 2017), and further empirical evidence is needed especially concerning the management accounting and control systems (Rikhardsson & Yigitbasioglu, 2018). Among the various BD applications that are gaining the attention of practitioners and researchers, the blockchain is certainly one of the most popular technologies at the moment. Many are trying to understand what real potential this type of IT solution can have for business management, wondering if this technology could be disruptive or if, vice versa, it is just hype. In the continuation of the chapter, they will be addressed the themes of what the blockchain is and how it can be involved in the business context.

1.4

What Is Blockchain?

Blockchain is a peer-to-peer system in which transactions are validated, timestamped and stored by the nodes of a network. The peculiarity of this system, which makes it different from other storage systems, is that blockchain is based on a shared ledger that is distributed among its peers and not centralized in the hand of one entity (Lacity, 2018). As the word itself suggests, this technology consists of two fundamental elements: blocks and chains. The “block” can be defined as a data package that contains different transactions; the “chain”, instead, is formed by adding new blocks to the previous ones, creating in this way a full ledger of the transaction (Nofer et al., 2017). Each block has a header and a body. The body contains the transactions, and the number of transactions that can be stored in a block depends on the size of both the transactions and the block. The header of the block contains a hash code, a timestamp and a nonce; the hash code (or a code generated by a cryptographic function) and the timestamp are the elements that connect the blocks; they can be seen as the virtual glue that cement the chain (Appelbaum & Smith, 2018) (Fig. 1.1).

Hash of current block 1

Hash of previous block Timestamp 2

Main data 1 ... Main data N

Other Information

Hash of current block 2

Hash of previous block Timestamp 3

Main data 2 ... Main data N

Fig. 1.1 Structure of blocks and chain. Source: Lin and Liao (2017)

Other Information

8

1

Information Technologies for Business Management: From Big Data. . .

The use of the abovementioned cryptographic function ensures that the decryption of the hash code is impossible and that each hash value is unique being impossible to create the same hash code (Filipova, 2018). The hash function, thus, ensures the integrity of the blockchain given that a change in a block would cause a change in the corresponding hash value with the consequence that also the hash value of the following blocks have to be changed. The latter process is impossible since it is impossible to change a transaction once it has been added to the chain. Therefore, the two main characteristics of blockchain are immutability and trust. Both these concepts are derived from the distributed nature of blockchain that, despite a centralized system, offers several advantages such as transacting directly with the counterparts, the identification of data provenance and settling transaction rapidly and cheaply. These characteristics of blockchain and its capacity to keep data safe make it clearer why today’s great attention on this technology, which promises huge changes in the economic and social sphere, across different sectors (Filipova, 2018). In fact, given the features of data immutability and indecipherability, blockchain has been widely used for bitcoin transactions. The application to the bitcoin market has modelled the technology in the way we know it today or an IT structure in which data are shared and replicated among the nodes of a network based on distributed ledger technology. A distributed ledger can be understood as a database that allows the participants of the blockchain, called “nodes”, to add transactions to a common ledger that is shared among all of them. Once the transactions have been added, any participant can see the data entered (Halaburda, 2018). In particular, in a distributed ledger, the nodes exchange information without a central server to which they refer (Halaburda & Haeringer, 2020). Each node has a copy of the entire database with the consequence that, in case of problems on a node, the database is still accessible (Filipova, 2018). To summarize, a distributed ledger is a database that is shared and synchronized among the participants of the network and which allows making visible each passage of the data entry process. The use of distributed ledger technology responds to the need to overcome the inherent limitations of a traditional database. The latter has a centralized structure in which a single entity verifies, approves and archives each transaction. These transactions are only kept for a limited period and can only be modified by the administrative entity. These characteristics imply that the information can be corrupted by the administrator as well as that it could be difficult to trace back the origin of an element since the information is stored only for a limited period with consequent ownership problems. Finally, centralizing all information also means that in the event of a failure of the main server, information cannot be accessed (Filipova, 2018). Figure 1.2 graphically shows the difference between the two types of databases. From the comparison shown above, it is clear why it was necessary to switch from a traditional database to a distributed ledger. Especially in a cryptocurrency context, where there is a risk of fraud and data tampering by hackers, it was necessary to define a technology that would guarantee security, traceability of operations and immutability of data. The blockchain, based on a distributed ledger infrastructure, represented the solution to the problem.

1.4

What Is Blockchain?

9

Fig. 1.2 Graphical comparison between the distributed ledger and traditional database. Source: Filipova (2018)

In light of what was stated above, it emerges that one of the main characteristics of the blockchain is that of decentralization. It allows the decentralized action of users since any two peers can carry out a transaction between them without the authentication of a central agency (Zheng et al., 2018). Nevertheless, the action can be allowed to a more or less large number of users. Once the general characteristics of the blockchain have been presented, we need to distinguish between three fundamental types of this technology which can be public, private or consortium. A public blockchain is open and transparent. This means that there are no access rights, and any user can join the network and become a node simply by downloading the software on its device. On the other hand, the transparency requirement deals with the possibility for every user to add and see the transactions in the chain (Zheng et al., 2018). On the opposite, a private blockchain is owned by a single organization that defines data access and rights to add or change the transactions in the chain. In this case, the decentralization requirement is partially lacking as a single centralized unit which controls the entire blockchain by regulating users’ access to it (Filipova, 2018). The consortium blockchain is a mediation between the two previous ones in that it is characterized by the centralization of the control of technology in a consortium of actors (rather than in a single organization) that manage the accessibility of the various users to the data and to the technology itself (Zheng et al., 2018). In the latter two cases, the possibility for users to view transactions and the totality of

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1 Information Technologies for Business Management: From Big Data. . .

data entered in the blockchain are subject to consent by the owners and it could be limited or denied. Given the features and functionality of the blockchain presented so far, it seems a little clearer why this technological solution is receiving great attention at the business level. It is not only a useful tool to guarantee virtual finance transactions but it can also be appropriately applied in other more purely business contexts. Given the features and functionality of the blockchain presented so far, it seems a little clearer why this technological solution is receiving great attention at the business level. It is not only a useful tool to guarantee virtual finance transactions, but it can also be useful in other more strictly corporate areas. For example, the public blockchain can be used by companies to transmit information relating to the characteristics of the products to customers, influencing their purchasing behaviour in terms of marketing. The private blockchain, on the other hand, could be used to transmit and share information between the different business areas within the same company, fulfilling an accounting and communication function. The private blockchain can also be used within a supply chain context to monitor and track supplier activities, thus responding to supply chain management logics. Ultimately, there are many uses that the blockchain could have in a business environment. Therefore, in the following paragraph, the issues about the application of the blockchain in business management will be deepened.

1.5

Blockchain and Management Accounting Issues

Blockchain is often considered one of the most disruptive and promising emerging technologies in the field of business management (Wang & Kogan, 2018; White, 2017). Yermack (2017) reviews the potential effects of the blockchain in several business contexts. In particular, the greater transparency that this technology promises to achieve can have significant effects in terms of corporate governance and shareholders’ investments, lowering trade costs and mitigating the risk of insiders and financial frauds (Yermack, 2017; Tan & Low, 2019). Still in terms of corporate governance, the blockchain can find helpful use in corporate elections since it could guarantee the anonymity of votes and greater accuracy and transparency of elections (Yermack, 2017). Within the sphere of business management, the blockchain has great potential even on accounting systems. Regarding this last area, there are numerous authors in literature dealing with the possible effects that the blockchain can have on accounting. According to Yermack (2017), the blockchain can lead to a substantial change in traditional accounting by shifting it to real-time accounting. In particular, the company’s accounting data could be recorded permanently in blockchain without the possibility of ex-post modification. In this way, the totality of the company accounting data would be immediately visible to any stakeholder. This functionality would allow anyone to be able to aggregate the accounting data in the form of an income statement and a balance sheet at any time with the consequence of no longer

1.5

Blockchain and Management Accounting Issues

11

having to prepare infra-annual financial statements (Yermack, 2017). Such a change could have positive effects in terms of reduction of redundant manual effort, increase in speed of transaction settlement and prevention of financial reporting fraud (Wang & Kogan, 2018). From an outside accounting perspective, Yu et al. (2018) argue that the transparency and immutability requirements of blockchain can affect the quality of external reporting information and effectively reduce the information asymmetry between firms and outside investors. Therefore, according to Yu et al. (2018), blockchain can represent a helpful accounting instrument to disclose firms’ financial information to stakeholders being able to reduce errors in disclosure and thus improving the quality of accounting information. In line with Yu et al. (2018), also Shyshkova (2018) states that, by improving the quality of accounting and reporting information, blockchain will provide a new level of transparency, efficiency and controllability of the management system. In this sense, Tan and Low (2019) consider the blockchain as the “engine” for accounting change since it enables real-time, verifiable, and transparent accounting data (Dai & Vasarhelyi, 2017). Despite the studies above, other authors have shown perplexity about the real capacity of blockchain-based accounting to guarantee the truthfulness of the data. Tan and Low (2019), although they recognize the importance of the blockchain in preventing fraud and reducing errors, they nevertheless argue that blockchain-based accounting, alone, does not guarantee that financial reports are true and fair. Such view is also shared by Coyne and McMickle (2017), who argue that the security benefits that make the blockchain immutable are not completely available or reliable in an accounting context, and by Roubini (2018) to which the blockchain does not decentralize power nor guarantee the truthfulness of the data it contains. Maffei et al. (2021), providing a comprehensive overview on the benefits, threats and risks arising from blockchain adoption in accounting, show that blockchain can hardly overwhelm the traditional accountant figure but, rather, it can stimulate an enhancement of the old accounting practices. In the auditing topic, Lombardi et al. (2022) developed a literature review in which, considering the insights of prior studies (such as, Dai et al., 2019; Rozario & Vasarhelyi, 2018; Schmitz & Leoni, 2019; Tan & Low, 2019), showed that blockchain technologies can improve the auditing activities by saving time and preventing fraud and increasing the audit efficiency, reporting and transparency. Finally, Pizzi et al. (2022) analysed the effects that the use of blockchain can have on non-financial reporting. Pizzi et al. (2022), analysing the case of Banca Mediolanum, showed that the “irrefutability” of the information published on blockchain can contribute to increase information reliability mitigating the asymmetries between a company and its stakeholders. Accordingly, stakeholders can clearly evaluate a company’s non-financial performance having less distorted information since companies cannot replace or revise their commitments after they have been included in the blockchain and thus notarised and certified. In light of these considerations, it seems that there is uncertainty about the real effects that the blockchain can have on accounting systems, making necessary further studies and empirical evidence on this topic. Beyond the boundaries of the individual company, the blockchain has found great adoption within the supply chains, responding to the logics of supply chain

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1 Information Technologies for Business Management: From Big Data. . .

management and inter-organizational accounting and control. On this theme, numerous authors have focused on outlining the opportunities and potential that the blockchain can disclose in supply chain contexts. Kshetri (2018), after analysing 11 cases of blockchain applications in the supply chain, found that technology impacts different dimensions in supply chain management. In particular, according to Kshetri (2018), blockchain can affect: • Costs: By detecting, measuring and tracking key supply chain processes, blockchain allows to allocate the right amount of resources among production phases and to easily identify and remove defective products. Therefore, blockchain can ensure high-quality products also by avoiding suppliers’ use of low quality and counterfeit raw materials. • Speed: The digitization induced by the blockchain involves a greater rapidity of data storage and minimization of physical interactions. • Dependability: Making it possible to know who is performing what actions, when and where, blockchain allows to exert pressure on supply chain partners to be more responsible and accountable for their actions. • Risk reduction: Since only parties mutually accepted in the network can engage in transactions in specific touchpoints and since blockchain’s ability to validate identities can be used to verify the provenance of items, the risks of frauds or false data entered are mitigated. • Sustainability: Tracking supply chain processes, blockchain allows to verify and monitor sustainability performance among suppliers. • Flexibility: Blockchain allows to go back and examine the recorded contents for all the relevant parties in case of disputes. Along the lines of Kshetri (2018), Kouhizadeh and Sarkis (2018) also propose a series of other possible impacts that the blockchain can generate in terms of supply chain management. For Kouhizadeh and Sarkis (2018), the blockchain, as well as for tracking production processes and raw materials and for suppliers monitoring and evaluation, can help in improving supplier development programs and can be a useful marketing tool by informing customers about the origin, quality and characteristics of the products. Moreover, by making available vendors’ historical performance (which traditionally are not reliable and not easily accessible data), blockchain can also support a focal company in the suppliers’ selection process (Kouhizadeh & Sarkis, 2018). Other authors take up, roughly, the aspects and potentialities presented so far, focusing more on single issues such as costs reduction, mitigation of business risks and improvements in terms of efficiency, security and transparency (see, e.g. Casado-Vara et al., 2018; Francisco & Swanson, 2018; Galvez et al., 2018; Min, 2019). So far, the opportunities for improvement deriving from the application of blockchain technology have been exposed. However, for these effects to occur, the technology must be adopted and spread along the supply chain. This operation is not immediate and can encounter different types of barriers (White, 2017). In this regard, Saberi et al. (2019) subdivide the barriers to the adoption of blockchain into four types: intra-organizational, inter-organizational, system-related and external.

1.6

Literature Shortcomings and Research’s Objectives

13

Intra-organizational barriers concern aspects related to the internal management of the company. They fundamentally involve the management’s commitment, the organization’s culture and the internal technical expertise. Technology like the blockchain (but in general any innovation) requires organizational changes as well as specific technical skills. Therefore, it is clear that the fundamental requisite for the adoption of this technology is the initial commitment of top management which must affect the culture of other employees and provide for the acquisition of the necessary expertise. Inter-organizational barriers have more to do with relationships within the supply chain between focal companies and suppliers. In the diffusion of technology along the supply chain, the focal company can run into the resistance of the partners. In this context the main barriers to the introduction of the blockchain concern cultural differences between partners as well as communication and coordination difficulties (Mangla et al., 2017). System-related barriers are related to technology’s specifications. In particular, the large number of data that is generated within a supply chain can generate storage and handling problems that may require investments in new computing infrastructures (Saberi et al., 2019) involving high costs (Hughes et al., 2019). In addition to this, system-related barriers are also those inherent to data security and privacy (Mougayar, 2016). Hughes et al. (2019) highlight latency as a further barrier, namely, the computational expense of adding new blocks and subsequent transaction records. The last type of barrier is that relating to the context outside the corporate one. External barriers concern, in particular, the lack of appropriate governmental and industrial policies as well as the reluctance of the institutions to accept or regulate this new technology and the uncertainty about external stakeholders’ involvement. In order not to excessively lengthen the body of the text, resulting in fragmentation or incoherence, below is presented the summary graph of the main barriers to the adoption of the blockchain proposed by Saberi et al. (2019) (Fig. 1.3). The following table (Table 1.1) closes the literature review by presenting a summary of the main findings on BD and blockchain in management.

1.6

Literature Shortcomings and Research’s Objectives

In this chapter, we have seen the potentialities and challenges in which companies can run into when approaching BD-based technologies such as blockchain. From the above paragraphs, it emerges that the potentials of these technologies are multiple and they can impact different business areas. However, this field of study is still in its infancy (Lombardi & Secundo, 2021), and most of the research on this topic lack empirical evidence (Maffei et al., 2021; Secinaro et al., 2022). In this regard, several authors call for new studies to collect empirical evidence about the effects and

Intraorganizational Barriers

technology adoption in sustainable supply chain

Barriers of blockchain

Barriers

Interorganizational

Challenge of information disclosure policy between partners in the supply chain

Fig. 1.3 Barriers of blockchain technology adoption. Source: Saberi et al. (2019)

Lack of tools for blockchain technology implementation in sustainable supply chains

Hesitation to convert to new systems

Diffculty in changing organizational culture

Lack of knowledge and expertise

Lack of new organizational policies for using technology

Problems in collaboration, communication and coordination in the supply chain

External Barriers

Related Barriers

Systems

Challenges in integrating sustainable practices and blockchain technology through SCM

Lack of rewards and encouragement programs

Lack of industry involvement in ethical and safe practices

Lack of external stakeholders' involvement

Market competation and uncertainty

Lack of governmental policies

Immaturity of technology

Immutability challenge of blockchain technology

Hesitation to adopt blockchain technology, due to negative public perception

Access to technology

Security challenge

Cultural difference of supply chain partners

1

Lack of management commitment and support

Financial constraints

Lack of customers' awareness and tendency about sustainability and blockchain technology

14 Information Technologies for Business Management: From Big Data. . .

1.6

Literature Shortcomings and Research’s Objectives

15

Table 1.1 Summary of the main literature insights on big data and blockchain in management Big data and management issues Main Topic Main Findings BD opportunities in Companies that adopt BD technologies can improve decision-making management (Mcafee & Brynjolfsson, 2012, Janssen et al., 2017; Sivarajah et al., 2017; Vajjhala & Ramollari, 2016), achieve higher performance (Liu, 2014), gain competitive advantage (Côrte-Real et al., 2017; FrizzoBarker et al., 2016) and improve flexibility, productivity and customer satisfaction (Sen et al., 2016) BD challenges and BD technologies require companies criticalities in to gain adequate cognitive and management dynamic capabilities (Manyika et al., 2011; Morabito, 2015; Wamba et al., 2017). They can also entail difficulties in data management and high investment costs (Russom, 2011) thus increasing companies’ cost structures complexities (Bhimani & Willcocks, 2014). Moreover, BD technologies can hardly guarantee perfect information or absolute rationality, potentially inducing managers to make wrong decisions faster (Quattrone, 2016) BD in management BD technologies can improve the quality of accounting data and accounting and increase the effectiveness of plancontrol ning practices (Frizzo-Barker et al., 2016; Warren Jr et al., 2015). BD can also affect accounting by changing measurement and evaluation methods of peculiar accounting items (Vasarhelyi et al., 2015; Warren Jr et al., 2015). BD can entail change or stability within management control dynamics according to the different forms of control (formal or informal) (Vitale et al., 2020) Blockchain and management issues Main topic Main findings The greater transparency provided Blockchain opporby blockchain technology can lower tunities in trade costs and mitigate the risk of management insiders and financial frauds (Yermack, 2017; Tan & Low, 2019;

Methodology adopted • Case study (Janssen et al., 2017) • Conceptual paper (Liu, 2014; Mcafee & Brynjolfsson, 2012; Sen et al., 2016) • Survey (Côrte-Real et al., 2017) • Systematic literature review (Frizzo-Barker et al., 2016; Sivarajah et al., 2017) • Comprehensive literature review (Vajjhala & Ramollari, 2016) • Book (Morabito, 2015) • Conceptual paper (Bhimani & Willcocks, 2014; Quattrone, 2016) • Mixed methods (Wamba et al., 2017) • Survey (Russom, 2011) • Technical report (Manyika et al., 2011)

• Conceptual paper (Vasarhelyi et al., 2015; Warren Jr et al., 2015) • Case study (Vitale et al., 2020) • Systematic literature review (Frizzo-Barker et al., 2016)

Methodology adopted • Conceptual paper (Kouhizadeh & Sarkis, 2018; Min, 2019; Tan & Low, 2019; Yermack, 2017) • Multiple case studies (Kshetri, 2018) (continued)

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Information Technologies for Business Management: From Big Data. . .

Table 1.1 (continued) Big data and management issues Main Topic Main Findings

Blockchain challenges and criticalities in management

Blockchain in management accounting and control

Wang & Kogan, 2018). Blockchain can support supply chain management by preventing incorrect suppliers’ behaviours, improving tracking processes and the suppliers’ selection process, enhancing the transparency of raw material quality and mitigating risks associated with hacking, compromised privacy and contractual disputes (Kshetri, 2018; Kouhizadeh & Sarkis, 2018; Min, 2019) The adoption of blockchain technology can involve several barriers. Blockchain adoption can be hindered by several issues such as communication and coordination difficulties (Mangla et al., 2017), high costs and data management problems (Hughes et al., 2019; Mougayar, 2016). In synthesis, the barriers to the adoption of blockchain can be classified into four categories: intraorganizational, inter-organizational, system-related and external (Saberi et al., 2019). Blockchain can also induce criticalities such as the underestimation of fraudulent activities or hidden manipulation as well as the unawareness of possible errors (Maffei et al., 2021) The transparency and immutability requirements of blockchain can affect the quality of external reporting and effectively reduce the information asymmetry (Pizzi et al., 2022; Shyshkova, 2018; Yu et al., 2018). Furthermore, blockchain can enable real-time, verifiable and transparent accounting data (Dai & Vasarhelyi, 2017). Lastly, blockchain technologies can improve the auditing activities by saving time, preventing fraud, increasing the audit efficiency and transparency (Dai et al., 2019; Lombardi et al., 2022; Rozario & Vasarhelyi, 2018; Schmitz & Leoni, 2019; Tan & Low, 2019)

Source: Own elaboration

Methodology adopted • Prototyping Methodology (Wang & Kogan, 2018)

• Book (Mougayar, 2016) • Conceptual paper (Maffei et al., 2021; Saberi et al., 2019) • Literature review (Hughes et al., 2019) • Mixed methods (Mangla et al., 2017)

• Conceptual paper (Dai & Vasarhelyi, 2017; Shyshkova, 2018; Tan & Low, 2019; Yu et al., 2018) • Case study (Pizzi et al., 2022) • Literature review (Schmitz & Leoni, 2019) • Prototyping Methodology (Dai et al., 2019; Rozario & Vasarhelyi, 2018) • Structured literature review (Lombardi et al., 2022)

1.6

Literature Shortcomings and Research’s Objectives

17

implementation dynamics of BD applications within companies (Arnaboldi et al., 2017; Lombardi et al., 2022; Lombardi & Secundo, 2021; Maffei et al., 2021; Mancini et al., 2021; Quattrone, 2016; Rikhardsson & Yigitbasioglu, 2018; Saberi et al., 2019; Secinaro et al., 2022; Vitale et al., 2020). More specifically, from the analysis of the literature carried out so far, we can identify a huge number of theoretical papers but a significant lack of empirical evidence about the interrelationship between BD and accounting practices and about the changes that these new technologies may induce in traditional accounting systems (Rikhardsson & Yigitbasioglu, 2018). With a particular reference to blockchain, the literature presents uncertainty about the real effects it may have on accounting (e.g., Maffei et al., 2021; Secinaro et al., 2022). So, the first topic of absolute relevance that deserves to be investigated is the one related to the interplay between blockchain and accounting and the effects they can have on each other (e.g. Lardo et al., 2022). About this, Shyshkova (2018) and Secinaro et al. (2022) stress the need to empirically investigate how blockchain and accounting systems interact with each other, to understand if and how their interaction concretely leads to a new level of transparency, efficiency and controllability. The second point that deserves to be investigated is related to the application of the blockchain within supply chains (Maffei et al., 2021). Also in this case, the literature is rich in proposals for blockchain applications and theoretical assumptions about the effects and the challenges that companies may run into in approaching this technology. However, to the best of my knowledge, a comprehensive study that empirically demonstrates which are the effects and the implementation dynamics which occur in adopting blockchain in supply chains is missing so far. Starting from the gaps in the literature and from the assumptions mentioned above, this research aims to analyse why and how the blockchain is adopted and spread within the supply chain by focusing on the managerial dynamics involved in this process. In parallel, particular attention will be paid to the interaction between blockchain and traditional accounting systems to show whether and how they influence each other, what changes blockchain may induce in traditional accounting systems and what effects it has in terms of inter-organizational control. By relying on the case of the first European application of blockchain in the food supply chain, empirical evidence will be provided on the topics discussed so far. Finally, given that the blockchain involves a plurality of actors that interact with each other within a network, the actor-network theory has appeared as the most logical choice to interpret the results that emerged from the analysis of the case study. The author is well aware that it does not exist a best theory allowing us to fully comprehend the complexity of the real world (Walsham, 1997). However, actor-network theory has been widely recognized as a valuable approach for understanding the socio-technical matters concerning IS and IT fields (Walsham, 1997). In the next chapter, therefore, the actor-network theory will be discussed.

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1.7

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Information Technologies for Business Management: From Big Data. . .

Conclusion

BD technologies are gaining great interest among practitioners and academics. This interest is mainly due to the potential of these innovations to revolutionize corporate management (Mcafee & Brynjolfsson, 2012). Nevertheless, the literature shows mixed results on the effects of BD on management practices. Indeed, on one hand, prior studies found that business management can benefit from BD technologies since they improve and speed up decision-making and accounting practices (e.g. Frizzo-Barker et al., 2016; Vasarhelyi et al., 2015; Warren Jr et al., 2015); on the other hand, BD can induce higher complexity and wrong decisions (e.g., Bhimani & Willcocks, 2014; Quattrone, 2016). One of the latest and most discussed BD technology is the blockchain. Blockchain has often been associated with cryptocurrencies. Nonetheless, it has also found application in management and accounting practices. In this context, the literature is rich in theoretical assumptions and lacks empirical evidence (e.g., Maffei et al., 2021; Secinaro et al., 2022). Despite several scholars theorized the effects, benefits and barriers deriving from blockchain adoption within companies, little is known about how blockchain can affect accounting. Given so, it is relevant to investigate the interplay between blockchain and accounting and the effects they can have on each other. This monograph contributes to filling the above gap by proposing one of the first European applications of a blockchain for the supply chain management. In so doing, the author deepens how the blockchain interacted with traditional management accounting and control practices. Given the purpose of this research work, the actor-network theory (ANT) proved to be a valuable lens through which to investigate and interpret the field study results. Accordingly, the next chapter addresses the main ANT insights.

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Chapter 2

Theoretical Framework: The Actor-Network Theory (ANT)

2.1

Introduction

In this chapter, the theoretical framework used to interpret the empirical evidence emerging from the case study analysis will be presented and discussed. The main purpose of this research is to understand the mechanisms which lay behind the adoption of blockchain technology in an agro-food supply chain. Therefore, the relationships established between the various actors of the supply chain as well as the roles that each company played in the process of building the network and, consequently, spreading the technology, represent fundamental social aspects that can be adequately interpreted through the actor-network theory (ANT from now on) lens. ANT is particularly suitable in exploring how human and non-human actors are enrolled and interplay with each other within a network (see about it: Callon & Latour, 1981; Callon, 1986a; Latour, 1996); consequently its use for the development of this research was, in a sense, mandatory. The choice of ANT is also justified based on the research paradigm adopted for this study and by virtue of the author’s ontological position. As it will be deepened in the methodology chapter, in this work has been adopted an interpretivist ontological approach to research on which basis the reality is not predefined but can be conceived as the product of social constructions (Husserl, 1965). In line with the ontological positions of the present work, ANT is an ontologically relativist theory (Lee & Hassard, 1999) that considers society not as a determined scaffolding with a precise domain and properties (Law, 1992) but as a social structure constituted by associations between various actors that play roles and establish relationships with other actors within the network (O'Connell et al., 2014). Because of the ontological affinities that exist between the present study and ANT, the latter was chosen as a reference theory in the development of the empirical part of the research.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5_2

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Theoretical Framework: The Actor-Network Theory (ANT)

Summarizing, the use of ANT as the theoretical framework of this research derives from a twofold motivation: the purpose of the study itself to analyse the dynamics of network creation in the development and spread of blockchain technology in a supply chain and the ontological affinities between ANT and the present research work.

2.2

Conceptualizing Technology in Management Research: Why ANT?

Over the years, management scholars have theorized and conceptualized the technology in several ways. On this topic, Orlikowski (2010) well explains the evolution of technology conceptualization in the management field, introducing a comprehensive classification. She identifies three main technology conceptualizations: absent presence, exogenous force (or techno-centred perspective) and emergent process (or human-centred perspective). To the absent presence perspective belong all those authors that considered the technology absent or detached from the social life (Orlikowski & Iacono, 2001). These scholars placed the ontological priority on the human actor relegating technology to a taken for granted (or black-boxed) artefact which has only a marginal role in the social life (Orlikowski, 2010). The second perspective is more techno-centric, assuming that the technology is an exogenous force which can autonomously drive organizational change (Orlikowski, 2007, 2010). According to this perspective, technology is assumed to be fixed, stable and unproblematic, and it has significant and predictable impacts on human actions (Orlikowski, 2010). Scholars embracing this perspective tend to ignore how technology takes shape in accordance with human agencies and historical and cultural influences (Orlikowski, 2007, 2010). The last conceptualization proposed by Orlikowski (2007, 2010) is the emergent process perspective. Scholars embracing this line of thinking consider the technology the result of a continuous interaction between human actions, social histories and institutional contexts. In this case, technology represents the material artefact that is socially defined by the human actors engaging with it. According to Orlikowski (2007, 2010), in this last perspective there is a human-centred view since technology changes and is shaped based on the meanings assigned to it by the humans engaging with it. Accordingly, the technology is not black-boxed, but it tends to change in line with the changes of human agencies, interests and interpretations. At the end of her essay, Orlikowski (2010) argues that despite the previous conceptualizations produced valuable insights, they present some critical issues. In particular, technology as an exogenous force offers a too simplistic view of technology. The latter is understood as unproblematic and detached from social contexts being stable over space and time. Such an understanding is far from the practice

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Conceptualizing Technology in Management Research: Why ANT?

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since, very often, technologies have flaws and break down and their configurations tend to vary from one social context to another (Orlikowski & Iacono, 2001). The emergent process perspective overcomes these criticalities considering the technology as socially constructed and linked to the social context and the human agencies and interests. The focus is on humans, and technology is shaped based on the meanings that people attribute to it. Nevertheless, this last perspective tends to minimize the role of technology and to overlook the technological affordances and capabilities (Orlikowski, 2010). The ontology priority is on humans and their social interactions, while technology is a material artefact subordinated to humans’ necessities. Despite the different features that characterize the previous perspectives, they all share the same criticality or the ontological separation between humans and technology that implies that agency is embedded either in the human or in the artefact (Introna, 2014). Accordingly, Orlikowski (2010) argues that all the previous conceptualizations of technology are based on an ontology of separateness since humans and technologies are considered as different and separate realities. Orlikowski (2010) suggests that, to overcome the criticalities that affected the traditional conceptualization of technology, scholars need to consider humans and objects as “ontologically inseparable” shifting from an ontology of separateness to a relational ontology. Relational ontology does not privilege individuals or artefacts but provides that human and non-human actors are symmetrical and acquire their forms and attributes only in relation to each other (Orlikowski, 2010). In this regard, human and non-human actors relate and aggregate to each other forming a network in which they have equal weight and where they temporary align their interests to achieve a specific goal (Law, 1992). In line with this, Orlikowski (2010) introduces the concept of “entanglement in practice” or the ability of actors of building a given reality through constitutive associations and assemblages in which technological artefacts and humans are treated symmetrically. These ontological assumptions make up the core of the ANT. According to ANT, actors (both humans and non-humans) have no inherent qualities but acquire their form and attributes through establishing relationships with each other in practice. Moreover, one of the fundamental assumptions of ANT is that human and non-human actors temporarily assemble and associate their interests forming a network through which pursuing a common goal. Given these features, ANT represents an influential example of “entanglement in practice” as well as a specific and valuable methodology for studying the co-evolution of socio-technical contexts and sociotechnical contents (Law & Callon, 1994; Orlikowski, 2010). All of this, combined with the widely discussed research objectives, further explains why the ANT approach guided the present study. In the following pages, the historical background and the key features of ANT will be deepened.

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Theoretical Framework: The Actor-Network Theory (ANT)

What Is Ant? A Historical Background

ANT was born as part of a broader scientific movement called science and technology studies (or science, technology and society), in which scientific facts and technological artefacts are interpreted through an investigation scientific approach of social type (Vicsek et al., 2016). Historically, the birth of ANT is traced back to the authors Michel Callon and Bruno Latour whose works (see: Callon & Latour, 1981; Callon, 1986a) are considered pioneers of this theory. The main objective of ANT is to understand how actors form alliances and enrol other actors, creating networks of aligned interests which are made up of humans as well as artefacts (Mähring et al., 2004). This last aspect has allowed ANT to achieve great notoriety and employment in the academic world since, in it, human and non-human, social and technical factors are brought together in the same analytical view, with the intent to comprehend complex social situations (Mclean & Hassard, 2004). In line with the above line of reasoning, Law (1992) identified the core of ANT as a concern with how actors and organizations mobilize, juxtapose and hold together the bits and pieces out of which they are composed. According to Law (1992), ANT concerns how actors manage to turn a network from a heterogeneous set of bits and pieces, each with its own inclinations, into something that passes as a “punctualized actor”. The arguments of Law (1992) fully represent the fundamental aspects of the ANT or the interrelationships of the pieces of which the network is composed and the unitary intent of those who constitute the network. At a closer look, these concepts recall the fundamental principles of ANT expressed by Callon (1986a). In particular, Callon (1986a) introduces three fundamental principles that interest ANT: generalized symmetry, agnosticism and free association (the abandonment of all a priori distinctions between the natural and the social). The first principle, or the generalized symmetry, refers to the importance to use the same terms for all actors of the network (without distinction between human and non-human actors or social and the technical artificial) (Van House, 2003) or in explaining conflicting viewpoints (Callon, 1986a). According to this principle, both human and non-human actors can act and, based on their action, influence each other. These concepts are clearly expressed by one of the fathers of ANT, Latour (1995, 2005), according to which ANT refuses any symmetries between humans and non-humans. Latour (2005) argued that to be symmetric in ANT means not to impose a priori asymmetry among human intentional action and a material world of causal relations. In order to clarify these concepts, an example proposed by Latour (1995) is reported: Humans delegate the job of closing the door to the nonhuman, pneumatic, door-closing device, but the device imposes behavior on the humans passing through it (if they wish to avoid being hit by the door). (Latour, 1995 cited by Van House, 2003)

The second principle of ANT is the one of agnosticism which recalls the concept of impartiality of the researcher in examining actors engaged in controversy (Callon, 1986a). According to Callon (1986a), the imperative is that no point of view is privileged and no interpretation must be censored. Considering this, the researcher

2.3

What Is Ant? A Historical Background

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must refrain from censoring the actors when they speak of the social context or themselves and must not even judge how the actors themselves interpret the reality that surrounds them (Callon, 1986a). Based on this principle, researchers have the role of following the actors through their work, but without replacing them in any way but rather describing how these actors deal with controversies (Mclean & Hassard, 2004). The third and last principle of the ANT introduced by Callon (1986a) is that of free association. According to this principle, the observer must not consider all the a priori distinctions that can be considered existing between natural and social events or human and non-human actors, thus rejecting the hypothesis of a definite boundary that separates the two (Callon, 1986a). According to Callon (1986a), such a separation could represent the result of the analysis rather than its starting point. Therefore, the researcher must not have pre-established models of analysis through which to study actors and their relationships but should follow the actors in the course of the events (Elder-Vass, 2008) to understand how they define and associate the different elements that constitute their world (Callon, 1986a). The three principles just illustrated constitute the prelude to the “sociology of translation”, that is, the core process through which the actor-network takes shape. Before explaining the various phases that make up the “sociology of translation”, it is appropriate to briefly outline the key concepts of the ANT.

2.3.1

Power

The concept of power is at the basis of ANT. Callon (1986a) defined the sociology of translation as a new analytical framework to study power relationships, underlining the core function of the concept of power. In light of its importance, it is, therefore, necessary to define what power is. Latour (1984) makes a distinction between power in potentia and power in actu stating that in the first case you simply have power but nothing happens while in the second case you have power and exert it having others perform an action while you remain inactive. According to Latour (1984), power over something or someone is a composition made by many and attributed to one of them. Latour (1984) argued that the amount of power exercised varies not according to the power someone has but to the number of other people who contribute to its composition. Therefore, power holds its essence in the action of those who are subjected to it. For Latour (1984), power is not the cause of the action but the effect and the consequence of the collective action. This conception of power as an effect rather than the cause is also referred to by Law (1986b). According to Law (1986b), power may be seen as an effect of the creation of a network of mobile, durable yet tractable agents. In line with this, Law (1986b) proposed an example:

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Theoretical Framework: The Actor-Network Theory (ANT)

A text by itself will be ignored. A person will be snubbed. A device will rust. But if the three are put together it may become more difficult to ignore them. Under the right circumstances the effect is that of power.

From these thoughts, it appears that power deals with people’s action. In light of this, thus, the translation process becomes crucial in understanding the power relationships that take shape in a chain of actors (Latour, 1984). The understanding of power relationships, in turn, means describing the way in which actors (both human and non-human) are defined, associated and simultaneously obliged to remain faithful to their alliances (Callon, 1986a). Translation, therefore, represents the mechanism by which the social and natural worlds progressively take form (Callon, 1986a). From the concepts above mentioned, two main elements emerge, and they constitute key elements of ANT: the actors (or the elements between which power relationships take shape) and the actor-network (or heterogeneous network of related actors which share aligned interests).

2.3.2

Actors

In ANT, actors have a central role, and the related definition is closely linked to the principle of generalized symmetry. According to Law (1986a), an actor is anything/ anyone that acts upon others. With the words “anything/anyone”, Law (1986a) emphasizes the concept that an actor can be both human and non-human and that the fundamental assumption for which an actor can be defined as such is his ability to act upon others. Latour (1996) defined the actor as something that acts—an actant— or to which activity is granted by another. Consequently, an actant can literally be anything as long as it is the source of the action (Latour, 1996). According to ANT, all actors, human and non-human, are part of a network in which their identity is defined through their interaction with other actors (Cressman, 2009). In this regard, we can speak of a “heterogeneous network”, or a network in which the duality between human and non-human is overcome”. In the wake of these concepts, Law (1992) argues that an actor is also always a network that, in turn, is produced as the effect of heterogeneous relationships between human and non-human actors. Law (1992) explains this concept through the following argumentation: . . .an actor is also, always, a network. The argument can easily be generalized. For instance, a machine is also a heterogeneous network—a set of roles played by technical materials but also by such human components as operators, users, and repair-persons.

This view of actor, in the opinion of the author, is particularly suitable when studying supply chain contexts. In a supply chain, several firms interplay with each other and share aligned interests generally under the guidance of a focal company that exerts forms of power and control over the other actors. In such a scenario, the supply chain represents the network, while single firms involved in it are the actors.

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What Is Ant? A Historical Background

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On closer inspection, however, the firms, which make up the supply chain, are also networks since they are formed by people, machines, computers and so on. All these elements represent a plurality of actors which, sharing aligned interests and interacting with each other, create the company and, thus, the network.

2.3.3

Actor-Network

Actor-network (or Network) could be defined as a heterogeneous set of actors who share aligned interests and who are linked together by different relationships (Law, 1992). According to Callon (1986b), the character of heterogeneity is what distinguishes an actor-network from a simple network. In addition to this, an actornetwork is also characterized by the fact that the elements of which it is composed are mutually defined in the course of their association (Callon, 1986b). For an actornetwork to be defined as a heterogeneous set of elements, it is necessary that these entities have first been successfully translated (see translation) or enrolled (see enrolment) by a (focal) actor who, in turn, can align their interests (Callon et al., 1986). From this, it emerges the key figure of the focal actor that is the one who can exercise control over the other actors by persuading them to perform particular roles and to act in a specific way to achieve the common goals of the network (Callon, 1986a; Sarker & Sidorova, 2006). Starting from the focal actor, the creation of the network takes place through a negotiation process through which the focal actor transmits the interests that he wants to characterize the network to all the actors that will be part of it (see interessement) (Callon, 1986a; Sarker & Sidorova, 2006). An actor-network can be considered relatively stable only when it is made up of a range of durable materials (Law, 1992) and whose effects and behaviours can be taken for granted and no longer questioned or tested (Callon & Latour, 1981; González et al., 2012). In this case, researchers tend to simplify the actor-network considering it as an individual actor (Sarker & Sidorova, 2006). Such simplification is commonly known as “punctualization”. This term refers to the process through which an actornetwork becomes a “black box” and it is connected to other networks forming larger actor-networks (Cressman, 2009). In other words, through the punctualization process, an entire network is converted into a node of another (and larger) network (Callon, 1991). “Punctualization” and “black boxing” are often linked and refer to similar aspects. In this sense, Van House (2003) considers the process of “blackboxing” as the process by which subnetworks disappear and example, methods, concepts and equipment are accepted without question or examination. These statements demonstrate how “punctualization” and “black boxing” are thematically very close. However, it must be emphasized that punctualization is always “precarious” (Law, 1992). Punctualization and black boxing do not happen once and forever, but the network can still be subject to changes and evolutions when the relationships between the actors weaken or other external actors compromise its stability (González & Cox, 2016). In such cases, if the actor-network is not able to face the resistances that occur, it may degenerate into a failing network (Law, 1992).

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2.3.4

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Theoretical Framework: The Actor-Network Theory (ANT)

Control

The figure of the focal actor is the one who finds himself in a privileged position within the network by virtue of which he can exercise control or force over the other elements of the network (Law, 1986c; Sarker & Sidorova, 2006). The control of the focal actor is an indispensable element so that the other actors of the network are persuaded to act in the interests of the network itself (González & Cox, 2016). However, control cannot be exercised immediately by the focal actor but requires the existence of a structure of heterogeneous elements, both human and natural, capable of generating an envelope (Law, 1986c). In addition to the structure, it is also necessary, for the focal actor, to make use of “raw materials” (i.e. other actors that can be both physical objects and people) that act as intermediaries for exercising control (Law, 1986c; Van House, 2003). In this regard, inscription represents a crucial means to the exercise of control. Inscription materializes knowledge into artefacts (such as journals, articles, patents, etc.) making it possible to coordinate work across space and time (Van House, 2003). Van House (2003) explains this concept very well by arguing that inscriptions make it possible to record, combine, compare, summarize, link, and manipulate work performed in a variety of places, allowing the coordination of work across space and time. In this sense, inscriptions facilitate action at a distance by linking one’s work to others’, persuading the reader, and enrolling others to accept what pictured by the text (Van House, 2003). The inscription process, therefore, can lead to the creation of intermediate actors who act as intermediaries for the exercise of control. However, for the inscription to become an integral part of the network and therefore black-boxed, it must become “mobile” and “durable” and be able to strengthen the relationships between the actors and concentrate a wider range of allies than what had previously been possible (Latour, 1987 cited by Law, 1986c). In this regard, an inscription is more durable the longer it can maintain the relationships between the actors while it is more mobile the more it can keep the focal actor tied to the other peripheral actors of the network (Law, 1986c). To summarize, the more the inscription becomes durable and mobile, the more it becomes a black box and will be able to support the focal actor’s control, allowing the coordination of work across space and time. The key elements of ANT presented so far are all functional to the network creation process otherwise known as the sociology of translation. In the next section will be explained in detail how this network creation process occurs, focusing on the different phases of which it is constituted.

2.4

The Sociology of Translation

According to Callon (1986a), the sociology of translation can be defined as an analytical framework through which study the role played by science and technology in structuring power relationships. More specifically speaking, within the ANT, the

2.4

The Sociology of Translation

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translation process represents the process through which a network takes shape or evolves (González & Cox, 2016). In this regard, Brown (2002) defined translation as the process of making connections, setting passages between domains or establishing communication. In such activities, a key role is played by the focal actor which can exert control on other actors trying to enrol them into the network aligning their interests with his own ones. In such a scenario, therefore, starting from many unconnected localities, the sociology of translation explores actors, objects, relations, inscriptions and other devices that make it up the network (Robson & Bottausci, 2018). Callon (1986a) identifies four interrelated stages through which the process of translation takes shape: problematization, interessement, enrolment and mobilization. In the following pages, these moments of translation will be presented. (a) Problematization In the first phase of the translation process, or problematization, a focal actor (which is the one who guides the creation of the network) frames a problem and identifies the set of actors, as well as their identities and their interests, to determine the ones to involve (in the network) by virtue of how much they are close to his own interests (Callon, 1986a; Costa & Cunha, 2015). The focal actor, here, has the key role of establishing roles and activities that other actors have to perform and which are consistent with the problem-solving and with his own interests, thus imposing himself as an obligatory passage point (OPP) (Law, 1986b). The concept of OPP concerns the idea that the other actors have the only choice to go through the focal actor to resolve their problems. However, for actors to pass through the OPP, it is essential that they first modify their interests aligning them to those of the focal actor (González & Cox, 2016). In this regard, the focal actor can persuade other actors by implementing several strategies and methods such as negotiation, seduction, violence and transactions (Costa & Cunha, 2015). Once the stage of problematization is ended and the problem to be solved as well as the OPP were established, it can take shape the stages of interessement and enrolment through which actors are concretely involved and included within the network. (b) Interessement At the end of the first stage of translation, the entities have been defined and the relationships have been envisaged, but nothing has been still tested (Callon, 1986a). Therefore, in the stage of interessement, the solidity of the problematization is tested, and the focal actor tries to attract other actors to the network. Each entity defined in the problematization stage can accept inclusion in the network or, conversely, reject the transaction by defining its identity, its objectives and its interests in another way (Callon, 1986a). Therefore, the focal actor implements a series of actions aimed at persuading other actors to become part of the network and to play the roles and be compliant with the identities defined in the problematization stage. In this regard Callon (1986a) gives a clear definition of interessement, defining it as the group of actions by which an entity [or the focal actor] attempts to impose and stabilize the identity of the other actors it defines through its problematization. “. . .

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Theoretical Framework: The Actor-Network Theory (ANT)

To attract other actors, and thus achieve a successful interessement, the focal actor can implement different strategies, tactics and devices (Callon, 1986a; González & Cox, 2016). Whatever the strategy used, however, the final result to be achieved for the focal actor is to isolate the actors to be enrolled by preventing any other possible alliance and any other possible external interference that could compromise the legitimacy of the OPP (González & Cox, 2016). Finally, to be successful, the interessement needs to achieve the enrolment (Callon, 1986a). (c) Enrolment If interessement is successful then it achieves enrolment (Callon, 1986a). In the stage of enrolment, the set of interrelated roles are defined and attributed to the actors, and the problem, defined in the first moment of translation, has to be translated into a series of clear and persuasive statements (Linde & Linderoth, 2006). In more concrete terms, the basic goals that the focal actor has defined for the network must be divided into more specific sub-goals, which must be accepted and fulfilled by the other actors (Linde & Linderoth, 2006). Regarding the enrolment, Callon (1986a) explains that it designates the device by which a set of interrelated roles is defined and attributed to actors who accept them. Accordingly, enrolment is the group of multilateral negotiations, trials of strength and tricks that accompany the interessements and enable them to succeed (Callon, 1986a). ... According to González and Cox (2016), these negotiations can be carried out both with the actors identified for the Enrolment and with those actors who are potentially able to threaten and compromise the network. In this regard, Callon (1986a) states that to ensure a successful enrolment, alternatives such as physical violence, seduction, transaction and consent without discussion can be used. (d) Mobilization Mobilization is the last moment of translation, and it occurs when the latter is complete and the interests of the actors are strengthened and aligned with those of the focal actor. The latter, consequently, can turn itself into the “spokesman” or the one which, borrowing the force of the actors that it has enrolled (Law, 1986a), is legitimated to speak on behalf of the network (Linde & Linderoth, 2006). The legitimation of the focal actor to be the spokesman derives from the acceptance gained from the other actors of the network which are now brought together and act as one, becoming a black box (see Sect. 2.1.3). To achieve this result, this phase includes the use of a set of methods to ensure that allied actors act according to the established and do not betray the network interests (Costa & Cunha, 2015). However, despite the strategies and methods used by the focal actor to induce other actors to act in compliance with the network’s interests, it could also happen that the actors themselves will not follow their spokesmen (González & Cox, 2016). In this case, reality begins to fluctuate, actors may start to follow other spokesman and to act in a divergent way compared to the initial interests and it might start a new translation process (Callon, 1986a). This situation deals with the concept that a network, in the present, must always contrast the uncertainties that lurk around the corner, in the

2.5

Latour’s Five Sources of Uncertainty

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near future. Therefore, a network is never given once and for all, but it always undergoes evolutions and changes through space and time. These themes are exhaustively exposed in the five sources of uncertainty of Latour (2005) according to which, in the re-construction of the network, such uncertainties need to be piled on until common sense will come out.

2.5

Latour’s Five Sources of Uncertainty

Applying ANT, a researcher has the main task of tracing associations within a network, taking into account five types of controversies that take place (Latour, 2005; Verhoeven, 2009). Latour (2005) identifies and explains these controversies in detail, defining them as “uncertainty” because it is impossible to decide whether it resides in the observer or the phenomenon observed. According to Latour (2005), the five sources of uncertainty are the nature of groups, the nature of actions, the nature of objects, the nature of facts and the nature of the study itself. Latour (2005) argues that the ANT does not intend to establish whether society is “really” made up of small individual agents or large macro actors, but it, adopting a relativist approach, intends to understand how the social is generated by seeking to trace social connections starting from controversies (or uncertainty). The first source of uncertainty is the nature of groups according to which there are no fixed groups but there is only group formation (Latour, 2005). This uncertainty recalls the concepts expressed in the final part of the previous paragraph or that a network is never given once and for all but it always undergoes evolutions and changes through space and time. Therefore, groups never stop to evolve and reshape. In this regard Latour (2005) argued that, in ANT, if you stop making and remaking groups, you won’t have any groups at all (Latour, 2005: p. 35). In dealing with group formation, Latour (2005) recalls some elements proposed also in Callon’s (1986a) sociology of translation, in particular the figure of the spokesperson, which is legitimated to speak on the behalf of other actors; for Latour (2005) it has the fundamental role of recruiting actors to be enrolled in the network. In this regard Latour (2005) states: There is no group without some kind of recruiting officer. No flock of sheep without a shepherd—and his dog, his walking stick, his piles of vaccination certificates, his mountain of paperwork to get EU subsidies. (Latour, 2005: p. 32)

Groups do not exist by themselves, but they exist by virtue of the work of a “recruiting officer” (or spokesperson) who marked, delineated and rendered fixed and durable the boundaries of the group itself. During their association, groups leave many more traces that a researcher can follow to explain and describe the network creation process. This makes networks traceable and, therefore, analysable. In the production of the social, Latour (2005) introduces two new concepts or intermediaries and mediators. These two figures can be both means for the creation of the network, but they have different characteristics and functions. About these two

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2 Theoretical Framework: The Actor-Network Theory (ANT)

concepts, Latour (2005) defines the intermediary as “what transports meaning or force without transformation: defining its inputs is enough to define its outputs. For all practical purposes, an intermediary can be taken as a black box, but also as a black box counting for one, even if it is internally made of many parts” (Latour, 2005: p. 39). Conversely, Latour identifies the mediator as something that “cannot be counted as just one; they might count for one, for nothing, for several, or infinity. Their input is never a good predictor of their output; their specificity has to be taken into account every time. Mediators transform, translate, distort, and modify the meaning or the elements they are supposed to carry” (Latour, 2005: p. 39). The dichotomy between these two elements represents a crucial point in the thinking of Latour since it is from the “constant uncertainty over the intimate nature of entities— are they behaving as intermediaries or as mediators?—that derives the source of all the other uncertainties we have decided to follow” (Latour, 2005: p. 39). The second source of uncertainty regards the nature of actions. To analyse this source of uncertainty, it is useful to start from Latour’s (2005) words about it: Action is not done under the full control of consciousness; action should rather be felt as a nod, a knot, and a conglomerate of many surprising sets of agencies that have to be slowly disentangled. It is this venerable source of uncertainty that we wish to render vivid again in the odd expression of actor-network. . . Action should remain a surprise, a mediation, an event. (Latour, 2005: pp. 44; 46)

This second source of uncertainty relates to the agency or to whom or what is acting when an action can be observed (Czarniawska, 2006). According to Latour (2005), an actor never acts alone but uses a multitude of items and other actors. This leads back to the concept of actor as a network (see Sect. 2.1.3 or Law, 1992), and, in this regard, this represents the major source of uncertainty about the origin of action. For Latour (2005), in fact: To use the word ‘actor’ means that it’s never clear who and what is acting when we act since an actor on stage is never alone in acting. . . Action is borrowed, distributed, suggested, influenced, dominated, betrayed, translated. If an actor is said to be an actor-network, it is, first of all, to underline that it represents the major source of uncertainty about the origin of action. (Latour, 2005: p. 46)

In such a scenario, it becomes important to understand how some actors can make some other actors do something. ANT considers the world as a “concatenation of mediators” in which each mediator, acting, triggers other mediators leading to a lot of new and unpredictable situations (Latour, 2005). Therefore, concerning the action of an actor that involves other actors or objects, we cannot speak of the cause-effect relationship but of an action that triggers other actions. Regarding this concept Latour (2005) states: When a force manipulates another, it does not mean that it is a cause generating effects; it can also be an occasion for other things to start acting. (Latour, 2005: p. 60)

This concept refers to one of the fundamental assumptions of the ANT or the assumption that the “non-human” elements are to be considered actors that have their own agency. This paves the way for the third source of uncertainty or the nature of objects. Here Latour’s position is very clear. Not only humans are part of the

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Latour’s Five Sources of Uncertainty

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social or of the network but also non-humans have their specific functions and participate in the action. About this, Latour (2005) states: If action is limited a priori to what ‘intentional’, ‘meaningful’ humans do, it is hard to see how a hammer, a basket, a door closer, a cat, a rug, a mug, a list, or a tag could act. They might exist in the domain of ‘material’ ‘causal’ relations, but not in the ‘reflexive’ ‘symbolic’ domain of social relations. By contrast, if we stick to our decision to start from the controversies about actors and agencies, then any thing that does modify a state of affairs by making a difference is an actor. Thus, the questions to ask about any agent are simply the following: Does it make a difference in the course of some other agent’s action or not?. (Latour, 2005: p. 71)

From Latour’s words, it is clear that to determine whether an element can be classified as an actor, it is necessary to assess whether he makes any difference in the course of action. Obviously, concerning non-human actors, Latour specifies that they do not act autonomously but participate in the action through interaction with a human actor. An action becomes social when there is a “human dimension”. In this regard, moreover, Latour states that it is rare that the course of action consists only of human-human interactions or object-object connections, but it will be characterized by a “zig-zag” between the two. In addition to ‘determining’ and serving as a ‘backdrop for human action’, things might authorize, allow, afford, encourage, permit, suggest, influence, block, render possible, forbid, and so on. ANT is not the empty claim that objects do things ‘instead’ of human actors: it simply says that no science of the social can even begin if the question of who and what participates in the action is not first of all thoroughly explored, even though it might mean letting elements in which, for lack of a better term, we would call non-humans. . . the continuity of any course of action will rarely consist of human-to-human connections (for which the basic social skills would be enough anyway) or of object-object connections, but will probably zigzag from one to the other. (Latour, 2005: p. 72; 75)

From the above Latour’s words, it appears that objects also have agency, that is, they can induce one action rather than another (“authorize, allow, afford, encourage, permit, suggest, influence, block, render possible, forbid, and so on”) based on their physical characteristics and/or their functionality. Objects, in other words, do not determine the action but they can undoubtedly influence it. The fourth source of uncertainty is about the dichotomy between matter of facts and matter of concerns. In this dichotomy, concerns can turn suppositions into facts, but, at the same time, from facts they can emerge concerns (Czarniawska, 2006). In this respect, the ANT intends to study how matters become concerns or facts. About the fourth source of uncertainty, Latour (2005) writes: This is exactly what the fourth uncertainty wishes to thrive from: the mapping of scientific controversies about matters of concern should allow us to renew from top to bottom the very scene of empiricism—and hence the divide between ‘natural’ and ‘social’. . . Matters of fact may remain silent, they may allow themselves to be simply kicked and thumped at, but we are not going to run out of data about matters of concern as their traces are now found everywhere. If there is something disheartening for sociologists of associations, it is not the deep silence of a mute ‘Nature’ that would render their enquiries impossible and force them to stick to the ‘symbolic’ human realm, but the sheer flood of information on the many modes in which matters of concern exist in the contemporary world. (Latour, 2005: pp. 114; 115)

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Theoretical Framework: The Actor-Network Theory (ANT)

From Latour’s words, it seems that facts and concerns belong to two different worlds. Facts are silent while concerns leave so many traces. Facts seem to be something that happened and, therefore, immutable while concerns are more abstract; it is about something that could happen, a supposition that may or may not occur. Therefore, a concern can turn into a fact in exactly the same way as expected in the assumptions (at the basis of concern) or in a (partially or totally) different way from them. As a consequence, “things could be different or at least they could fail” (Latour, 2005: p. 89). From this, it derives the importance of focusing on how matters become concerns or facts, and, in particular, the importance of analysing the facts involved in the creation/evolution of networks. The fifth source of uncertainty regards the uncertainty about the study itself. Here the uncertainty lies in the fact that texts produced by social scientists can fail. As Latour himself states, “the mere description” is always a difficult task in a research report (Czarniawska, 2006) and it can easily fail (Latour, 2005: p. 133). The social can be understood as “a trail of associations between heterogeneous elements” (Latour, 2005: p. 5). According to Latour, therefore, a good text is the one that is able to draw a network (Latour, 2005 p. 128). A good ANT account is the one in which is outlined a story of actors who are doing something (“and don’t just sit there”) (Latour, 2005: p. 128) who are treated as mediators. In other words, a good ANT account makes the social visible by showing the movements of the mediators (Verhoeven, 2009) following the traces of the set of relations defined as so many translations (Latour, 2005: p. 129). At the end of this paragraph, it is interesting to conclude with a short aside by Latour (2005) which encases the meaning of what has been written so far. In order to trace an actor-network, what we have to do is to add to the many traces left by the social fluid through which the traces are rendered again present, provided something happens in it. In an actor-network account the relative proportion of mediators to intermediaries is increased. I will call such a description a risky account, meaning that it can easily fail—it does fail most of the time—since it can put aside neither the complete artificiality of the enterprise nor its claim to accuracy and truthfulness (Latour, 2005: p. 133).

2.6

ANT in Management Accounting and Control Studies

Since its origin, corresponding to the works of Callon (1986a) and Latour (1987), the ANT has inspired numerous management accounting researchers who have adopted this theory to explain different issues and dynamics related to management accounting and control. During the years, ANT in accounting research has been used for several purposes. Among the most widespread uses of ANT, it has been used to interpret and analyse the dynamics of change in accounting and control systems (Justesen & Mouritsen, 2011). Examples of this type of study are Miller (1991) and Robson (1991) who, through the ANT lens, explained accounting changes adopting a macro-level and historical inquiry approach. Other authors, rather than studying the change in accounting systems, have focused on the dynamics of introducing new accounting models by investigating the factors that come into play in such situations.

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ANT in Management Accounting and Control Studies

37

In this regard, Preston et al. (1992) analysed a case of the introduction of a new budgeting system in the UK health sector. In their study, Preston et al. (1992), taking as a theoretical point of reference Latour’s work “Science in action” (1987), developed a case study in which they highlighted the organizational and managerial dynamics which lay behind the introduction of a budgeting system. On the same line of research, Chua (1995) adopted a case study in the health sector to illustrate the introduction of a management accounting system, taking into account the events and actors involved in this process within the organization. Chua (1995) concludes that the management accounting system can only work if it is part of a larger network in which it acted as a moral mediator by helping to change the moral basis of healthcare debates. Similarly, Lowe (2001a, 2001b) studied the introduction of an accounting system in the New Zealand health sector with a particular focus on the role of actors and networks. In particular, Lowe (2001a, 2001b) analysed how human and non-human actors combine to constitute networks, and, consequently, provided insights into how accounting is practised within organizations. Beyond the studies on the health sector, Briers and Chua (2001) have shifted their attention to the manufacturing sector by elaborating a case study in which the introduction of an activity-based costing (ABC) system was analysed through the theoretical approach of the ANT. In their study, Briers and Chua (2001) introduced an idea of accounting as a means to connect and tie together all the different actors belonging to the network despite their different goals and agencies. On a similar line of thinking, Busco and Quattrone (2015) found that a traditional management control tool such as the Balanced Scorecard (BSC) represents a platform for mediation between various actors of a network. In particular, collecting and making visible the accounting inscriptions of various business areas, BSC can be conceived as a visual performable space that allows for discussion between the different actors thus triggering order and invention (Busco & Quattrone, 2015). In a similar vein, Revellino and Mouritsen (2015) emphasized the performative role of accounting showing that the calculative practices it stimulates foster innovation problematization and development. In other words, the calculative practices induced by the accounting inscriptions stimulate actors’ thinking and foster their decisions and behaviours. In the studies related to the implementation of new accounting systems, the ANT allows ascertaining how, in making the initial ideas concrete, the interactions between the actors and the facts that follow one another in the network can lead to unexpected and different results from those estimated (Justesen & Mouritsen, 2011).

2.6.1

ANT in Business Information Technologies Studies

In the ANT view, the creation and evolution of information technologies (IT) artefacts are the results of a complex and ever-changing social and material

38

2 Theoretical Framework: The Actor-Network Theory (ANT)

process (Orlikowski & Iacono, 2001) over time and space (Quattrone & Hopper, 2006). Orlikowski and Iacono (2001) highlight the fundamental characteristics of IT artefacts from an ANT perspective: • They are never neutral, universal or independent, but are the result of a continuous process of interpretations and interactions with social and material actors. IT is placed in a specific time and space and cannot disregard historical and cultural aspects. • They are made up of interconnected internal parts, often in a fragile or temporary way. While many scholars consider IT to be uniform and unproblematic, in practice they tend to be fragmented, causing problems or even failing. • They are characterized by being dynamic, not fixed, complete or immutable. They are never complete or black-boxed, and any stabilization state is only temporary (Orlikowski, 2000). The temporary nature of IT stabilization is because IT artefacts continually evolve due to the continuous social and material interactions they have with other actors of the network. Over the years, technological innovation has expanded exponentially, and IT have taken on an increasingly important role in business management, also integrating with traditional accounting and control systems. In particular, the use of IT solutions for management control is particularly suitable in operational contexts in which there is a distance between controlled and controlling subjects (such as multinationals or supply chains) (see, e.g., Quattrone & Hopper, 2005). In line with this, even the ANT has undergone a readjustment in its use by being adopted to analyse the implementation dynamics of new IT management control systems (such as ERP or SAP systems), especially in complex contexts such as multinational ones. One of the most cited studies in this field is the one of Quattrone and Hopper (2005) which paved the way for this line of research. The two authors, investigating the ERP introduction dynamics in two multinational organizations, highlighted that the new technologies did not increase the centralization of control but rather produced continual changes in loci of control. The existence of multiple and shifting centres and peripheries, with different interests and demands, has hindered action at a distance. This is strongly in line with the typical idea of the ANT that the networks are dynamic and always evolving, and the different interactions between human and non-human actors, as well as the agencies of which they are carriers, lead to changing and not unique results. These concepts emerge also in the work of Dechow and Mouritsen (2005) in which the authors underline as human actors and non-human actors (represented by ERP systems) influence each other in the course of their interaction. In the wake of Quattrone and Hopper (2005), Hyvönen et al. (2008) studied the case of a division-wide management control system introduction in a multinational enterprise. Hyvönen et al. (2008) also found that the different actors involved in the network (such as IT solutions, accountants and management) affect each other interacting with each other. Such interactions created new agency and rationality, beyond those proper of the actors themselves.

2.7

Research Questions Development

39

All these works seem to converge on the fact that the actors, human or non-human, tend to influence each other in the course of their interactions within the network, making the latter constantly evolving and difficult to take for granted. Furthermore, from the contributions analysed so far, it emerges that accounting and management control systems can have different roles and functions within the network dynamics. In this regard, Zawawi (2018) has recently proposed a distinction of the ANT-inspired accounting studies, distinguishing between “Accounting in the making” and “Accounting in the action”, basing on the role of accounting (and management control) within the network. In particular, in the studies in which the role of accounting is “in the making”, the accounting procedures are examined in the production, change and acceptance phases. The translation process, in this case, aims at ensuring that the accounting practices are accepted by the actors (Zawawi, 2018). Concerning the other point of the dichotomy, in the accounting “in the action”, the focus of the studies moves towards the role of accounting in influencing the behaviours within the network (Zawawi, 2018). In this case, scholars start from the assumption that the accounting systems are black-boxed and, therefore, have a role in organizations and society that is worth studying. More specifically, accounting can be understood as an inscription or the material representation of a meaning that translates a fact into a tangible sign (Latour, 1987), giving visibility to “invisible” objects (Justesen & Mouritsen, 2011). In the accounting field, inscriptions are signs that give a representation of company activities that can be recorded as they matured at the end of a decision-making process (Chua, 1995; Quattrone, 2016). Accounting inscriptions, therefore, are traces, histograms and recorded numbers that enable the action at distance (Corvellec et al., 2018), which is the capacity of an actor to influence many contexts in different spaces at the same time (Robson, 1992). Since accounting is increasingly computerized, new technological solutions have to become IT devices that, through the inscription of accounting numbers, make the action at distance possible by transferring the accounting numbers from one context to another (Corvellec et al., 2018; Quattrone, 2016).

2.7

Research Questions Development

The concepts and topics discussed so far are effectively summarized in the review by Robson and Bottausci (2018), which proposed another classification of accounting studies informed by ANT. In particular, the authors propose the following tripartite division: 1. The role of accounting inscriptions in making visible and constituting the entities and agencies upon which accounting operates 2. Processes of problematization, and in particular the construction of accounting “problems” and their “solutions”

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Theoretical Framework: The Actor-Network Theory (ANT)

3. The circulation of accounting and accountings at the margins, as accounting techniques both originate from and impact upon, domains that are far from the field of accounting, so as to shape private and economic action This last point provides a particular starting point for reflection since it considers accounting as an actor capable of influencing other actors and domains that are far from accounting issues. Starting from this, in the research field concerning control in situations of distance, the various authors cited so far focused mainly on the impact of new technologies on accounting and management control systems. What about the converse effect? If it is the interaction between the actors and the facts that take place in the network that constitutes the fulcrum of the ANT, then it is also interesting to study the way in which accounting and control systems affect and interplay with the technology and the other actors involved in the network (even if they are far from accounting issues). In line with this, this research aims to understand how accounting and management control systems interplay with a new technology (or the blockchain) highlighting their role in the process of introduction and acceptance of blockchain technology. More specifically, since accounting could affect actors’ emotional feelings (Boedker & Chua, 2013) as well as their innovative capacities (Busco & Quattrone, 2015), it could favour or hinder the acceptance and, thus, the introduction of the new technology. Therefore, the empirical section will highlight how existing and (temporary) black-boxed accounting and management control systems interplayed with the new technology and, conversely, if and how this latter, once implemented, affected in some way those taken for granted accounting and management control practices. Blockchain technology, given its peculiarities, can provide accounting information relating to the various actors it involves (controlled), integrating and making them visible in a centralized way to a single actor (controller). Anyway, will these features be enough to change and centralize the control systems? How could the complexity of the network and the multiplicity of interests, agencies and relationships between the various actors influence the introduction of this technology? Which role did the accounting actor have? Were the expected results of the blockchain implementation fully verified, or were there any deviations from what was expected due to the complexity of the network? All these theoretical prepositions, derived from the literature background presented above, can be translated into the following research questions that, in turn, will be addressed in the empirical section: R.Q. 1. How was blockchain was spread within a supply chain in an ANT approach? R.Q. 2. Which role did the management accounting and control systems have in the process of blockchain implementation and acceptance? How did accounting, management control and blockchain interplay and affect each other?

2.8

2.8

Conclusion

41

Conclusion

ANT has its roots in the scientific movement called science and technology studies. The main objective of ANT is to understand how actors form alliances and enrolled other actors, creating networks of aligned interests which are made up of humans as well as artefacts (Mähring et al., 2004). Over the years, this theoretical approach has been widely used by scholars to explain the role of technology within management practices (e.g., Orlikowski, 2010). This is mainly due to the three principles that characterize the ANT: generalized symmetry, agnosticism and free association (Callon, 1986a). These three principles require to abandon any a priori distinction between natural and social events or human and non-human actors, inducing the observer to adopt a neutral position without influencing or replacing the actors but rather following them and describing how they act and deal with controversies (Mclean & Hassard, 2004). Therefore, since human and non-human actors are symmetrical and each has its own interests and agencies, ANT is particularly suitable for explaining the dynamics of technologies’ use within companies and their effects on human actions and management practices. Among the different theoretical frameworks derived from ANT philosophy, in this research work the “sociology of translation” (Callon, 1986a) and the “five sources of uncertainties” (Latour, 2005) have been adopted to develop and interpret the field study. The “sociology of translation” is a helpful framework to trace the process through which a network takes shape or evolves (González & Cox, 2016). It refers to the process of making connections, setting passages between domains or establishing communication (Brown, 2002). In such a process, a key role is played by the focal actor who can exert control over other actors trying to enrol them into the network and aligning their interests with his own ones. Callon (1986a) identifies four interrelated stages through which the process of translation takes shape: problematization, interessement, enrolment and mobilization. The “five sources of uncertainties” (Latour, 2005) represent the main controversies that a researcher must consider when tracing associations within a network. According to Latour (2005), the five sources of uncertainty are the nature of groups, the nature of actions, the nature of objects, the nature of facts and the nature of the study itself. Based on this theoretical approach, a researcher should understand how the social is generated by seeking to trace social connections starting from controversies (or uncertainty). In this monograph, these two theoretical approaches have been combined to give a detailed representation of the network creation path related to the implementation of blockchain within a supply chain. Consequently, following the academic tradition of using ANT to explain the interaction dynamics between technology and management practices (e.g. Dechow & Mouritsen, 2005; Chua, 1995; Corvellec et al., 2018; Justesen & Mouritsen, 2011; Hyvönen et al., 2008; Orlikowski & Iacono, 2001; Quattrone & Hopper, 2005; Quattrone, 2006, 2016; Robson, 1992), and considering the literature shortcomings presented in the first chapter, the author has drawn the following research questions:

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R.Q. 1. How was blockchain spread within a supply chain in an ANT approach? R.Q. 2. Which role did the management accounting and control systems have in the process of blockchain implementation and acceptance? How did accounting, management control and blockchain interplay and affect each other?

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Chapter 3

Research Methodology

3.1

Introduction

The methodology represents a fundamental pillar in any research work. It represents the way in which a given reality is known or, in other words, “how to go about acquiring knowledge” (Grix, 2002). In social science, the objective of the researcher is to gather a series of data useful for understanding the different aspects that characterize a given society (Bailey, 2001). Unlike the natural sciences, in which a single paradigm can explain a certain reality, social science involves a plurality of paradigms, theories and methods (Hassard, 1995). In this sense, social science can be defined as a multi-paradigmatic science since there is no universally valid paradigm. This is due to the strong complexity that characterizes society. The latter can be understood not as a simple sum of individuals but as a collective reality with its own characteristics and within which particular consciences are present (Durkheim, 1895). The aggregation, combination and interdependence of individuals’ consciences give rise to a new individuality, and, from them, it derives the social life (Durkheim, 1895). In line with this definition, Durkheim (1895) thought that social phenomena can be defined as “the way of doing, established or not, likely to exert an external constraint on the individual or even that is general within a given society, regardless of its individual manifestations”. Consequently, a social phenomenon must have two characteristics: exteriority and constriction. Exteriority refers to the existence of a social fact regardless of its manifestation, while constriction concerns the pressure generated by the social fact itself on individuals. From Durkheim’s perspective (1895) it seems that social phenomena are given and that individuals passively suffer their effects as part of society. Weber (1949, 1958), on the other hand, believes that social phenomena are not given only by preconceived facts or laws but also derive from the voluntary actions of individuals who, therefore, constitute an active part of the social phenomenon. From the contributions of Durkheim and Weber to social science methodology, the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5_3

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Fig. 3.1 Stages in the research process. Source: Adapted from Bailey (2001)

complexity that characterizes social phenomena is even clearer. In light of this complexity, any research work in the social field needs to be structured in specific phases so that it can acquire rigour and scientific nature (Bailey, 2001). In line with this, Bailey (2001) argues that research is a system of connected and interdependent phases (see Fig. 3.1). The starting point of this circle, or the choice of the problem to be addressed and the related research hypothesis, is particularly influenced by the paradigm with which the researcher identifies. What is a paradigm, therefore, represents an important topic to be defined and discussed.

3.2

The Paradigm Concept

In social science, the concept of paradigm has crucial importance, but, at the same time, it has often been confused or misinterpreted by the different schools of thought (Corbetta, 2003). In philosophy, Platone defines paradigm as a stable model of changing realities, while for Aristotle the concept is defined as an example or as an archetype to refer to in explaining little-known facts. In modern sociology, Kuhn (1962), in his famous essay “The Structure of Scientific Revolutions”, gives one of the most accredited definitions of paradigm defining it as a conceptual structure or a general vision through which researchers look at the world and which precedes and grounds both theory and techniques. In his essay, Kuhn distinguishes between “normal” science and “revolutionary” periods. Within this duality, periods of normal science are constituted by the progressive accumulation of discoveries, and, therefore, there is a relationship of continuity between present and past discoveries and dominates a specific paradigm.

3.2

The Paradigm Concept

49

At some moments, defined as revolutionaries, this relationship of continuity with the past is interrupted by the impossibility of resolving certain problems, and a new period of science begins in which a completely new paradigm is affirmed. In Kuhn’s conception, therefore, the paradigm represents a conceptual structure, shared by a community of scientists, which, basing on previous assumptions and results, guides researchers in formulating hypotheses as well as in the choice of methods and techniques to be used in the research. More recently, Bailey (2001) defined the paradigm as “the mental window through which the researcher views the world”. To clarify the concept of paradigm, Bailey (2001) introduced a significant example. Malthus and Marx both faced the problem of overpopulation in the world. However, Malthus considered the existence of a natural law for which the population growth was exponential and of a geometric nature and proposed as a solution the moral control and the abstention from sexuality. Marx, on the other hand, rejected the existence of a natural law and traced the cause of the overpopulation to the surplus of labour required by capitalism. Therefore, the solution proposed by Marx was to move from a capitalist system to a socialist one. The differences that emerge between the two scholars in thinking about the problem and its possible solutions derive from the deeply different paradigms in which they are identified. Malthus, as an ecclesiastic, considered concepts such as poverty, vice and misery; Marx, on the contrary, placed the focus on class struggle and the exploitation of the lower classes. Different paradigms are characterized by different starting concepts and assumptions and, therefore, lead to different conclusions. In social science, a multitude of paradigms exist, and it is the researcher who chooses the one that he thinks is best able to explain a given phenomenon and, based on it, formulate hypotheses and research questions. Although each paradigm is different from the other, all of them are made up of three fundamental dimensions: ontology, epistemology and methodology. • Ontology: relates to being, to what exists, is the constituent units of reality (Hay, 2006) • Epistemology: concerns the ways in which it is possible to gain knowledge of reality (Blaikie, 2007), or what we can know about reality (Hay, 2002) • Methodology: how to go about acquiring knowledge of reality (Grix, 2002) These three elements are all related in a directional dependence through which ontology logically precedes epistemology which logically precedes methodology (Fig. 3.2) (Hay, 2002). In this sense, we cannot know (epistemology) something which nature and essence have not been defined (ontology), and, at the same time, we cannot set the strategies or the techniques for acquiring knowledge (methodology) if we don’t comprehend what can be known (epistemology) (Hay, 2006).

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Fig. 3.2 The directional dependence of ontology, epistemology and methodology. Source: Hay, 2002

3.2.1

Ontology

Ontology is a branch of philosophy that studies the nature of what exists (Blaikie, 2007). The more traditional philosophical treatments of ontology differentiate between two closely related sense of the term (Hay, 2006). A more abstract sense of ontology concerns the nature of being “itself”, while a second sense concerns the set of assumptions regarding the nature and the characteristics of a given object (Hay, 2006). Jacquette (2002) distinguishes between pure philosophical ontology and applied scientific ontology. In this latter context, ontology can be further understood as a discipline or a domain. Ontology as a discipline can be defined as an activity of enquiry into the philosophical problems of the concept or facts of existence, while ontology as a domain represents the topic of ontology as a discipline (Jacquette, 2002). In social science, ontology answers the question: “what is the nature of social reality?”, and each research starts from specific ontological assumptions and, therefore, from adopting a specific view of the world (Blaikie, 2007). Since ontology relates to the essence of what exists, it is evident why it precedes epistemology. It is impossible to realize what we are able to know if we don’t understand, at first, the nature of the reality in which knowledge has to be acquired (Hay, 2006). Once that the essence of reality has been ascertained, then it can be defined what it is possible to know, and thus the epistemology comes in.

3.2.2

Epistemology

If ontology concerns the nature of reality, epistemology concerns the nature and the structure of knowledge (Goldman, 2004). In light of this epistemology can be understood as the science or philosophy of knowledge, since it tries to respond to the question: “What are the conditions of acquiring knowledge of that which exists?”

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(Hay, 2002). In a sense, epistemology sets the limits to what we can know (Hay, 2006). In epistemology, therefore, the focus is on knowledge. Since knowledge is everchanging, epistemology is concerned with developing new models or theories that are better able to explain a given phenomenon than existing models and theories (Grix, 2002). Epistemology also contains values, and, as a consequence, it represents the basis for explaining the rightness or wrongness, the admissibility or inadmissibility, of types of knowledge (Carter & Little, 2007). In this sense, Carter and Little (2007) agree that epistemology justifies knowledge, while methodology justifies the method which, in turn, creates the basis of knowledge. In light of this, Carter and Little (2007) identified three main ways through which epistemology influences methodology: • Influencing the relationship between the researcher and the participant. • Influencing the way in which quality of methods is demonstrated. • Influencing the ways in which the researcher communicates with his audience. Choosing a given epistemological position, therefore, implies the use of a specific methodology to analyse a particular social phenomenon (Grix, 2002). This allows us to confirm the relation between epistemology and methodology since the choice of the techniques to be used in research (methodology) depends on the conditions and the limits related to the knowledge acquisition process (epistemology) (Hay, 2006).

3.2.3

Methodology

According to Blaikie (1993) the methodology concerns how research should or does proceed. Very often methodology is confused with methods used in the research (Grix, 2002), but these two elements are very different from each other. Methodology guides and justifies methods to be chosen (Carter & Little, 2007) which, in turn, represent the techniques for gathering evidence (Harding, 1987). The differences and the link between methodology and method are very well explained by Carter and Little (2007) according to which a methodologist is someone who helps us understand what methods are by describing, explaining, justifying and evaluating them. Carter and Little (2007), arguing that methodology deals with the set of logics that lay behind qualitative research, have elaborated, starting from the literature, a list of methodologies, typically used for qualitative researches, each of which justifies the use of different methods: 1. 2. 3. 4.

Grounded theory approaches Narrative, life history and biographical methodologies Ethnographies Participatory action research traditions

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5. Phenomenological or phenomenographic traditions 6. Case study approaches Based on the researcher’s position about ontology and epistemology, the qualitative methodology will be adopted (Corbetta, 2003). Historically there have been several paradigms, each of which interprets reality based on the different positions taken on the ontological, epistemological and methodological aspects (Corbetta, 2003). The three main alternative paradigms in the history of social studies are positivism, postpositivism and interpretivism.

3.3 3.3.1

Historical Approaches to Social Studies Positivism

The positivist paradigm was the first to be used in the social sciences (Corbetta, 2003). One of the founding fathers of this paradigm is Durkheim, who considered social facts as effectively existing independently of the individual consciousness of the researcher and, therefore, they can be objectively studied (Durkheim, 1895). Starting from these considerations, the positivist ontology is characterized by a naive realism since, for the positivists, the social reality exists and has a precise natural order, and its complexity could be overcome by reductionism (Aliyu et al., 2014). In light of this, in the positivist paradigm, human behaviours are guided by universal causal laws, and the researcher’s goal is to discover and document these laws (Neuman, 2014). Since reality exists apart from the researcher’s knowledge, on an epistemological level, positivism is characterized by the dualism between researcher and object of study that does not influence each other in any way (Corbetta, 2003). For these reasons, the methodology is experimental and manipulative. In particular, questions and/or hypotheses are stated in propositional form and subjected to empirical tests to verify them (Guba & Lincoln, 1994). Moreover, the separation between observed and observer leads the latter to proceed in a mainly inductive way (Corbetta, 2003). Researchers who adopt a positivist approach tend to have a realistic and objective world view and, therefore, prefer quantitative and confirmatory methods of analysis (Aliyu et al., 2014). Although the positivist philosophy has been adopted for many years by numerous scholars (including Comte and Durkheim were the precursors), it has revealed some important critical points. Orlikowski and Baroudi (1991) discuss two fundamental weaknesses of positivist philosophy. At first, the quest for universal laws can lead to neglecting the influences that history or contexts can have on human action. However, in any social field, actions and decisions are often taken based on past experiences (Orlikowski & Baroudi, 1991). Therefore, conducting social research regardless of the historical events that preceded and characterized a given phenomenon could be misleading.

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The other criticism that Orlikowski and Baroudi (1991) move towards positivist philosophy concerns research techniques. Having a deterministic approach to the explanation of phenomena, the positivist researcher places himself in a predefined and circumscribed position concerning the object of study. This approach appears to be weak and limiting when the research aims to discover and understand non-deterministic and reciprocal relationships (Orlikowski & Baroudi, 1991). Finally, on an epistemological level, positivism supports the duality between the observed and the observer, which is characterized by being detached, objective and impartial. However, Aliyu et al. (2014) underline how the positivist philosophy has not been able to define a truly impartial approach, and, therefore, it tends to be selfcontradictory by examining events that are formed by the researcher. The limits revealed by positivism have led scholars to modify the paradigm itself. Therefore, to respond to the criticisms that had been advanced on positivism, scholars founded the paradigm of postpositivism (Corbetta, 2003).

3.3.2

Postpositivism

Postpositivism has its roots in positivism but shows significant differences compared to it in ontological, epistemological and methodological terms. Although postpositivism takes up, from positivism, the valorization of rationality and empirical knowledge over other ways of knowing (Henderson, 2011), it is partially detached as regards the ontological position. With postpositivism, there is a transition from naive realism to critical realism. In postpositivism, it is assumed that reality exists but that it is not perfectly knowable (as instead was thought in positivism) because of the limited human intellectual abilities and the complex nature of the phenomena (Guba & Lincoln, 1994). Ultimately, for the positivists, the understanding of reality can take place as faithfully as possible but never perfectly (Guba & Lincoln, 1994). The new ontology that characterizes the postpositivism paradigm implies changes also at the epistemological level. In this case, epistemology recognizes the existence of a relationship of interference between researcher and object of study (Corbetta, 2003) simultaneously denying the duality between the two and the total independence of the scholar preached in positivism. The acknowledged impossibility of knowing perfectly the reality and the abandonment of the complete objectivity of the researcher lead to affirm that in postpositivism the existence of a cause-effect relationship can never be verified in an absolute way but only falsified or not falsified (Popper, 1934). Non-falsification states that a given hypothesis cannot be confirmed positively but only negatively. In other words, if the research results confirm the basic hypothesis, it is possible to affirm that the hypothesis has not been denied by the observations made and by the relative empirical results (Corbetta, 2003).

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Lastly, the methodology continues to be purely quantitative but also shows an openness towards more qualitative methods of investigation (Corbetta, 2003) or mixed methods (Henderson, 2011). In particular, postpositivism, opening itself to more qualitative methods, intends to correct some distortions of positivism (such as the search for absolute natural laws that go beyond the social context) gathering information related also to the context of investigation and trying to interpret the meaning and the purpose that people attribute to their actions (Guba & Lincoln, 1994). In so doing postpositivism contributes to the creation of grounded theory (Strauss & Corbin, 1990) or general theories built on empirical findings.

3.3.3

Interpretivism

The paradigm of interpretivism is placed at the opposite of positivism and postpositivism. According to the interpretive philosophy, reality and human knowledge are social products, and, therefore, they are impossible to understand apart from the social actors (including researchers) who build and give meaning to that reality (Orlikowski & Baroudi, 1991). Ontologically speaking, in interpretivism, reality exists, but it is not objectively predetermined; rather it turns out to be the product of social constructions (Husserl, 1965). Epistemology provides for a separation between the scholar and the object of the study, but social research, in this case, aims to interpret a given reality rather than seek universally valid laws (Corbetta, 2003). This paradigm, therefore, concerns the investigation of the uniqueness of a given phenomenon and the understanding of its most intimate and profound aspects (Kelliher, 2011). Given its peculiarities, interpretivism promotes the validity of qualitative data in the pursuit of knowledge (Kaplan & Maxwell, 1994). Unlike the positivists, therefore, the interpretivists prefer a qualitative methodology since the latter is more adequate in studying a given phenomenon in its complexity, trying to understand its deeper characteristics. In the social sciences, the fathers of interpretivist philosophy were Max Weber and Wilhelm Dilthey. Weber (1981), in particular, argued that the social sciences should have, as a final goal, the study of social action. Accordingly, we must learn the personal reasons that shape a person’s internal feelings and guide its decisions to act in a certain way (Weber, 1981; Neuman, 2014). In light of these reflections, the interpretivist researcher needs to empathize with the people he studies, temporarily sharing their values and social commitments (Neuman, 2014). In this sense interpretivism adopts a relativist position since no single point of view or value position is better than others, and all are equally valid for those who hold them (Neuman, 2014).

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Historical Approaches to Social Studies

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In modern interpretivism, the relativistic position is flanked by the constructivist one. In constructivism, the realities are learnable in the form of multiple and intangible mental constructions, based on the social experiences and cultures of individuals or groups of them, from which the form and content of the realities themselves are also determined (Guba & Lincoln, 1994). In light of this, individuals develop subjective and multiple meanings of their experiences that are often not simply imprinted on individuals but are formed both through the interaction with others (hence social constructivism) and through the individuals’ historical and cultural background (Creswell, 2014). Therefore, constructivist researchers tend to take into consideration the processes of interaction between individuals as well as the specific contexts in which people live and work, to understand the complexity of opinions, also considering the historical and cultural background of the participants (Creswell, 2014). The investigator and the subject of the investigation, hence, are connected interactively so that the results are literally created as the investigation proceeds (Guba & Lincoln, 1994). These constructions are interpreted by the researcher based on his personal background and compared through a dialectical exchange with the research participants (Guba & Lincoln, 1994; Creswell, 2014). What has been shown so far regards the three main paradigms that have taken place, over the last century, in the field of social sciences. Each paradigm starts from different ontological assumptions and ways of perceiving realities which, consequently, lead to different research processes. Table 3.1 provides a summary of the main features of social research paradigms. After illustrating the paradigms of social research, it is appropriate to focus attention on a peculiar social phenomenon that represents the main object of the present research work: the company. The company is a social phenomenon that encompasses multiple research realities and is characterized by the presence, participation and interaction of people. People, in turn, with their culture, their experiences and their uniqueness, make a company unique and unrepeatable in the multiplicity of the economic context (Catturi, 2003). In other words, the company represents a social reality that is too complex to be universally understood and, therefore, should be interpreted rather than demonstrated. As composed of people, the corporate organism cannot be traced back to numerical factors as men with their ideas, their culture and their creativity make the company phenomenon unpredictable as well as unique in its multiplicity (Catturi, 2003). For this reason, the methodological approach to be used, when one intends to study the most intimate aspects of a business reality as well as its internal dynamics and its peculiarities, is the qualitative one (Eriksson & Kovalainen, 2015) and, in particular, the case study approach (Eisenhardt, 1989; Siggelkow, 2007). Accordingly, the case study method constitutes the investigation approach used for the empirical development of this work. In the following lines, the features of the case study method will be highlighted.

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Table 3.1 Summary table of the main paradigms of social research Ontology

Positivism Naive realism Reality exists and has a precise natural order and it is fully knowable (Aliyu et al., 2014)

Epistemology

Dualism and objectivity The goal is to find universally true and generalizable results and to explain the existence of immutable “natural” laws (Aliyu et al., 2014; Neuman, 2014)

Methodology

Experimental and Manipulative (Guba & Lincoln, 1994) Methods: Quantitative techniques of analysis (Guba & Lincoln, 1994)

Postpositivism Critical Realism Reality exists but it is not perfectly knowable because of the limited human intellectual abilities and the complex nature of the phenomena (Guba & Lincoln, 1994) Modified dualism and objectivity The goal is to find probabilistically true results and find temporary laws that could be falsified or not falsified (Popper, 1934; Corbetta, 2003)

Modified Experimental and Manipulative (Guba & Lincoln, 1994) Methods: Quantitative techniques of analysis with openings to qualitative and mixed ones (Corbetta, 2003; Henderson, 2011)

Interpretivism Relativism and constructivism Reality exists but it is not objectively predetermined; rather it turns out to be the product of social constructions (Husserl, 1965) Non-dualism and non-objectivity The goal is to understand reality (rather than explain it) by investigating unique phenomena in order to understand their most intimate and profound aspects (Kelliher, 2011) also considering peoples’ background (Creswell, 2014) Empathic interaction between scholar and object of study (Neuman, 2014) Methods: Qualitative techniques of analysis (Kaplan & Maxwell, 1994)

Source: Own elaboration based on literature

3.4

The Case Study Method

In the business field, the qualitative approach to research is appropriate, as well as needed, when the researcher aims to deepen the internal firm’s dynamics focusing on the complexity of business-related phenomena (Eriksson & Kovalainen, 2015). Starting from these premises, more and more scholars are adopting qualitative perspectives of analysis in studying management and accounting topics as well as an ever-increasing number of management journals are focussing upon qualitative methods and issues (Cassell et al., 2017). The most distinctive characteristic of qualitative research is its emphasis on interpretation (Erickson, 1986). The interpretative approach is particularly effective when dealing with complex phenomena of which a researcher wants to gain an in-depth understanding. In such circumstance, the case study represents an appropriate methodology to catch the complexity of a

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The Case Study Method

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given phenomenon (Stake, 1995). In particular, the case study emphasizes the uniqueness of the case under investigation, and it is particularly effective when the objective of analysis has a special interest (Stake, 1995). As widely debated in the prior paragraph, companies are unique and complex, and, thus, case study methodology can represent an effective methodology for the interpretation and understanding of their complexity. For this reason, the research methodology chosen was the case study. Stake (1995) gives a particular and widely supported definition of case study: Case study is the study of the particularity and complexity of a single case. . . [emphasising] episodes of nuance, the sequentially of happenings in the context, the wholeness of the individual.

From this definition, we can understand how the case study turns out to be an appropriate investigative approach when conducting interpretive-based research in which the important thing is the in-depth understanding rather than the generalization of results. The case study is well suited for answering questions about “why”, “who” and “how”; and, thus, it is useful for investigating events that are occurring in a contemporary context (Farquhar, 2012). The case study approach, anyway, can be adopted in several ways, according to the aims or the type of research to be carried out. In particular, Scapens (1990) and Scholz and Tietje (2002) classified the main types of case study based on the different research purposes to be reached: • Exploratory case studies. This kind of case study is used when the objective of the research is to explore reasons for particular business practices. It helps in getting insights into the structure of a phenomenon to develop hypotheses, models and theories. This kind of case study is generally used in pilot studies. • Explanatory case studies. Through this case study, the researcher attempts to explain the reasons for given business practices. In this circumstance, the theory is used to understand and explain the specificity of a phenomenon, rather than to produce generalisations. • Illustrative case studies. This type of case study attempts to illustrate new and innovative practices developed by particular companies. Such case studies illustrate what has been achieved in practice. • Descriptive case studies. With this case study, the researcher attempts to describe particular business practices. This kind of case study could be useful in highlighting similarities and differences in the practices of different companies. In this circumstance, the reference theory guides the case description as well as the data collection process. • Experimental case studies. This particular case study is used to practically experiment with the application of new managerial practices (developed by the researcher) to evaluate the relative difficulties and benefits. Beyond this classification, any case study can be designed on a single subject or on a plurality of subjects (here case study can be defined respectively as single and

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Fig. 3.3 The Welch et al. (2011) methods of theorizing from case studies. Source: Welch et al. (2011)

multiple case study) and can also be classified as a holistic or embedded case study, according to the type of analysis performed (Scholz & Tietje, 2002). The single case study should be chosen when the case to be investigated is unique and particularly revelatory to the understanding of a phenomenon (Scholz & Tietje, 2002). On the other hand, the multiple case study is used, in a logic of replication, to perform multiple experiments (Scholz & Tietje, 2002) and eventually construct new theoretical assumptions (Eisenhardt, 1989). Based on the type of analysis conducted, instead, the case study can be classified as holistic or embedded. The holistic case study involves a single unit of analysis and relies on narrative and phenomenological description. The embedded case study, on the other hand, involves a plurality of subjects (which generally make up the subunits of the entity under investigation), resulting particularly useful in comparing the rival interpretations strengthening, therefore, the internal validity of the analysis (Yin, 2003). In addition to these categorizations, in recent years, Welch et al. (2011) and Tsang (2013) propose a new case study classification based on the emphasis that the research has on contextualization, theory development and causal explanation. In particular, Welch et al. (2011) stated that case studies deal with two particular factors or the contextualization and research for causal explanation. In line with the emphasis that the case study places on these factors, it can be classified into one of the following categories (Fig. 3.3). By combining the degree of emphasis on contextualization and causal explanation, the case study can be classified in four different ways. In the first quadrant (quadrant 1), the case study put weak emphasis on both contextualisation and causal explanation. Here the case study privileges the pursuit of nomothetic, law-like generalizations, and the search for regularities rather than causes, in an inductive theory-building approach (Welch et al., 2011). In the second quadrant (quadrant 2), the case is characterized by a weak emphasis on contextualization, but, at the same time, it puts a strong emphasis on causal explanation. In this circumstance, the case study aims to generate causal, internally valid explanations through natural

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The Case Study Method

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Fig. 3.4 The Tsang (2013) methods of theorizing from case studies. Source: Tsang (2013)

experiments. The third and fourth quadrants (quadrant 3 and 4) are characterized by the strong emphasis put by the case study on contextualization. In particular, in the “interpretive-sensemaking method” (or quadrant 3), the case study aims in seeking an in-depth understanding of human experience embedded in a real-world context, and it is less focused on contributing to the development of any abstract theory (Tsang, 2013). In the last quadrant (quadrant 4) or the method of “contextualized explanation”, there is a strong emphasis on both contextualization and causal explanation so that the focus of the case study is more on testing or developing theoretical assumptions. The categorization of the case study proposed by Welch et al. (2011) has been partially criticized by Tsang (2013). According to the latter, Welch et al. (2011) commit an inaccuracy in the trade-off between contextualization and causal explanation. According to Tsang (2013), many unequivocally causal explanations are yet highly contextualized, and, therefore, he argues that the trade-off proposed by Welch et al. (2011) has more to do with the generalization-contextualization dichotomy. In light of these considerations, Tsang (2013) proposes a new and little modified classification of case studies replacing the emphasis on causal explanation with the emphasis that the case itself puts on theory development (Fig. 3.4). In other words, the new dimension concerns the extent to which researchers rely on existing theories to interpret their case studies’ results or use such results for advancing theory, thus testing existing theories or creating new ones (Tsang, 2013). In the new framework proposed by Tsang (2013), quadrants 3 and 4 (or “interpretive sensemaking” and “contextualized explanation”) remain unchanged. Quadrants 1 and 2, instead, are revised. In the first quadrant, characterized by both weak emphasis on contextualization and weak emphasis on theory development, case study results highlight empirical regularities rather than theory creation (as instead provided in Welch et al. framework). The creation of a new theory is rather the result of a strong emphasis on theory development and a weak emphasis on contextualization (or quadrant 2.). In this circumstance, the researcher

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aims to extract theoretical assumptions from the case or case, with the specific intent of building a new theory or testing an existing one (Tsang, 2013). In light of these categorizations of case study, it is possible, as well as needed, to define the type of case study which will be performed in the empirical chapter of this study. Since the phenomenon under investigation (the application of blockchain in business management) is new and innovative, but, at the same time, it still has a small diffusion, the case study will be surely illustrative. Moreover, since this study aims to be among the first to investigate the managerial implications related to blockchain use, the case study will seek both to explore the reasons and internal dynamics that supported the adoption of this technology (exploratory) and to explain how this adoption process took place within a supply chain context (explanatory). As a consequence, the case study performed has a threefold nature: illustrative, exploratory and explanatory. Finally, about the framework of Tsang (2013), the main purpose of this work is to in-depth understand the human experience related to blockchain use in management practices embedded in a supply chain context. Considering this, the case study falls into the “interpretive sensemaking” category, and, therefore, the reference theory is used to understand and explain the specificity of the phenomenon. Despite that case study has been recognized as a useful methodology to understand the complexity and contextual depth of phenomena, it has been widely criticized in terms of validity and reliability (Kelliher, 2011). In a single case study, these latter criticisms have been partially overcome through triangulation, which is a particular method to fortify validation, especially when terms of comparison are absent (Kelliher, 2011), and that will be discussed in the next paragraph.

3.4.1

Triangulation

Triangulation refers to the combination of different kinds of methods, samples and perspectives that a researcher realizes to improve the validity of qualitative research and to obtain a comprehensive understanding of phenomena (Patton, 1999). According to Patton (1999), single methods do not provide for a comprehensive understanding, but each method reveals specific aspects of an empirical reality. Triangulation aims at overcoming such criticality through the combination of multiple methods of data collection and analysis. Carter et al. (2014), starting from the works of Denzin (1978a) and Patton (1999), realize an overview of the different types of triangulation, deepening the characteristics of each of them. In particular, Carter et al. (2014) show four types of triangulation: theory triangulation, methods triangulation, investigator triangulation and data source triangulation. Theory triangulation requires that the same data source is interpreted through multiple perspectives, hypotheses and various theoretical points of view, to assess its utility (Flick, 2018). In this type of triangulation, theoretical assumptions represent useful means to assist the researcher in supporting or refuting findings (Carter et al., 2014).

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Methods triangulation often involves the adoption of both qualitative and quantitative methods in data gathering (Patton, 1999) or, at least, the use of different kind of methods such as the combination of demographic techniques with formal interviewing and unstructured interviews (Denzin, 1978b). Since quantitative and qualitative methods are generally used to answer different types of research questions, this triangulation is often difficult to implement (Patton, 1999). Investigator triangulation aims at reducing subjectivity or minimizing biased results employing two or more researchers in the data gathering and data analysis processes (Denzin, 1978b; Flick, 2018). This kind of triangulation requires a systematic comparison of different researchers’ points of view on the results of the research, rather than a simple division of labour, (Flick, 2018) to confirm the results themselves or raise different perspectives, adding breadth to the phenomenon of interest (Carter et al., 2014). The most important form of triangulation is the data one. Data triangulation refers to the use of different sources of data to strengthen the validity of the results enhancing, in this way, the quality of the case study (Yin, 2014). According to Yin (2014) gathering data from different sources is not enough; it is necessary to corroborate them consistent with the same finding. In this sense, Yin (2014) identifies two fundamental conditions: the first in which the data collected lead to the same finding (convergence of sources) and the second in which the various documentary sources lead to different findings (non-convergence of sources) (Fig. 3.5). Multiple sources of evidence provide multiple measures of the same phenomenon, but it is the convergence of evidence that strengthens the validity of the case study (Yin, 2014). This is especially true when the phenomenon of interest may pertain to behavioural or social aspects, which, by nature, are difficult to interpret. The use and convergence of evidence from multiple sources would then increase accuracy in the analysis and interpretation of the phenomenon under investigation (Yin, 2014). The sources involved in the data triangulation can be historical archives or written documents which, in the case of business case studies, can be both public and internal. These sources are then supported by open-ended interviews, structured interviews and surveys, aimed at corroborating the case study findings and supporting the researcher in interpreting the phenomenon studied rigorously. Data triangulation is more and more used by case study researchers as part of their data collection strategy (Ridder, 2017) strengthening, thus, case study validity. The author of this monograph recognizes the validity of considering multiple documentary sources in developing a case study, just as proposed by the scholars cited so far. Unlike the latter, however, the author believes that analysing different documentary sources serves not to give a complete representation of reality (which is impossible to represent given the multitude of actors involved and the complexity of the phenomenon) but rather to clarify how the interpretations of events and the meanings attributed to the actors have been derived to outline a story pertinent to the research problems (Quattrone & Hopper, 2005). In this sense, relying on multiple data sources and triangulating them is functional to retrace the events and elaborate a meaningful narrative plot (Czarniawska, 2011).

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Convergence of Evidence (Single study)

Documents

Archival Records

Open-ended Interviews

Findings

Observations (direct and participant)

Structured interviews and surveys

Focus Interviews

Non-Convergence of Evidence (separate substudies) Site visits

Findings

Conclusions

Survey

Findings

Conclusions

Document

Findings

Conclusions

analysis

Fig. 3.5 Convergence and non-convergence of multiple sources of evidence. Source: Yin (2014)

3.5

Case Selection and Data Collection

Case studies are often criticized as being considered too context-specific and their results difficult to generalize (Flyvbjerg, 2006). In general, science tries to find results that are as generalizable as possible and that can universally explain a given phenomenon. This statement is not entirely valid concerning the social sciences. According to Flyvbjerg (2006), social science can hardly produce general and context-independent theory, while it often offers concrete and contextdependent knowledge. As discussed in the first paragraphs of this chapter, the reality is not fully knowable but only interpretable. In line with this, social research should not focus on producing irrefutable and universally valid results, but on producing in-depth knowledge of the different facets of a given phenomenon (Quattrone, 2006; Czarniawska, 2014). Accordingly, Flyvbjerg (2006) states that in social science, a “hard” theory (capable of explaining a given phenomenon once and for all) is absent, whereas learning is certainly possible. From this, we can deduce that, in social research, the ultimate goal is not to demonstrate something but rather to understand and learn from a phenomenon. In light of this, the case study, delving into unique exemplars of a given context, is particularly suitable for producing contextdependent knowledge (Flyvbjerg, 2006), which contributes to the understanding of

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Case Selection and Data Collection

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a specific phenomenon. Despite these reflections, the generalizability of case studies can be improved through a strategic selection of the case study (Flyvbjerg, 2006). In particular, among the different types of case study, the paradigmatic case (Agamben, 2009; Flyvbjerg, 2006) is the one that can better mitigate the generalizability issues and the problem of the context-specific knowledge. Agamben (2009), relying on Kuhn’s (1970) reflections, defines a paradigm as a singular case, an example that, due to its singularity, makes intelligible a new phenomenon and tacitly models the behaviour and the research practices of scientists. In this regard, Flyvbjerg (2006) argues that no standard exists for the paradigmatic case because it sets the standard. Given the above methodological assumptions and the research objectives of this study, the first European case of blockchain implementation in the agro-food supply chain was selected in developing this research. This represents a paradigmatic case since it set the standard of a new phenomenon being among the first practical blockchain application within a supply chain. Being careful to not confuse the case study with a single organization but recognizing it as the study of a single phenomenon, the analysis involved a plurality of companies participating in the process of blockchain implementation within an agro-food supply chain. The first company involved was ALFA (fantasy name to protect the company’s privacy) which is a food retailer that at first promoted the implementation of the blockchain within its supply chains. It is a very big company with a high influence on its suppliers and business partners. The second company involved was BETA (fantasy name to protect the company’s privacy) which is the leader of the supply chain in which the blockchain was implemented (namely, the chicken supply chain). It is a big food producer, and it has strong contractual relationships with the breeders upstream of the supply chain. The third company involved is GAMMA (fantasy name to protect the company’s privacy) that is the technology consultant and provider. Finally, a breeder was involved as a counterpoint to the empirical observations made in previous actors. The data collection process was performed in a period of 6 months, from February 2019 to July 2019. The data collection process was functional at tracing back all the events and actors involved in the blockchain technology diffusion process. As a first step, it was collected official publicly available information about the ALFA blockchain project to have a first understanding of the technology and its application along the supply chain. In a second step, ALFA’s managers mainly involved in the blockchain project were identified and thus interviewed. This step of the analysis was crucial to have a map of all the actors, work phases and events followed throughout the entire project. From the information gathered in this second step, it was intercepted and interviewed: the managers of BETA (or the manufacturer and supplier of ALFA), a farmer and the blockchain experts of GAMMA (or the company that provided the technical consultancy and that installed the technology). In this step, all the main actors participating in the blockchain project were involved. The interviews were conducted by asking open questions to the actors involved, thus adopting a narrative approach. Following Czarniawska (2011), the interviewee was free to choose the structure of the speech, the contents and the examples through which to reconstruct and narrate the events that occurred

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Table 3.2 Summary table of the interviews carried out for the development of the case study Interviewee’s company affiliation ALFA ALFA ALFA ALFA ALFA ALFA

BETA BETA GAMMA GAMMA Farm

Interviewee’s company position Strategic planning manager Private label director Supply chain manager Innovation manager Brand manager and project manager Blockchain Junior brand manager

Number of interviews 2

Average duration of each interview 1 hour and half

Type of interview Face to face

1 1 1 1

1 hour 2 hours 2 hours 2 hours

Face to face Face to face Face to face Face to face

2

1 hour

IT manager Quality manager & suppliers’ controller Partner in the transaction advisory services (TAS) Blockchain HUB MED leader Owner (breeder in the text)

1 1

1 hour 1 hour

Face to face and phone call Skype call Skype call

1

30 min

Phone call

1

30 min

Phone call

1

1 hour

Face to face

Source: Own elaboration

in a specific period. Table 3.2 illustrates the people interviewed and summarizes the details of the interviews carried out for this research. Annex 1 reports the draft of the questions asked in the business organizations involved. For length reasons, the author has selected and reported only some extracts of the vast narrative actors gave during the interviews. The author included in this monograph only the sentences and the anecdotes that, according to him, are most suitable to represent the investigated phenomenon. During the several face-to-face interviews, furthermore, the internal documents and the physical artefacts inherent in both the blockchain technology and the accounting and management control systems have been observed and, thus, taken into account into the development of the case study. The observations, combined with interviews, allow the researcher to follow the actors and reconstruct the events that characterize the social reality (Latour, 2005). In this way, the researcher can see how actors work, act and interact with each other forming associations in the investigated context. Therefore, multiple and various documentary sources were analysed to interpret the events of the phenomenon under investigation. In particular, care was taken to question the various actors regarding the same events and facts, trying to maintain maximum consistency throughout the data collection process. The various statements obtained during the interviews were then corroborated with the analysis of the documents collected (such as interviews previously released by the managers themselves with journalistic publications, brochures explaining the blockchain technology, accounting and data collection

3.6

Conclusion

65

systems, blockchain landing pages, etc.). The use of multiple documentary sources was also useful for tracing back the events that characterized the investigated phenomenon and to develop a meaningful narrative plot (Czarniawska, 2011). This represented the core of the research since, as Czarniawska (2011: p. 27) argues citing Law (1994): Nothing ever happens right where and when the researcher is observing. All important events happen at some other time, other place . . . Nobody is aware that an important event is happening when it takes place.

Finally, the involvement of numerous corporate actors with different backgrounds and different roles within the project allowed me to study the phenomenon under investigation from different points of view, increasing the accuracy in the interpretation of events. In summary, Table 3.3 shows the main phases in which the research was articulated, explaining the actions taken and the protocol followed, from the conception of the research idea to the final interpretation of the data.

3.6

Conclusion

This chapter deals with the methodological aspects underlying the research. The methodology represents the way through which a researcher acquires knowledge (Grix, 2002). In social science, the researcher aims to understand the different aspects that characterize a given society (Bailey, 2001). Social science involves a plurality of paradigms, theories and methods (Hassard, 1995), and, for this reason, it can be defined as a multi-paradigmatic science since. Although multiple paradigms exist, and each is different from the other, all of them are made up of three fundamental dimensions: ontology, epistemology and methodology. Ontology relates to being, to what exists, is the constituent units of reality (Hay, 2006). Epistemology concerns the ways in which it is possible to gain knowledge of reality (Blaikie, 2007), or what we can know about reality (Hay, 2002). Methodology concerns how to go about acquiring knowledge of reality (Grix, 2002). Historically there have been several paradigms, each of which interprets reality based on the different positions taken on the ontological, epistemological and methodological aspects (Corbetta, 2003). The three main alternative paradigms in the history of social studies are positivism, postpositivism and interpretivism. The company, which is the object of this research, constitutes a social reality that is too complex to be universally understood, and, therefore, it should be interpreted rather than demonstrated. In this regard, the case study represents the appropriate methodology to deepen the most intimate aspects of a business reality as well as its internal dynamics and its peculiarities (e.g. Eisenhardt, 1989; Siggelkow, 2007). To carry out the research, the author relied on a paradigmatic case study or a unique case that, due to its singularity, makes intelligible a new phenomenon (Agamben, 2009; Kuhn, 1970). The investigated case study concerns one of the first European

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Table 3.3 Summary table of the research steps Steps of the research Step 1

Step 2

Actions taken Identification of research gaps and formulation of the research questions The choice of the business case

Step 3

Interviews

Step 4

Business documents analysis

Step 5

Data triangulation

Description of activities carried out On the basis of the gaps found in literature, they were identified the research questions to be investigated in the study Identification of the ALFA case (as it was the first blockchain adopter in the EU agri-food sector) and verification of willingness to collaborate by sending emails to the main company managers Semi-structured interviews have been conducted with the main business actors involved in the blockchain project in order to have their viewpoints about the phenomenon investigated. The main contents and statements, which emerged from the interviews, were then transcribed and corroborated with the business documents analysis (see next step) During the interviews it was asked to the managers to show the business documents involved in the blockchain project. In this step the author was able to take a look at accounting models, software, business presentations and other documentation explaining the technology peculiarities. This step was useful for increasing the reliability of the managers’ declarations and for carrying out the data triangulation Once the oral and documentary sources were collected, the data triangulation was carried out. In particular, the data collected from public sources, the statements made by managers and the documents consulted during the visits to the companies’ headquarters were compared in order to strengthen the results of the case study and to trace-back the flow of events that led to the creation of the network. Specifically, the interviews were recorded and subsequently transcribed. Then the researcher extracted the key phrases and examples helpful to represent the phenomenon. These sentences were compared with publicly available data and the researcher’s observations about the contents of accounting systems and blockchain technology. This step was functional in verifying the consistency and coherence of the documentary sources and providing a detailed narrative of the events that characterized the investigated phenomenon. (continued)

References

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Table 3.3 (continued) Steps of the research Step 6

Actions taken Interpretation of the results and monograph writing

Description of activities carried out In the last step of the research, the case study results and insights have been interpreted and presented in written form, thus proceeding to the writing of the monograph. Obviously, the author is well aware that it is not possible to affirm that the data collected is representative of the entire reality observed. In fact, as extremely complex and articulated, the reality of a company can never be fully knowable. However, based on the data collected, the author tried to interpret the events and the actions occurred in the network investigated, in order to fulfill the research purposes.

Source: Own elaboration

applications of the blockchain within a supply chain, and, for this reason, it sets the standard in the reference research field. In developing the case study, the author involved a plurality of companies participating in the process of blockchain implementation. The author collected official publicly available information about the blockchain project, interviewed the main business actors involved in the initiative and examined the internal documents and the physical artefacts inherent in both the blockchain technology and the accounting and management control systems. At the end of the data collection process, data triangulation was performed to accurately trace back and report all the events and actors involved in the blockchain technology diffusion process.

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Chapter 4

Unboxing the Network: The Empirical Case Study

4.1

Introduction

Once the theoretical background has been clarified and explained, the work proceeds with the empirical analysis of the case study. In this research, the frameworks of Callon (1986) and Latour (2005) will be combined in the explanation of the dynamics that occurred during the introduction and spread of blockchain technology in the ALFA chicken supply chain. In particular, at first will be presented the case background; secondly, actors and facts that occurred in the process of spread of the blockchain will be highlighted according to the sources of uncertainty proposed by Latour (2005) which are combined with the phases of the sociology of translation of Callon (1986). The present empirical section closes with the discussion of the results through which the research questions that guided the study will be answered, and the contribution of the present work to the existing literature will be shown.

4.2

Background

ALFA is one of the world’s biggest large-scale retailer that operates 12,000 stores in 30 countries around the world with global net sales of about €72 billion in 2021. Despite the large size and its presence all over the world, in the latest years, ALFA has achieved significant operating losses. This was mainly due to an increase in market competition due above all to the ever-increasing competitiveness of the discount stores which have conquered important market shares through a strategy based on modest product quality and low sales prices. Consumers are increasingly directing their choices based on prices rather than quality. This has penalized ALFA which, instead, adopts a strategy based on the high quality of the products offered. At this point ALFA had two choices: change its strategy also distorting its mission and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5_4

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vision or try to influence customer choices. The company has opted for the latter solution. Since 1992 ALFA has adopted its quality-oriented strategy having introduced, since that year, the “premium” brands that characterize high-quality products. This strategic approach, over the years, has become the soul of ALFA and still guides the long-term goals as well as the strategic planning of the group. Therefore, it would have been unthinkable to distort that strategic structure as it would have meant a significant rethinking of the entire core business. This meant that the only solution to regain market share was to act on customer preferences. To do this, the top management started several clients’ education activities to inform them about the importance of consuming quality and healthy food, trying to promote the food transition. In this regard the ALFA’s President and General Director publicly stated: ALFA has the goal to become the world leader in food transition by offering customers quality, reliable food at an affordable price.

About such topics, also the innovation manager and the strategic planning manager of ALFA Italia expressed their opinion during the interviews stating: [Pursuing the aforementioned strategy with the help of the blockchain] the objective is prospective . . . it is to intercept and educate the current twenty years old people. . . they are more open to this type of innovation [blockchain] and above all, they are the consumers of tomorrow . . . [therefore] it is an investment by we expect an economic return in the future.

Based on these premises, ALFA has chosen to inform the customer about the “history” of the product or to make visible all the production steps that it has undergone before arriving on the shelf. In this way, the retailer aims to give maximum transparency and product traceability, making the customer aware of the quality and origin of the product itself. To this end, the group chose to invest in blockchain technology to trace the production steps along the entire supply chain. Therefore, in the first half of 2018, ALFA installed the first blockchain in the d’Auvergne chicken supply chain in France, becoming the first company in Europe to adopt a blockchain solution for food traceability. The functionality of the blockchain is very simple: customers can access a landing page through a QR code and consult the information about the product. Blockchain technology guarantees the immutability of the recorded data and makes visible all the production steps that occurred along the supply chain. Following the positive experience in the French chicken supply chain, in which the blockchain installation led to an increase in sales, the company decided to expand its adoption also to other products and to the European markets. Because of this, the ALFA group has chosen to replicate the blockchain application on the French chicken supply chain also in Italy. Therefore, ALFA Italia inaugurated the blockchain in the Italian chicken supply chain in October 2018, at the end of a period of several months in which the Italian headquarters provided for the design and customization of the technology. In Italy, the first blockchain application, in the chicken supply chain, involved 29 farms, 2 feed mills and 1 slaughterhouse. Despite the simplicity of use of the blockchain by the customer, behind the landing page dedicated to him, there is an organic structure of data collection and storage that involves all the players in the supply chain: from the single farmer to the

4.3

The First Source of Uncertainty: The Nature of Groups

73

producer and distributor company or BETA. The number and diversity of the players to be involved makes the phenomenon more complex than it appears. This complexity is reflected in the implementation dynamics that ALFA has put in place to reach the final and successful implementation of the technology. On a theoretical level, this relates to the dynamics of creating a new network and, therefore, in the activities of enrolment of other actors (those involved in the chicken supply chain) put in place by a focal actor (or ALFA). From an accounting and managerial perspective, instead, it is necessary to specify that the blockchain responds to two particular needs. On one hand, it responds to the typical marketing need to attract customer preferences by reducing information asymmetry making it known origin, quality and production phases of the product. On the other hand, the blockchain activates a flow of information throughout the supply chain that allows the focal company (in this case ALFA) to also carry out monitoring and control activities. All this was confirmed by one of the two GAMMA blockchain experts interviewed who, about these topics, stated: In markets where large percentages of turnover derive from exports (such as the Italian wine), from a marketing point of view, it is necessary to rely on differentiation and positioning logics. In this sense, the use of the blockchain, ensuring the traceability and the origin of the product, guarantees a better product positioning especially on foreign markets [strengthening the “made in“ effect]. . . On more complex supply chains, where the marketer makes use of a series of producers, the former needs to track the activities of each supplier to control and monitor such activities and check if they are in line or not with the production contracts. . . In these cases, the blockchain also acquires operational value.

From what is reported in this background section, some key points emerge which will be explored in the next lines. The development of information flow along the entire supply chain allows a glimpse of the possible role of accounting systems which, in addition to their traditional data collection function, they can also represent assessing tools or be used for managing relations between various business entities (see, e.g. Martinez Ramos, 2004). The complexity of the supply chain, on the other hand, suggests that, during the implementation of the blockchain, particular tensions and resistance to innovation could have occurred. In this case, it is of interest to understand if the management control systems have played a role as promoters of innovation and carriers of new knowledge (see, e.g. Ditillo, 2004; Davila et al., 2009). Over the next few pages, in discussing the dynamics of creating the network that led to the spread of the blockchain, adequate space will be reserved for the analysis of the role played by accounting and management control systems.

4.3

The First Source of Uncertainty: The Nature of Groups

In ANT what is considered as an actor is also a network. For example, a single firm can be considered as an actor since it acts as one in the achievement of specific interests. That firm, anyway, is also a network since it is composed of several offices and departments in turn made up of people and physical objects. All the elements

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4 Unboxing the Network: The Empirical Case Study

that compose the firm, however, act for a shared interest, and, in this sense, they are black-boxed. Acting as one means that sub-networks (or the several offices and departments that compose the firm) disappear and the firm can act as one representing a node of a higher network (Van House, 2003). It is clear that even when black-boxed, a network can be subject to change, for example, two departments may be merged, new employees are hired or some others retire, etc. This paragraph adopts a broader perspective focusing on the formation of macro-groups that involve companies participating in the blockchain project. Although the author is aware of the changing nature of the networks, he will consider the companies involved in the formation of the groups as actors, although the actions carried out for groups formation have been carried out by specific departments, but which have acted as intermediaries accepting without questioning the directives issued by the top management. This last aspect allows considering companies black-boxed networks and, therefore, as actors. In this regard the private label director of ALFA Italia, answering the question on why they started the blockchain project, stated: We had the impulse from the French headquarter [that is the general headquarter of the group] to start the process of digitization of the supply chains by adopting the blockchain . . . we fulfilled these directives [without questioning].

As shown in the previous paragraph, the first supply chain involved in the process of digitization through the blockchain was the chicken one. Before the introduction of the blockchain, the supply chain network had a given configuration. In particular, ALFA interfaced and had business relationships only with the final producer or the BETA company. BETA has been supplying ALFA since 1988, the year in which the latter entered the Italian market (BETA Quality manager & suppliers’ controller); therefore, between the two companies, there is a relationship, which can be defined as trust that has been consolidated over time. The consolidation of this trust relationship is connected to the fact that the two companies share the same strategy and corporate vision oriented to the high quality and healthiness of the product. The commercial relationships between ALFA and BETA are based on the fact that ALFA deals with the distribution and the final sale to the customer, while BETA is responsible for the quality of the products supplied and, therefore, for the productive activities of the breeders upstream of the supply chain. In its continuous and frequent operational and commercial relationships with breeders, BETA shares and, in a certain sense, imposes its own strict quality standards that breeders must fulfil to keep working for the leader company. Breeders able to comply with these standards become part of the supply chain (and therefore of the network) of BETA through a particular contract named “Soccida”. According to this contract, BETA supplies the productive inputs (i.e. the chick and the feed), and the breeders take care only of the growth of the chicken receiving, at the end of the production process, a basic remuneration plus a production bonus calculated based on both qualitative and technical efficiency parameters. This last aspect implies that BETA has also monitoring and assessment relationships with the breeders, as well as the commercial ones. In this regard, the BETA quality manager and suppliers’ controller confirmed:

4.3

The First Source of Uncertainty: The Nature of Groups

75

Fig. 4.1 Groups formation before blockchain. Source: Own elaboration

To keep the supply chain in line with our production philosophy, we monitor our suppliers and evaluate them based on the results achieved . . . If they do not reach the required standards, they receive a recall first and then [in case of further negative performances] are expelled from the network.

The breeders, for their part, adhere to the network because both they share its production philosophy and they have an economic convenience given by the remuneration paid by BETA that is, on average, higher than that offered by the market. In the light of what just explained, before the supply chain digitizing process, there were two distinct groups. The first composed of the two big companies ALFA and BETA and the second composed of BETA and all the breeders adhering to its supply chain. It is noteworthy to note that ALFA had no contact with breeders who therefore remained outside the first network. BETA being the only one to have relations with both the breeders and ALFA represented the point of intersection between the two networks (Fig. 4.1). To be clear, the representation of the groups just described is to be understood as a “snapshot” of the situation before the blockchain implementation. This description served the author to show the initial situation from which the blockchain project started, but it is obvious that these networks have not remained unchanged over the years. During the years, the actors and the relationships between them have certainly changed. For example, new breeders have entered the supply chain, while others have left, certain contractual conditions have changed, the number of actors involved could be increased or decreased, etc. What is important to emphasize is that the groups are in continuous “making and remaking” (Latour, 2005: p. 35), and it is unthinkable that a network remains unchanged in 30 years.

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As pointed out in the background paragraph, in the first half of 2018, ALFA started the process of digitizing the supply chains through the implementation of the blockchain. In the wake of the French experience, the group’s headquarters started the digitization process also in the Italian context. ALFA Italia, therefore, starts the blockchain project in spring 2018. Blockchain technology, although easy to use, is structurally very complex. In the absence of the advanced technical skills required for the effective implementation of the blockchain, ALFA Italia starts a collaboration with a technology provider. The latter, in particular, had the role of providing technical support for the development and customization of the technology based on the specific requests and needs of ALFA Italia. Already from these earliest stages of the project, it is clear that ALFA Italia, from a theoretical point of view, plays the role of the focal actor, which is the “recruiting officer” (Latour, 2005: p. 32) which starts the creation of the network and that will have the task of identifying and aligning the actors that will be part of it. From another theoretical point of view, ALFA Italia, at this juncture, also initiates the problematization phase of Callon’s framework (1986a). The problem in question is that of influencing and reorienting the choices of consumers (towards quality rather than price) by showing them the productive activities that lie behind a product and, at the same time, giving visibility to the actors in the supply chain. The solution to this problem lies in the adoption of blockchain technology. As ALFA is the first European food company to adopt this technology, it is not difficult to imagine its position as an OPP for anyone who shared the problems described above. This finds confirmation in the words of the ALFA Supply Chain manager: ALFA has financed the blockchain playing the role of corporate social leader, that is we have accompanied the small farmers in the change, making them evolve together with us. . . There is no contractual obligation [to join the blockchain] because there is a true accompaniment from ALFA that takes responsibility, the leadership to implement this change, spreading its philosophy and its vision . . . from now on we [referring to all the actors of the new network formed by virtue of the adhesion to the blockchain project] have the same common vision.

The collaboration and the mediation between ALFA and GAMMA lead to the technical realization of blockchain technology. From here on, ALFA Italia managers needed to identify which supply chain to choose for the first implementation of the blockchain. In this regard, the private label director and the brand manager of ALFA Italia stated: We chose the chicken supply chain because there is a story to tell . . . it is a supply chain in which there were already solid relationships of trust [the reference here is to BETA and the long-standing commercial partnership with it].

Once the technical infrastructure of the blockchain was created, it was necessary to involve the various partners and actors in the supply chain. In this sense, the interessement and enrolment phases began. BETA was the first to be enrolled and with which to mediate. The latter, sharing the basic philosophy and strategy of ALFA, has easily joined the initiative. About this, the IT manager and the quality manager & suppliers’ controller of BETA stated:

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The managers of ALFA told us about this initiative, we found it interesting and we participated in it . . . The only way [to compete in the market] is to bring the customers to our side by showing them the quality of our products . . . The blockchain represents a good solution in this regard.

The predisposition of BETA meant that the phases of interessement and enrolment rapidly took place. In particular, mediation and interessement were immediately successful since BETA had long shared the philosophy and the ideas behind the project, becoming immediately enrolled in the network. Once BETA was enrolled, it was necessary to involve the numerous breeders belonging to the supply chain. In this case, the matter was not so simple. If BETA had joined the new network as already in line with ALFA’s ideas, breeders, who traditionally tend to be more conservative and less open to innovation, could have resisted and been reluctant to share information about their activities. In addition to this, ALFA had never had relations with breeders, having always interfaced with BETA. This latter, on the other hand, has stable relationships with the breeders whose performance and activities are monitored and assessed by BETA itself. BETA therefore already had a consolidated accounting system in which all the production information requested by ALFA to insert into the blockchain was already accounted for. It was “only” necessary to talk and convince breeders to join the project. By virtue of its interposed position between ALFA and the breeders, BETA acted as a mediator carrying out the phases of interessement and, therefore, of enrolment among the breeders. Here the problem of defining why BETA is considered a mediator rather than an intermediary emerges. According to the definition of Latour (2005), an intermediary is one who “transports meaning or force without transformation” (Latour, 2005: p. 39). BETA being perfectly in line with ALFA and having embraced the objectives and ideas underlying the project transferred to the breeders the meanings and the conditions of joining the network without any reinterpretation or transformation by acting as spokesperson on behalf of the focal actor ALFA. Anyway, since it does not just sit still and passively suffer the actions of others but it adds something to the translation process and the chain of interactions, BETA is to be considered as a mediator. BETA, in fact, carried out an activity of mediation and dialogue with the breeders to ensure their successful involvement into the network. In this phase of dialogue and negotiation, as well as in the last phase of the translation or the mobilization, the accounting and management control systems played a key role. All this, however, will be discussed and deepened in the following paragraphs. At the end of the phases of involvement and enrolment of the breeders, the network is definitively created. With the creation of the network and the definitive diffusion of the blockchain technology along the entire supply chain, an information flow is created that connects, for the first time, the breeders to ALFA. In particular, through the blockchain, the production information is communicated, as well as to BETA, also to ALFA, and this involves an extension of the monitoring and control activities also to the large-scale retailer. With the blockchain, therefore, ALFA comes into possession of a large amount of data that it uses on the one hand to monitor production activities and promptly intervene if some alarm or criticality emerges from the system and, on the other hand, to provide some selected

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Fig. 4.2 Group formation after blockchain. Source: own elaboration

information to the final customer to influence his purchasing choices. This dual purpose is achieved through the use of two different types of blockchains, one public and one private. These aspects, however, will be deepened in the paragraph concerning the nature of objects. In the light of what presented above, it emerges that the two pre-existing groups (or networks), in a certain sense, merge to create a single network in which all the various actors are connected (although in different ways and forms of relationship or ties) (Fig. 4.2) and act in the pursuit of a single shared interest: the one promoted by ALFA to give transparency to the production activities along the supply chain to make the final consumer understand the quality of the product offered. In this paragraph, the formation of the network was described in a macro approach, without going into the details of the actors, actions and facts that followed one another in the construction of the network itself. These aspects will be deepened starting from the next paragraph.

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The Second Source of Uncertainty: The Nature of Actions

4.4

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The Second Source of Uncertainty: The Nature of Actions

The action is unpredictable. This concept underlies the second source of uncertainty. Since the action involves numerous elements and each actor, being also a network, makes use of other objects or actors each of which has its own agency, it is not possible to determine the result of an action a priori. If this is true, then the problem emerges of how a focal actor can ensure that the other actors in the network act in the interests of the network itself and not based on its own interests or agencies. In the previous paragraph, it has been underlined that, in the case study under analysis, two main networks existed before the blockchain implementation. In the first one, ALFA and BETA, by virtue of their long-time commercial relationships, shared the same philosophy and interests. This aspect was fundamental during the interessement and enrolment phases of the breeders. In a sense, that first network was blackboxed, and BETA was legitimated to speak on behalf of ALFA playing the role of mediator and spokesperson. This premise was necessary and introduces the actions that have been undertaken in the dissemination of blockchain technology and, therefore, in the construction of the network (Fig. 4.2). In this paragraph, the actions performed by the several actors involved or to be involved in the network will be highlighted. In this regard, it will be also explained how the focal actor ALFA dealt with the uncertainty linked to the action of the other actors and how it ensured that, despite their agencies, those actors have acted in pursuit of the common interests of the network. In the first phase of the implementation project, ALFA Italia managers had to deal with the problem of creating the technological infrastructure. In the absence of the necessary know-how, it was necessary to rely on a third company that had the right skills. In this regard the private label director stated: The blockchain requires advanced computer skills that were not available in ALFA Italia . . . Speaking with some acquaintances, working in our same field, I became aware of GAMMA and their experience about blockchain applications.

EY had already had experiences with blockchain applications in the wine supply chains and, therefore, had the skills suitable for the development of technology. Despite this, before the collaboration between the two companies took place, there was uncertainty about how the interaction between them could take place. It could be that ALFA’s requests were not applicable, or the different characteristics of the ALFA supply chains could have required other types of skills. In that case, there was nothing left but to start the collaboration, mediate and find out which activities the two companies would have put in place. The collaboration (and the mediation) involved the marketing department and the private label director, on the side of ALFA, while two blockchain experts (both interviewed for the present research) intervened on the GAMMA side. About the actions carried out during the collaboration, the private label director of ALFA has

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released the following statements (later confirmed also by the two GAMMA blockchain experts): The collaboration with GAMMA has led to the implementation of 4 fundamental activities: the definition of a timetable [that is, a work planning with objectives to be achieved and relative timing]; the choice of information to be requested from suppliers and to be included in the blockchain [in this case the reference is to the private blockchain or the technological infrastructure mainly intended to extend and strengthen the monitoring of suppliers carried out by ALFA]; of the information to be allocated to the customer [in this regard, in another interview, the Supply Chain manager stated: “the final consumer is not interested in certain detailed information relating to production and would not even have time to consult them . . . therefore it is necessary to do a skimming by showing him only the summary information that is of interest to him such as the origin of the product, the main treatments and the supply chain passages”]; and finally the creation of the landing page [or the screen that appears to the customer and in which the information intended for him is displayed].

From ALFA manager’s words, some important considerations emerge. One of the main barriers related to the implementation of the blockchain concerns the technical aspect related to know-how availability. In this case, ALFA chose to rely on a third-party company rather than develop the necessary skills in-door. This was due to reasons of timing and management costs. This choice triggered the mediation between the two companies and the first step in the creation of the network. ALFA and GAMMA represented (in chronological order) the first two nodes of the network, developing a tie primarily based on a consulting relationship. Their relationship did not end with the creation of the technical infrastructure as GAMMA provides continuous technical assistance to ALFA regarding blockchain issues. The actions carried out during the construction of the blockchain and those of continuous technical assistance ensure the correct functioning of the technology. In this case, it is impossible to predict what actions will be necessary and how they will be carried out as the issues that could emerge are many and different. What is certain is that the two companies will act in pursuit of the same goal or the correct functioning of the blockchain, given that both have the obvious interest that this happens. Therefore, in this first step, the uncertainty linked to the action is high given the peculiarities of the context but, at the same time, it is mitigated by the communion of interests that these two first companies involved in the network share. Once the technological infrastructure had been created, it had to be applied and disseminated within the supply chains. As explained in the previous paragraphs, ALFA Italia chose to begin the process of digitizing supply chains in the chicken sector where there were already trust relationships, especially with the BETA company. By virtue of these ties, the ALFA Italia supply chain managers started a dialogue (or a mediation) with BETA managers to present the blockchain project and involve BETA in the network. This is for a dual purpose. BETA can be considered the focal actor of the second network (Fig. 4.1) or the leader of the chicken supply chain. By virtue of this role, BETA has stable and continuous relations with farmers, and this means that it would have represented an excellent mediator in the process of technology diffusion, being able to interact directly with the breeders. In a sense, BETA represented a sort of second “recruiting officer” which could have easily mediated with breeders on behalf of ALFA. Secondly, BETA has an advanced and

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consolidated accounting system that contains all the information that ALFA Italia would have included in the blockchain and which regards the productive activities conducted by the breeders based on the production disciplinaries. Regarding the interaction between ALFA Italia and BETA, the brand manager of ALFA and the quality manager and suppliers’ controller of BETA declared: All producers have a specification that has been written with the leader [or BETA]. . . the data we request from suppliers is based on that specification [and included in BETA management system]. . . the blockchain database communicates with the BETA management system . . . . (ALFA Brand manager) The managers of ALFA came to our office to talk to us and to explain the project. . . we joined immediately because we share the same ideas [referring to the strategy based on product quality and the importance of traceability to make the production process visible to the final consumer and influence his purchasing choices]. . . It was relatively easy to join the project as all the information requested was already contained in our management system. . . . (BETA Quality manager & suppliers’ controller)

In this phase of the project, the actions undertaken by ALFA Italia can be included in the interessement and enrolment phases of the sociology of translation. This step was characterized by the mediation, the involvement and the participation of BETA in the blockchain project and therefore in the new network. However, in these interessement and enrolment activities, the uncertainty related to the actions was not lacking. BETA, due to its position in the supply chain, could have acted in a way that was different from what ALFA had hoped. BETA could have requested changes to the project or started a negotiation phase to pursue its goals. However, BETA has fully and rapidly joined the project. This is because his interests and strategies already coincided with those of ALFA. Once again, the action is unpredictable and depends on the agencies and the interests of the actors, but the uncertainty linked to the action is partially reduced when there is a sharing of interests between the focal actor and actors to be involved. A priori, it was and it is impossible to predict how BETA would have behaved or how it behaves, but it is reasonable to expect that any action it adopts will be aimed at pursuing the interests of the network as they coincide with its own. Until now, the issue of uncertainty of action between actors presenting an a priori sharing of interests or fiduciary relationships has been addressed. But what happens when the actors to involve do not fully embrace the network’s interests and may have additional agencies and interests to those of the network itself? This eventuality can undermine the composition of the network, but how may a focal actor or a spokesperson behave in such a case? In the following lines, the issue of the uncertainty of action in these contexts or the interaction between BETA and the breeders will be addressed. The breeders, being small companies, do not always have strategies and interests that coincide with those of BETA and ALFA, just as they are not always open to change and innovation. In these cases, it arises the problem of how to involve them in the network, how to keep them inside it and how to prevent them from acting in a way that differs from what is desired by the focal actor. On closer inspection, the concepts described above fall within the definition of management control system.

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Unboxing the Network: The Empirical Case Study

The Role of Management Control Activities in Network Creation

As explained in the first chapter, the management control system is understood in this research work as the organic set of different tools, practices, roles and procedures (both formal and informal) used in the company to ensure that the behaviour and actions of business actors are consistent with the organization’s objectives and strategies (Malmi & Brown, 2008; Merchant & Riccaboni, 2001; Sandelin, 2008). According to Merchant and Van der stede (2007), management control is divided into four different types of control (not necessarily applicable simultaneously): results control, action control, personnel control and cultural control. These different forms of control can play a decisive role in aligning the behaviour of the actors to the interests of the network and in spreading values and knowledge among the supply chain (Ditillo, 2012). Therefore, in the next lines, we will see how the different types of control have intervened in the different phases of involvement of the breeders in the network, demonstrating the crucial role that the control activities have in the construction of the network itself. “Involving breeders in the blockchain project was not an easy task. . .” (BETA Quality manager & suppliers’ controller). The breeders operate in a very competitive context in which the goal is to survive achieving a higher profit (even if slightly) compared to other competitors. For this reason, breeders do not have as a priority innovation or traceability of processes but rather to reduce costs to earn more than competitors. This can thus lead breeders to be less inclined to collaborative logics and to be poorly open to innovation such as the blockchain which presupposes data sharing. In this regard, the quality manager and suppliers’ controller of BETA and the supply chain manager of ALFA confirmed: Breeders are generally small entrepreneurs accustomed to a very strong competitive environment by virtue of which they are reluctant to share their production data. . . we must make them understand that, instead, it is important to collaborate and give visibility to production practices. . . it takes time and a continuous field training activity. (BETA Quality manager & suppliers’ controller) We are talking about many small suppliers. . . there is a work of training to explain to suppliers what blockchain is. . . there must be a support for suppliers as it is difficult for them to go from a very competitive perspective to a cooperation perspective. (ALFA supply chain manager)

In the phases of approaching and involving breeders in the network (i.e. the phases of interessement and enrolment), ALFA and BETA face a dual challenge: on the one hand to convince farmers to adopt a cooperative logic by sharing their data with ALFA as well as making them visible (at least some of them) to the final consumer and, on the other hand, transfer to breeders the technical knowledge necessary to allow them to successfully interact with the new information technologies. In particular, it was necessary to explain the aims of the project, the interests and objectives that were intended to be achieved with it and the technical

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characteristics related to the blockchain. In this context, the typology of personnel control comes into play. According to Merchant and Van der stede (2007: p. 83, 84), personnel control is aimed at making company players understand what the company expects from them, motivating and providing them with the right skills through appropriate training activities. In this regard, ALFA and BETA organized several meetings and training activities to be able to motivate farmers to join the blockchain project on the one hand and, on the other, provide them with the appropriate technical skills. The transfer of this type of skills, in particular, can be more difficult through formalized contents, making it necessary for the organization of face-to-face meetings where various perceptions and uses of this knowledge can be properly explained (Ditillo, 2012). In this sense, personnel control, in the form of training activities, represents one of the best solutions for technical knowledge transfer (Ditillo, 2012). Training and motivation activities, conducted by ALFA and BETA, gave rise to the interest and subsequent enrolment of the entire supply chain. From now on, the goal is to keep breeders in line with the interests of the network, avoiding possible behavioural distortions. Despite the diffusion of the values and logic of the network, as previously stated, breeders have other priorities that could more easily lead them to deviate from the interests of the network. We are therefore in the presence of the mobilization phase of the sociology of translation in which the objective is to ensure that the actors act in line with what is established by the focal actor and are not persuaded to join other networks or compromise the stability of the one in which they are involved. Also in this case, management control, by virtue of its basic purpose and characteristics, plays an essential role. Unlike the phases of interessement and enrolment in which the objective was to transfer knowledge and management philosophies, in the mobilization phase, the need for the focal actor is that the actors of the network act according to what it has established. In this regard, a twofold source of uncertainty emerges linked to the actions of the farmers. First of all, it is necessary to make sure that the breeders respect the quality standards set by ALFA and BETA following the provisions of the specifications. Secondly, if on the one hand the blockchain has the advantage of guaranteeing the traceability of the processes ensuring the immutability of the data, on the other hand, it has the defect that it is not possible to ascertain the truthfulness of the data entered. To mitigate these two sources of uncertainty, BETA, as spokesperson and supply chain leader, implements two particular forms of control, namely, action control and results control. Specifically, each breeder, through the use of an IT accounting system, gives a daily account of the activities he carries out and the actions he has put in place at each stage of the production cycle. This information is made immediately visible by the system to BETA managers who, by examining such information, have a complete overview of the activities of the entire supply chain carrying out continuous monitoring of suppliers. It is, therefore, a method of “action accountability” (Merchant & Van Der Stede, 2007: p. 78) through which every single activity of the breeders is inscribed in the system allowing BETA to know in real time what happens and to ascertain promptly about deviations from what expected. With the implementation of the blockchain, these accounting and monitoring practices are also extended to ALFA [thus achieving the union of the two

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initial networks and the effective creation of the new network (Figs. 4.1 and 4.2)]. BETA managers are required to transfer the information contained in the accounting system to the blockchain database, connecting the two IT tools. This, in turn, has led to an extension of the monitoring activities by virtue of which also ALFA has an immediate and general overview of what happens in the supply chain being able to intervene promptly in case of need. About this the breeder, the BETA quality manager and suppliers’ controller and the ALFA private label director stated: Daily, I enter the data relating to the activities carried out. . . if something goes wrong, I immediately receive a call from the BETA managers asking for explanations. . . the system keeps track of every activity carried out in each phase of the production process. (Breeder) Our breeders enter the data daily so that we can immediately become aware of any problems and have our technicians intervene, located throughout the Italian territory, directly at the breeder’s farm. . . Now, with the blockchain, we transfer the data contained in our accounting system into the blockchain database so that also ALFA can have real-time monitoring of breeders and perform on-field checks when deemed appropriate. (BETA quality manager and suppliers’ controller) With the information contained in the blockchain we have increased the timeliness of intervention, in case of problems, by 70% . . . Furthermore, we can work with precision or if before, due to a problem or product defect, it was necessary to interrupt the entire activity of a supplier, we can now intercept directly the defective lot avoiding damaging the supplier beyond all measure. (ALFA private label director)

Through this type of control (or action accountability), BETA (and thus ALFA) ensures that breeders act following the provisions of the specifications. All this, however, still leaves the problem of verifying the truthfulness of the data entered by the suppliers partially unsolved. No one can guarantee that the data entered by the breeders are true. Breeders, to continue to be part of the supply chain, could lie about the activities carried out by entering distorted information. Again, the action control comes into play, but this time not in the form of “action accountability” but in the form of “action scrutiny”. In particular, the action scrutiny is carried out by weekly visits of the BETA technicians to the farms of the breeders. During these visits, the technicians, in addition to giving operational support to the breeders, physically and personally monitor the activities that are carried out, the quantities of productive inputs used and the progress of the production process. In this way, it becomes impossible (or at least very difficult) for breeders to enter distorted data. A possible behavioural distortion would be immediately discovered following the field checks carried out by the BETA technicians located throughout the Italian territory. A similar distortion, moreover, would entail a deterioration of relations with the supply chain leader with consequent expulsion from the network. In this regard, the breeder and the BETA quality manager and suppliers’ controller stated: It is not possible to enter untruthful data either because the accounting system records everything and any anomalies, sooner or later, they would emerge and also because we receive weekly visits by BETA technicians who see with their own eyes what is happening on the farm. (Breeder)

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Our technicians go weekly on the various farms to support the activities of the breeders. . . This allows them to personally follow the production activities and ascertain the state of the art of the production process. (BETA quality manager and suppliers’ controller)

From what is reported in the last lines, an extremely important concept emerges. As IT may be new, innovative and technologically advanced, they cannot prescind from human and managerial activities. They remain objects that need human action to function. This means that, in line with Quattrone’s (2016) recommendations, accounting systems and management control activities play a fundamental role in business management which IT, alone, cannot perform. This is true also for blockchain that, although it ensures an effective monitoring activity, it needs an existent and consolidated accounting system from which it takes the data and of the performing of action controls to guarantee the truthfulness of the data. Continuing with the analysis of the actions carried out during the creation of the network, we arrive at a final step within the mobilization phase of the sociology of translation. As mentioned earlier, in the mobilization phase, the objective is to ensure that the actors act in the interests of the network. This does not only mean avoiding distortive behaviours but also means ensuring that the actors respect the conditions necessary for their permanence in the network. In the case study analysed, this means assessing the performance of the farmers ensuring that they comply with the quality standards and production requirements set by the focal actor (ALFA) and the spokesperson and supply chain leader (BETA). In this case, therefore, we are in the presence of a form of “results control”. The control of the results achieved by the breeders has a dual purpose: on the one hand, calculating the production premium based on an efficiency indicator given by the ratio between the amount of input consumed and the quantity of output produced and, on the other hand, BETA can ascertain any failure to achieve pre-established results in terms of quality or production requirements and, in this case, proceed with a formal warning and, in case of perseverance, with expulsion from the supply chain. About this, the BETA quality manager and suppliers’ controller confirmed: Every year each farmer is evaluated based on the results he has achieved and, if these are lacking, he is first warned and then, if he perseveres, he can also be eliminated. [from the supply chain and, thus, from the network]

This activity of results assessment is essential to ensure that they are part of the network the actors who are really able to satisfy the interests of the focal actor and, therefore, of the network itself. In the light of what has been explained in this subparagraph, it emerges that the different control activities have had a specific role in the different phases of network creation and, at the same time, produced different effects in the management of the supply chain within the blockchain project. Table 4.1 summarizes the roles covered and the effects produced by each form of control, in line with the classification proposed by Merchant and Van der Stede (2007). In conclusion, this paragraph highlighted the actions and the activities carried out during the network creation. Despite the undoubted uncertainties that lie behind an action, management control activities could play a crucial role in mitigating such

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Table 4.1 The role of the different types of control in the network creation

Type of control Personnel

Translation phase in which the control was involved Interessement and enrolment

Action

Mobilization

Results

Mobilization

Activities characterizing control Training activities carried out through face-to-face meetings

Reporting of activities on the accounting system and blockchain and on field activities control Assessment of suppliers’ performance based on the contents of the accounting system

Effects produced by control activities Transfer of knowledge and network’s values and strengthening of breeders’ motivation Continuous monitoring of activities and guarantee of the truthfulness of the data entered in the blockchain Verification of the persistence of the requisites required for breeders for their stay in the supply chain and therefore in the network

Source: Own elaboration

uncertainties supporting the network creation in several phases and different ways. As represented in Table 4.1, the different forms of control intervened in different phases of the sociology of translation not only supporting the acceptance of the project by the breeders and their consequent involvement in the network (interessement and enrolment) but also remedying the defects inherent in blockchain technology and ensuring the stability of the network in the face of uncertainties (mobilization).

4.5

The Third Source of Uncertainty: The Nature of Objects

According to the ANT, objects are (non-human) actors. Obviously, they are not able to execute an action independently, but they always need a human action that gives impulse to their operation. Despite this, objects have their own agency or, based on their specific characteristics, can influence human action (Latour, 2005: p. 72). In a process of network creation, there are countless objects involved and employed: computers, software, paper, telephones, and anything else you can imagine using in a workplace. Such abundance makes it impossible (for reasons of both length and clarity of exposition of the work) to provide a detailed description of each object involved in the network creation process. Therefore, in this paragraph, the main objects that have played a significant role in the implementation of the blockchain project acting as a black-boxed network (and thus as an actor) will be discussed. In this regard, it will be highlighted their main characteristics and the ways of interacting with human actors. In particular, in this paragraph, the role played by

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objects in the different phases of sociology of translation will be analysed, focusing on their agencies and the way in which they have influenced human actions.

4.5.1

The Accounting Objects

Since one of the research questions that characterize the present work is to investigate the role of accounting and control systems in the diffusion of technology, the first objects to be analysed are those related to accounting. In particular, two main accounting “objects” intervened during the network creation process. The first is represented by the investment budget that ALFA set up in the initial phases of the project, while the second is the BETA accounting system used for the recording of production data and the performance of breeders. In the selection phase of the supply chains (and therefore of the actors) to be involved in the blockchain project, the ALFA managers had to plan the implementation costs of the blockchain. Depending on the actors involved and the length of the supply chain, the costs associated with the blockchain can vary especially those related to data management and cleaning. Therefore, in the first phase of actors selection (i.e. problematization), the investment budget represented an accounting “object” that directed the managers’ planning activities towards the definition of the project costs based on the supply chains to be involved. In this regard, the private label director of ALFA stated: The blockchain project provide for costs of management and data cleaning which, although they may vary from one supply chain to another, are around 50 thousand euros. . . it is clear that for a project of this economic range you have to budget for the operation. . . we have therefore drawn up appropriate investment budgets with which we have defined the costs related to the diffusion of the technology along the supply chain. [referring to the chicken one]

In this situation, the budget instrument had a more functional role than anything else. It represented the tool through which costs and activities related to the blockchain project were planned, having a key role in the early stages of network creation. In this case, more than a stand-alone actor, the budget was one of the actors that are part of the wider and black-boxed network ALFA as it is a tool of common use and, therefore, consolidated in company managerial practices. A different discourse is to be reserved to the accounting system used by BETA for the monitoring and evaluation of breeders. This system, which has been computerized since 2005, represents a unique accounting model since it is customized to BETA’s specific needs and the characteristics of the supply chain. It is, therefore, not a common tool like the budget, but a unique system exclusively used by BETA. Specifically, BETA uses a peculiar ERP system, based on ACG software and IBM system, which provides for the integration of the company database ensuring greater ease and speed in data management. Among the various areas affected by this technology is the production and, thus, the supply chain management ones. In this context, the system predisposes a real computerized accounting system that is shared by BETA and its breeders. This accounting model includes a double interface, one

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for BETA and the other for breeders. The interface for the breeders shows all the inputs and raw materials used, dividing them by production lines, also showing realtime management costs. In addition, the system allows the calculation of the so-called transformation index or an efficiency ratio given by the division between the quantity of productive inputs used and the quantity of output produced on the basis of which the production premiums are calculated. In this regard the interviewed breeder stated: Here [showing and indicating the PC on which the accounting system was run] there are all the pieces of information relating to my activities . . . feed, chickens, costs, there is everything . . . Moreover, when BETA sends me some inputs, such as feeds, they upload such information on the system and it becomes immediately available on my pc. Vice-versa, when I upload something, the information is immediately available on BETA managers’ pc. . . Such a system is extremely useful in the phases of programming activities. . . BETA then, in addition to programming, also carries out control activities. . . This system also allows me to know in real-time not only the management costs but also to know my personal transformation index. [and therefore the production premium that will eventually reach]

Some interesting information emerges from the words of the interviewed breeder. First of all, the double function of programming and control carried out by the accounting system. This, in a sense, is part of the typical features of any accounting system. What is really innovative is the joint compilation, by BETA and the breeders, of accounting models. In other words, this system allows a continuous exchange, and therefore a constant dialogue, between the breeders and the supply chain leader. The accounting system, therefore, represents a communication tool that creates a tie between BETA and the breeders. This tie consists in the exchange of useful information both to the breeders that can always have an overview of their activities and to BETA that through the information entered in the system can monitor in real time the performance and behaviour of the breeders. Furthermore, this tie gives meaning to the commercial relations between BETA and the breeders since the former, based on the performance data (or accounting inscriptions) contained in the accounting system, defines the rewards (or penalties) of the latter. In this sense, following Busco and Quattrone’s (2015) insights, the accounting system materializes a visual space for calculative practices (Revellino & Mouritsen, 2015) in which BETA and the breeders activate dialogue and mediation by supporting the mobilization and the balance of the network. The amount of data contained in this accounting system then represented the information base on which the blockchain was built. Unlike the budget instrument which was discussed above and which played a more functional role in the project, the BETA accounting system, instead, made the difference during the actions representing a crucial node for the success of the project and the consequent creation of the network. About this the BETA quality manager and suppliers’ controller stated: In other supply chains, the project failed because there was no database like ours on which the blockchain could be based. . . It was enough for us to insert the information we already had [since registered in the accounting system] on the new blockchain database and, therefore, the implementation of this new technology has not required so much effort, at least in this area. [alluding to the difficulties that they encountered in the training activities of the breeders]

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The Third Source of Uncertainty: The Nature of Objects

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Fig. 4.3 The network including companies and objects. Source: Own elaboration

To summarizing, BETA accounting system represented a non-human actor which played two fundamental roles. The first was to materialize the visual space in which BETA and its breeders gave meaning to their commercial relations through a two-way communication process based on the exchange of information flows concerning production activities. The latter are then functional to the programming and control activities (both of BETA and the breeders) as well as to those of performance evaluation of the farmers by BETA. The second role played by the accounting actor was to direct and support the synthesis and data collection activities of the human actors, necessary for the construction of the blockchain. Given its characteristics (and its agency) the accounting system has allowed and greatly facilitated the collection of data to be included in the blockchain and to be allocated to ALFA and the final consumer. Ultimately the accounting system is to be considered as a node of the network that connects breeders, BETA, blockchain and ALFA (Fig. 4.3) as well as a non-human actor which, with its own agency, allows and facilitates the passage of information flows between the various actors of the network (Fig. 4.3).

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Unboxing the Network: The Empirical Case Study

The Blockchain Objects

Blockchain is a technology that, by definition, involves different actors or peers. The actors are required to share, on a shared platform, a series of data that, once inserted into the system, are no longer modifiable and pass from one block to another. Based on these premises, the technology involves the action of data input by human actors and the use of objects such as software, PCs, databases, etc. As already mentioned at the beginning of this paragraph, for reasons of length exposition, it is impossible to describe every single object belonging to the blockchain. These objects constitute elements of the broader blockchain technology which, in a sense, we can consider as a black-boxed network structurally composed of the non-human actors mentioned above. Technically speaking, the blockchain is based on the distributed ledger technology (DLP) which represents an IT solution thanks to which all information on the traceability and composition of the products can be archived and shared along a chain of actors. Coming to the empirical case, the blockchain solutions adopted by ALFA are two. The first is the public blockchain that is based on an open-source platform that makes the information inserted visible to those interested. This type of blockchain is used for mainly marketing purposes since its functionality is to give consumers access to information about the origin and production phases of the product. The second type of blockchain instead is that of a private type which is based on a platform whose access must be authorized by the focal actor. This second type of blockchain means that all the breeders of the network are involved, but they cannot see the information entered by the competitors. In other words, this is a peculiar type of blockchain in which information converges from decentralized actors to ALFA which is the only one (besides BETA for the reasons widely presented in the previous pages) to be able to view all the information entered by all the breeders of the supply chain. Specifically, as previously written, breeders, using a PC and specific software, upload the information relating to their activities on the BETA accounting system from which, subsequently, the BETA managers transfer such information on the ALFA blockchain. The two systems, therefore, interact with each other, and about this the BETA IT manager and the GAMMA blockchain experts confirmed: Our accounting system is based on ERP solutions, specifically on an ACG software and IBM system, and it communicates with the blockchain database. (BETA IT manager) The blockchain has a data gathering that can be integrated with any IT such as ERP systems. (GAMMA blockchain expert)

Once the data are uploaded, ALFA can have a broad overview of the activities carried out along the supply chain, thus being able to carry out its monitoring and control activities. ALFA, therefore, is the final recipient of the information flows channelled by the blockchain and because of this, it is enabled to perform physical checks on product batches if irregularities emerge from the system. In this regard the

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BETA Quality manager & suppliers’ controller and the ALFA Private label director stated: From today onwards [referring to the entry into service of the blockchain], ALFA can also carry out field checks and verify production activities in real-time. (BETA quality manager & suppliers’ controller) With the blockchain, we have real-time access to information relating to all the breeders and, in the event of problems, we can intervene with 70% more timeliness. . . We also act with greater precision. . . We know in real-time and precisely which lot presents defects and we can directly intervene on it with positive effects also on the breeder. In the past, in case of discrepancy, we had to block the entire activity of the breeder and this entailed not negligible costs for him. . . now instead we act directly on the defective lot avoiding hindering beyond all measure the breeder’s activities. (ALFA private label director)

To summarize, the blockchain starting from the accounting base of BETA extends the information flows, coming from the suppliers, from BETA to ALFA. It represents a “superstructure” of the accounting system that extends the visual space that initially involved breeders and BETA. Accordingly, the blockchain enables ALFA’s monitoring activities on the suppliers, also through the immutability of data. To this end, the blockchain puts order in the network by guaranteeing the managers of the leading company greater surveillance and control of their suppliers over time and space. Indeed, the lack of interaction between who produces, who collects and who processes the data can negatively influence the decision-making process leading to spurious correlations (Janssen et al., 2017). Furthermore, the multidimensionality that characterizes the actors of a network leads to different interpretations of the data (e.g. Callon, 1986; Emsley, 2008; Latour, 2005). The absence of a direct connection between actors can cause the data to be altered or take on other meanings in the various communication steps. Guaranteeing the immutability of the data, the blockchain makes evident all the steps of the accounting data by putting order in the dynamics of calculation, monitoring and controlling the whole supply chain activities. In light of what has been written so far, it emerges that the blockchain represented a node of the network which, by channelling and redirecting information flows, creates a tie between ALFA and the breeders, which was previously absent. It expands the visual space for calculative practices that initially involved only BETA and the breeders. The blockchain is the end product of the network creation process. Therefore, it intervenes in the last phase of the sociology of translation, or mobilization, allowing ALFA (focal actor) to monitor and control that the actors act according to the network interests. From this derives also the more functionalist vision of the instrument that did not intervene in the phases of network creation (being rather its final product) and that was developed precisely to carry out the specific functions of traceability and monitoring. Figure 4.3 gives a complete picture of the final network. Concluding this paragraph, the empirical evidence highlighted so far show how the objects constitute non-human actors who can play an active and crucial role in the construction of the network by activating and/or reinforcing the ties between

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actors. In this sense we have seen that the accounting system materialized a visual space for calculations and mediation (Busco & Quattrone, 2015; Revellino & Mouritsen, 2015), while the blockchain represented the “superstructure” of the accounting system extending that visual space and putting order in the network. From the case study experience, it emerges that it is possible to empirically confirm the theoretical assumptions proposed by Latour (2005), which is that an object has its own agency but it always needs human interaction to act. Moreover, objects can be considered actors of the network only when they make some difference in the action. The two key objects involved in the network did not have the sole functional role, but, by activating new links between the actors (blockchain) and conveying the information flows that allowed the development of the new technology and therefore of the network (accounting system), they represented key actors actively involved in the various phases of network construction as well as of the sociology of translation.

4.6

The Fourth Source of Uncertainty: Matter of Facts Vs. Matter of Concerns

Things could be different or at least they could fail. (Latour, 2005: p. 89)

This phrase of Latour contains the meaning of the fourth source of uncertainty. Things do not always go as hoped. What worries people or what they hope for could occur, not occur at all or occur differently from what expected. In other words, a concern can remain so or become a fact. In the process of creating a network, some numerous concerns and facts alternate over time and deserve to be analysed. In the case study analysed, several concerns have characterized the network creation process and that have affected the different actors involved. As already mentioned in the opening bars of this chapter, ALFA Italia had the impulse to adopt the blockchain from the French headquarters. So, the first fundamental concern was to create the blockchain from a purely technological point of view. This concern paved the way for different scenarios. ALFA managers had to choose between developing the technology in-door or relying on a third expert company. In the first case, however, the risk of not being able to develop the necessary skills and, consequently, seeing the project fail was greater. Furthermore, the project required limited development times which were not compatible with those that would have been necessary to acquire adequate internal skills. For these reasons, the ALFA managers opted to rely on a third company expert in blockchain technology (i.e. GAMMA). In this regard, the ALFA private label director stated: The blockchain requires advanced computer skills that were not available in ALFA Italia. . . GAMMA had the know-how necessary for the development of the project . . . It already had the technical part of the blockchain and so we started a collaboration with them which led to the co-planning of the features and contents that would then distinguish our blockchain.

The concern to create the blockchain becomes a fact due to the collaboration (and the mediation) between ALFA and GAMMA. The different design activities

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(presented in Sect. 4.3) led to the creation of the technical infrastructure of the blockchain and its customization based on the specific needs of ALFA. Once the infrastructure was created, however, it was necessary to use it and have it applied in the supply chains. In other words, it was necessary to start the process of digitization of the supply chains. The initial idea was to involve different supply chains, choosing, in particular, those whose products had a story to tell. Now the concern was to spread the technology in the supply chains. The problem here is that each supply chain is different from the other and has specific characteristics not only productive but also organizational. The supply chains can be more or less complex depending on the number of actors involved and the commercial relationships that exist within them. This complexity affects both the mediation process and the ability to track the activities carried out in the various production phases, making the blockchain more or less difficult to apply. Regarding these aspects, the strategic planning manager and the brand manager of ALFA stated: We tried to install the blockchain in some supply chains such as the sea bream or clams, however, it was impossible to identify all the actors, especially those upstream, and track their activities due to the complexity of the supply chain. (ALFA strategic planning manager) The blockchain is applicable in chains that are not too long and complex and in which there are already solid relationships with those who work there. . . when complexity increases it becomes difficult not only to track down the various actors but also to involve them in the project. (ALFA brand manager)

In this case, therefore, the concern to spread the blockchain among several supply chains has only partially turned into fact. In some of the sectors in which ALFA Italia initially intended to apply the blockchain, the project failed due to the complexity of the supply chains. The concern has become a fact in the case of the chicken supply chain. In this case, there were the necessary conditions for the success of the project, that is, the involvement of a relatively limited number of actors and the presence of solid commercial relationships (especially between ALFA and BETA). Concerning the path of sociology of translation, the two concerns presented above fall into the phase of problematization. These two concerns deal with the definition of ALFA as an OPP (starting the blockchain project with the material construction of the technology) as well as with its activity of selecting the actors to be involved in the network. The successful application of the blockchain in the chicken supply chain, however, was not immediate but required challenging training activities for the involvement of the breeders. From here derives another concern that interests both ALFA and BETA and that consists in involving and convincing the actors to adopt the blockchain thus joining the network. Because of the bargaining power that BETA has with breeders, it had the possibility of convincing them, more or less immediately, by asserting its position as a supply chain leader. However, the work of involvement took time. It was not an immediate activity, but it required repeated meetings with the breeders both to support them in overcoming their own resistance to innovation and to instruct them in the use of technology. About this the BETA quality manager and suppliers’ controller stated:

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It takes time [referring to farmers’ involvement activities]. . . We need to make them [the breeders] understand the importance of sharing data. . . it wasn’t easy. . . Many of them belong to the older generation, extremely competitive and jealous of their data and their production information . . . It is not easy to interface with them. . . The young breeders can be more inclined to innovation and easier to involve but there are many breeders with whom you have to work a lot [at a mental level] to train and involve them.

In the context of the interessement and enrolment phases, therefore, the concern to involve breeders has finally turned into fact since the network has taken shape (as also seen in the previous paragraphs). However, this process of involvement was not immediate, as the relations of power between BETA and the breeders could lead to believe, but it required considerable time and efforts for that initial concern to be transformed into fact. This confirms that concerns so that they can turn into facts may require ways and times that may differ from those expected. The latest concern that characterizes the new network has to do with the stabilization of the network itself and the keeping of the actors within it. In other words, this concern affects the mobilization phase, and, in particular, it regards the permanence of breeders in the supply chain. As already highlighted several times, the permanence of the breeders in the network is subject to the essential condition that they respect the quality standards imposed by ALFA and BETA. This is a source of double concern. The first is that of the breeders of being able to meet the essential requirements to continue in being part of the supply chain; the second is that of BETA to ensure that the breeders achieve the desired results. As already explained in previous paragraphs, once the network has formed, the actors must act in the interest of the network itself and of its focal actor. In the case study examined, one of the fundamental interests underlying the entire network is the achievement of highquality standards. This aspect is a source of concern for the breeders since their possible exclusion from the network would lead them to the loss of a considerable source of income. To reach the required quality levels, making the concern become fact, the breeders adapt their breeding procedures in line with the BETA provisions and, in doing so, make use of the constant support of expert technicians sent weekly by the supply chain leader. In this regard the breeder interviewed stated: With BETA I have changed my mentality and my way of producing. . . now I have to operate in a totally different way than in the past and I have to respect strict quality standards, following BETA’s specification, so that I can continue to work for them [and therefore remain in the network]. . . BETA managers constantly monitor us to evaluate our activities and give us physical support by bringing expert technicians to our farms to support us in our work.

Breeders, therefore, have a road to follow that has been traced by BETA who also supports them physically in following it. In this way, it is ensured that the concern to respect the network requirements is respected exactly in the ways and times expected, avoiding, or at least mitigating, the risk of losing actors from the network. Therefore, if breeders have a concern to comply with BETA’s directives, the latter has the concern to make sure that the farmers act in the desired ways. To this end, the leading company in the supply chain carries out continuous field monitoring and periodically evaluates the results achieved by the breeders through its accounting

4.7

The Fifth Source of Uncertainty: The Nature of the Study Itself

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system. The management control activities (presented in Table 3.3), therefore, come back into vogue in supporting BETA to ensure that the concern of keeping the actors within the network becomes fact and, consequently, represent fundamental activities in the performance of the mobilization phase. In this regard the BETA quality manager and suppliers’ controller stated: Our technicians go weekly on the various farms to support the activities of the breeders. . . This allows them to personally follow the production activities and ascertain the state of the art of the production process. . . Every year each farmer is evaluated based on the results he has achieved and, if these are lacking, he is first warned and then, if he perseveres, he can also be eliminated [from the supply chain and, thus, from the network].

Concluding this paragraph, the uncertainty about how a concern becomes fact is a crucial aspect in the path of network creation. In line with Latour (2005), the case has shown that there are different ways for a concern to become fact, and, sometimes, it can also happen that a concern remains a concern without becoming fact. However, management control activities can reduce uncertainties about how and when a concern becomes fact. Where the management control activities took place, the concern became fact much closer to what was expected. When, on the other hand, no type of control activity has taken place the concerns or have not really become facts or have become so in ways and times different from those expected. From this, it follows that within the fourth source of uncertainty, the management control systems have played a decisive role in reducing uncertainty about the way through which concerns have become facts.

4.7

The Fifth Source of Uncertainty: The Nature of the Study Itself

In outlining the network, great emphasis was placed on tracing the trial of associations between the actors, also treating the latter as active elements in the network creation process. The narration was carried out passing through the different phases of the network creation, and, in each of them, it was highlighted the role of the actors (both human and non-human) in giving impetus to events and facts. The hope, therefore, is to have given a representation of the network that is as close as possible to reality. Despite this, it is inevitable that some uncertainties, linked to research intrinsic limits, may persist. For example, due to privacy restrictions and business secrets, it was not possible to access the accounting documents involved in the planning phase. Furthermore, consent was not granted to interview all the breeders in the supply chain, having to limit the investigation to the experience of only one of them. This made it possible to investigate only objective elements of the network creation process (such as having the counter-proof about the execution dynamics of the meetings and control activities), but it was not possible to assess more subjective elements related more to the personal perceptions of the breeders. This may have partially made the analysis a little less complete. Finally, again for corporate privacy

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issues, it was not possible to graphically report the accounting systems viewed during the interviews at the expense of greater clarity. In conclusion, due to the inevitable restrictions that generally concern research work, there remains a minimal source of uncertainty that the analysis may diverge, albeit slightly, from reality. It is, therefore, in the researcher’s ability to attempt to describe the reality examined as faithfully as possible, not letting himself be discouraged or negatively influenced by the restrictions that unavoidably emerge during the investigation.

4.8

Discussion

As mentioned in the first part of this monograph, this research aimed to investigate the following research questions: R. Q. 1. How was blockchain spread within a supply chain in an ANT approach? R.Q. 2. Which role did the management accounting and control systems have in the process of blockchain implementation and acceptance? How did accounting, management control and blockchain interplay and affect each other? From the case study results, numerous and significant empirical evidence emerge which provide new and significant insights about the research issues investigated. Regarding the first research question, it has been analysed the network creation path, and thus the blockchain implementation process, interpreting the events and facts that occurred in this process through the theoretical frameworks of the sociology of translation (Callon, 1986) and the sources of uncertainty (Latour, 2005). Through the combination of these two theoretical frameworks, it was ascertained how each of the different sources of uncertainty proposed by Latour (2005) can occur at any stage of the sociology of translation, making the path of network creation more or less unstable and difficult to predict. Despite this, the unpredictability of the facts and the dynamics of network creation has been partially mitigated by the use of traditional accounting and management control systems. In particular, the accounting system and the various types of control (Merchant & Van Der Stede, 2007) have played a crucial role above all in the area of uncertainties related to the nature of the actions and the transformation of the concerns into facts. Accounting and control procedures have made it possible to mitigate the risk that concerns may turn into facts differently from those desired and have also minimized the risk that breeders (driven by agencies and personal interests) can act in a way that is not conforming to the interests of the network. This brings us to the second research question. In this regard, important empirical evidence was provided about the interplay between the traditional accounting system and blockchain. In contrast to most of the literature that claims that blockchain can positively affect traditional accounting systems (see, e.g. Pizzi et al., 2022; Shyshkova, 2018; Yermack, 2017; Wang & Kogan, 2018), the present case study has shown that, instead, it is the traditional accounting system to have affected the blockchain. More specifically, the accounting

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Discussion

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system represented the information base on which the ALFA blockchain was built and customized and, for this reason, accounting represented the engine of technology (partially contrasting Tan & Low, 2019). Furthermore, the requirements of transparency and immutability of data, proper to the blockchain, have not been completely reliable. In this case, the decentralization and the presence of agencies and personal interests of the supply chain partners have opened up the possibility of inserting untruthful data into the blockchain. Such a risk has been avoided by traditional accounting and control activities which, through physical control in the field (or action control) and the constant monitoring of the farmers’ activities, have made it impossible to enter untruthful data guaranteeing the real transparency of production processes. This result, therefore, partially confirms the concerns of Coyne and McMickle (2017) and Roubini (2018), according to which the blockchain does not automatically guarantee the truthfulness of the data it contains and its security benefits are not completely available or reliable in the managerial context. However, the case study showed that the accounting system and the traditional control activities have strengthened the security and transparency requirements of the blockchain, mitigating its intrinsic defects. The interaction between blockchain and traditional accounting and control systems, therefore, has strengthened the technology ensuring the real truthfulness of the data entered, thus inducing a greater level of controllability of the supply chain. Accordingly, traditional accounting and control systems in support of blockchain allow human actors to trust digital data more, limiting the risks of unawareness and underestimation of possible errors or fraudulent manipulations (e.g. Maffei et al., 2021). Ultimately, in the light of case study results, accounting has an “in the action” function that is the function to guide the behaviour of actors, both human and non-human, within the network (Zawawi, 2018) and to align their interests with those that the focal actor chooses for the network itself. In this sense, in line with Briers and Chua (2001) and Latour (2005), it represents a non-human actor able to regulate supply chain relationships by creating strong ties (especially between BETA and the breeders) based on dialogue and the continuous exchange of information between actors, and this, in turn, guarantees the survival and persistence of the network. The accounting system played a crucial role in materialising the visual space in which, through the calculations and the reasoning on the accounting inscriptions, BETA and the breeders built their ties and relationships (Busco & Quattrone, 2015). In particular, especially during the last phase of sociology of translation (or mobilization), the performance assessment carried out through the traditional accounting system allowed BETA to ascertain the actors (or the breeders) really in line with the objectives and interests of the network, removing, eventually, those unable to meet the expectations of the focal company. The blockchain, for its part, following the interaction with BETA’s accounting system, has become a key actor which, by gathering and transferring the accounting numbers (or inscriptions) from BETA to ALFA, has allowed action at distance (in line with Corvellec et al., 2018; Quattrone, 2016; Robson, 1992) by extending monitoring and traceability activities to ALFA. It represents a “superstructure” of the accounting system that expanded the visual space for calculative practices that initially involved BETA and the breeders. In so doing, the blockchain put order

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within the network. Indeed, before the blockchain implementation, ALFA had no relationship with the breeders and any information about them had to come from BETA. The absence of a direct relationship exposed the risk that an accounting data, in the various communication passages, underwent interpretations and/or changes with the consequent risk of distorted decisions. Furthermore, the multiple accounting data coming from the breeders could become scattered or confusing since the increase of the data can increase the difficulty in collecting and interpreting them (Cupertino et al., 2021; Quattrone, 2016). The blockchain, due to its characteristics (fostered and improved by the traditional accounting and control practices), put order within the network by guaranteeing ALFA direct, precise and undistorted accounting inscriptions that have allowed it to monitor the supply chain activities. This, in turn, was useful in fostering mobilization and in keeping the entire network in balance. Such evidence appears particularly useful in specific supply chain contexts in which, often, the problem for the focal company to manage and control suppliers that operate at distance—not only geographically but also in organizational and cultural terms— can emerge (Awaysheh & Klassen, 2010). In this regard, the real-time control induced by the blockchain has allowed ALFA to increase the speed of intervention achieving significant improvements in terms of management efficiency. In particular, in line with the Kshetri (2018) findings, the blockchain allowed a more rapid and efficient tracing of defective products which, in turn, allowed cost savings especially for breeders. Moreover, the blockchain has enabled greater ease of data storage and the dematerialization of paper documents since all documentation relating to production activities is now stored in the blockchain databases, with consequent positive effects also in terms of sustainability. Ultimately, in line with Quattrone (2016), new technologies such as blockchain, for whatever they may be advanced and modern, can hardly replace traditional accounting and management control systems which still play a key role in business management. This, however, does not diminish the usefulness of technologies such as the blockchain which, on the contrary, are strengthened when they are integrated by the traditional accounting and control dynamics. This is, in all probability, the main and most important empirical evidence of this research. From a more managerial perspective, the blockchain implementation path has been characterized by different barriers, confirming some of the claims proposed by Saberi et al. (2019). From the results of the case study, it emerges that the first barrier, encountered since the problematization phase, is intra-organizational and is related to the lack of the needed know-how and expertise to develop the technology. In the case analysed, this barrier was tackled by entrusting the design and construction of the technical infrastructure to a third company that is an expert in this technology. Naturally, such an operation requires an economic investment as well as a strong will of the company management to go ahead with the project. Therefore, the financial resources and the managerial commitment, in this case, did not represent barriers but drivers for blockchain adoption. In the subsequent phases of extension of the technology among the various players in the supply chain (i.e. interessement and enrolment), the focal company

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has faced inter-organizational barriers. In particular, several farmers were reluctant to adopt this technology as well as to share their production data. In addition to this, the dispersion in the territory and the small size of these players have also caused coordination problems. To address these problems, ALFA involved the leading company in the supply chain, namely, BETA, in the project, as it already had solid commercial relationships with breeders and long-standing experience in their coordination. Once BETA has been included in the network, the two companies have started a training activity for all the breeders to get them to overcome their resistance to change and to teach them functionalities and logics of the technology. Finally, once the technology was implemented, in the last phase of the sociology of translation or mobilization, two types of barriers were revealed, the external and the system-related ones. The barriers connected to technology have been related to the difficulties related to guaranteeing the truthfulness of the data entered by the breeders. As seen during the analysis of the case, the field controls (action control) combined with the continuous monitoring of the breeders’ performance (result control), made it possible to assess the presence of any anomalies, thus ensuring the full truthfulness of the data. The other barrier that emerged, on the other hand, is related to the lack of a policy that regulates the use of this technology as well as the poor attitude of the institutions to interface with digital documentation. This last barrier, in particular, makes the process of dematerialization of documents partially vain. In this regard the interviewed breeder stated: Unfortunately, health institutions do not care [referring to the possibility of digitizing documents]. . . They still want the paper format and so I still have to fill out the papers for them.

At present, no solution has been found to this problem. In the future, however, the interested parties have planned to start a dialogue with the institutions to remedy this criticality. Intending to make the concepts discussed so far clearer, Table 4.2 summarizes the main barriers involved in the process of adopting blockchain technology and the relative solutions adopted. In conclusion, the process of spreading a technology, such as a blockchain one, presents several challenges, and it needs to be adequately supported by appropriate managerial activities. Furthermore, within the supply chains, a crucial aspect concerns the bargaining power and the role of leading companies. According to Latour (2005), in the creation of a network, are involved different mediators that carry out a process of negotiation with the actors to be enrolled on the network itself. Referring to the R.Q. 1, the case study showed that, in a supply chain context, the presence of strong bargaining power in the hands of a leading company, which also shares interests and objectives with an intermediary company, implies that the mediation process has been softened in part. On the other hand, the absence of bargaining power in the “weaker companies” (or small breeders) means that they must comply with the provisions of the focal actor (and of the spokesperson) to be part of a network from which they derive the economic benefits which are essential for their survival. This meant that the company that acted as mediator and spokesperson

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Table 4.2 Summary of the main case study findings Sociology of translation steps Problematization

Type of barrier Intraorganizational

Interessement and enrolment

Interorganizational

Cultural differences of supply chain partners and coordination difficulties

Mobilization

System related

Difficulties in guaranteeing truthfulness of data

Mobilization

External

Lack of governmental policies and awareness

Barriers Lack of know-how and technical expertise

Managerial solutions Involvement of a third-party company expert of blockchain technology Training activities among all the breeders (personnel control) and involvement of an intermediary company (BETA) closer to the breeders and with whom it already had solid commercial relations Combination of in-field controls (action control) and continuous monitoring of breeders’ performance through the traditional accounting system (result control) In the future it will start a dialogue between companies and institution to increase governmental awareness about the importance of digitization

Source: Own elaboration

(namely, BETA) did not mediate with breeders as much on the conditions of joining the network, but rather on the modalities of action required within the new network. Finally, the activities carried out by the focal company, as OPP, were essential in carrying out the managerial solutions aimed at overcoming the barriers connected to the blockchain, just as the traditional accounting and control activities were fundamental in dealing with uncertainties and in the final realization of the network, supporting the focal actor in the activities of engagement, communication, coordination and transfer of information flows.

4.9

Conclusion

In this chapter, the empirical results of the investigated case study have been presented. Relying on the “sociology of translation” (Callon, 1986) and “five sources of uncertainty” (Latour, 2005) frameworks, the network creation path related to the application of the blockchain within a supply chain was traced and narrated. In so doing, the chapter shows the events that occurred in each phase of the sociology of translation highlighting the uncertainties that affected the network creation process. In this regard, particular attention was given to the role of management accounting

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and control practices in addressing such uncertainties and in fostering blockchain adoption within the supply chain, thus supporting the network formation. The case study showed original evidence that allows this research work to contribute to the literature by demonstrating that the traditional accounting and control mechanisms represent the engine of the blockchain rather than vice versa (as pointed out by several scholars so far). Accounting and control mechanisms remedy some of the intrinsic blockchain’s defects (such as data security and coordination difficulties) improving its effectiveness. On the other hand, the blockchain can be understood as a superstructure of the accounting system that, by expanding the visual space for calculative practices, allows action at distance, thus improving inter-organizational controls and putting order in the network. From a practical perspective, the case study showed the main barriers to blockchain implementation and several managerial solutions to address them. Practical implications and the contribution of this monograph to the scientific debate are presented in detail in the next and last section.

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Emsley, D. (2008). Different interpretations of a “fixed” concept: Examining Juran’s cost of quality from an actor-network perspective. Accounting, Auditing & Accountability Journal, 21(3), 375–397. https://doi.org/10.1108/09513570810863978 Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. https://doi.org/10.1016/j. ijinfomgt.2017.12.005 Janssen, M., Van Der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decisionmaking quality. Journal of Business Research, 70, 338–345. https://doi.org/10.1016/j.jbusres. 2016.08.007 Latour, B. (Ed.). (2005). Reassembling the social: An introduction to actor-network-theory. Oxford University Press. Maffei, M., Casciello, R., & Meucci, F. (2021). Blockchain technology: Uninvestigated issues emerging from an integrated view within accounting and auditing practices. Journal of Organizational Change Management, 34(2), 462–476. https://doi.org/10.1108/JOCM-09-2020-0264 Malmi, T., & Brown, D. A. (2008). Management control systems as a package—Opportunities, challenges and research directions. Management Accounting Research, 19(4), 287–300. https:// doi.org/10.1016/j.mar.2008.09.003 Martinez Ramos, M. (2004). Interaction between management accounting and supply chain management. Supply Chain Management: An International Journal, 9(2), 134–138. https:// doi.org/10.1108/13598540410527033 Merchant, K. A., & Riccaboni, A. (Eds.). (2001). Il controllo di gestione. McGraw-Hill. Merchant, K. A., & Van Der Stede, W. A. (Eds.). (2007). Management control systems: Performance measurement, evaluation and incentives. Pearson Education. Pizzi, S., Caputo, A., Venturelli, A., & Caputo, F. (2022). Embedding and managing blockchain in sustainability reporting: A practical framework. Sustainability Accounting, Management and Policy Journal, 13(3), 545–567. https://doi.org/10.1108/SAMPJ-07-2021-0288 Quattrone, P. (2016). Management accounting goes digital: Will the move make it wiser? Management Accounting Research, 31, 118–122. https://doi.org/10.1016/j.mar.2016.01.003 Revellino, S., & Mouritsen, J. (2015). Accounting as an engine: The performativity of calculative practices and the dynamics of innovation. Management Accounting Research, 28, 31–49. https://doi.org/10.1016/j.mar.2015.04.005 Robson, K. (1992). Accounting numbers as “inscription”: Action at a distance and the development of accounting. Accounting, Organizations and Society, 17(7), 685–708. https://doi.org/10.1016/ 0361-3682(92)90019-O Roubini, N. (2018, October 21). The big blockchain lie. Project Syndicate. Retrieved 8 June 2021, from http://www.mkwinc.com/wp-content/uploads/2018/10/The-Big-Blockchain-Lie.pdf Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261 Sandelin, M. (2008). Operation of management control practices as a package—A case study on control system variety in a growth firm context. Management Accounting Research, 19(4), 324–343. https://doi.org/10.1016/j.mar.2008.08.002 Shyshkova, N. (2018). Prospects for the implementation of Blockchain in accounting. Accounting and Finance, 2, 61–68. Tan, B. S., & Low, K. Y. (2019). Blockchain as the database engine in the accounting system. Australian Accounting Review, 29(2), 312–318. https://doi.org/10.1111/auar.12278

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Chapter 5

Conclusion, Managerial Implications and Limitations

This research aimed to carry out an exploratory study on the managerial dynamics involved in the process of adopting blockchain technology in a supply chain context, focusing, in particular, on the interplay between the blockchain itself, accounting and control systems. By relying on the case of the first European application of blockchain in the food supply chain, and through the lens of the actor-network theory (ANT), evidence was given of the managerial solutions that are necessary for dealing with this new technology as well as of the effects that the blockchain has produced in terms of business management and monitoring of supply chain processes. Starting from the uncertainties highlighted in the literature about the real effects generated by an interaction between blockchain and accounting systems (Coyne & Mcmickle, 2017; Roubini, 2018; Tan & Low, 2019), it was investigated the role that a traditional accounting system had in both the adoption of the blockchain and the network creation process. Empirical evidence has shown that accounting has played the role of the non-human actor (Latour, 2005) in the process of creating the network which underlies the blockchain technology, connecting the various actors involved in it (Briers & Chua, 2001) and acting as an information base for blockchain customization. The latter contains part of the data that traditionally were included in the accounting system. In this way the blockchain has become a “superstructure” of the accounting system by storing and transferring accounting numbers (or inscriptions), expressing the activities performed throughout the supply chain and providing action at distance (Corvellec et al., 2018; Quattrone, 2016; Robson, 1992). Through this last feature, blockchain has made it possible to extend the monitoring activities to ALFA which, in turn, is now able to keep the entire production process under control in real time and can also intervene promptly and precisely in the event of anomalies or manufacturing defects. Alongside the accounting system, traditional control activities were also crucial for the success of the blockchain project. The different forms of control (in line with Merchant & Van Der Stede, 2007) made it possible to overcome various barriers in the various moments of network creation [or sociology of translation (Callon, 1986)], mitigating © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5_5

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uncertainties and risks that gradually emerged and ensuring the success of the entire project. Finally, accounting and control activities have remedied some intrinsic defects of the blockchain that could have compromised its effectiveness, proving to be fundamental drivers for the adequate adoption of this technology. This research work contributes to the current knowledge in different ways. First of all, to the best of my knowledge, this is among the first research works to use Latour’s (2005) sources of uncertainty framework to explain the network creation path generated by the application of new technology within a supply chain. The case study showed that these sources of uncertainty are not only manifested in the formation of the network but are significantly intertwined with the sociology of translation phases proposed by Callon (1986), demonstrating how these two ways of using ANT are fully complementary. Secondly, this is also one of the first research works to provide empirical evidence about the relationship between blockchain and accounting, responding to the scientific need of giving an empirical demonstration of the theoretical assumptions presented in literature so far (e.g. Lardo et al., 2022; Lombardi et al., 2022; Lombardi & Secundo, 2021; Mancini et al., 2021; Maffei et al., 2021; Secinaro et al., 2022). Finally, showing that accounting is one of the main drivers for the blockchain application, this study contributes to the present literature proving that the traditional accounting system still has an indispensable role in business management and, at least until now, it cannot be replaced by the new technological automatisms (Quattrone, 2016). This, consequently, allows us to support the traditional role of accounting, and it also encourages the continuous integration between human and non-human actors and between tradition and innovation. In this regard, this study has shown how the integration between traditional accounting and control practices and blockchain innovation led to a strengthening of both the technology itself and the monitoring and control activities, making the combination of tradition and innovation both desirable and profitable. In addition to the previous contributions to the literature, this study also provides important managerial implications. It shows that, to implement the blockchain in a supply chain context, appropriate managerial solutions are needed to overcome the different types of barriers that inevitably arise. First of all, the presence of a solid information base from which to derive the vast amount of data that will flow into the blockchain is essential. Moreover, it seems that the blockchain only works in supply chains that are not too fragmented and in which solid commercial relationships already exist that facilitate coordination. As emerged from the declarations of the managers of ALFA about the approaches to innovation in the various supply chains of the company, the adoption of the blockchain failed in excessively fragmented supply chains that also lack an accounting base that served as the basis for customizing the blockchain itself. Moreover, an adequate training activity for smaller suppliers appears to be indispensable as well, since they generally tend to be more reluctant to adopt innovation as well as to share their business data. In this sense, a crucial role must be played by the supply chain leading company which has to support its suppliers in the process of adopting technology not only economically but above all on a cultural and cognitive level.

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Like any research work, this study also has some limitations. Due to privacy restrictions and company policies, it was not possible to graphically report the contents of the accounting system under examination at the expense of greater clarity of the monograph. Furthermore, for the same reasons, it was not possible to interview all the breeders involved in the network, having to limit the investigation to only one of them. This has restricted the investigation to only the objective aspects of the phenomenon analysed or to those aspects that are common to all breeders (such as the counter-proof of the declarations of the managers of ALFA and BETA about the dynamics of execution of the meetings or the methods for entering production data). More subjective aspects, related, for example, to the breeders’ perception about the utility of the technology or the difficulties and benefits connected to the participation in the network, could not be investigated at all. Furthermore, the empirical evidence derives from a single case study, and, therefore, they are difficult to generalize. This, however, leaves room for future investigation. In particular, this research work stands as one of the first studies related to blockchain and its use in business management, proposing preliminary empirical evidence that needs to be enriched by further studies on this topic. Indeed, the topics covered here are still in an embryonic stage. Further research is needed, exploring also other productive contexts, to find new empirical evidence about the design and implementation of blockchain. In this regard, multiple case studies should be developed to expand the results found in this research work by producing new evidence on how companies—with their own peculiarities—deal with the implementation of the blockchain for accounting and control purposes. Furthermore, a more mature context of blockchain adoption should be analysed to better understand the implications of the technology for accounting and management control and dayto-day business operations. Finally, how the role and tasks of accountants change due to the adoption of the blockchain and how traditional accounting practices merge with new technological solutions are research topics to be extensively explored in the near future.

References Briers, M., & Chua, W. F. (2001). The role of actor-networks and boundary objects in management accounting change: A field study of implementation of activity-based costing. Accounting, Organizations and Society, 26(3), 237–269. https://doi.org/10.1016/S0361-3682(00)00029-5 Callon, M. (1986). Some elements of a sociology of translation: Domestication of the scallops and the fishermen of St Brieuc Bay. In J. Law (Ed.), Power, action and belief (pp. 196–233). Routledge & Kegan Paul. Corvellec, H., Ek, R., Zapata, P., & Campos, M. J. Z. (2018). Acting on distances: A topology of accounting inscriptions. Accounting, Organizations and Society, 67, 56–65. https://doi.org/10. 1016/j.aos.2016.02.005 Coyne, J. G., & Mcmickle, P. L. (2017). Can blockchains serve an accounting purpose? Journal of Emerging Technologies in Accounting, 14(2), 101–111. https://doi.org/10.2308/jeta-51910

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Lardo, A., Corsi, K., Varma, A., & Mancini, D. (2022). Exploring blockchain in the accounting domain: A bibliometric analysis. Accounting, Auditing & Accountability Journal, 35(9), 204–233. https://doi.org/10.1108/AAAJ-10-2020-4995 Latour, B. (Ed.). (2005). Reassembling the social: An introduction to actor-network-theory. Oxford University Press. Lombardi, R., De Villiers, C., Moscariello, N., & Pizzo, M. (2022). The disruption of blockchain in auditing–A systematic literature review and an agenda for future research. Accounting, Auditing & Accountability Journal, 35(7), 1534–1565. https://doi.org/10.1108/AAAJ-10-2020-4992 Lombardi, R., & Secundo, G. (2021). The digital transformation of corporate reporting–A systematic literature review and avenues for future research. Meditari Accountancy Research, 29(5), 1179–1208. https://doi.org/10.1108/MEDAR-04-2020-0870 Mancini, D., Lombardi, R., & Tavana, M. (2021). Four research pathways for understanding the role of smart technologies in accounting. Meditari Accountancy Research, 29(5), 1041–1062. https://doi.org/10.1108/MEDAR-03-2021-1258 Maffei, M., Casciello, R., & Meucci, F. (2021). Blockchain technology: Uninvestigated issues emerging from an integrated view within accounting and auditing practices. Journal of Organizational Change Management, 34(2), 462–476. https://doi.org/10.1108/JOCM-09-2020-0264 Merchant, K. A., & Van Der Stede, W. A. (Eds.) (2007). Management control systems: Performance measurement, evaluation and incentives. Pearson Education. Quattrone, P. (2016). Management accounting goes digital: Will the move make it wiser? Management Accounting Research, 31, 118–122. https://doi.org/10.1016/j.mar.2016.01.003 Robson, K. (1992). Accounting numbers as “inscription”: Action at a distance and the development of accounting. Accounting, Organizations and Society, 17(7), 685–708. https://doi.org/10.1016/ 0361-3682(92)90019-O Roubini, N. (2018, October 21). The big blockchain lie. Project Syndicate. Retrieved 8 June 2021, from: http://www.mkwinc.com/wp-content/uploads/2018/10/The-Big-BlockchainLie.pdf. Secinaro, S., Dal Mas, F., Brescia, V., & Calandra, D. (2022). Blockchain in the accounting, auditing and accountability fields: A bibliometric and coding analysis. Accounting, Auditing & Accountability Journal, 35(9), 168–203. https://doi.org/10.1108/AAAJ-10-2020-4987 Tan, B. S., & Low, K. Y. (2019). Blockchain as the database engine in the accounting system. Australian Accounting Review, 29(2), 312–318. https://doi.org/10.1111/auar.12278

Annex 1: Draft of the Questions Made During the Semi-Structured Interviews

Questions addressed in the company “ALFA” 1. Why did you choose to adopt blockchain technology? 2. Could you describe how it works? 3. How did you approach this new technology? Did you develop it in-door, or did you rely on third-party companies? 4. In which supply chains have you spread the blockchain and why? 5. Which actors are made up of the chicken supply chain (i.e. the supply chain in which the blockchain was spread)? 6. Which actors have been involved in the technology diffusion process? 7. Could you tell me about the implementation process of the blockchain in the chicken supply chain? 8. In this path of adoption and diffusion of technology, have accounting tools and control practices played any role? If so, which one? 9. How does “ALFA” use the blockchain? What information does “ALFA” get from it? 10. What are the accounting and control practices that “ALFA” uses in the management of the supply chain? 11. Have these practices changed following the implementation of the blockchain? If yes, how? 12. What results and/or changes has the adoption of the blockchain brought to the management of the supply chain? 13. Was there any resistance from actors to adopting this technology? 14. How did “ALFA” manage them? 15. In general, what barriers have you faced in adopting and spreading blockchain? 16. What are the key elements that enable the successful adoption and diffusion of the blockchain within a supply chain? Questions addressed in the company “BETA” 1. Why did “BETA” join the “ALFA” project to adopt the blockchain for supply chain management? 2. What is the role of “BETA” within the supply chain? Which relationships does “BETA” have with “ALFA” and the breeders? 3. What was and what is the role of “BETA” in this project? 4. What does “ALFA” expect from “BETA”, and how does “BETA” benefit from the project of “ALFA”? 5. How does “BETA” use the blockchain? Which kind of information do you put in? (continued) © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 G. Vitale, Understanding Supply Chain Digitalization Through Actor-Network Theory, SIDREA Series in Accounting and Business Administration, https://doi.org/10.1007/978-3-031-30988-5

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6. What kind of accounting and control systems does “BETA” employ? 7. Did the traditional accounting and control systems employed by “BETA” have any role in the process of adoption and diffusion of the blockchain along the supply chain? If so, which one? 8. What has changed following the adoption of the blockchain in the chicken supply chain? 9. Have accounting and control systems been affected in any way by the new technology? 10. What barriers, resistances and/or difficulties have you encountered in the blockchain adoption process? 11. How did you handle the problems that emerged? 12. What are the main risks and critical issues associated with the use of the blockchain? 13. What are the benefits and opportunities instead? 14. What are the key elements that enable the successful adoption and diffusion of the blockchain within a supply chain? Questions addressed in the company “GAMMA” 1. Why should a company invest in blockchain technology? 2. In which business context the blockchain would be particularly useful? 3. What are the technical aspects that distinguish the blockchain you designed for “ALFA”? 4. Could you explain how it works? 5. How did the interaction between “GAMMA” and “ALFA” take place? 6. What requests did “ALFA” make? 7. What risks and technical problems are associated with the blockchain? 8. What benefits can it induce instead? 9. What can be the main difficulties of use? 10. How do you support users in using the blockchain? Questions addressed to the breeder 1. Why did you join the “ALFA” project? 2. How did you interact with “ALFA” and “BETA” for this project? 3. What are the relationships between you, “ALFA” and “BETA”? 4. What does “ALFA” and “BETA” expect from you, and how do you benefit from the project of “ALFA”? 5. Can you tell me about how the blockchain works? How do you interact with this technology? Which kind of information do you put in? Can you show me how you use it? 6. What accounting and control practices do “ALFA” and “BETA” adopt to monitor your activities? 7. What accounting practices do you adopt? 8. What changed after the blockchain implementation? 9. What difficulties did you have in using the blockchain? 10. What positive aspects are related to the adoption of this technology?