THE ROLE OF EMERGENT DIGITAL TECHNOLOGIES IN MARKETING RESEARCH AND STRATEGY By Shana Leslie Redd A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Business Administration - Marketing - Doctor of Philosophy 2021 ABSTRACT THE ROLE OF EMERGENT DIGITAL TECHNOLOGIES IN MARKETING RESEARCH AND STRATEGY By Shana Leslie Redd Emergent digital technologies (EDTs), such as artificial intelligence (AI), augmented and virtual reality (AR/VR), and robotic and mechanical automation, are of increasing strategic value to practitioners and marketing academics. Collectively, these technologies are expected to contribute more than $17 trillion to global GDP by 2030, up 760% from 2019 (PwC 2019a; PwC 2019b). This rapid growth presents significant challenges for marketing researchers and practitioners. Specifically, despite the movement towards EDT-oriented topics, marketing scholars assert that academic research has been outpaced by industry in the understanding and implementation of EDT. Additionally, firms face critical challenges such as when and how to integrate EDTs into their product offerings to provide a competitive advantage. Consequently, my two-essay dissertation seeks to: (1) fill a gap in EDT understanding by offering a macro-level perspective of EDT-oriented research in marketing and related business disciplines to advance marketing research (Essay One) and (2) fill a gap in brand-level understanding of EDTs by empirically examining theoretically driven factors that influence a firm's marketing performance (Essay Two). In Essay One, I employ multidimensional scaling (MDS) to examine the intellectual structure of EDT research in marketing (and, for comparison, across six related business disciplines) by evaluating 280,961 citations drawn from 6,099 articles in a sample of 221 journals. To advance EDT-oriented research within marketing, I develop a cross-disciplinary and integrative research framework supported by three distinct theoretical perspectives: the resource-based view (RBV), the technology acceptance model (TAM), and the theory of reasoned action (TRA). In Essay Two, I draw upon the three theories (i.e., RBV, TAM, and TRA) in conjunction with the economic theory of additive utility to develop a theoretical framework to examine the marketing performance of a firm's digital technology capabilities. Specifically, I address two research questions in Essay Two: 1) To what extent should a firm establish its digital technology capability? 2) Under what conditions does a firm's digital technology capability lead to a competitive advantage? I compiled a unique and knowledge-rich panel data set comprising 20 automotive brands, 304 vehicle models, and 8,692 observations from 2010 - 2019. The data set integrates variables from nine separate data sources. Broadly, the results show a nuanced picture, which suggests that while digital technology capabilities lead to short-term gains (e.g., brand sales), the long-term effect (e.g., customer satisfaction) may be detrimental for extremely advanced firms. Essay Two captures the full details of these digital technology results and provides actionable, practical implications. Copyright by SHANA LESLIE REDD 2021 ACKNOWLEDGEMENTS I am tremendously grateful to my classmates, the Broad marketing support staff, colleagues, and family for their continuous support and encouragement. To the brilliant members of the Ph.D. Project and MDSA, thank you for creating a community that inspires, supports, and develops URM scholars. To Dr. Roger Calantone, thank you for fueling my interest in new product and service development. To Dr. G. Tomas Hult, thank you for your invaluable insight, direction, and encouragement. To Dr. Ayalla Ruvio, thank you for sharing your expertise and passion for research. To Dr. Wyatt Schrock, thank you for your mentorship and unmatched attention to detail. To Dr. Brian Chabowksi, thank you for your guidance and generous support in shaping my dissertation. To Dr. Clay Voorhees, thank you for encouraging me to pursue my Ph.D. and for your honest feedback throughout this process. To Dr. Forrest Morgeson III, thank you for accepting the “honorary” committee member role and your insightful feedback and guidance. To my family, there's no way in the world I could have done this without you. To my father and mother, Virgil and Odette, thank you for encouraging me to pursue my dreams always. To my sister, Christina, thank you for your brilliant advice and unwavering support. To my Auntie Leatha, thank you for inspiring me to pursue academia. To my loving Husband and furry son, Brad and Teddy, thank you for being my chosen family and for the countless words of encouragement, meals served in my office, and hugs on the tough days. v TABLE OF CONTENTS LIST OF TABLES..................................................................................................................... viii LIST OF FIGURES.................................................................................................................... ix KEY TO ABBREVIATIONS.................................................................................................... x DISSERTATION INTRODUCTION........................................................................................ 1 ESSAY ONE.............................................................................................................................. 5 A Cross-Disciplinary View of Emergent Digital Technology Literature: Opportunities for Future Advancements in Marketing Research..................................... 5 Abstract............................................................................................................................. 5 Introduction....................................................................................................................... 6 Theoretical Foundation: Social Network Theory............................................................. 9 Method.............................................................................................................................. 11 Results............................................................................................................................... 16 Discussion and Implications……………………………………………………………. 20 EDT Research Framework...................................................................................... 20 Recently Published EDT Articles in Marketing...................................................... 25 Future Research Opportunities................................................................................ 27 APPENDICES.................................................................................................................. 31 APPENDIX A: TABLES........................................................................................ 32 APPENDIX B: FIGURES....................................................................................... 35 REFERENCES................................................................................................................. 42 ESSAY TWO............................................................................................................................. 55 Riding the Digital Technology Wave: Embracing Emergent Digital Technology Capabilities to Gain a Competitive Advantage................................................................. 55 Abstract............................................................................................................................. 55 Introduction....................................................................................................................... 56 Theory and Hypotheses.................................................................................................... 60 Digital Technology Capability and Brand Sales..................................................... 60 Digital Technology Capability and Customer Satisfaction..................................... 63 Digital Technology Surplus as a Competitive Advantage...................................... 64 vi Research Methodology..................................................................................................... 67 Data Collection........................................................................................................ 67 Measures................................................................................................................. 68 Model Specification................................................................................................ 73 Estimation Results............................................................................................................ 75 Sample Description................................................................................................. 75 Hypotheses Testing................................................................................................. 76 Robustness Checks and Generalizability Assessment............................................ 80 Discussion and Implications............................................................................................. 81 Theoretical Contributions....................................................................................... 81 Managerial Contributions....................................................................................... 83 Limitations and Future Research Directions.................................................................... 85 APPENDICES.................................................................................................................. 87 APPENDIX A: TABLES........................................................................................ 88 APPENDIX B: FIGURES....................................................................................... 100 REFERENCES................................................................................................................. 107 DISSERTATION CONCLUSION............................................................................................. 114 vii LIST OF TABLES Table 1-1 Journals Included in the Study by Discipline........................................................ 32 Table 1-2 Most Influential Recently Published Theory-Based EDT Articles in the Marketing Literature.............................................................................................. 34 Table 2-1 Parent Firms and Brands Included in this Study................................................... 88 Table 2-2 Variables, Measures, and Sources......................................................................... 89 Table 2-3 Digital Technology Features Included in the Study.............................................. 91 Table 2-4 Descriptive Statistics............................................................................................. 94 Table 2-5 Correlations Table................................................................................................. 95 Table 2-6 The Effect of Digital Technology Indices on Brand Sales.................................... 96 Table 2-7 The Effect of Digital Technology Indices on Customer Satisfaction.................... 97 Table 2-8 The Effect of Digital Technology Differences on Brand Sales............................. 98 Table 2-9 The Effect of Digital Technology Differences Customer Satisfaction................. 99 viii LIST OF FIGURES Figure 1-1 EDT-Oriented Articles Published in Top 10 Marketing Journals (2010 - 2020)......................................................................................................... 35 Figure 1-2 EDT Intellectual Structure in the Marketing Literature........................................ 36 Figure 1-3 EDT Intellectual Structure in the Innovation Literature........................................ 37 Figure 1-4 EDT Intellectual Structure in the Organizational Behavior and Human Resource Management Literatures........................................................................ 38 Figure 1-5 EDT Intellectual Structure in the Management Information Systems and Knowledge Management Literatures.................................................................... 39 Figure 1-6 EDT Intellectual Structure in the Finance and Accounting Literatures................ 40 Figure 1-7 A Research Framework for the EDT Literature.................................................... 41 Figure 2-1 Examples of Technology-Focused Automotive Advertisements.......................... 100 Figure 2-2 Conceptual Model................................................................................................. 101 Figure 2-3 Example of U.S. News (Cars) Webpage with Vehicle Features........................... 102 Figure 2-4 Model-Free Changes in Key Measures from 2010 - 2019.................................... 103 Figure 2-5 Mean Differences Between Mainstream and Luxury Brands............................... 104 Figure 2-6 Digital Technology Index, Brand Status, Sales, and Customer Satisfaction......... 105 Figure 2-7 Digital Technology Difference, Brand Status, Sales, and Customer Satisfaction............................................................................................................ 106 ix KEY TO ABBREVIATIONS ACSI American Customer Satisfaction Index AI Artificial Intelligence AR Augmented Reality CSAT Customer Satisfaction EDT Emergent Digital Technology FWDIFF Feature-Weighted Digital Technology Index Difference FWDTI Feature-Weighted Digital Technology Index JDPA JP Powers & Associates MDS Multidimensional Scaling UDIFF Unweighted Digital Technology Index Difference UDTI Unweighted Digital Technology Index VR Virtual Reality x DISSERTATION INTRODUCTION Emergent digital technologies (EDTs) have revolutionized consumer experiences and enhanced firms’ revenue significantly. Global consumer spending on digital technologies such as artificial intelligence (AI), augmented and virtual reality (AR/VR), drones, internet of things (IoT), and robotic and mechanical systems totaled $1.6 trillion in 2018 and is forecasted to reach nearly $2.1 trillion in 2023 (Statista 2021a). Collectively, these technologies are expected to contribute more than $17 trillion to global GDP by 2030, up 760% from 2019 (PwC 2019a; PwC 2019b). In fact, the fusion of digital technologies (i.e., the Fourth Industrial Revolution) is projected to "create more capital and enable humans to accumulate more wealth to drive economic growth" than revolutions of the past (Skilton and Hovsepian 2017, p. 6). Accordingly, researchers have taken an interest in the financial and societal impacts of EDTs on marketing phenomena (e.g., Marinova et al. 2017; Mende et al. 2019; Tellis, Yin, and Niraj 2009) and the application of EDTs as methodological tools in industry and academic research (e.g., Hershfield et al. 2011; Thieme, Song, and Calantone 2000). However, despite the progressive movement towards understanding the impact of EDTs on marketing phenomena, the rapid proliferation and technological advancements of digital technologies present significant challenges for marketing researchers and practitioners. Specifically, marketing scholars assert that academic research has been outpaced by industry in the understanding and implementation of EDT. Current topics of interest include AI's effect on customer engagement and decision-making, long-term value creation, and marketing capabilities (Marketing Science Institute 2020), "Marketing in the Age of [Technological] Disruption" (American Marketing Association Summer Academic Conference 2020 Theme), and "Creating 1 Customer, Firm, and Social Value through Cutting-Edge Digital Technologies" (Journal of the Academy of Marketing Science Special Issues for Publication in 2021). While these topics will advance EDT knowledge in the marketing discipline, there is an opportunity to propel research forward more efficiently through a thorough examination of EDT literature's cross-disciplinary foundations. Therefore, Essay One of my dissertation seeks to fill this gap in EDT understanding by offering a macro-level perspective of EDT-oriented research in marketing and related business disciplines to advance marketing research. Essay One intends to provide three key contributions to the marketing discipline and EDT domain. First, I conduct a cross-disciplinary quantitative examination of the EDT literature. Using co-citation analysis, I employ multidimensional scaling (MDS) to examine the intellectual structure of EDT research in marketing and, for comparison, across six other related business disciplines, which include marketing, innovation, general management and strategy, organizational behavior and human resource management, operations research and management science, management information systems and knowledge management, and finance and accounting. Second, I investigate and synthesize the interrelationships of EDT-related research topics and methods across the disciplines to develop a cross-disciplinary and integrative research framework supported by three distinct theoretical perspectives: the resource-based view (RBV), the technology acceptance model (TAM), and the theory of reasoned action (TRA). Third, I delineate the most influential recently published and theory-based EDT articles in the marketing literature in the context of the proposed framework. My guiding purpose in this research is to remove the silos between related business disciplines, take inventory of EDT-oriented business literature, and build theoretical and methodological bridges between marketing and related business disciplines to accelerate EDT-oriented research in the marketing discipline. 2 Additionally, firms face critical challenges such as when and how to integrate EDTs into their product offerings to gain a competitive advantage. EDTs are becoming far more prevalent in every aspect of consumers' lives, enabling more personalized, seamless, and relevant experiences by providing new forms of knowledge, entertainment, and interactions (Hamel and Prahalad 1994; Schmitt 2019; Tellis, Yin, and Niraj 2009). These seamless digital technology experiences are made possible by brands that embrace existing and emerging digital technologies. Prior research suggests that embracing digital technology as a strategic resource enables brands to establish a competitive advantage by offering consumers greater value such as personalized offerings, enhanced consumer delight, and revolutionize customer experiences (Hilken et al. 2017; Hoffman and Novak 2018; Ramaswamy and Ozcan 2018). This competitive advantage may be evidenced by greater sales and high customer satisfaction than a brand’s competitive set. However, research on technology adoption and technological learning curves indicate that EDTs may adversely affect critical brand outcomes such as lower adoption of technology products and lower product evaluations (Billeter, Kalra, and Loewenstein 2011; Davis, Bagozzi, and Warshaw 1992; Thompson, Hamilton, and Rust 2005). Given these conflicting findings, the questions pertinent to brand decision-making as it pertains to digital technology are: 1) To what extent should a brand establish its digital technology capability? 2) Under what conditions does a brand's digital technology capability lead to a competitive advantage? Essay Two intends to provide four key contributions to the marketing discipline and EDT domain. First, I draw upon the three theories discussed in Essay One (i.e., RBV, TAM, and TRA) in conjunction with the economic theory of additive utility to develop a theoretical framework to examine the marketing performance of a firm's digital technology capabilities. 3 Specifically, I posit that the relationships between digital technology capability and marketing outcomes are dynamic, divergent, and non-linear. Second, I empirically test the model using a unique and knowledge-rich panel data set comprising 20 automotive brands, 304 vehicle models, and 8,692 observations from 2010 - 2019. The data set integrates variables from nine separate data sources, including US News (Cars), American Customer Satisfaction Index (ACSI), Automotive News, J.D. Power & Associates (JDPA), Wards Intelligence, Compustat, Statista, automotive brand websites, and expert raters. Third, I examine the moderating role of brand status in the purchase of mainstream versus luxury products. Luxury brand products are those that signal the highest level of quality and design, may be purchased for utility, symbolic, and experiential motivations, and promote a plethora of features that may not be functionally necessary (e.g., Berthon et al. 2009; Hagtvedt and Patrick 2009; Silverstein and Fiske 2003). As a result, luxury brand products are often perceived as possessing greater value than mainstream brand products. Subsequently, I postulate that luxury brands have greater exposure to the positive effects and are more insulated from the negative effects of a brand's digital technology capability than mainstream brands. Fourth, I adopt a resource-based view (RBV) theoretical perspective to understanding how a brand's digital technology capability promotes a sustainable competitive advantage (Barney 1991). Specifically, I propose that brands that exceed their competitive set's digital technology capability standard may be uniquely positioned to garner greater sales and greater customer satisfaction than their direct competitors. I refer to the excess capability beyond the competitive set as a brand's digital technology capability surplus. Broadly, the results show a nuanced picture, which suggests that brand managers should consider both the short- and long-term implications of investing in digital technology capabilities. 4 ESSAY ONE A Cross-Disciplinary View of Emergent Digital Technology Literature: Opportunities for Future Advancements in Marketing Research Abstract The scholarly study of emergent digital technologies (EDTs) in marketing has led to a substantial body of literature and an accelerated need for conceptual research that addresses how EDTs impact our understanding of marketing phenomena. This research aims to conduct a holistic examination of the EDT domain in marketing and across six other related business disciplines and identifies the topics informed by each discipline's most influential works. Using co-citation analysis, we employ multidimensional scaling (MDS) to evaluate 280,961 citations drawn from 6,099 articles in a sample of 221 journals, resulting in an intellectual structure of EDT research for each discipline. To advance EDT-oriented research within the marketing discipline, we develop a cross-disciplinary and integrative research framework based on established literature from each field and recently published influential works in the marketing literature to suggest theoretical and research stream gaps to advance EDT research in marketing. Keywords: Emergent Digital Technology, Artificial Intelligence, Virtual Reality, Augmented Reality, Automation, Multidimensional Scaling, Social Network Theory 5 Introduction Emergent digital technologies (EDTs), such as artificial intelligence (AI), augmented and virtual reality (AR/VR), and robotic and mechanical automation, are of increasing interest to practitioners and marketing academics. Collectively, these technologies are expected to contribute more than $17 trillion to global GDP by 2030, up 760% from 2019 (PwC 2019a; PwC 2019b). The fusion of digital technologies, often referred to as the Fourth Industrial Revolution, is projected to "create more capital and enable humans to accumulate more wealth to drive economic growth" than revolutions of the past (Skilton and Hovsepian 2017, p. 6). Subsequently, this digital revolution has led to a surge of EDT-oriented literature in marketing over the last two years. For example, between 2000-2018, the total number of EDT-oriented articles published in the top 10 marketing journals was 88 compared to 91 articles published between 2019-2020.1 Thus, this accelerated need to understand the current and future impact of EDTs on marketing phenomena is significant for practitioners and researchers alike. Researchers have traditionally focused on the effect of individual EDTs (e.g., AI, AR/VR, and robotic and mechanical automation) on marketing outcomes. For example, EDT topics examined in marketing include perceptions of EDTs in the service domain (Hilken et al. 2017; Marinova et al. 2017; Van Doorn et al. 2017), job replacement and supplement (Huang and Rust 2018; Mende et al. 2019), adoption and utilization (Kumar et al. 2016; Leung, Paolacci, and Puntoni 2018), consumer experience enhancement (Hoffman and Novak 2018; Kozinets et 1 Articles retrieved from Clarivate Analytics (2020) Web of Science Platform published 2010-2020 for the following journals: Journal of Marketing, Journal of Marketing Research, Marketing Science, Journal of Consumer Research, Journal of the Academy of Marketing Science, Journal of Consumer Psychology, Journal of Advertising, Journal of Interactive Marketing, Journal of Retailing, International Journal of Research in Marketing. 6 al. 2002), and notably, EDTs as methodological tools applied to industry and academic research (Hershfield et al. 2011; Little 1979; Thieme, Song, and Calantone 2000). Collectively, these studies indicate that EDTs have a profound and potentially volatile effect on business outcomes. However, despite the progressive movement towards EDT-oriented topics, scholars continue to assert that the academic research to date is outpaced by industry in the study and implementation of technology tools and further guidance for leveraging the benefits of technologies in marketing is needed (Huang and Rust 2021; Wedel and Kannan 2016). Drawing attention to the accelerated need for EDT-oriented literature, the Marketing Science Institute (MSI) and prominent marketing journals have called for theoretical papers that address how EDTs impact our understanding of critical marketing issues. Recent topics include AI's effect on customer engagement and decision-making, long-term value creation, and marketing capabilities (Marketing Science Institute 2020). Similarly, advances in real-world applications of digital technologies have motivated interest in topics like "Marketing in the Age of [Technological] Disruption" (American Marketing Association Summer Academic Conference 2020 Theme), "Leveraging AI to Create Value for Consumers, Organizational Frontlines, and Firms," and "Creating Customer, Firm, and Social Value through Cutting-Edge Digital Technologies" (Journal of the Academy of Marketing Science Special Issues for Publication in 2021). Scholarly interest in these topics, among others, will assuredly advance EDT knowledge in the marketing discipline. However, marketing researchers have an opportunity to advance research topics through a thorough examination of EDT literature's cross- disciplinary foundations. We propose that a thorough examination calls for an aggregated view of EDT literature across marketing and related business disciplines. In practice, marketers who seek to integrate 7 digital technologies into their business successfully are often guided by a broader business strategy that allows for the combinative application of several digital tools (Tabrizi, Lam, Girard, and Irvin 2019). This "best practice" highlights the need for EDTs to be evaluated and applied collectively and impresses upon marketing leaders the importance of viewing digital integration as a cross-disciplinary goal. This view is consistent with the principle that marketing researchers, in the study of marketing phenomena, should "cast their nets wider to consider more disciplines" in pursuit of "intellectual cross-pollination" (Deshpande 1999, p. 166). Thus, we posit that a holistic examination is critical to advancing pertinent marketing research in the EDT domain. This research provides three key contributions to the marketing discipline and EDT domain. First, we conduct a cross-disciplinary quantitative examination of the EDT literature. Using co-citation analysis, we employ multidimensional scaling (MDS) to provide a cross- disciplinary view of the foundational literature. As an essential step in the scientific process, we present careful identification and synthesis of relevant literature to provide scholars with a "state- of-the-art" view of the EDT domain (Bem 1995; Palmatier, Houston, and Hulland 2018). This approach offers a richer, more in-depth understanding of our collective, scholarly knowledge to date. Guided by Harzing's Journal Quality List (Harzing 2019), this examination includes theoretical and conceptual perspectives from selected publications across seven business disciplines (marketing, innovation, general management and strategy, organizational behavior and human resource management, operations research and management science, management information systems and knowledge management, and finance and accounting). Table 1-1 provides a list of the journals included in this study by discipline. Second, we investigate and synthesize the interrelationships of EDT-related research topics and methods across the disciplines. We draw from these findings theoretical and 8 methodological research gaps in the EDT literature and propose a multi-disciplinary research framework. Third, to complement the quantitative examination, the qualitative examination introduces the most influential recently published and theory-based EDT articles in the marketing literature and discusses these articles in the context of the proposed framework. This approach is designed to provide a rigorous, usable, and thoughtful guide for future research (Palmatier, Houston, and Hulland 2018). We structure the rest of this article as follows: We first discuss social network theory as the theoretical lens through which we analyze the intellectual structure for each discipline. Then, we offer a quantitative examination of the literature and introduce MDS as the method employed to analyze co-citation data. Following the method review, we present our results. We then present a multi-disciplinary framework of the EDT literature. Lastly, we conclude by discussing our findings' theoretical and managerial implications and providing suggestions for future research. Theoretical Foundation: Social Network Theory Social network theory suggests that members exchange valuable resources through interactions over time (Baumgartner and Pieters 2003; Pieters, Baumgartner, Vermunt, and Bijmolt 1999). In bibliometric studies, the members may consist of journals, articles, or authors. The generation of ideas, knowledge, and influence are the valuable resources exchanged. The interactions are co-citations drawn from influential published works that form an intellectual structure (e.g., Kuhn 1962). ). Within this structure, distinct subgroups of ideas and knowledge 9 are identified based on network ties (Tichy, Tushman, and Fombrun 1979). These subgroups can represent scholarly themes, theories, and methodologies within a domain. Social network theory is often the basis for co-citation research. Co-citation pattern analysis uncovers the exchange or cross-fertilization of influential research within a topical domain (Zinkhan, Roth, and Saxton 1992). Spatially, the nodes represent influential scholarly works and are joined by links (network ties) representing co-creation patterns. The spatial proximity between each node is determined by the strength of the link (Samiee and Chabowski 2021). Nodes that are close in proximity (i.e., strong ties) are similar in nature. Nodes that are farther in proximity from others (i.e., weak ties) often represent novel knowledge generation, institutional voids, or different types of information (e.g., Borgatti and Halgin 2011). Importantly, these intellectual structures bring forth the past and current knowledge of a discipline or domain. From this knowledge or understanding, scholars may infer future research developments (Borgatti, Mehra, Brass, and Labianca 2009). This study views the seven business disciplines as distinct social networks (e.g., scholarly communities, sets of publication outlets for intellectual exchange). This approach provides a deeper understanding of the themes, theories, and methodologies formed by influential works and highlights recent trends and traditions within each discipline (Carrington, Scott, and Wasserman 2005) that have and will continue to influence future studies within related fields (e.g., Borgatti et al. 2009). By revealing the concentration or dispersion of knowledge (Baumgartner and Pieters 2003) within each unique environment, we are primed for cross-disciplinary comparisons. Insights drawn from the observed similarities and differences between neighboring disciplines should serve as a multi-disciplinary guide to future EDT- oriented research in marketing. Additionally, marketing is inherently a cross-functional 10 discipline that has been cross-functional in both practice and research (Grønholdt and Martensen 2005). As such, there is a tremendous opportunity for marketing to take a multi-disciplinary view to advance EDT-oriented research. Method This study of the EDT literature originated with the identification of 221 journals listed in Harzing (2019) as ranked A or higher in the ABDC categorization of research publication outlets (Chabowski and Mena 2017). Since the goal of this evaluation is meant to reflect the multi- disciplinary nature of EDT in the study of business, data were drawn representing the following disciplines: marketing (28 journals), innovation (6 journals), general management and strategy (27 journals), organizational behavior and human resource management (31 journals), operations management and management science (40 journals), management information systems and knowledge management (33 journals), and finance and accounting (56 journals) (Chabowski, Samiee, and Hult 2017; Harzing 2019). The list of journals included in the analysis is found in Table 1-1. Guided by prior bibliometric mapping techniques used in marketing (Martínez-López, Merigó, Gázquez-Abad, and Ruiz-Real 2020; Ringel and Skiera 2016; Samiee, Chabowski, and Hult 2015) and other business-related subject areas such as general management and strategy (Shafique 2013; Zupic and Čater 2015), innovation (Rossetto, de Carvalho, Bernardes, and Borini 2017; Van Eck, Waltman, Dekker, and van den Berg 2010) and operations research (Colicchia, Creazza, Noè, and Strozzi 2019; de Campos, de Paula, Pagani, and Guarnieri 2017), we employ MDS to analyze the co-citation data from each subject area. MDS is one of the most 11 widely accepted statistical techniques for constructing bibliometric maps (McCain 1991) and has proven more dynamic than factor and cluster analysis in the delineation of past and current research as well as future research opportunities (Chabowski and Mena 2017; Samiee, Chabowski, and Hult 2015). Research related to the EDT topic was consulted extensively, and keywords emphasizing the theme were included in the syntax were used to draw a meaningful sample from the commonly used Web of Science (WOS) database (Zha, Melewar, Foroudi, and Jin 2020). We followed other bibliometric studies in an attempt to be thorough and included keyword terms such as "artificial intelligence," "augmented reality," "automated technology," "deep learning," "eye-tracking," "machine learning," "neural networks," and "virtual reality" (cf. Samiee, Chabowski, and Hult 2015).2 As is typical in bibliometric studies, the articles included in the database for analysis were retrieved if a syntax keyword was found in the title, abstract, author- supplied keyword, or reference identifiers (Clarivate Analytics 2020; Foroudi, Kitchen, Marvi, Akarsu, and Uddin 2020; Zha et al. 2020). Publications not considered directly applicable to EDT research- such as book reviews, biographical items, editorials, and other non-central research materials - were not included in the sample (Chabowski, Kekec, Morgan, Hult, Walkowiak, and Runnalls 2018; Foroudi et al. 2020; Zha et al. 2020). In all, 280,961 citations from 6,099 articles were gathered across the seven business disciplines (marketing: 18,693 citations in 309 articles; innovation: 13,575 citations in 263 articles; general management and strategy: 10,087 citations in 221 articles; organizational behavior and human resource 2 The precise syntax is available from the authors upon request. For review purposes, the syntax is as follows: (“artificial intelligence” OR “augmented reality” OR “automated technology” OR “automation” OR “avatar” OR “bot” OR “chatbot” OR “cognitive technology” OR “conversational agent” OR “deep learning” OR “digital assistant” OR “e-human” OR “emotional technology” OR “eye-tracking” OR “human intelligence” OR “human- computer interaction” OR “information agent” OR “intelligence agent” OR “intelligent agent” OR “machine learning” OR “mechanical intelligence” OR “natural language processing” OR “neural networks” OR “robot” OR “virtual assistant” OR “virtual reality”). 12 management: 6,484 citations in 104 articles; operations research and management science: 110,676 citations in 2,652 articles; management information systems and knowledge management: 110,899 citations in 2,357 articles; and finance and accounting: 10,547 citations in 193 articles). Following previous studies, a citation analysis of approximately 25 of the most highly cited publications was conducted for each of the seven EDT disciplines under consideration (Ramos-Rodríguez and Ruíz-Navarro 2004). Then, co-citation matrices were developed for use in MDS. As found in bibliometrics, MDS is a suitable method to use with models possessing fewer than 100 plotted items (van Eck et al. 2010). In fact, based on previous applications, such an approach leads to more interpretable and meaningful results (Hair, Black, Babin, Anderson, and Tatham 1998; Foroudi et al. 2020; Zha et al. 2020). Since the data used were co-occurrences between publications in our seven databases, a proximity-based function of MDS called PROXSCAL was applied. The loss function that is minimized in low-dimensional space by PROXSCAL is shown in Equation 1: 𝑚 𝑛 1 (1) ƒ(𝑿1 , … , 𝑿𝑚 ) ≡ ∑ ∑ 𝑤𝑖𝑗𝑘 [𝛿𝑖𝑗𝑘 − 𝑑𝑖𝑗 (𝑿k )]𝟐 𝑚 𝑘=1 i