Dynamics of individual actors’ self, social, and task pre-dispositions in multi-actor service ecosystems
Introduction
Value co-creation has received extensive scholarly coverage and has been the fulcrum of investigation and debate for well over a decade (e.g., Prahalad and Ramaswamy, 2004, Vargo and Lusch, 2016). Within this realm, research has aimed to understand value co-creation at the different levels of aggregation in a service ecosystem, that is, at micro, meso, and macro level (Beirão et al., 2017). However, due to the concept of value co-creation being located at a meta-theoretical level, i.e. the highest level of abstraction (Vargo & Lusch, 2017), scholars have drawn on mid-range theorizing to make the concept more “tangible”. As one of the concepts used in combination with mid-range theory (MRT), actor engagement (Brodie et al., 2019) has been established to enable operationalizing and measuring the higher-level general theory. Empirical work assists with shaping and verifying MRT, which in turn can “verify and consolidate general theories [e.g., value co-creation] and refine and expand their scope” (Brodie, Saren, et al., 2011, p. 81), as well as bridge “the high-level conceptual perspective of Service-Dominant Logic with specific empirical findings” (Beirão et al., 2017, p. 227). While early research focused on understanding the dimensions of customer engagement from a dyadic perspective (Brodie, Hollebeek, et al., 2011), later work has broadened the scope and introduced actor engagement as the more encompassing construct (Storbacka et al., 2016). More recently, engagement scholars have turned their attention to a systems perspective to consider other actors in the service ecosystem (Brodie et al., 2019, Sharma et al., 2020). Other researchers have also recognized the importance of multi-actor environments, however utilizing labels, such as multi-actor interaction, and collective or collaborative consumption (e.g., Bruce et al., 2019, Kelleher et al., 2020). Such a surge in interest is surprising considering that multi-actor constellations have long been studied, not only in non-service disciplines (e.g., Freud, 1921, Le Bon, 1896), but also in a value co-creation context (e.g., Finsterwalder & Kuppelwieser, 2011).
In spite of more efforts to understand the service ecosystems perspective (Frow et al., 2019), some scholars have lamented the scarcity of endeavors to comprehend the individual and its influence on value co-creation in such contexts (Koskela-Huotari and Siltaloppi, 2020, Ranjan and Read, 2019). Particularly, actor-related factors as determinants of actor engagement and value co-creation have not received sufficient attention, and “identifying general actor properties of engagement is still in its infancy” (Brodie et al., 2019, p. 178; italics added). Amongst those actor properties, actor disposition, that is, the readiness to integrate resources in service ecosystems, as well as the resulting actor engagement activity, i.e., the observable engagement behavior (Brodie et al., 2019) have been focal points in explicating MRT from a micro-foundational perspective (Raub et al., 2011). Nevertheless, pre-cursors to the mechanisms underlying actor engagement at the micro-foundational level in concert with multi-actor interactions in a service ecosystem have not been researched.
Further, except for a few studies (e.g., Fehrer et al., 2018, Li et al., 2017), actor engagement literature offers virtually no time-based perspective on how such factors could change. These studies focus on the dynamics of actor engagement, that is, on actor disposition and actor engagement activities. However, we found no studies that focus on pre-dispositions taking a longitudinal perspective. Longitudinal studies are essential in understanding how actor properties change or might influence actor engagement activities over an extended period of time (Fehrer et al., 2018). Longitudinal studies can range from a few weeks up to decades and require for the same participants to be observed repeatedly. With our study design explained later we are thus meeting the criteria of a longitudinal study design (Bernhardt et al., 2000, Fehrer et al., 2018, Rindfleisch et al., 2008). This is also where our study adds value to extant literature on value co-creation and related MRT’s micro-foundations of actor engagement, as these imply time-dimensioning (Foss, 2016).
Moreover, relating to providing empirical evidence for MRT (Brodie, Saren, et al., 2011), including constructs and measurements from psychology has been flagged as an overlooked area of investigation in the wider context of value co-creation (Ranjan & Read, 2019). This is despite a long history of conceptualizing and measuring personal pre-dispositions for multi-actor contexts in psychology where items and scales have specifically been developed for such scenarios (e.g., Bass, 1960, Bass, 1962a, Bass, 1962b, Ray, 1973).
In summary, our research answers multiple calls in the literature. From the perspective of the co-creation literature (meta-theoretical level), we respond to the “demand for research that moves from bilateral supplier–customer service–value cocreation to a multi-actor perspective and ecosystem service–value cocreation” (Ostrom et al., 2015, p. 136). Further, we respond to Koskela-Huotari and Siltaloppi’s (2020, pp. 437, 452, italics added) call for more work on how “collectives of individuals (…) produce shared goals and achieve coordinated behaviors [… and how] coordinated action emerges and is maintained within human groups (…). [There is a] need for a more robust conceptualization of humans as actors that adopts a processual, as opposed to a static, view.” Our paper investigates the roots of coordinated behavior from a processual perspective and also resonates with Kelleher et al.’s (2020) work that highlights this as an underexplored area, and with Bruce et al. (2019, p. 173) who give precedence to understanding “how multiple actors combine to create value” and to examine “collective resource integration.”
From a mid-range theoretical perspective and in combination with actor engagement, we address the research gap mentioned above (Brodie et al., 2019) regarding actor properties, as well as Sharma et al.’s (2020) call to “accommodate the role of other members [in] multi-actor service ecosystems in the research on customer engagement and relationships.”
Thus, our paper addresses under-researched issues by a) introducing actor pre-dispositions, which add a novel layer to actor engagement, b) advancing the understanding of multi-actor engagement from a micro-foundational perspective within MRT, c) establishing empirical evidence for these micro-foundations of actor engagement and hence MRT, d) introducing established constructs, dimensions, and measurements from psychology to comprehend individual actors pre-dispositions, and e) exploring a longitudinal and dynamic perspective of actor pre-dispositions and their influence during actor engagement activities.
This article reports a quantitative multistage study by applying the dimensions of actors’ self-, social, and task pre-dispositions from psychology to student group assignment settings at a tertiary education provider. We are cognizant of the fact that the education context may create a power imbalance between service provider (university/instructor) and customers (students) due to the latter being graded by the former (Rayburn, 2015) and this might have influenced findings. We view behavior in assemblages of actors as a function of the actors’ self-, social, and task pre-dispositions (Bass & Dunteman, 1963). Our work highlights actor engagement’s pre-cursors, while avoiding the replication of previous studies, and we shed light on the preceding factors of value co-creation via actor engagement and MRT. Out of scope is a focus on actor dispositions and actor engagement activities already explored elsewhere (Brodie et al., 2019, Fehrer et al., 2018). In other words, our work does not intend to measure actor engagement; rather, we investigate innate attitudes or pre-dispositions that influence how actors engage.
Section snippets
Theorizing approach, conceptual locus, and framing
We employ Brodie and Peters’ (2020) work which expands on the process of theorizing with a focus on integrating general theories (e.g., on value co-creation) and contextual research (e.g., on actor engagement) to advance mid-range theory (MRT). Brodie and Peters (2020) speak of MRT as a kind of theory that bridges the domains of empirical research and general theory. To contribute to such bridging, we focus on establishing micro-foundations of MRT (Raub et al., 2011) concerning actor engagement
Multi-actor assemblages and engagement in service ecosystems
Per definition, systems of service exchange require that actors interact, work together, and integrate their resources to co-create value for themselves and others (Vargo & Lusch, 2016). For example, one actor, such as a customer might have to cooperate with another actor, e.g., a second customer, or might become part of a constellation of actors (Finsterwalder and Tuzovic, 2010, Tombs and McColl-Kennedy, 2003). Regarding actor engagement contexts, Clark et al. (2020) noted that a focal actors’
Individual norms and self-, social, and task pre-disposition of actors
This section explicates an actor’s individual norms and attitudes or pre-dispositions. Our conception is based on the notion of the individual nature of norms, accepting that they are heterogeneous across actors. Individual norms are expectations that actors hold for themselves (Schwartz, 1973). Attitude mediates the relationship between personal norms and behavioral intentions (Kim et al., 2013). Fishbein and Ajzen (1977, p. 6; italics added) define attitude as a “learned predisposition to
Study context embedded in the theoretical framing
Our study traces whether individuals’ pre-dispositions in an actor-to-actor setting are visible in multi-actor service ecosystems where actors interact in groups (Finsterwalder & Kuppelwieser, 2011). We do this by utilizing the three domains of self-, social, and task pre-disposition.1
Method
Measuring participants’ pre-dispositions when they engage in value co-creation processes occurred at an individual level and not at a group level (e.g., Mason & Griffin, 2002). In other words, the study examined how individuals viewed their own pre-dispositions when interacting in a group of actors. We started by identifying previously used scales in measuring dispositions of customer or actor engagement (see Web Appendix D for an overview). A few earlier studies inexplicitly included measures
Results
We adapted all of the survey items from the established reflective measures and adjusted them to fit this study’s research context and had them verified in a pre-study (Web Appendix B). Appendix E shows the items corresponding to the three dimensions. It displays data on individuals’ pre-dispositions influencing behavioral intentions for the group assignments and surveyed before the groups formed. We captured students’ perceptions of their own pre-dispositions during group engagement activity
Discussion
The results show that actors’ pre-disposition in the mini groups throughout the marketing course under investigation change over time (Tuckman, 2001, Tuckman and Jensen, 1977), as viewed through the lens of the individual actors when using self-report measures. While the changes are statistically significant they appear not to be substantial. This allows for two different streams of interpretation.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgment
The authors thank Marko Sarstedt (Otto-von-Guericke-University, Magdeburg, Germany), Fouad Ben Abdelaziz (NEOMA Business School, Rouen, France), Sven Tuzovic (Queensland University of Technology, Brisbane, Australia), and Alastair Tombs (University of Queensland, Brisbane, Australia) for their helpful remarks on prior versions of this manuscript.
Financial Disclosure
Research grants provided by the University of Canterbury, Department of Management, Marketing and Entrepreneurship, and NEOMA Business School, Area of Excellence “The World We Want”, funded this research.
Jörg Finsterwalder is Associate Professor of Marketing in the UC Business School at the University of Canterbury (UC), New Zealand. His work has been published in international journals, such as European Journal of Marketing, Journal of Business Research, Journal of Marketing Management, Journal of Public Policy & Marketing, Journal of Retailing and Consumer Services, Journal of Service Management, Journal of Services Marketing, Journal of Service Theory and Practice, Journal of Strategic
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2023, Journal of Business ResearchCitation Excerpt :However, though the stakeholder perspective of value cocreation is rapidly gaining traction (e.g., Ravazzani, and Hazée, 2022; Siaw and Sarpong, 2021), it remains an emerging field of study due to the complexity of multi-stakeholder encounters and cocreation’s highly abstract, metatheoretical nature (Vargo & Lusch, 2017). To unpack this complexity, scholars are increasingly adopting the stakeholder engagement (SE) concept to operationalize cocreation and make it “more tangible” (Finsterwalder, Kuppelwieser, and Fisk, 2022). To date, only a handful of studies has addressed stakeholders’ engagement within service ecosystems (Ravazzani, and Hazée, 2022; Hollebeek et al., 2022a; Storbacka et al., 2016), exposing a pertinent literature-based gap.
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Jörg Finsterwalder is Associate Professor of Marketing in the UC Business School at the University of Canterbury (UC), New Zealand. His work has been published in international journals, such as European Journal of Marketing, Journal of Business Research, Journal of Marketing Management, Journal of Public Policy & Marketing, Journal of Retailing and Consumer Services, Journal of Service Management, Journal of Services Marketing, Journal of Service Theory and Practice, Journal of Strategic Marketing and Service Industries Journal.
Volker G. Kuppelwieser is a Full Professor in Marketing at the NEOMA Business School (France). His main research interests are service experiences, aging consumers’ behavior, and customer inclusion. He previously held several positions in the service industry and has 12 years’ experience of industry. He has published in journals such as Journal of Service Research, Journal of Services Marketing, Annals of Operations Research, Marketing Letters, Human Relations, Journal of Business Research, Journal of Service Management, and Journal of Retailing and Consumer Services, amongst others. He has also given numerous conference presentations and serves as a reviewer and editorial board member for several marketing and organizational behavior journals.
Raymond P. Fisk is Professor of Marketing at Texas State University. His research focuses on services marketing, service design, and transformative service research. He has published in the Journal of Service Research, Journal of Marketing, Journal of Retailing, Journal of the Academy of Marketing Science, European Journal of Marketing, Journal of Public Policy and Marketing, and others. Ray has published six books including Serving Customers: Global Services Marketing Perspectives. In 1993, he founded the AMA Services Marketing Special Interest Group (SERVSIG). In 2005, Ray received the Career Contributions to the Services Discipline Award from SERVSIG. In 2012, he received the Grönroos Service Research Award from the Hanken School of Economics in Finland. In 2016, the American Marketing Association made him the Inaugural Recipient of the SIG Leadership Award. In 2018, Ray founded ServCollab, which seeks to serve humanity through collaborative service research.