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Despite the significant strides made in the customer engagement literature, the need to understand any marketing actor's engagement (vs. merely the customer's) is increasingly recognized. Therefore, the budding actor engagement (AE) concept, which is commonly grounded in S-D logic, describes any marketing actor's engagement, including that of customers, firms, employees, suppliers, and so on. However, while S-D logic-informed AE offers important insight into actors' mutual value creation, it largely overlooks the sociopolitical notions that (a) actors' potentially diverging goals may see them act against (vs. pro) focal others' interests and (b) different actors may extract differing levels of value from interactions, as advanced in stakeholder theory. Based on these gaps, we extend existing AE research by developing integrative stakeholder theory/S-D logic-informed stakeholder engagement (SE). We deduce five core SE tenets, from which we conceptualize SE as a stakeholder's state-based, boundedly volitional resource endowment in his/her role-related interactions, activities, and/or relationships. We conclude this article by discussing important implications that arise from our analyses and by identifying avenues for further research.

Artificial intelligence (AI) is likely to spawn revolutionary transformational effects on service organizations, including by impacting the ways in which firms engage with their customers. In parallel, customer engagement (CE), which reflects customer interactions with brands, offerings, or firms, has risen to the top of many managers' strategic wish lists in the last decade. However, despite literature-based advances made in both areas, AI and CE are largely investigated in isolation to date, yielding a paucity of insight into their interface. In response to this gap, this Special Issue offers a pioneering exploration of CE in automated or AI-based service interactions. Our editorial first reviews AI's Industry 4.0 underpinnings, followed by an important AI typology that comprises robotic process automation (RPA), machine learning (ML), and deep learning (DL) applications. We then offer a high-level synopsis of existing CE research, followed by the development of a set of integrative propositions of CE in automated service interactions. Next, we introduce the Special Issue papers, which feature particular RPA, ML, or DL applications. We conclude with an overview of further research avenues in this growing area, which has the potential to develop into a powerful service research substream in the coming years.

In today's highly dynamic and interactive business environment, the role of "customer engagement" (CE) in cocreating customer experience and value is receiving increasing attention from business practitioners and academics alike. Despite this interest, systematic scholarly inquiry into the concept and its conceptual distinctiveness from other, associated relational concepts has been limited to date. This article explores the theoretical foundations of CE by drawing on relationship marketing theory and the service-dominant (S-D) logic. The analysis also examines the use of the term "engagement" in the social science, management, and marketing academic literatures, as well as in specific business practice applications. Five fundamental propositions (FPs) derived from this analysis are used to develop a general definition of CE, and distinguish the concept from other relational concepts, including "participation" and "involvement." The five propositions are used in the development of a framework for future research, the undertaking of which would facilitate the subsequent refinement of the conceptual domain of CE. Overall, CE, based on its relational foundations of interactive experience and the cocreation of value, is shown to represent an important concept for research in marketing and service management.

PurposeThis study investigates the mediating role of consumer engagement (CE) in the relationship between perceived behavioral control (PBC) and purchase intent and the moderating role of perceived safety in the relationship between PBC and CE in the self-driving car (SDC) context.Design/methodology/approachTo test the model, a sample of 368 consumers was deployed using partial least-squares structural equation modeling (PLS-SEM).FindingsThe findings reveal that consumers' SDC engagement mediates the relationship between PBC and their intent to purchase an SDC. Consumer-perceived SDC safety also moderates the association of PBC/engagement.Originality/valueWhile prior research has examined consumer-based drivers of SDC adoption, understanding of consumers' SDC engagement-related dynamics and outcomes lags behind. Addressing this gap, we propose and test a model that explores consumers' SDC engagement vis-à-vis its drivers (perceived SDC safety/behavioral control) and outcomes (SDC purchase intent).

AbstractWhile insight into consumer brand engagement, experience, and identification is rapidly developing, little remains known regarding the association of these, and related, concepts, as therefore explored in this article. Drawing on social identity theory and service‐dominant‐logic, this study develops and tests a model that explores the effect of customers' brand credibility, ‐value congruence, and ‐experience on their brand identification, and its subsequent effect on their brand advocacy, ‐attachment, and ‐loyalty. We also examine the potentially moderating role of consumers' engagement in affecting these relationships. To explore these issues, we collected tourist‐based survey data. To analyze the data, we used confirmatory factor analysis, followed by structural equation modeling. The findings reveal that brand value congruence, credibility, and experience exercise significant positive effects on customers' brand identification, which, in turn, impact their brand advocacy, attachment, and loyalty. Further, brand engagement is shown to moderate the association of these factors. We conclude by outlining key theoretical/practical implications that arise from this research.

Resource integration, as it relates to value creation, has recently been a key aspect of the discussions about service-dominant (S-D) logic. However, the majority of research pays relatively little explicit attention to the process of theorizing and the epistomological and ontological assumptions upon which the theorizing process is based. This article addresses these issues. The processes that relate to theorizing and developing strong theory are discussed. We then examine how to conceptualize 'resources' and 'resource integration' following differing ontological and epistemological assumptions that guide the theorizing process. Research recommendations to help navigate through the finer details underlying the theorizing process and to advance a general theory of resource integration are developed.