Numerous forms of customer engagement behaviors (CEBs) have surfaced, highlighting the need for finding common conceptual ground to explore different CEBs. From a resource-based perspective, this paper presents a typology of CEBs that is derived conceptually and a framework that expounds on how customers develop perceptions of engagement value that shape their likelihood to perform different types of CEBs. More specifically, their perceptions of benefits, costs, and risks differ in affecting perceived customer engagement value (CEV) and subsequent intention to perform CEBs. We also examine two boundary conditions based on the attributes of resources. The paper concludes with managerial implications and future research opportunities, encouraging practitioners to consider how firms can utilize customer resources effectively and what resources they can provide to foster and stimulate CEBs.

More than 50 million consumers participate in online group buying, hence its importance to retailers cannot be ignored. Four studies are conducted to determine (a) whether customers' preferences to participate in group buying relative to buying alone are more in the case of experiential (vs. material) purchases; (b) underlying psychological mechanisms affecting an individual's willingness to invite additional buyers; and (c) the moderating role of analytic versus holistic thinking orientation within the mediational framework. Consistent with expectations, preferences to invite additional buyers to receive a further discount (vs. buying alone and taking the deal-of-the-day) were greater for experiential purchases than material purchases. Three psychological motivators, namely social relatedness, conversational value, and anticipatory enjoyment, act as parallel mediators. Finally, moderated-mediation analysis shows holistic thinking accentuates the mediational pathway of anticipatory enjoyment but not for social relatedness, whereas analytical thinking accentuates the mediational pathway of conversational value. Of practical relevance to those designing group buying websites is that offering an additional discount to buyers if they are willing to expend the effort to form a larger group not only reduced the number of individuals indicating that they would not make a purchase at all, but about a quarter of respondents indicated that they would endeavor to find additional buyers. In addition, there is a clear preference for experiential goods; and for material goods, the findings suggest drawing attention to the experiences that material goods offer.

Political uncertainty generates non-trivial costs for business, resulting in suboptimal decision-making and suppression of economic activity. Managing political uncertainty and attaining greater accuracy in risk analysis of a country's political environment remain a challenge. Our research attempts to fill this gap by re-directing scholarly attention from the questions of what and why to how political uncertainty and political risks can be identified and assessed by (1) offering a process-based theoretical framework of a country's political environment that explicitly incorporates its dynamic structure; and (2) proposing a new methodological framework based on DFA to empirically estimate it. We demonstrate how DFA enables evaluating the country's political environment, in terms of: (1) complexity of the political environment, (2) potency (or importance) of the dimensions of the political environment; (3) stability of the political environment, and (4) nomological validity of the model. To demonstrate the application of this methodology, we analyze Brazil's political environment for the period 1984–2018 using monthly political risk time-series data. The paper then maps Brazil's political environment using political science scholarship with our empirical results triangulating the insights. The final section discusses contributions to research on political risk in IB as well as the methodological challenges and opportunities of using DFA.

Political uncertainty generates non-trivial costs for business, resulting in suboptimal decision-making and suppression of economic activity. Decreasing political uncertainty and attaining greater accuracy in risk analysis of a country’s political environment remain a challenge. Our research attempts to fill this gap by: (1) re-directing scholarly attention from the questions of what and why to how political uncertainty and risks can be identified and assessed by (1) offering a process-based theoretical framework of a country’s political environment; and (2) proposing a new methodological framework based on Dynamic Factor Analysis (DFA) to estimate the dynamic structure of a country’s political environment. To demonstrate the application of this methodology, we analyze Brazil’s political environment for the period 1984-2018 using monthly political risk time-series data. Specifically, we demonstrate how the results of the DFA methodology allow us in evaluating the characteristics of the country’s political environment, in terms of: (1) complexity of the political environment, (2) potency (or importance) of the drivers and dimensions of political environment; (3) stability of political environment, and (4) nomological validity of the model. The paper ends by mapping Brazil’s historical political environment with our empirical results and focusing on the methodological challenges and opportunities of using DFA.

In Chapter 2, we map the evolution of customer relationship marketing (CRM) and chronicle its shifting emphasis from one of value distribution and independence, i.e., short-term competition and conflict, to value (co)creation and interdependence, i.e., long-term mutual cooperation. Over the years, the foundational premises and axioms of relationship marketing (RM) have both broadened and deepened, intersecting with allied marketing concepts including service-dominant (S-D) logic, customer-centric marketing, customer-as-assets thinking, and customer experience and engagement models.Although the earliest concept of relationship marketing dates back to the pre-industrial era, we examine its lifecycle stages of adoption, development, and expansion in B2C marketing over the last three decades. Several theories, models, and frameworks, both classic and contemporary that explain antecedents, processes, and outcomes of customer relationships with companies are briefly discussed. In particular, we discuss the following models and frameworks:buyer–seller model (Dwyer et al., 1987);trust–commitment model (Morgan and Hunt,1994);S-D logic (Vargo and Lusch, 2004);interpersonal RM (B2C) model (Palmatier, 2007a);interfirm RM (B2B) model (Palmatier, 2008);reverse logic framework (RLF) of relationship marketing (Kumar et al., 2009);customer engagement behavior (CEB) model (Van Doorn et al., 2010);customer engagement marketing theory (Harmeling et al., 2017);customer experience model (Lemon and Verhoef, 2016); andcustomer valuation model (Kumar, 2018).At the end of the chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of CRM initiatives, we provide some real-life vignettes.

In Chapter 11, we discuss several important research directions that are promising as a result of big data revolution, availability of computing power, and emerging models of estimating customer lifetime value (CLV), both transaction/engagement-based B2C activities. We also discuss some unintended consequences (dark side) of customer–brand relationships including forms of dis-identification and privacy related issues. In particular, we provide a discussion on the role of ethics in general, and normative ethics in particular, in building customer relationship marketing (CRM). Finally, we provide a brief discussion on some challenges and research opportunities facing B2B relationship marketing. At the end of the chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of CRM and future research trends, we provide some real-life vignettes.

In Chapter 5, we first provide a stakeholder-based framework that examines the criteria, pillars, and dimensions of relationship quality for employees and customers. Our stakeholder framework is consistent with established theoretical perspectives on organizations. In advancing this framework, we intersect the multiple views of stakeholder management and relationship quality. We argue that effective management of relationships is a function of understanding the appropriate stakeholder relationship criteria (i.e., descriptive, instrumental, and normative) for each stakeholder type (i.e., employees and customers) and how these influence the foundational pillars of relationship quality and, consequently, the dimensions of relationship quality. Next, we discuss employee–customer engagement theories, particularly the service-profit chain (SPC) paradigm, a set of moderating factors, and finally employee–customer engagement strategies. At the end of the chapter, we provide key takeaways and conclude with HBS and Ivey cases. But first, to give a flavor of customer relationship marketing (CRM) employee–customer relationship and engagement strategies, we provide some real-life vignettes.

In Chapter 1, we provide a formal definition of marketing followed by several definitions of relationship marketing highlighting the key aspects of this concept. Customer relationship marketing (CRM) opportunities are embedded in the entire customer journey spanning several touch points across all stages including prepurchase, purchase, and postpurchase stage. Customer relationship marketing evolved from a traditional marketing concept and has broadened its scope today, intersecting with the following domains, namely customer buying behavior process models, customer satisfaction and loyalty, service quality, customer relationship management tools and strategies, customer centricity, and customer engagement activities. In this chapter, we present a structure of how the book is organized and provide a brief summary of the contents broken down by chapters (Chapters 2 to 11). At the end of each chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of CRM, we provide some real-life vignettes.

Online retailers provide social selling cues, such as “39 customers bought this product” or “156 customers viewed our product per hour”, to encourage sales. Revealing the numbers bought has been shown to increase purchase intentions, but what remains unexplored are the ramifications of posting the number of brand-related views or revealing both numbers bought and viewed so customers can determine the views-to-bought ratio. The number of views is much higher than the numbers bought, which customers may anchor on as a signal for product quality; however, a countervailing force is that views are a more ambiguous, hence a less diagnostic, cue. Five experiments revealed that: (1) showing the number of views or bought can, but does not always, increase purchase intentions; (2) revealing the number bought has a monotonically increasing (at diminishing rate) effect on purchase intentions; and (3) views exhibit a concave curvilinear effect in that, beyond a tipping point, increasing the number of views lowers purchase intentions. Given the anchoring effect of the larger views number, if the number of views or the number bought are relatively low, it is better to show the larger views number, but the reverse is true if the respective numbers are both high. Additional insights reveal that it is only advantageous to reveal both numbers if the views-to-bought ratio is lower than 20:1, which would apply to about the top 25% of brand landing pages. These findings were further validated in a choice experiment. Perceptions of product quality mediate the relationship between these social selling cues and purchase intentions; however, this is not the case for perceived skepticism (lack of trust in the information). Revealing these social selling cues is an online retailer’s prerogative; hence, these insights are theoretically interesting and have practical relevance.

In Chapter 1, we provide a formal definition of marketing followed by several definitions of relationship marketing highlighting the key aspects of this concept. Customer relationship marketing (CRM) opportunities are embedded in the entire customer journey spanning several touch points across all stages including prepurchase, purchase, and postpurchase stage. Customer relationship marketing evolved from a traditional marketing concept and has broadened its scope today, intersecting with the following domains, namely customer buying behavior process models, customer satisfaction and loyalty, service quality, customer relationship management tools and strategies, customer centricity, and customer engagement activities. In this chapter, we present a structure of how the book is organized and provide a brief summary of the contents broken down by chapters (Chapters 2 to 11). At the end of each chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of CRM, we provide some real-life vignettes.

In Chapter 6, first we discuss customer relationship marketing (CRM)-based analytical models, both for purchase and non-purchase customer behavior. Various models are discussed including traditional metrics such as recency–frequency–monetary value (RFM) model, share of wallet (SOW) model, and past customer value (PCV) model, as well as contemporary models based on customer lifetime value (CLV) concepts. CLV is an advanced forward-looking metric and several variations of the family of CLV models are briefly discussed, including model formulation, estimation, and key merits and demerits. Next, we provide models for customer engagement including customer referral value (CRV), customer influence value (CIV), and customer knowledge value (CKV). Finally, we discuss strategies for maximizing CLV, segmentation strategies, extending CLV to customer engagement value, and linking customer equity to shareholder value. At the end of the chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of CRM analytical models, we provide some real-life vignettes.

In Chapter 10, we examine the intricate relationship between digital and social media marketing and customer–brand relationship. First, we discuss how digital technologies are changing marketing strategies by way of search engine advertising, mobile marketing, and the Internet of Things (IoT), followed by a framework of digital marketing that links the five ‘C’s: (1) customers, (2) collaborators, (3) competitors, (4) context, and the (5) company. The next part of this chapter relates to social media marketing and relationship marketing. We discuss social media marketing followed by two frameworks of social media: (1) contingency framework of social commerce and (2) the functional blocks framework. We then discuss and provide an assessment of the critical issues in the implementation of social media marketing. In particular, we discuss seven functions: (1) identity function, (2) conversation function, (3) sharing function, (4) presence function, (5) relationship function, (6) reputation function, and (7) group function. Finally, we summarize the seven steps to social media success for firms (Kumar and Mirchandani, 2012). At the end of the chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of customer relationship marketing (CRM) in an age of digital technologies and social media, we provide some real-life vignettes.

In Chapter 4, first we discuss how firms build and sustain customer relationships by stimulating customer purchase behavior via loyalty programs. Loyalty programs often tap into multiple psychological and social processes simultaneously. Here we discuss four motivational mechanisms including (1) instrumental benefits, (2) symbolic benefits, (3) emotional benefits, and (4) cognitive benefits. Next we discuss how firms build and sustain customer relationships by stimulating customer non-purchase behavior via engagement strategies. Specifically, we discuss the concept of customer engagement (CE), provide a framework of customer engagement, and then discuss customer engagement behaviors (CEBs). Similar to purchase behavior, non-purchase engagement behaviors are also motivated by several underlying psychological mechanisms including relationship-based motivation, identification-based motivation, justice-based motivation, goal-based motivation, and control-based motivation. Finally, we discuss how customers engage in customizing firm level marketing-mix strategies. At the end of this chapter, we provide key takeaways and conclude with discussion questions and HBS and Ivey cases. But first, to give a flavor of customer relationship marketing (CRM) purchase and non-purchase-related initiatives, we provide some real-life vignettes.

The ways in which emergent technologies are disrupting retailing are manifold. The Internet, social media, mobile technologies, augmented reality, artificial intelligence, robotics, and natural user interfaces all combine to grant consumers access to more information and channels than ever before, through virtually seamless connections with retailers, competitors, and other consumers. The resulting transformations, due to such technologies, thus are widespread, affecting retail marketplaces, the retailing industry, retail real estate, and consumers' behaviors in terms of where and how they shop for products and services. In response to these changing circumstances, retailers develop innovative strategies and new business models in their efforts to enter, expand, and defend their markets. This special issue offers some insights, with the objective of motivating researchers to undertake in-depth investigations of the effects of new, emergent technologies, on both retailers and evolving consumer behaviors.

Organizational reputation is a strategic asset leading to numerous firm-level benefits. Yet, the translation of favorable reputation into valuable organizational outcomes in global markets depends on whether national (vs. individual) culture is modeled. We provide a framework of customer-based ‘organizational reputation’ comprising three distinct reputational facets: product & service efficacy, market prominence, and societal ethicality, with organizational character forming a higher-order ‘halo effect’. Individual (vs. national) culture plays a significant moderating role in translating reputation into customer-specific outcomes and these insights have implications on how MNEs can form and leverage their reputation in global markets.

To succeed in the complex and fast-changing marketplace nowadays, firms must not only exploit existing marketing knowledge and practices but also explore new ones; that is, firms must incorporate ambidexterity into their marketing functions (Day 2011). Through the simultaneous pursuit of exploitation and exploration across marketing programs, firms would be able to identify and seize market opportunities to a greater extent, resulting in higher performance. However, studies examining the link between marketing ambidexterity (MA) and firm performance are scarce, and limitations in these studies restrict our understanding of this complex relationship. This study aims to contribute to the marketing literature in several ways. First, we refine the conceptualization of MA as the marketing function’s bilateral focus with equal attention paid to marketing exploitation and marketing exploration respectively. Empirically, MA is operationalized as convergent levels of exploitation and exploration across major marketing actions, including product design, promotion, segmentation and targeting, pricing, and customer service. Then, we examine the nature of the relationship between MA and firm performance in terms of sales growth. Second, this study examines how the firm’s AC moderates the relationship between MA and sales growth. Since one salient aspect of AC is the capability of integrating internal and external knowledge (Cohen and Levinthal 1990; Rothaermel and Alexandre 2008), AC plays a crucial role in resolving the trade-offs between the inward-focused exploitation and the outward-focused exploration. In addition, it is likely that firms that possess strong AC are vigilant to emergent market opportunities and proactive in seizing those opportunities through the use of market-related knowledge stored in organizational knowledge repository (Vorhies et al. 2011). Therefore, AC possibly affects the extent to which firms can benefit from embracing MA. Examining the interplay between MA and AC, the present study shows their complementarity in creating market offerings that induce greater customer demand, resulting in higher sales. Analyzing a unique dataset that combines survey and archival financial data from 318 private firms, this study finds that MA is positively associated with sales growth for firms with relatively strong AC. This relationship becomes negative for firms with weak AC. Results are robust when the additive and multiplicative terms of exploitation and exploration are controlled for. The findings underscore the critical role of organizational knowledge processing in ensuring that firms can benefit from the pursuit of MA.