Technology is rapidly changing the nature of service, customers' service frontline experiences, and customers' relationships with service providers. Based on the prediction that in the marketplace of 2025, technology (e.g., service-providing humanoid robots) will be melded into numerous service experiences, this article spotlights technology's ability to engage customers on a social level as a critical advancement of technology infusions. Specifically, it introduces the novel concept of automated social presence (ASP; i.e., the extent to which technology makes customers feel the presence of another social entity) to the services literature. The authors develop a typology that highlights different combinations of automated and human social presence in organizational frontlines and indicates literature gaps, thereby emphasizing avenues for future research. Moreover, the article presents a conceptual framework that focuses on (a) how the relationship between ASP and several key service and customer outcomes is mediated by social cognition and perceptions of psychological ownership as well as (b) three customer-related factors that moderate the relationship between ASP and social cognition and psychological ownership (i.e., a customer's relationship orientation, tendency to anthropomorphize, and technology readiness). Finally, propositions are presented that can be a catalyst for future work to enhance the understanding of how technology infusion, particularly service robots, influences customers' frontline experiences in the future.Keywords automation, service robots, social cognition, organizational frontlines, psychological ownership Any sufficiently advanced technology is indistinguishable from magic.-Arthur C. Clarke, Profiles of the Future: An Inquiry into the Limits of the Possible Technology continues to radically and rapidly change the nature of service, customers' service experiences, and customers' relationships with service providers (Ostrom et al. 2015;Rust and Huang 2014).1 Consider, for example, the technology advancements of how consumers purchase a meal in some restaurants. Rather than the traditional interaction in which customers wait for staff to serve them, several restaurants (e.g., Chili's) now allow customers to interact with the chefs in the kitchen using tabletop tablets to order their meals (Garber 2014). A restaurant in Ningbo, China, has already replaced humans with robot waiters (Fox News 2014). The robots take orders and speak to customers in simple Mandarin phrases. Their optical sensing systems help them to avoid collisions, and they travel along magnetic strips on the floor, allowing them to move throughout the restaurant. Consistent with the idea that service robots are on the rise, the global market for robots functioning in consumer and office applications is estimated to grow exponentially to US$1.5 billion by 2019, and it is predicted to grow 7 times faster than the market for manufacturing robots (Business Insider 2015).In this new environment, the nature of the interp...

The firm–customer exchange process consists of three key parts: (1) firm-initiated marketing communications, (2) customer buying behavior, and (3) customer product return behavior. To date, the literature in marketing has largely focused on how marketing communications affect customer buying behavior and, to some extent, how past buying behavior affects a firm's decisions to initiate future marketing communications. However, the literature on product returns is sparse, especially in relation to analyzing individual customer product return behavior. Although the magnitude of the value of product returns is known to be high ($100 billion per year), how it affects customer buying behavior is not known because of a lack of data availability and understanding of the role of product returns in the firm–customer exchange process. Given that product returns are considered a hassle for a firm's supply chain management and a drain on overall profitability, it is important to study product return behavior. Thus, the authors empirically demonstrate the role of product returns in the exchange process by determining the exchange process factors that help explain product return behavior and the consequences of product returns on future customer and firm behavior. In addition, the authors demonstrate that product returns are inevitable but by no means evil.

The firm-customer exchange process consists of three key parts: (1) firm-initiated marketing communications, (2) customer buying behavior, and (3) customer product return behavior. To date, the literature in marketing has largely focused on how marketing communications affect customer buying behavior and, to some extent, how past buying behavior affects a firm's decisions to initiate future marketing communications. However, the literature on product returns is sparse, especially in relation to analyzing individual customer product return behavior. Although the magnitude of the value of product returns is known to be high ($100 billion per year), how it affects customer buying behavior is not known because of a lack of data availability and understanding of the role of product returns in the firm-customer exchange process. Given that product returns are considered a hassle for a firm's supply chain management and a drain on overall profitability, it is important to study product return behavior. Thus, the authors empirically demonstrate the role of product returns in the exchange process by determining the exchange process factors that help explain product return behavior and the consequences of product returns on future customer and firm behavior. In addition, the authors demonstrate that product returns are inevitable but by no means evil.

Consumers frequently make important financial decisions that have short- and long-term impacts on their welfare. The authors expect that these financial decisions are a function of consumers' past experiences and interactions with a financial services firm as well as consumers' long-term priorities (e.g., national culture). They determine how three cultural dimensions (long-term orientation, uncertainty avoidance, and masculinity) and marketing communication type (promotion focused vs. prevention focused) affect three key consumer financial decisions: (1) savings rate, (2) use of credit, and (3) spending pattern. To do so, they empirically test both the direct effect of national culture on consumer financial decision making and its moderating effect on the link between a firm's marketing efforts and consumer financial decision making. Drawing on regulatory focus theory, the authors develop and empirically test their hypotheses using a customer database from a multinational financial services firm based in the United Arab Emirates, with customers originating from 34 countries. They find that national culture directly affects consumer financial decision making and moderates the impact of marketing efforts by the financial services firm, which suggests that financial services firms should account for national culture when managing customers.

Many firms are now using referral marketing campaigns to harness the power of word of mouth and to increase referrals to acquire new customers. Prior research has identified a method of computing the value of referrals using only a customer's actual past referral behavior to compute customer referral value (CRV). In this article, the authors develop and test a new four-step approach to compute CRV. In addition, they determine the behavioral drivers of CRV and then identify the most effective methods of targeting the most promising customers on the basis of their customer lifetime value (CLV) and CRV scores. The authors illustrate and test this approach through four separate field experiments with firms from two industries: financial services and retailing. They find that to maximize profitability, it is critical to manage customers in terms of both their CLV and CRV scores and that understanding the behavioral drivers of CRV can help managers better target the most profitable customers with their referral marketing campaigns.