Guest article by Martin Mende, recipient of the 2017 SERVSIG Emerging Service Scholar Award
It is a tremendous privilege for me share some brief thoughts on one of my growing areas of research passion with our wonderful SERVSIG community—Thank You Werner and SERVSIG! With that said, I’d like to share…
Three (and a Half) Reasons Why Service Scholars Should Study Service Robots
Reason 1: The train has already left the station! The notion of service robots is not as futuristic as it might seem. Indeed, service robots have been a prominent topic of study in the field of engineering and computer science for nearly three decades. However, due to decreasing costs and advanced computational capabilities, we will increasingly see artificial intelligence and service robots enter the marketplace. Some robots are already hard at work. For example, in Asia, Pizza Hut is rolling out robot waiters to take orders and interact with customers (Curtis 2016). In the United States, Softbank’s ‘Pepper’ recently worked in a restaurant at the Oakland Airport, serving as a restaurant host and offering food recommendations (Heater 2017). Related to the rise of service robots, researchers at Oxford University have predicted that some service professions face up to a 90% chance of being fully replaced by automation within two decades (Frey and Osborn 2013). In short, the emergence of service robots is likely to be among the most dramatic evolutions in the service realm; and it is already underway! Luckily, service scholars are well-equipped to contribute to the scientific discussion of service robots, as illustrated next.
Reason 2: Service scholars have unique expertise to offer! As service robots enter the marketplace, it is noteworthy that the majority of empirical research on robots to date has been generated by scholars in the fields of engineering and computer science rather than service scholars. Yet, service scholars can contribute valuable insights to this (hopefully multi-disciplinary) discussion. Engineers and computer scientists typically do not examine commercial service settings. In other words, prior research on robots has examined how people interact with robots; as service scholars, one of our core competencies could be the study of how customers respond to and interact with robots. This terminological distinction is meaningful because many robots will serve customers, and as prior research has demonstrated, commercial contexts create distinct norms, which lay on top of broader social relationship norms and ultimately influence consumer attitudes and behavior (Aggarwal 2004). In other words, service scholars seamlessly adopt the company perspective (i.e., how firms can leverage their robotic resources), emphasize the role of users as customers, and offer insight into the psychology related to the consumption experience. For example, we could focus on one of our core areas of expertise: coproduction. That is, as service scholars we have a unique understanding of the antecedents and consequences of service coproduction processes and we study coproduction with a deliberate focus on designing and managing positive customer experiences (e.g., Lemon and Verhoef 2017). This expertise could be helpful in examining how customers coproduce with robots in commercial settings and how customer desires, preferences, needs, and responses toward service robots might be different from what prior findings in the robotics literature suggest. Moreover, this expertise could also be a fertile platform for collaborations between scholars and practitioners, because companies strive to understand how to best engage customers through service robots to stay competitive. In parallel, it is inspiring to think about research on how service robots can not only fulfill organizational goals but also contribute to human well-being.
Reason 3: Research opportunities abound—consider service robots and TSR! Despite its increasing relevance and fruition, more work is needed on transformative service research (TSR), which is concerned with “the integration of consumer and service research that centers on creating uplifting changes and improvements in the well-being of consumer entities: individuals (consumers and employees), communities and ecosystems” (Anderson et al. 2011, p. 3; see also Mick 2006).
Even a brief consideration of a major area of TSR, health care, suggests that service robots will affect multiple entities. As mentioned before, on the customer level, questions arise related to customer-robot coproduction (for a more expansive discussion of these research challenges, see van Doorn et al. 2017). Especially because robots will increasingly be designed to resemble a social presence, customer-robot encounters point to a new set of research issues (e.g., how would these encounters alter customer experiences, behaviors, and outcomes?). With regard to service employees, we should examine how frontline staff members experience and respond to the emergence of their automated robotic co-workers (e.g., job satisfaction).
Service robots will also affect the broader service system. For instance, robots might serve customers (e.g., patients) as agents of multiple service-providing entities (e.g., clinics/hospitals and insurance companies). Such service system configurations result in novel issues; for example, robots might collect data on patients’ facial expressions as indicators of their emotional states and biophysical data (e.g., blood pressure, heart rate, hormonal levels). Although such data offer clear benefits (e.g., preventative treatment), this data collection can have dark sides (e.g., how accurate and reliable is the robots’ data collection, who owns these data, what may they be used for?) (see van Doorn et al. 2017). Many more intriguing questions come to mind that need be researched and service scholars can and should contribute to this scientific discovery!
The ‘Half’ Reason: It’s FUN! I find reading the robotics literature exhilarating and my interest in service robots has led me to some amazing collaborations. Of course, we all have our favorite topics and that is one of the most wonderful aspects of this fantastic profession: we have the privilege of choosing which aspects of the ever-changing service world we investigate. In this spirit, I hope to have fruitful robot-related conversations with many of you but I also – and most importantly – wish all of you lots of fun with whatever research you choose
P.S. For those who are curious to learn more: Please consider attending SERVSIG’s Special Session at Winter AMA 2018 on “Artificial Intelligence and Service”.
Photo by Alex Knight on Unsplash
References
Aggarwal, Pankaj (2004), “The Effects of Brand Relationship Norms on Consumer Attitudes and Behavior,” Journal of Consumer Research, 31 (1), 87-101.
Anderson, Laurel, Amy L. Ostrom, Mary Jo Bitner, Canan Corus, Raymond P. Fisk, Andrew S. Gallan, et al. (2013), “Transformative Service Research: An Agenda for the Future,” Journal of Business Research, 66 (8), 1203–1210.
Curtis, Sophie (2016), “Pizza Hut Hires Robot Waiters to Take Orders and Process Payments at its Fast-Food Restaurants,” The Mirror, [http://www.mirror.co.uk/tech/pizza-hut-hires-robot-waiters-8045172 ].
Doorn van, Jenny, Martin Mende, Stephanie Noble, John Hulland, Dhruv Grewal, Amy Ostrom, and Andrew Petersen (2017), “Domo Arigato Mr. Roboto: How Technology Could Change the Service Customer Experience of the Future – A Research Vision and Agenda”, Journal of Service Research, 20 (1), 43-58.
Heater, Brian (2017), “Pepper the Robot Gets a Gig at the Oakland Airport,” [https://techcrunch.com/2017/01/25/pepper-robot].
Frey, Carl Benedikt, and Michael A. Osborne (2013), “The Future of Employment: How Susceptible Are Jobs to Computerization,” working paper, Oxford Martin School, University of Oxford, UK.
Mick, David G. (2006), “Meaning and Mattering through Transformative Consumer Research,” Advances in Consumer Research 33 (1), 1-4.
Lemon, Katherine N. and Peter C. Verhoef (2016), “Understanding Customer Experience throughout the Customer Journey,” Journal of Marketing, AMA/MSI Special Issue, 80 (November), 69–96.
