Special Section in Journal of the Academy of Marketing Science
Empirical Insights on Artificial Intelligence (AI) and Robotics in the Retail and Service Sector: Leveraging AI to Create Value for Consumers, Organizational Frontlines, and Firms
Guest editors: Stephanie M. Noble (University of Tennessee) and Martin Mende (Florida State University)
Submission deadline: 31 January 2021
AI – broadly defined as machines and systems performing tasks that normally require human intelligence (Huang and Rust 2018) – is fundamentally changing the retail and service environment (Davenport, Guha, Grewal, Bressgott, 2020). As the competitive intensity for retail and service organizations continues to increase, some observers have suggested that a retail apocalypse could be on the horizon (Danziger 2017); however, the changing retail and service landscape can also be seen as an opportunity to better serve and delight customers in new and innovative ways with AI and AI-driven robotics. As such, AI’s impact represents both opportunities and challenges for marketers.
AI’s impact will be far-reaching given global estimates of the increasing service sector. For example, the service sector accounts for approximately 80% of the U.S. economy (US Bureau of Labor Statistics 2018), 70% of the U.K., Japan and France’s economy, and 50% of China’s economy (Statista 2017). The service sector includes a wide range of industries including retail trade, transportation, entertainment, health care, hospitality, professional and technical services, and the government. Against this background, there are numerous opportunities for AI to impact not only consumers’ in-store and on-line experiences, but also influence organizational frontlines (e.g., service employees and their interactions with customers), and ultimately firm outcomes.
Consumers’ journeys, which include all touchpoints with organizations (Lemon and Verhoef 2016), have been considerably impacted by AI. For example, while consumers are standing in a grocery store, virtual technology can place them in fields where spices are harvested (Baldwin 2019), smart windows and mirrors in department stores can suggest products to complete (fashion) outfits or send products directly to their homes, and ‘grab and go’ checkout options in convenience stores allow frictionless shopping experiences. Embodied robots now roam stores taking inventory and answering consumer questions (Barker 2018; Grosman 2017), serve food (ET Retail 2019), and assist in health care (Soon 2019). Other examples of AI-powered technologies include disembodied robots, avatars, virtual bots, touch screen kiosks, and narrowcasting (see Grewal, Noble, Roggeveen and Nordfält, 2020, and Huang and Rust 2018). This list is not exhaustive, but illustrates the varied ways in which AI is changing how consumers interact with organizations.
Organizational frontlines, or the interfaces and interactions that link organizations with their customers (Singh, Brady, Arnold, and Brown 2017) are also influenced by AI. For example, van Doorn et al. (2017) provide numerous examples in the healthcare industry for how AI-powered robots and avatars might assist doctors (i.e., frontline employees – FLEs). On the other hand, Huang and Rust (2018) review instances when FLEs can be replaced by AI, such as with touch screen kiosks or virtual bots that provide customer support, and Mende et al. (2019) illustrate the discomfort and threats to human identity that customers might perceive when interacting with AI-driven humanoid robots. These examples further highlight the realms of positive and negative possibilities with AI in retailing and service environments.
In this special section of the Journal of the Academy of Marketing Science (JAMS), we will publish papers that help retailers and service organizations understand how AI and AI-driven robotics can be leveraged to affect consumers’ journeys, organizational frontlines, and other relevant firm outcomes. Empirical research is a crucial component of the development of marketing theory. Therefore, we are primarily interested in empirical work, both qualitative and quantitative, that explores topics in these domains. We encourage collaborative work between scholars and managers/companies and data from diverse sources including secondary data, lab and field experiments, performance-related data, ethnographic work, etc. Because data-collection is one essential element of empirical work, we also believe that assessing strengths and weaknesses of certain data collection approaches in the context of AI related to marketing purposes can enrich the marketing literature. Furthermore, marketing scholars also could consider whether AI brings with it novel and different types of questions and challenges, which might require different empirical approaches to provide meaningful answers. Finally, we believe that the empirical study of AI and robotics in retail and service settings, given the nascent nature of this research in marketing, provides strong opportunities for cross-disciplinary research.
Possible topics include the following (this list is not exhaustive and other topics are welcomed):
– Investigating Nuanced Effects of AI: Under what circumstances does AI lead to positive outcomes versus negative outcomes for consumers, organizational frontlines, or the firm? Are there boundary conditions that alter these outcomes (i.e., how, where, and why would un/desirable outcomes emerge)? What are specific types/categories of benefits firms can leverage with AI? Are there international/transnational insights related to using AI (e.g., related to culture or legal frameworks)? Are there service-/sector-specific findings related to AI?
– Ethical Issues: What are areas of ethical concerns or promises related to AI? How can organizations or consumers reduce AI threats to ethics / consumer well-being?
– Embodiment and AI: Many AI applications are embedded in an embodied robot (broadly defined). What forms, shapes, or configurations yield (un)desirable outcomes? Why might this be?
What are boundary conditions (e.g., might these effects depend on the focal consumer, task, or service sector)?
– AI and the Marketing Mix: How does AI interact with other levers of the 4Ps of Marketing or the 7Ps of Service? When and why can AI support or undermine other tools in the marketing mix?
– General Challenges and Opportunities: What are drivers/barriers related to adoption of AI (by companies and consumers)? Might they vary across sectors/industries? Which new marketing jobs/tasks are associated with AI? What is the impact on customers, firms, and/or employees?
Submission Guidelines and Deadlines
Papers targeting the special section should be submitted through the JAMS submission system, and will undergo a similar review process as regularly submitted papers. Submissions for the special section begin December 1, 2020 with the final deadline for submissions being January 31, 2021. Questions pertaining to the special section should be submitted to the JAMS Editorial Office or directed to one of the special issue editors: Stephanie Noble ([email protected]) and Martin Mende ([email protected]).
Baldwin, Caroline (2019). #NRF2019: AR and VR is “The Icing On The Cake”.
Barker, J. (2018). More Robots To Hit the Aisles at Schnucks Grocery Stores in St. Louis Area.
Danziger, Pamela N. (2017). Retail Apocalypse: A Look At What Comes Next and It Isn’t Pretty.
Davenport, Thomas, Abhijit Guha, Dhruv Grewal, Timna Bressgott (2020), How Artificial Intelligences Will Change the Future of Marketing, Journal of the Academy of Marketing Science, 48 (1), 24-42.
ET Retail (2019), Robots Restaurant Comes to Bengaluru.
Grewal, Dhruv, Stephanie M. Noble, Anne Roggeveen and Jens Nordfält (2020), “The Future of In-Store Technology,” Journal of the Academy of Marketing Science, 48 (1), 96-113.
Grosman, L. (2017). The Future of Retail: How We’ll Be Shopping in 10 Years.
Huang, Ming-Hui and Roland T. Rust (2018), “Artificial Intelligence in Service,” Journal of Service Research, 21 (2), 155-172.
Lemon, Katherine N. and Peter C. Verhoef (2016), “Understanding Customer Experience Throughout the Customer Journey,” Journal of Marketing, 80 (6), 69-96.
Mende, Martin, Maura L. Scott, Jenny van Doorn, Dhruv Grewal, and Illana Shanks (2019), “Service Robots Rising: How Humanoid Robots Influence Service Experiences and Elicit Compensatory Consumer Responses,” Journal of Marketing Research, 56(4), 535-556.
Singh, Jagdip, Michael Brady, Todd Arnold and Tom Brown (2017), “The Emergent Field of Organizational Frontlines,” Journal of Service Research, 20 (1), 3-11.
Soon, Stella (2019), Robots Can Help Doctors Perform Heart Surgery Remotely.
US Bureau of Labor Statistics (2018)
van Doorn, Jenny, Martin Mende, Stephanie M. 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.
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