Special issue of the Journal of Service Research.

AI Service and Emotion

Special Issue Editors:
Bagozzi R., Brady M.K., Huang M.N.

Submission Deadline: 15 April 2021.


JSR, the leading service journal, with a 5-year impact factor of 9.211, announces a special issue on AI Service and Emotion. This special issue, likes JSR, is broad and interdisciplinary, and is relevant and timely to important managerial and societal service issues. As AI (artificial intelligence) continues to advance, it plays an ever-increasing role in service. However, people tend to mistake that AI is just about rational thinking; however, recent research reveals that AI in service has important implications for emotions as well.

At the micro-task level, frontline interactions are interaction- and emotion-intensive, requiring HI (human intelligence) to be capable of emotional intelligence, and when AI is used to perform frontline interactions, it either has to have such emotional intelligence or it should compliment HI for such interactions. We have witnessed such a replacement effect during the COVID-19 pandemic, when social distancing is required and AI is used to automate ordering and delivery to avoid human contact (see the JSR call for Frontline-in-Change special issue).

At the macroeconomic level, AI, as thinking machines, has pushed the economy from manufacturing, to thinking service, to feeling service. The feeling service economy is characterized by AI doing the thinking tasks and HI doing the feeling tasks. This has important implications for how the economy should prepare HI for this disruptive change, for example, human workers will need to re-skill to be more feeling and empathetic.

The special issue welcomes submissions from all disciplines with a service interest, such as service management, marketing, strategic management, information systems, economics, engineering, human resources, operations research, computer science, consumer research, psychology, and sociology. The analysis level can be micro, meso, or macro, and the methodology can be conceptual, empirical, or computational. Potential topics include, but are not limited to:
– The Feeling Economy, e.g., the nature, characteristics, composition, timing, transformation mechanism, and consequences of the economy (more equal and inclusive, or less).
– Managing AI, e.g., how firms can transform to become more feeling-oriented, how to apply and manage various AI intelligences for efficiency (productivity) and effectiveness.
– The roles and benefits of AI for emotions in service, e.g., engaging customers in their service journeys, meeting their emotional needs.
– The dark sides of using AI for emotions in service, e.g., increasing loneliness, distancing service interaction and relationships, disengaging customers, and customer rage.
– The collaboration, augmentation, or replacement of AI for HI in service, e.g., what types and levels of HI skills are required (e.g., empathy, authenticity, sincerity), how AI and HI work as a team.
– Data, machine learning, AI and service emotions, e.g., AI for capturing and sensing emotional data, for analyzing, simulating and synthesizing service emotions, and for reacting to emotions in service interactions
– Driving technologies and technological requirements for the Feeling Economy and for service emotions, e.g., what AI can be considered as emotion-aware AI, what is required to develop feeling AI, and what are the technological bottlenecks for emotional AI.

Process and Timeline
Full papers due 15 April 2021.
Papers will undergo no more than two stages of full peer review. After the second round of review, a final decision will be made, to ensure the timeliness of publication. The special issue operates in a tight timeline, and authors should expect quick turnaround for reviews and revisions. The special issue is planned to be published in May 2022 and accepted papers will be published online first.

SI Guest Editors:
– Richard Bagozzi, Dwight F. Benton Professor of Behavioral Science in Management, University of Michigan ([email protected])
– Michael K. Brady, Bob Sasser Professor of Marketing, Florida State University ([email protected])
– Ming-Hui Huang, Distinguished Professor, Department of Information Management, National Taiwan University ([email protected])

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