Service Robot Morality in Customer–Robot Interactions: A Mixed-Methods Study

The increasing human–robot interactions across service domains require an examination of their moral challenges, particularly from the user’s perspective. This study explores how efficiency and morality intersect in deploying service robots during the customer encounter. Utilizing a mixed-methods approach, we examine behavioral and attitudinal customer responses to service robot morality. In a field study, we uncover a tradeoff between efficiency-oriented and moral robots, varying based on product involvement (Study 1). Customers prefer moral robots for high-involvement products and efficiency-oriented robots for low-involvement products. In a subsequent laboratory study (Study 2), we focus on a high-involvement retail scenario to elucidate the underlying mechanisms of customer responses to moral service robots. We demonstrate that experienced robot morality benefits relational interactions by increasing customer trust. However, in transactional interactions where customers prioritize robot functionality, experienced robot morality can lead to drawbacks. By demonstrating the inadequacy of a one-size-fits-all approach to robot morality, we underscore the importance of adopting a customer-centric design for moral service robots and show that the effectiveness of their placement depends largely on the type of service encounter. These results can serve to guide managers and robot designers toward aligning robot morality with customer demands, facilitating positive human–robot interactions.

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Publication Details

Journal
ACM Transactions on Human-Robot Interaction
Published
2024-11-27
DOI
https://doi.org/10.1145/3706067
Citations
3
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.04
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article

Service Robot Morality in Customer–Robot Interactions: A Mixed-Methods Study

Tuure Tuunanen, Ruth Stock‐Homburg, Mona Mareen Kegel
3 citations
ACM Transactions on Human-Robot Interaction
AI in Service Interactions
1.04
article

Service Robot Morality in Customer–Robot Interactions: A Mixed-Methods Study

Tuure Tuunanen, Ruth Stock‐Homburg, Mona Mareen Kegel
article en
3 citations

Abstract

The increasing human–robot interactions across service domains require an examination of their moral challenges, particularly from the user’s perspective. This study explores how efficiency and morality intersect in deploying service robots during the customer encounter. Utilizing a mixed-methods approach, we examine behavioral and attitudinal customer responses to service robot morality. In a field study, we uncover a tradeoff between efficiency-oriented and moral robots, varying based on product involvement (Study 1). Customers prefer moral robots for high-involvement products and efficiency-oriented robots for low-involvement products. In a subsequent laboratory study (Study 2), we focus on a high-involvement retail scenario to elucidate the underlying mechanisms of customer responses to moral service robots. We demonstrate that experienced robot morality benefits relational interactions by increasing customer trust. However, in transactional interactions where customers prioritize robot functionality, experienced robot morality can lead to drawbacks. By demonstrating the inadequacy of a one-size-fits-all approach to robot morality, we underscore the importance of adopting a customer-centric design for moral service robots and show that the effectiveness of their placement depends largely on the type of service encounter. These results can serve to guide managers and robot designers toward aligning robot morality with customer demands, facilitating positive human–robot interactions.

ACM Transactions on Human-Robot InteractionVol. 14(2)
Technische Universität Darmstadt (DE), University of Jyväskylä (FI)
Decent work and economic growth
Openalex Percentile: Top 18%
AI in Service Interactions
1.04
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Service Robot Morality in Customer–Robot Interactions: A Mixed-Methods Study — Tuure Tuunanen, Ruth Stock‐Homburg, et al. · ACM Transactions on Human-Robot Interaction (2024) | TGRS Research Map | TGRS