“Servant” versus “Partner”: Investigating the effect of service robot personas on customer misbehavior
Shaohui Lei and
Lishan Xie
Journal of Business Research, 2025, vol. 199, issue C
Abstract:
Research indicates that customers are more likely to misbehave toward service robots than toward humans. Nonetheless, the relationship between perceived service robot power and customer misbehavior remains underexplored. From the perspective of customer–robot power comparison, we categorize a robot’s persona as either “servant” or “partner.” Leveraging the social comparison theory of power, we examine the association between service robot personas and customer misbehavior. Three scenario-based studies reveal that customers are more prone to misbehavior when interacting with servant robots than partner robot, driven by increased psychological entitlement. This effect is mitigated among customers with low power distance beliefs and when robots employ social-oriented communication. Our findings offer both theoretical contributions and practical recommendations for designing service robots that foster positive customer interactions and reduce customer misbehavior.
Keywords: Service robot; Customer misbehavior; Social comparison theory; Psychological entitlement; Power distance belief; Communication style (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296325003728
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:199:y:2025:i:c:s0148296325003728
DOI: 10.1016/j.jbusres.2025.115549
Access Statistics for this article
Journal of Business Research is currently edited by A. G. Woodside
More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().