The influence of an additional robot apology and robot gender after a human service failure

Bin Ding, Zixuan Guo, Wei Liu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Service robots have come to play important roles in the front line of service organizations, transforming the service ecosystem. Although past research has examined how human intervention can help to remedy a robot failure, this study takes an alternative perspective and presents a “robot intervention recovery strategy.” We propose that service robot intervention can help to remedy a human service failure. Drawing on role congruity theory and gender studies in robotics, this research further examines the effect of robot gender during robot intervention. We suggest that customers are more likely to forgive a service failure when the apology is offered by female (vs male or genderless) robots. Moreover, we examine failure severity and tangible compensation as boundary conditions for the effects of robot intervention and robot gender. Design/methodology/approach: We test our hypotheses using five between-subjects experiments with a total of 1,099 participants recruited from the Credamo platform. Findings: Our results show that customers are more likely to forgive service failure and be satisfied with the recovery when service robots provide an additional apology after a human apology, especially when the robots are female. Our findings further reveal that the effect of robot intervention is more salient when the failure is severe and when tangible compensation is not offered. We found that this female advantage was consistent regardless of the severity of the service failure but was more salient when tangible compensation was not offered. Originality/value: This research bridges the literature on service failure and recovery, service robot adoption and gender studies in robotics. It draws our attention to the value of robot intervention and the importance of robot gender for service recovery.

Original languageEnglish
JournalIndustrial Management and Data Systems
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • Gender stereotype
  • Human–robot interaction
  • Robot intervention
  • Service failure and recovery
  • Service robots

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