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Robot or human? Manoeuvring switching intention after robot service failure
Wing Han Helen Lee1, Suk Ha Grace Chan2, Binglin Martin Tang3,4
1Institute of Management and Health, University of Wales Trinity Saint David, Swansea, The United Kingdom.
Plos One
|November 4, 2025
Summary
Tourists do not automatically switch to human service after robot failure. However, their tolerance and trust in technology moderate satisfaction with robot service, influencing switching intentions.
Area of Science:
- Tourism Management
- Human-Robot Interaction
- Service Science
Background:
- Robot service failures can impact tourist satisfaction and loyalty.
- Understanding tourist behavior after service disruptions is crucial for service providers.
- The role of psychological factors like trust and tolerance in service recovery is increasingly important.
Purpose of the Study:
- To investigate tourists' intentions to switch to human service following a robot service failure.
- To examine the moderating effects of the zone of tolerance and trust in technology on this switching intention.
- To apply the Unified Theory of Acceptance and Use of Technology (UTAUT) framework.
Main Methods:
- Quantitative research approach utilizing a retrospective survey.
- Data collected from 330 valid tourist samples recalling robot service failures.
- Structural Equation Modeling (SEM) employed for data analysis.
Main Results:
- No significant direct effect was found for tourists switching to human service after robot failure.
- The zone of tolerance and trust in technology significantly moderated tourist satisfaction concerning severity and controllability of the failure.
- The reliability aspect of robot service failure was not found to be moderated by the studied factors.
Conclusions:
- Tourist switching intention post-robot failure is complex and not solely dependent on the failure event.
- Psychological factors like tolerance and trust play a critical role in shaping customer satisfaction and subsequent behavior.
- The study contributes to understanding human-robot interaction dynamics and service recovery in the tourism industry.

