When human employees and robots serve together: what drives diners’ intention to revisit?

Purpose With the rise of automation in the restaurant industry, human–robot collaboration is emerging as a dominant service model. However, little is known about how customers’ evaluations of such collaborations influence their intention to revisit. Grounded in cognitive appraisal theory (CAT), this study aims to explore how perceived process fluency and team cohesion impact revisit intention through the mediating roles of robotic service authenticity, customer delight and existential authenticity. Design/methodology/approach An online survey was conducted with Chinese diners who had experienced human–robot team service in restaurants. A total of 448 valid responses were collected, and the proposed model was tested using partial least squares structural equation modelling. Findings The findings indicate that perceived process fluency and team cohesion positively influence robotic service authenticity. Besides, robotic service authenticity positively affects customer delight and existential authenticity, which leads to revisit intention. The mediating effects of robotic service authenticity, customer delight and existential authenticity are all confirmed. Practical implications The findings offer actionable insights for restaurant managers on optimizing human–robot team collaboration to enhance service authenticity and foster emotional engagement, ultimately encouraging customers to revisit. Originality/value This study extends CAT by integrating emotional and cognitive mechanisms into the evaluation of human–robot collaboration services, offering one of the first empirical investigations in semiautomated restaurant settings.

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Publication Details

Journal
International Journal of Contemporary Hospitality Management
Published
2026-01-09
DOI
https://doi.org/10.1108/ijchm-05-2025-0736
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

When human employees and robots serve together: what drives diners’ intention to revisit?

Jihad Mohammad, Yi Zhang, Yanrui Michael Tao, Farzana Quoquab
International Journal of Contemporary Hospitality Management
AI in Service Interactions
article

When human employees and robots serve together: what drives diners’ intention to revisit?

Jihad Mohammad, Yi Zhang, Yanrui Michael Tao, Farzana Quoquab
article en

Abstract

Purpose With the rise of automation in the restaurant industry, human–robot collaboration is emerging as a dominant service model. However, little is known about how customers’ evaluations of such collaborations influence their intention to revisit. Grounded in cognitive appraisal theory (CAT), this study aims to explore how perceived process fluency and team cohesion impact revisit intention through the mediating roles of robotic service authenticity, customer delight and existential authenticity. Design/methodology/approach An online survey was conducted with Chinese diners who had experienced human–robot team service in restaurants. A total of 448 valid responses were collected, and the proposed model was tested using partial least squares structural equation modelling. Findings The findings indicate that perceived process fluency and team cohesion positively influence robotic service authenticity. Besides, robotic service authenticity positively affects customer delight and existential authenticity, which leads to revisit intention. The mediating effects of robotic service authenticity, customer delight and existential authenticity are all confirmed. Practical implications The findings offer actionable insights for restaurant managers on optimizing human–robot team collaboration to enhance service authenticity and foster emotional engagement, ultimately encouraging customers to revisit. Originality/value This study extends CAT by integrating emotional and cognitive mechanisms into the evaluation of human–robot collaboration services, offering one of the first empirical investigations in semiautomated restaurant settings.

International Journal of Contemporary Hospitality ManagementVol. 38(2)
University of Kuala Lumpur (MY), National Defence University of Malaysia (MY), UCSI University (MY)
Openalex Percentile: Top 93%
AI in Service Interactions
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