From TAM to AIDUA and Beyond

This review examines the emerging field of service robot adoption in hospitality. It provides a comprehensive overview of their evolution, classification, and conceptualization. The review offers a theoretically grounded analysis of customer intentions, identifying and evaluating salient models and frameworks. Through research synthesis, it pinpoints key gaps hindering holistic understanding of customer acceptance, particularly in hotels. The review highlights limitations of traditional acceptance models like TAM, advocating exploration of alternatives for a unified understanding. It underscores the need for robust methodologies to capture real-world interactions, as well as meta-analyses to establish consensus. The review also identifies critical gaps related to anthropomorphism, customer segmentation, and resistance, emphasizing the importance of contextual factors. By addressing these theoretical and methodological limitations, the review provides valuable insights to guide future research on enhancing service robot integration in hospitality.

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Publication Details

Journal
Journal of Global Information Management
Published
2025-04-03
DOI
https://doi.org/10.4018/jgim.372420
Citations
3
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
7.44
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article

From TAM to AIDUA and Beyond

Nripendra P. Rana, Mohd. Nishat Faisal, Rana Sobh, Nusaiba Begum
3 citations
Journal of Global Information Management
AI in Service Interactions
7.44
article

From TAM to AIDUA and Beyond

Nripendra P. Rana, Mohd. Nishat Faisal, Rana Sobh, Nusaiba Begum
article en
3 citations

Abstract

This review examines the emerging field of service robot adoption in hospitality. It provides a comprehensive overview of their evolution, classification, and conceptualization. The review offers a theoretically grounded analysis of customer intentions, identifying and evaluating salient models and frameworks. Through research synthesis, it pinpoints key gaps hindering holistic understanding of customer acceptance, particularly in hotels. The review highlights limitations of traditional acceptance models like TAM, advocating exploration of alternatives for a unified understanding. It underscores the need for robust methodologies to capture real-world interactions, as well as meta-analyses to establish consensus. The review also identifies critical gaps related to anthropomorphism, customer segmentation, and resistance, emphasizing the importance of contextual factors. By addressing these theoretical and methodological limitations, the review provides valuable insights to guide future research on enhancing service robot integration in hospitality.

Journal of Global Information ManagementVol. 33(1)
Queen's University Belfast (GB), Jaipuria Institute of Management (IN), Qatar University (QA)
Openalex Percentile: Top 4%
AI in Service Interactions
7.44
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