Robots at your service: Understanding hotel guest acceptance with meta-UTAUT investigation

This study examines the main factors contributing to robot acceptance by UK hotel guests, aiming to increase the acceptance of robot technology and ensure the success of robot initiatives. To reach this aim, it combines the Meta-UTAUT model and four additional factors, including anthropomorphism, aesthetics, interaction, and trust. The study employs a quantitative approach, analysing 358 online surveys from UK hotel guests using AMOS-SEM. The findings reveal that performance expectancy and effort expectancy influence attitudes. However, performance expectancy does not directly impact intentions and effort expectancy was found to significantly affect intention in a negative manner. Also, the social influence, facilitating conditions, anthropomorphism, aesthetics, and trust significantly affect intentions to use robots. Moreover, attitude mediates the relationship between performance expectancy, effort expectancy, and behavioural intentions. This study contributes a more comprehensive framework for understanding robot acceptance in hospitality and offers valuable insights for hoteliers and robot designers. It emphasises the significance of user-centred design, clear communication of benefits, and supportive environments to enhance guest experiences and promote robotic service adoption. • Integrates the Meta-UTAUT model with the factors of anthropomorphism, aesthetics, interaction, and trust to understand guest acceptance towards robots. • This study employed a quantitative design, including a sample of 358 via a survey. • Anthropomorphism, aesthetics, and trust significantly impact behavioural intentions. • Provides hoteliers and designers insights into key factors shaping guest perceptions of robots.

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Institutions

Publication Details

Journal
International Journal of Hospitality Management
Published
2025-05-09
DOI
https://doi.org/10.1016/j.ijhm.2025.104227
Citations
12
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
29.77
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article

Robots at your service: Understanding hotel guest acceptance with meta-UTAUT investigation

Nirmeen Elmohandes, Mostafa Marghany, Mohamed Youssef Ibrahim Helal, Khaled Ghazy et al.
12 citations
International Journal of Hospitality Management
AI in Service Interactions
29.77
article

Robots at your service: Understanding hotel guest acceptance with meta-UTAUT investigation

Nirmeen Elmohandes, Mostafa Marghany, Mohamed Youssef Ibrahim Helal, Khaled Ghazy, Nabila N. Elshawarbi, Mahmoud Ibraheam Saleh, Ibrahim Mohamad
article en
12 citations

Abstract

This study examines the main factors contributing to robot acceptance by UK hotel guests, aiming to increase the acceptance of robot technology and ensure the success of robot initiatives. To reach this aim, it combines the Meta-UTAUT model and four additional factors, including anthropomorphism, aesthetics, interaction, and trust. The study employs a quantitative approach, analysing 358 online surveys from UK hotel guests using AMOS-SEM. The findings reveal that performance expectancy and effort expectancy influence attitudes. However, performance expectancy does not directly impact intentions and effort expectancy was found to significantly affect intention in a negative manner. Also, the social influence, facilitating conditions, anthropomorphism, aesthetics, and trust significantly affect intentions to use robots. Moreover, attitude mediates the relationship between performance expectancy, effort expectancy, and behavioural intentions. This study contributes a more comprehensive framework for understanding robot acceptance in hospitality and offers valuable insights for hoteliers and robot designers. It emphasises the significance of user-centred design, clear communication of benefits, and supportive environments to enhance guest experiences and promote robotic service adoption. • Integrates the Meta-UTAUT model with the factors of anthropomorphism, aesthetics, interaction, and trust to understand guest acceptance towards robots. • This study employed a quantitative design, including a sample of 358 via a survey. • Anthropomorphism, aesthetics, and trust significantly impact behavioural intentions. • Provides hoteliers and designers insights into key factors shaping guest perceptions of robots.

International Journal of Hospitality ManagementVol. 130
University of Essex (GB), Canterbury Christ Church University (GB), Ural Federal University (RU), University of Debrecen (HU), King Fahd University of Petroleum and Minerals (SA), Hashemite University (JO), Helwan University (EG)
Decent work and economic growth
Openalex Percentile: Top 0%
AI in Service Interactions
29.77
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