Artificial intelligence and service performance: empirical findings from the hospitality sector

Purpose This study aims to analyse the factors influencing AI adoption in the hospitality sector, utilising the technology acceptance model (TAM) and the technology-organisational-environmental (TOE) framework to understand how Industry 4.0 pressures drive the integration of emerging technologies, such as artificial intelligence (AI). Design/methodology/approach Data were collected via structured questionnaires from 312 valid responses from luxury hotels offering lodging and food services, and the hypotheses were tested using structural equation modelling. Findings This study demonstrates that perceived ease of use, competitive pressure, robust IT infrastructure and supportive government policies significantly drive AI adoption, thereby enhancing service performance. These factors also supplement each other: technological innovations enable new functionality, organisational preparation prepares for implementation and exogenous factors accelerate adoption processes, all together building significant momentum for the digital transformation of the hospitality industry. Practical implications The results give a hotel management, policy, and tourism stakeholder AI technology deployment strategic framework for boosting service performance, operation efficiency improvement and competitive advantage entrenchment during an industry being accelerated digitalised at a greater speed. Originality/value This study advances the literature by offering a novel, integrative perspective on AI adoption in the hospitality sector through the combined application of the TAM and the TOE framework. Positioned within a developing economy, it adopts a rigorous empirical lens to foreground organisational decision-making, thereby moving beyond the dominant customer-centric discourse. Further, by empirically linking AI adoption with service performance outcomes, the study bridges the critical gap between adoption intent and operational realisation, with particular relevance to the underexplored context of luxury hotels in India.

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Publication Details

Journal
International Journal of Quality & Reliability Management
Published
2026-05-29
DOI
https://doi.org/10.1108/ijqrm-02-2025-0082
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence and service performance: empirical findings from the hospitality sector

Kiran Cotha, Rashmi Ranjan Panigrahi, Shad Ahmad Khan, Subhodeep Mukherjee
International Journal of Quality & Reliability Management
AI in Service Interactions
article

Artificial intelligence and service performance: empirical findings from the hospitality sector

Kiran Cotha, Rashmi Ranjan Panigrahi, Shad Ahmad Khan, Subhodeep Mukherjee
article en

Abstract

Purpose This study aims to analyse the factors influencing AI adoption in the hospitality sector, utilising the technology acceptance model (TAM) and the technology-organisational-environmental (TOE) framework to understand how Industry 4.0 pressures drive the integration of emerging technologies, such as artificial intelligence (AI). Design/methodology/approach Data were collected via structured questionnaires from 312 valid responses from luxury hotels offering lodging and food services, and the hypotheses were tested using structural equation modelling. Findings This study demonstrates that perceived ease of use, competitive pressure, robust IT infrastructure and supportive government policies significantly drive AI adoption, thereby enhancing service performance. These factors also supplement each other: technological innovations enable new functionality, organisational preparation prepares for implementation and exogenous factors accelerate adoption processes, all together building significant momentum for the digital transformation of the hospitality industry. Practical implications The results give a hotel management, policy, and tourism stakeholder AI technology deployment strategic framework for boosting service performance, operation efficiency improvement and competitive advantage entrenchment during an industry being accelerated digitalised at a greater speed. Originality/value This study advances the literature by offering a novel, integrative perspective on AI adoption in the hospitality sector through the combined application of the TAM and the TOE framework. Positioned within a developing economy, it adopts a rigorous empirical lens to foreground organisational decision-making, thereby moving beyond the dominant customer-centric discourse. Further, by empirically linking AI adoption with service performance outcomes, the study bridges the critical gap between adoption intent and operational realisation, with particular relevance to the underexplored context of luxury hotels in India.

International Journal of Quality & Reliability Management
Xidian University (CN), Mount Aloysius College (US), American University of Phnom Penh (KH), Koneru Lakshmaiah Education Foundation (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
AI in Service Interactions
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