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Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19

Yuangao Chen (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China)
Yuqing Hu (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China)
Shasha Zhou (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China)
Shuiqing Yang (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 15 December 2022

168

Abstract

Purpose

Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant.

Design/methodology/approach

A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry.

Findings

The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants.

Practical implications

This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology.

Originality/value

This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.

Keywords

Acknowledgements

This research is supported by the National Social Science Foundation of China under Grant No. 21BGL245.

Citation

Chen, Y., Hu, Y., Zhou, S. and Yang, S. (2022), "Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19", International Journal of Contemporary Hospitality Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJCHM-04-2022-0433

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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