Artificial intelligence features and their service outcomes: a meta-analysis

With the permeation of artificial intelligence (AI) through the tourism and hospitality industry, a comprehensive understanding of its features and service outcomes is important for both academia and practice. In this study, a meta-analytic framework with 23 constructs from 91 research papers was developed. This analysis indicated that AI features can be categorized as sensory, social or functional; and the relationships among these features were revealed. Additionally, these features lead to positive service outcomes via a process involving customers' cognition, affect and relationships with service providers. The research method, AI type and participants' gender moderate the influence of AI features on service outcomes, but stimulants and prior experience do not. These findings enhance the understanding of AI applications and consequences and have managerial implications.

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Publication Details

Journal
Journal of Hospitality Marketing & Management
Published
2024-08-23
DOI
https://doi.org/10.1080/19368623.2024.2391856
Citations
17
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
5.91

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article

Artificial intelligence features and their service outcomes: a meta-analysis

Xiaoyang Sun, Minglong Li, Hailian Qiu, Meichen Hua
17 citations
Journal of Hospitality Marketing & Management
AI in Service Interactions
5.91
article

Artificial intelligence features and their service outcomes: a meta-analysis

Xiaoyang Sun, Minglong Li, Hailian Qiu, Meichen Hua
article en
17 citations

Abstract

With the permeation of artificial intelligence (AI) through the tourism and hospitality industry, a comprehensive understanding of its features and service outcomes is important for both academia and practice. In this study, a meta-analytic framework with 23 constructs from 91 research papers was developed. This analysis indicated that AI features can be categorized as sensory, social or functional; and the relationships among these features were revealed. Additionally, these features lead to positive service outcomes via a process involving customers' cognition, affect and relationships with service providers. The research method, AI type and participants' gender moderate the influence of AI features on service outcomes, but stimulants and prior experience do not. These findings enhance the understanding of AI applications and consequences and have managerial implications.

Journal of Hospitality Marketing & ManagementVol. 34(1)
Zhongnan University of Economics and Law (CN), Hubei University (CN)
National Natural Science Foundation of China, National Social Science Fund of China
Openalex Percentile: Top 3%
AI in Service Interactions
5.91
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