Artificial intelligence in service industries: customers’ assessment of service production and resilient service operations
Marcello M. Mariani and
Matteo Borghi
International Journal of Production Research, 2024, vol. 62, issue 15, 5400-5416
Abstract:
Artificial intelligence (AI) is increasingly embedded into service firms’ operations. However, production systems and operations management scholars have not yet examined if AI-empowered service operations are positively judged by service customers. To bridge this gap, this study draws on the three-factor theory of customer satisfaction applied to online review data, to capture the effect of AI-empowered service operations on overall customer satisfaction, operationalised by means of online review ratings. Based on text analytics techniques applied to a sample of more than 50,000 TripAdvisor ORs covering 35 international hotels in Asia and America, we develop a penalty–reward contrast analysis. The findings reveal that the effects of customer interaction with mechanical AI on customer satisfaction with service operations are asymmetric: positive customer interaction with mechanical AI positively and significantly influences overall customer satisfaction with AI-empowered service operations, whereas negative customer interaction with mechanical AI does not significantly alter customer satisfaction. Taken together, these findings suggest that mechanical AI constitutes a key element of resilient AI-empowered service operations.
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2022.2160027 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:62:y:2024:i:15:p:5400-5416
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2022.2160027
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().