The augmentation effect of artificial intelligence: can AI framing shape customer acceptance of AI-based services?

Darina Vorobeva (), Diego Costa Pinto, Nuno António and Anna S. Mattila
Additional contact information
Darina Vorobeva: EM - EMLyon Business School
Diego Costa Pinto: Universidade Nova de Lisboa (Portugal, Lisbon) - NOVA
Nuno António: Universidade Nova de Lisboa (Portugal, Lisbon) - NOVA
Anna S. Mattila: Penn State - Pennsylvania State University [State College, PA] - Penn State System

Post-Print from HAL

Abstract: Although Artificial Intelligence is a big revolution in the tourism and hospitality industry, prior research provides little insight into how customers respond to AI replacement and how providers can mitigate AI aversion. Drawing on the Feeling Economy framework, three studies examine how customers react to a different framing of AI replacement (augmentation vs. substitution) compared to using only human employees, affecting their acceptance of AI-based services. The findings contribute to the tourism and hospitality literature by revealing that framing AI as augmentation (vs. substitution) can increase enjoyment and ease of use and improve AI acceptance. Consistent with the Feeling Economy account, the findings highlight the proposed mechanism of enjoyment and perceived ease of use underlying the AI framing effects. This research provides important theoretical and managerial implications for tourism and hospitality providers, helping them understand how to effectively introduce AI-based services to win customers' acceptance.

Keywords: augmentation; feeling economy; hospitality; technology acceptance (search for similar items in EconPapers)
Date: 2024-05-18
References: Add references at CitEc
Citations:

Published in Current Issues in Tourism, 2024, 27 (10), pp.1551 - 1571. ⟨10.1080/13683500.2023.2214353⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:hal:journl:hal-05488125

DOI: 10.1080/13683500.2023.2214353

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().