2021
DOI: 10.1108/ijchm-06-2020-0622
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Customers’ evaluation of mechanical artificial intelligence in hospitality services: a study using online reviews analytics

Abstract: Purpose This paper aims to analyze if and to what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled hotel service interactions. This study deploys online reviews (ORs) analytics to understand if the presence of mechanical AI-related text in ORs influences customers’ OR valence across 19 leading international hotels that have integrated mechanical AI – in the guise of service robots – into their operations. Design/methodology/approac… Show more

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Cited by 71 publications
(53 citation statements)
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References 76 publications
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“…The existing literature has investigated the impact of AI technology applications on enterprises regarding service efficiency, costs and economic benefits (Chi et al , 2020) or customers in terms of user acceptance and service experience (Gursoy et al , 2019; Zhang et al , 2021). The influence of AI-enabled service attributes on the service work of FLEs (as the core provider of hospitality services) was ignored (Mariani and Borghi, 2021). This study addressed this gap.…”
Section: Discussionmentioning
confidence: 99%
“…The existing literature has investigated the impact of AI technology applications on enterprises regarding service efficiency, costs and economic benefits (Chi et al , 2020) or customers in terms of user acceptance and service experience (Gursoy et al , 2019; Zhang et al , 2021). The influence of AI-enabled service attributes on the service work of FLEs (as the core provider of hospitality services) was ignored (Mariani and Borghi, 2021). This study addressed this gap.…”
Section: Discussionmentioning
confidence: 99%
“…Developments in AI and its acceptance by service industries, have been translating the hospitality and tourism industries in many ways, impacting on areas, including consumer demand, tourist experiences and perceptions, destination management and prediction of tourists' behaviours (Wu et al, 2017;Filieri et al, 2021). Recent studies confirm this by demonstrating a significant correlation between AI services, the perceptions of quality, consumer happiness and engagement (Prentice et al, 2020;Mariani and Borghi, 2021;Kong et al, 2021). Several review experiments have been conducted in the hospitality and tourism literature and many have studied a diverse range of existing AI applications.…”
Section: Introductionmentioning
confidence: 95%
“…Gamification designs, such as badges, points and leaderboards, are widely applied by online review websites, such as Tripadvisor, and users can gain additional badges and high status in communities by posting numerous reviews (Liang et al , 2017b). However, numerous studies found that the provision of internal incentives will likely affect review quality because some users may attempt to gain a high status by increasing review quantity but reducing review quality (Goes et al , 2016; Liu et al , 2018; Mariani and Borghi, 2021).…”
Section: Literature Review and Hypothesis Developmentmentioning
confidence: 99%