Abstract
The advancement of technology following the Fourth Industrial Revolution and the surge in demand for untact services caused by COVID-19 will gradually expand the scope of service automation through artificial intelligence (AI) technologies. In practice, numerous hotels are adopting AI-based service technologies, but it is still in its early stage to provide guidelines for the overall service strategy for this technology. Therefore, this study conducted a study on the failure of AI based self-service technologies (SSTs), service recovery, and the psychological expectations of customers’ SST. An online survey was conducted on respondents who had experience using AI based SSTs, and a total of 370 responses were used for analysis. As a result of structural model analysis through AMOS, it was found that adequate service recovery and low expectations for SSTs were satisfied with SSTs and hotels as a result, even if service failures were experienced. These findings provide specific practical guidelines for many hotels promoting AI-based service automation.
Highlights
The radical development of information and communication technologies (ICTs) and the Fourth Industrial Revolution have affected almost all industries, and the hotel industry is no exception
No matter how actively self-service technologies (SSTs) are used by recent customers, since artificial intelligence (AI) technology has not been applied to the service stage for a long time and unless it is a service failure situation caused by the customers, there may be anxiety about receiving services using the technology [5]
Technology failure was measured with 4 items adapted from [13], poorly designed interface was measured with 6 items adapted from [4], and excessive customer waiting line was measured with 5 items adapted from [8]
Summary
The radical development of information and communication technologies (ICTs) and the Fourth Industrial Revolution have affected almost all industries, and the hotel industry is no exception. The Fourth Industrial Revolution has taken this hotel service automation to the level, and hotels are providing more sophisticated and diverse self-services based on AI. When AI-based self-service fails and when service recovery occurs, there has been insufficient discussion on how hotel customers perceive the technology and how they perceive the hotel that introduced the technology. This study aims to provide guidelines for hotels to successfully automate AI based services in response to social phenomena. We will look at AI-based self-service failure, and empirically review the factors that cause failure, service recovery, and customer response. We expect the results of this analysis to provide effective guidelines for hotels to successfully realize efficient AI-based service automation
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