Customer’s Acceptance of Artificial Intelligence in Hospitality Industry: A Systematic Literature Review

Abstract

This paper explores the literature review on customers' acceptance/rejection of AI and what factors affect the customers' acceptance/rejection of AI in the hospitality industry. This paper's centre of attention is reading the research papers or articles to analyze SLR. Artificial intelligence is altering the old-fashioned outlooks of hotel services with its cleverness, shortening processes, furnishing valuable insights, and enhancing guest experiences. Chatbots, Voice Assistance, Facial recognition technology, Personalized Experience, Virtual Realities, Google maps, and robots are all AI tech used in the hospitality industry. Henna Hotel (japan) is treated purely by robots for reception, exchange of information, cleansing and luggage-carrying. This paper chases the SLR research method. Relevant data has been collected from online databases such as ResearchGate, Google Scholar, ScienceDirect, Academia, and Emerald. The researcher initially compasses on the research gate as it has more content other than the online databases allied to the topic. The research gate search is based on the following keywords: "artificial intelligence", 'Consumer's acceptance', 'hospitality', 'robotics', 'hedonic attitudes', 'utilitarian attitudes, 'perceived user', 'perceived ease of user'. This paper includes two main models: the Technology Acceptance Model (TAM) and the Artificial Intelligence Device User Acceptance (AIDUA) model. Human voices or robots and participants shared the same gender; participants felt closer to robots and had greater acceptance of robots. Attitude is positively impacted by PU, PEOU, and Perceived Innovativeness.

Along with that, Attitude, PU, and PEOU simultaneously affect Intentions. The AIDUA model refers to the first stage, in which consumers analyze the AI devices' use, centred on three factors: hedonic motivation, anthropomorphism, and social influence. In the next stage, people analyze AI's use, which is centred on two factors: effort expectancy and performance expectancy. In the outcome stage, the emotions of the previous stage determine people's acceptance and rejection of AI in the hospitality industry.