Luis V. Casaló , Paola Millastre-Valencia , Daniel Belanche , Carlos Flavián
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引用次数: 0
Abstract
Automated service agents with different levels of artificial intelligence (AI) - mechanical, analytical, and emotional - are gradually replacing employees in their interactions with customers. Previous research suggests that these agents (e.g., chatbots) should embed human behavioral traits such as warmth, competence, and even automated social presence (i.e., perceiving that one is interacting with someone else). However, it is unknown whether different levels of AI are perceived by customers as features increasing humanness and, subsequently, leading to higher functional, monetary, social, or emotional value. Through an experimental design based on tourism chatbots, the results from structural equation analysis reveal that whereas mechanical AI decreases automated social presence, analytical AI increases perceptions of competence and warmth, and emotional AI improves all humanness cues. The article merges the research streams of service agent design and customers’ perceptions of humanness to guide tourism managers in implementing generative AI agents to increase service value.
期刊介绍:
The International Journal of Hospitality Management serves as a platform for discussing significant trends and advancements in various disciplines related to the hospitality industry. The publication covers a wide range of topics, including human resources management, consumer behavior and marketing, business forecasting and applied economics, operational management, strategic management, financial management, planning and design, information technology and e-commerce, training and development, technological developments, and national and international legislation.
In addition to covering these topics, the journal features research papers, state-of-the-art reviews, and analyses of business practices within the hospitality industry. It aims to provide readers with valuable insights and knowledge in order to advance research and improve practices in the field.
The journal is also indexed and abstracted in various databases, including the Journal of Travel Research, PIRA, Academic Journal Guide, Documentation Touristique, Leisure, Recreation and Tourism Abstracts, Lodging and Restaurant Index, Scopus, CIRET, and the Social Sciences Citation Index. This ensures that the journal's content is widely accessible and discoverable by researchers and practitioners in the hospitality field.