Hongmei Yang

Digital tourism is an essential product of the digital economy, which is significant in promoting sustainable tourism. The study aims to analyze the current research status of digital tourism with the CiteSpace tool. One thousand thirteen documents related to digital tourism, AI tourism, and tourism digitization in the Web of Science (WOS) database from 1991–2022 were collected. This study conducts bibliometric analysis to portray the knowledge map. Furthermore, this paper explores the publication years, co-occurrence of authors, institutions, subjects, research hotspots, and evolution of digital tourism research. The analysis findings revealed that social and environmental sciences are the core disciplines in digital tourism research. Hong Kong Polytechnic University is the foremost institution, and Tussyadiah and Wirtz are the authors with the highest contribution rate. Moreover, the results emphasized the frontier studies of digital tourism referring to technology, consumption, tourists’ reviews, and the progress of the tourism industry. In addition, China, Europe, and the United States should strengthen their digital tourism cooperation with Africa and the South America to promote the sustainable development of global tourism. Finally, the results implicate the future development trends of digital tourism.

Acknowledgment
We acknowledge all the authors involved in the creation of this paper: Chen Luo for providing the opportunity for this research and collaborative creation, and Dr. Songyu Jiang, Dr. Ruihui Pu, and Dr. Lin Li for providing creative ideas and collaborative division for this paper, and for funding the research. Dr. Hongmei Yang further provides the research direction and future in the development process of digital tourism.

It is significant to promote food tourism behavior. This paper aims to build a comprehensive behavior model of tourists suitable for food tourism to promote such tourism in Chongqing city, China. The paper deals with the place-bound and people-bound memories affecting tourist satisfaction, perceived holiday quality of life, and experience loyalty in the food tourism industry. The data were collected from 413 tourists who have experience traveling to Chongqing city through the online questionnaire. Multi-layer perceptron artificial neural network simulation provides a basis for factor ranking for structural equation modeling. The results show that place-bound and people-bound factors can predict experience memory, experience satisfaction, holiday quality of life, experience loyalty, and destination loyalty. In addition, it reveals the mediating role of experiential memory and contributes to the process of memory formation. Place-bound factors emphasize the vital role of marketing and social media information. They are consistent with the actual food experience of tourists at the destination. People-bound factors explained the different aspects of the food experience. The noteworthy aspects are intelligence, emotion, sense, behavior, and natural flow experience. The research results show that tourists, local governments, and tourism departments should focus on developing memory structures with local characteristics and improving quality and experienced food tourism destinations so that tourists can gain more sensory experiences or other experiences to attract more food tourists.