Technology has become an important driving force in high-quality tourism development. Macroscopically, this study discusses the present situation and tasks of technological innovation in China’s tourism industry and the important areas of technology-enabled high-quality tourism development. At the meso level, this study analyzes the practical paths and research issues of digital technology-empowered tourist destinations. At the micro level, this study discusses the impact of digital visual technology and various digital technologies on the tourist experience and their application in tourist locations such as museums. This study draws the following conclusions: (1) China should carry out demand-oriented technological innovation in the field of tourism, improve the quality of tourist services, upgrade elements of tourist enterprises, modernize the governance skills of mass tourism in various destinations, and form a green development capacity for the sustainable use of resources so that technology will comprehensively empower high-quality tourism development. (2) AI technology empowers high-quality tourism development, especially in shaping a more coordinated and greener tourism development model. (3) The practice of applying digital technology to promote the high-quality development of tourist destinations has given rise to issues worthy of study, such as the “liquid interaction” between destinations and tourists, value co-creation by multiple participants, and the construction of digital ecology and digital competitiveness. (4) Innovation in tourist experience products and services empowered by digital visual technology can help China upgrade and develop its tourist industry in the direction of service innovation, product technology, and brand uniqueness. (5) Digital technology reshapes the forms of museums, enriches the content and methods of museum exhibitions, enhances visitors’ immersive experiences and edutainment, and helps create more diverse communication channels.

The development of the sharing economy has given birth to a new form of experience economy called shared accommodation, which benefits from many innovations in its ability to shape “unforgettable experiences” for tourists. However, it is unclear how tourists form unforgettable experiences based on individual interactions in shared accommodation scenarios. Based on the comprehensive experience paradigm, this study systematically explores the influence mechanism of the features of shared accommodation on the tourist experience through grounded theory and further refines the formation path of tourists’ unforgettable experiences. The results show that tourists form unforgettable experiences in shared accommodation scenarios through three experiential paths: functional, emotional, and symbolic, and which correspond to the physical, psychological, and spiritual dimensions, respectively. Simultaneously, four major factors influenced the occurrence of unforgettable experiences: infrastructure functions, service experiences, interpersonal interactions, and novel experiences. These results provide a reference for the sharing economy industry to optimize “experience-based” products and services.

Research on the structural characteristics and factors influencing tourism flow networks in cities along the Canal is of great significance to the development of canal tourism. This study extracts flow information from the online travelogues of tourists in 39 cities along the Canal to construct the tourism flow network. The social network analysis method (SNA) and exponential random graph model (ERGM) are used to analyze the structural characteristics of tourism flow networks, along with the common influences of different factors on the tourism flow network of cities along the Canal. By exploring the deep influence mechanism of the structural characteristics of tourism flow networks in Canal cities, we found that such networks result from a combination of factors. The results show that (1) tourism attraction leads to differences in the distribution of tourism flow frequency in cities along the Canal in the Yangtze River Delta region; (2) the capacity of tourism flow distribution is jointly affected by the level of economic development, urban accessibility, urban environmental quality, and urban tourism attractiveness; (3) the non-substitutability of core transit cities mainly stems from urban accessibility; and (4) the level of economic development is an important influencing factor in the formation of core-periphery structural characteristics. It is hoped that this paper will provide insights for the planning, management, and sustainable development of tourist flows in cities along the Canal.

By collecting and screening 74 papers related to tourist destination image research in the big data environment — and published in the Science Citation Index (SCI), Social Science Citation Index (SSCI), and Peking University Chinese Core Journal Catalog (2020 Edition), as of April 2023 — this study combs through the current status of the field, and analyzes and summarizes existing research from three perspectives — data (sources and modalities), methodology, and technology (tools) — and looks forward to future research trends. The research shows that user-generated content is the main data source, textual data is dominant in terms of modality, and content analysis is the basic method of tourist destination image research in the big data environment. Other commonly used methods in the field of computer science — such as sentiment analysis, topic modeling, image annotation, and image recognition — can also be classified into this category. Technically, application programming interfaces (APIs) and software tools are mostly used, and the application of deep learning mainly focuses on image data, which has not yet been fully investigated in research on the image of tourist destinations.

Just as the senses are core tools in a human body’s ability to collect information, the tourist sensory experience plays an integral part of the tourist experience. The tourist sensory experience is formed by receiving stimuli from sensory organs and translating it into vision, hearing, smell, taste, and touch. Although research on tourist sensory experiences has made some progress, there remains a lack of systematic discussion and outlook on this topic. So as to define the relevant concepts relating to a tourist’s sensory experience, this study systematically reviews the prevailing body of research in reference to the situation, content, and mechanism behind tourist sensory experiences. This study then proposes future research themes, including the refinement of the concept and measurement content, the exploration of the intrinsic formation mechanism of the tourist sensory experience, and the enrichment of sensory experiences of different tourism phases, multiple destinations, and differentiated tourist types, with the aim of enriching and enhancing the depth and breadth of the research on tourist sensory experiences.