Lin Li

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.

The digital economy has enforced women’s employment and provided more possibilities for promoting employment for gender equality (SGD5). In order to achieve SDG5, the study aims to explore the role of digital employment policy and digital employment value on digital employment intention based on the support alliance theory and employment behavior theory and to build a model of digital employment for gender equality. 492 women with digital work experience from China participated in the survey. The results reveal that digital employment policy (β = 0.327, p < 0.001) and digital employment value (β = 0.454, p < 0.001) predict digital employment intention. Digital employment policy plays an active role in determining digital employment value (β = 0.546, p < 0.001). At the same time, the study claims the intermediary role of digital employment value in the structural model. This study can inspire the government and relevant departments to design more scientific and diversified employment policies for women, including policy support in economic, educational, and social aspects. Furthermore, women in the digital era should actively participate in training, improve their digital skills, understand the possibilities that digitalization brings to their work and life, and adapt themselves to the development of the digital society. This study encourages women to integrate into the digital society and actively improve their values, thus achieving SDG5.

Digital employment is one of the critical concepts of the digital economy for sustainable development. Promoting digital employment intention of potential employees is indispensable for developing the digital economy. The study aims to explore how digital employment policies predict digital employment intentions and to construct a structural equation model. Based on an online survey of 470 students with digital work experience from Chinese higher education institutions, the data were processed using SPSS 26.0 and Amos 26.0. The results uncover that digital employment policies have a positive impact on digital employability (β = 0.538, p < 0.001), digital employment capital (β = 0.524, p < 0.001), and digital employment intentions (β = 0.257, p < 0.001). At the same time, digital employability (β = 0.216, p < 0.001) and digital employment capital (β = 0.505, p < 0.001) also have a positive impact on digital employment intentions. The structural equation model emphasizes the significant mediating effect of digital employability (0.116) and digital employment capital (0.265). Therefore, the government should actively promote digital policies to encourage and enhance digital employment capabilities, promoting digital employment intentions and behaviors. The support and development of digital employability by the entire society, especially schools, and families, is also significant.