Based on mobile positioning big data, this study analyzes the quantity of visitation changes of leisure tourism facilities under the impact of COVID-19, which is a direct way to evaluate the impact of COVID-19 on the leisure tourism industry. The quantity of visitation to the four types of leisure facilities (scenic spots, shopping services, sports services, science and cultural education services) in the three Chinese cities (Beijing, Shanghai, and Qingdao) decreased by 63.06% and 44.74% respectively on the Tomb Sweeping Day and the Labor Day in 2020 compared with 2019. The biggest decreasing was in science and cultural education services, followed by scenic spots and sports services, and finally shopping services. The curve of hourly visitations to leisure facilities in 2020 shows a smooth feature, indicating that the public has reduced the risk of pandemic through peak shifting leisure. The analysis of influencing factors shows that the influence of the floor area on visitation is different in different phases. From Tomb Sweeping Day to Labour Day in 2020, the influence of area on leisure behaviour changes from negative to positive. This paper provides a technical framework for assessing the impact of crisis event, and expands the protection motivation theory.

This study investigates the evolution of the structures of China’s domestic intercity tourism information flow networks, an increasingly important issue in an information-driven society. Moving beyond prior research that primarily emphasizes urban node attributes and multidimensional distances, this study applies social network analysis to develop an integrated analytical framework that incorporates endogenous structural effects, exogenous network effects, node attributes, and similarity effects. Using tourism information flows in China as an empirical proxy, the study examines the mechanisms underlying the formation and persistence of intercity relationships within the country. The results indicate that the self-organization of microscopic network structures plays a significant role in both tie formation and persistence, particularly through reciprocity, cyclicity, and convergence. Notably, the effect of cyclicity reversed during the COVID-19 pandemic and changed direction from relationship formation to persistence. In addition, cultural distance (proxied by dialect distance), geographical distance, and institutional distance significantly inhibit both the formation and persistence of intercity tourism information flows. Changes in urban node scale and node similarity also exert significant influences on network evolution. This study deepens the understanding of the spatial structural dynamics of China’s domestic intercity tourism information flows and provides a conceptual basis for future research on the evolutionary mechanisms of tourism network structures within a domestic context. Its direct significance lies in promoting sustainable urban tourism development, network resilience, and adaptive governance of urban systems.

基于新质生产力形成背景，论文以战略性新兴产业中的智能制造、生物医药和绿色环保行业为例，利用截至2023年企业对外投资数据构建中国城市新质生产功能网络，应用社会网络分析方法，开展网络空间结构特征与影响因素研究。研究发现：① 与以往城市网络研究相比较，新质生产功能网络未出现明显的“菱形结构”，中高强度联系呈现出以北京为核心的放射型空间特征；② 影响因素结果表明，省际边界对三种网络均产生了显著的负向影响，但地理距离的负向作用未发生在智能制造网络中，在中国重大区域高速交通基础设施建设的影响下，地理距离对于要素空间流动的抑制作用相对弱化，但行政壁垒仍然发挥着显著影响；③ 城市节点属性变量在三个细分网络中影响效应存在差异，体现出不同行业发展尤其是在异地投资的空间选择行为中，对目标城市发展水平与功能特征的针对性要求。研究揭示了新质生产力形成背景下中国城市网络空间结构的变化特征，丰富了城市地理学积极响应国家发展重大战略需求的研究视角，对于完善新发展背景下中国城市体系空间结构演化一般规律的科学认识具有学术意义。