Regional integration, as an essential measurement for solving unbalanced and uncoordinated regional development, plays an important role in achieving regional sustainable development. In this study, we aimed to construct a systematic research framework to facilitate the development of regional integration. Using 31 prefecture-level cities in the urban agglomeration in the Middle Reaches of the Yangtze River (MYR-UA) as case sites, this study applied box plots, kernel density estimation, GIS visualization tools, Markov chains, and geographic detectors to reveal the dynamic spatiotemporal evolution and factors influencing regional integration from 2009 to 2018. The results indicate that the level of regional integration and its subsystem development is suboptimal in MYR-UA; the temporal characteristic shows an upward fluctuating trend, and the spatial distribution shows remarkable spatial correlation and clustering characteristics. Additionally, we found that the level of regional integration development in MYR-UA has both “path dependence” and “self-locking” effects, and the spatial lag type has a crucial impact on the degree of regional transfer stability. The dominant factors affecting regional integration development include the GDP per capita, economic openness, industrial structure, proportion of education expenditure in fiscal expenditure, urbanization rate, proportion of environmental investment in fiscal expenditure, population density, capital flow, information flow, and technology flow. Finally, based on the findings of this study, policy recommendations for promoting regional integration are proposed.

Achieving customer satisfaction is an important goal of the high-quality development (HQD) of the hotel industry. The purpose of this study is to summarize the spatial distribution characteristics and influencing factors of the HQD of the hotel industry to better help improve hotel customer satisfaction and realize the HQD of the hotel industry. Taking Sanya as an example, this study applied kernel density analysis, grid analysis and a geographically weighted regression (GWR) model to reveal the distribution characteristics and influencing factors of the HQD of the hotel industry. The research results show that (1) from 2010 to 2020, both budget hotels and luxury hotels showed an increasing trend year by year and the degree of spatial agglomeration was continuously strengthened. (2) The overall HQD of the hotel industry in Sanya is at a medium to high level, but the development between different regions is unbalanced. The HQD level of the hotel industry in the eastern part of the city is better than that in the western region. (3) There are significant differences in the HQD level and its spatial distribution characteristics of budget hotels and luxury hotels. (4) Hardware facilities, price levels, market popularity and traffic conditions have a positive impact on the HQD level of the hotel industry, while hotel scale and business prosperity have a negative impact on the HQD level of the hotel industry. The public service level does not pass the significance test. The conclusions of this study can provide theoretical reference for the decision-making of HQD of urban tourism.

Family farms, considered the most desirable form of Chinese agriculture, play a pivotal role in promoting rural revitalization and agricultural modernization. The purpose of this study was to summarize the spatiotemporal evolution characteristics and influencing factors of family farms to better promote the development of modern agriculture. Using provincial demonstration family farms in the urban agglomeration in the middle reaches of the Yangtze River (MYR-UA) as the research object, this study applied the nearest neighbor index, kernel density analysis, multiscale spatial clustering analysis (Ripley’s K-function), and geographically weighted regression (GWR) model to reveal the spatiotemporal dynamic evolution and influencing factors of family farms. The results indicate that: 1) from 2013 to 2021, family farms exhibited annual increases, and their development stages could be divided into rapid, stable, and slow growth periods. 2) The spatial agglomeration pattern of family farms was significant, and the intercepted points at different time periods show the distribution characteristics of the entire dispersion and local concentration. The spatial evolution characteristics of different types of family farms are nearly consistent with those of the overall family farms. 3) The overall family farms and various types of family farms show a scale effect, which first strengthens and then weakens with the change in geographical distance. 4) The spatial pattern of family farms in MYR-UA is affected by both natural and social factors, of which, social factors had the greatest influence. Finally, based on the findings of the study, policy recommendations for promoting the high-quality development of family farms are proposed.

The subjective well-being (SWB) of older adult sojourners is a complex psychological phenomenon. This study employs a combined approach of partial least squares structural equation modeling (PLS-SEM) and fuzzy qualitative comparative analysis (fsQCA) to investigate the linear and nonlinear effects of motivation on the SWB of older adult sojourners. The results indicate that relaxation and decompression, wellness retreats, escape, and self-actualization motivations have a significant positive impact on the SWB of older adult sojourners. However, simple antecedent variables do not individually constitute the necessary conditions for high-level SWB; each variable requires a conditional combination with other factors to generate high-level SWB. Furthermore, this study reveals that nine different combinations of fsQCA consistently lead to high levels of SWB in older adult sojourners. These nine combinations can be categorized into five specific causal pathways, with the escape motivation serving as a core condition in each pathway. This study extends the research on senior residential tourism and offers practical insights for enhancing the competitiveness of senior residential tourism destinations.

The synergistic development of new quality productive forces (NQPFs) and forestry economic resilience is vital for sustainable growth in China’s forestry sector, positioning the country as a global leader. This study develops a theoretical framework and employs spatial Kernel density, the Gini coefficient, spatial Markov chains, and geographical detectors to analyze coordination levels, regional disparities, evolutionary trends, and influencing factors. The results reveal that national coordination has progressed from imbalance to high-quality synergy, though regional disparities remain. Development trajectories show stability, with strong path dependence, a Matthew effect, and high transition probabilities between adjacent levels, accompanied by significant spatial spillovers. Factors such as economic development, openness, marketization, social security, the digital economy, and infrastructure play a major role in enhancing coupling coordination, while policy intervention and human capital show limited standalone effects, although their interactions are important. Based on these findings, policy recommendations are provided to guide China’s forestry economy in the new era.

Despite extensive research on the network structure of tourism destinations, literature on the spatial network structure of cross-border tourism–economic connections is relatively limited, specifically the complex geopolitical relationship between China and the Association of Southeast Asian Nations (ASEAN). Thus, in this study we explored the relevant characteristics and influencing factors of the spatial structure of tourism economic networks. The results first indicate that the China–ASEAN tourism economic network exhibits distinct stage characteristics, with an ‘N’-shaped fluctuating growth trend, evolving from a point-like network to a multipolar development in spatial structure. In addition, China demonstrates a distinctive personality in the network and occupies a central leadership position. Secondly, an analysis of influencing factors shows that institutional distance and geographic distance have a significant impact on the network. Geopolitical risk plays a notable indirect moderating role in the network through its association with tourism policies and regulations, tourism promotion, and cooperation. This further reveals the diverse pathways through which geopolitical risk affects the network, providing a novel perspective for research on the tourism economic network.