The rural three-tier healthcare system is an essential part of the Chinese healthcare service system. To ensure rural residents’ equal access to such healthcare services, it is necessary to examine the current status of the healthcare system in rural China and formulate corresponding improvement suggestions. This study therefore collects the data from the China Health Statistics Yearbook, the China Health Yearbook and the China Statistical Yearbook between the years 2004 and 2021 to calculate the Gini coefficient (G), health resource density index (HRDI) and Theil index (T) first, and then perform the Mann–Kendall test afterwards to evaluate the equity of healthcare resource allocation comprehensively. This series of analysis helps in drawing the following conclusions: (1) county and county-level city medical and health institutions (CMHIs) show a higher development trend in comparison with township hospitals (THs) and village clinics (VCs); (2) VCs have higher institutional fairness, while for beds and personnel, CMHIs and THs are more fairly positioned; (3) more specifically for CMHIs and THs, personnel allocation is more fair than beds and institution allocations; (4) the density of healthcare resources in the eastern and central regions is higher than that in the western part, while the intra-regional distribution of beds and personnel in the west and central regions is better than that in the eastern region; (5) intra-regional differences are more significant than inter-regional differences and the fairness according to population distribution is higher than that of geographical area allocation. The results of this study provide theoretical basis for further optimizing the allocation of healthcare resources and improving the fairness of healthcare resources allocation from a macro perspective.

Industrial land is under transition globally. Insights into this transition are important to plan a sustainable future. Since industrial land follows parcel shapes and the transition process requires multi-year data to observe the impacts of such changes, multi-year vector data should be used to analyse industrial land transition. This paper presents a framework to analyse path-dependent regional industrial land transition processes using vector data. A step by step instruction is presented. In the analysis, the changed percentages of land use in the surroundings of appeared or disappeared industrial land are visualized. The visualized surrounding land use compositions give planners an idea on what causes land use transitions, the most frequent transition forms and their impacts on the surroundings, purely from a land use point of view to reduce data collection efforts. The North Brabant region in the Netherlands is used as a case study. The region is split into urban and non-urban areas to show the generic applicability of this framework.

The global climate change has resulted in huge flood damages, which seriously hinders the sustainable development of rural economy and society and causes famers’ livelihood problems. In flood-prone areas, it is imperative to actively study short and long-term strategies and solve farmers’ livelihood problems accordingly. Following the sustainable development analysis framework proposed by the Department for International Development (DFID), this study collects empirical data of 360 rural households in six sample villages in the Jialing River Basin of Sichuan Province, China through a village-to-household field questionnaire and applies the Multinominal Logit Model (MNL) to explore the influence of farmer households’ capital on livelihood strategy choice. Research results show that: (1) In human capital category, the education level of the household head has a significant positive impact on the livelihood strategies of farmers’ families; (2) In physical capital category, farmer households with larger space have more funds to choose among flood adaptation strategies; (3) In natural capital category, house location and the sale of family property for cash have the greatest negative impact on farmers’ livelihood strategies; (4) Rural households with more credit opportunities in financial capital are more willing to obtain emergency relief funds; (5) Farmers’ families helped by the village for a long time will probably not choose to move to avoid floods, but are more likely to choose buying flood insurance. This study provides an empirical reference for effective short and long term prevention and mitigation strategies design and application in rural in flood-prone areas.

With the popularization and application of Building Information Modeling (BIM), the demand for BIM technical talents in the construction industry is increasing. Exploring college students’ BIM technical learning behavior is of great practical significance to improve education activities. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), this research adds learning attitude variables to construct a theoretical model of influencing factors of college students’ BIM technology learning behavior. Chinese undergraduate students were asked to complete online questionnaires through peer-to-peer contact with sample colleges and universities. Finally, 1090 valid questionnaires were obtained. The students were sampled from research-oriented, applied research-oriented, application-oriented, and private research-oriented universities in seven regions of China: northeast, north, east, south, central, northwest, and southwest. The structural equation model was used to analyze the sampling data. The results indicate that college students’ BIM learning attitude, performance expectations, and social influence positively and directly impact their learning intention, which indirectly impacts their learning behavior. At the same time, promoting factors and learning intention demonstrate a significant positive and direct impact on learning behavior. Therefore, the following suggestions have been put forward to enhance college students’ learning motivation for BIM technology: increase the popularization of BIM technology in colleges and universities and improve the operation level of full-time BIM teachers. The latter enables colleges and universities to continuously and stably export qualified BIM technical talents to society and the market, resulting in a continuous industry development cycle.

As coronavirus disease 2019 (COVID-19) swept the world in early 2020, all the Chinese universities and colleges adopted online learning to fulfill the directive saying “classes suspended but learning continues.” Understanding the impact of this large-scale online learning experience on the future online learning intention of Chinese university students can help design better blended-learning activities. This study applies flow experience and theory of planned behavior (TPB) to construct a theoretical framework for assumption making and the assumptions made are validated by data gained from questionnaires. A total of 6,933 students from 54 institutions in China participated in the investigation, with 5,456 valid questionnaires returned. This study employs partial least squares (PLS) regression and confirmative factor analysis (CFA) to analyze and estimate the measurement model and the structural model. The results indicate that the experience of home-based learning significantly influenced the attitudes of Chinese university students, which in turn had a positive influence on their intention to continue online learning. The research findings provide a theoretical framework and practical guidelines on building a scientific online learning platform with appropriate online learning environments and tasks for a post-COVID-19 era blended-learning in Chinese universities.