Rural teacher recruitment and retention has become a common concern globally including in China. In order to understand the underlying reasons that cause rural teachers' attrition, this study aims to explore the school culture and professional development of the teachers from urban and rural areas of China provinces, by examining three study objectives: teaching location and socio-demographic factor; challenges faced by rural teachers; and strategies to develop teaching professionalism in rural schools. A mixed-method approach involving survey forms and interview sessions was used for data collection. Data were analyzed using SPSS and ATLAS.ti which included inferential and thematic analysis. A number of 1547 teachers under Compulsory Education in Jiangxi, China were involved as participants. Results indicated that teaching location is significantly related to the socio-demographic condition. Additionally, five challenges reported by rural school teachers include parental involvement, working environment, salary, personal growth, and family environment. Meanwhile, three main strategies used for professional development are educational beliefs, collaboration relationships, and teacher self-training. The outcome of this study would contribute towards effective and feasible measures to stabilize rural teachers, promote educational and social equity, and promote the integration of urban and rural teachers. Findings conclude the importance to explore further and propose the corresponding measures to improve the working and living status of rural teachers.

Based on a spatial vector autoregression (VAR) model and generalized spatiotemporal impulse responses, this paper analyzes urban house price diffusion in East China. The results suggest that a certain amount of spatial and temporal diffusion of neighboring cities exists within the study area. When the central city of the urban agglomeration, Shanghai (SH), and the subcenter city, Hangzhou (HZ), are assumed to be the price diffusion center cities, more than half the surrounding cities are significantly affected by any house price changes in the diffusion center city. Current price changes in SH and HZ have the greatest scope of influence, while SH is the most unlikely city to be affected by house price changes in other cities in the long term. The central city, SH, has a wider radiation range of house price diffusion, while HZ, as a subcenter, has a greater but shorter-lasting impact on the prices of houses within a closer range. However, SH and HZ are not completely dominant in the regional housing market. The house price diffusion mechanism is more significant under conditions of economic connection. Transportation, accessibility, and information dissemination could also explain house price diffusion in East China.

The accumulation and delayed processing of notices generated during the engineering construction process have a significant impact on project settlement and, thus, project cost. Currently, there is a lack of research on intelligent notice processing. Although large language models (LLMs), such as ChatGPT, have demonstrated exceptional performance in natural language processing, their effectiveness in specific vertical fields, such as construction engineering, is limited due to a lack of specialized training. In light of this, this study proposes a knowledge-augmented language model for intelligently processing design notices in EPC (engineering–procurement–construction) projects. This method consists of the following three key components: database construction, price retrieval, and prompt development. During database construction, exception detection was introduced to ensure data quality, and an appropriate database framework was proposed. The price retrieval module features innovative retrieval rules for improved efficiency and accuracy. Prompt development was based on mainstream methods, which were tailored for this task. The result of processing notices includes cost analysis and claimability judgement. The method achieved promising results in experiments with real project data. Based on these results, the paper discusses the model’s advantages, application scenarios, and input text requirements, providing insights and suggestions for future research.

People usually take point of interest (POI) accessibility into consideration when choosing a residential location. Based on a digital map and actual traffic time costs, this paper measures the accessibility of residential communities to the urban center, employment center, and other related POIs in Hangzhou, China. Furthermore, three different models of geographically weighted regressions are constructed in order to explore the dynamic impact of the accessibility of POIs on housing prices. The results show that the geographically and temporally weighted regression model has the best goodness of fit. The evolution of POI accessibility is an essential driving force for the temporal–spatial differentiation of housing prices; significant differences also exist in their impact on residential prices across time and space. The residential prices in Hangzhou present an evolving multicenter spatial distribution pattern. In addition to the accessibility of central business district (CBD) and employment concentration, the quality of education resources and access to convenient transportation have become more prominent in terms of the impact on housing prices over time.

China’s construction industry is facing increasing pressure for transformation and upgrading, with high-quality development becoming an essential goal. However, the precise definition and evaluation criteria for high-quality development remain ambiguous. Against this backdrop, this study focuses on 11 cities in Zhejiang province to explore the connotations of high-quality development in the construction industry and establishes an evaluation index system for assessing it. This study employs the entropy weight method and matter–element extension method to evaluate the high-quality development levels of the construction industry across these cities. The empirical results reveal that the development of the construction industry in Zhejiang province is uneven across cities, with significant potential for overall improvement. This study validates the proposed index system and evaluation model while supplementing empirical evidence; it also enriches the literature and provides both theoretical and technical support for advancing the construction industry’s transition toward high-quality development.