Housing is a fundamental human need significantly impacting societal and economic aspects. The construction industry consumes substantial global energy and contributes significantly to carbon emissions. Rapid urbanization in China, particularly the development of Desakota regions (a blend of urban and rural areas), necessitates understanding the influencing factors of housing construction technology within these unique contexts. Previous research on Chinese housing focuses on price increases and urban-rural disparities, but lacks a comprehensive framework for understanding technological influences in Desakota communities. This study addresses this gap by investigating the key factors shaping housing construction technologies in these regions, aiming to inform sustainable and equitable urban development in China and globally.

Existing literature highlights various factors influencing housing affordability and construction technology. Studies reveal that inflation, urbanization, and construction material costs significantly impact housing affordability (Zakaria and Kuusaana, 2020). Supply and demand dynamics, macroeconomic conditions, and housing finance are also crucial (Trimbath and Montoya, 2002; Ato Kwamena Senayah, 2016). Other research focuses on the influence of land tenure, political and economic climate, and government regulations on housing delivery (Ajayi, 2017; Assaf et al., 2010; Nyamushamba, 2016). Studies on green building technologies in rural China emphasize economic, technical, political, social, and managerial factors (Gan et al., 2022). This study builds upon these existing works by providing a specific focus on Desakota regions in China, utilizing a robust statistical analysis to rank the importance of various influencing factors.

This study employed a mixed-methods approach, combining a comprehensive literature review with a quantitative survey. The literature review identified six primary and twenty secondary factors influencing housing construction technology in Desakota regions. These factors were categorized into broader themes: political, economic, cultural, and natural influences. An expert panel, including engineers, architects, and contractors, refined the factor list. A five-point Likert scale questionnaire was developed and administered to 120 respondents from various roles within the Chinese construction industry. Data analysis utilized the Relative Importance Index (RII) to rank the factors. Cronbach's alpha test validated the reliability of the survey data (α = 0.909 for primary factors and α = 0.972 for secondary factors). The findings are presented using stacked bar plots, doughnut diagrams, frequency distributions, and ridgeline charts to provide a detailed view of the survey responses.

The statistical analysis, using the RII, revealed that "Architectural and engineering mechanical factors" (RII = 0.8149) was the most significant primary factor influencing housing construction technology in the Desakota communities. Other primary factors, all with RII values above 0.7, included project adaptability and maintainability, construction project environment and market conditions, sustainable construction materials and resources, economic benefits of the project, and human factors of participants and users. Among the secondary factors, "Cost, financial, and economic evaluation" and "Analysis of the impact of the natural environment on buildings" shared the top rank (RII = 0.823). Other highly ranked secondary factors (RII > 0.8) included reasonable maintenance and replacement processes, support from authorities and policies, proper waste disposal, project management awareness, efficient material supply chains, use of resource-friendly materials, and consideration of aging and low-carbon policies. The data analysis showed the internal consistency of the data is excellent, validating the quality of the results.

The findings highlight the interconnectedness of various factors in shaping housing construction technologies in China's Desakota regions. The top-ranked factors, emphasizing both technical aspects (architectural and engineering) and economic considerations (cost and financial evaluation), underscore the need for a holistic approach to development. The strong emphasis on environmental analysis reflects the growing awareness of sustainability concerns. The results directly address the research question by providing a ranked list of influential factors, enabling stakeholders to prioritize resource allocation and policy development. These findings are relevant to the field by contributing a unique perspective on housing construction in rapidly urbanizing semi-rural areas, offering a framework applicable beyond China.

This study provides valuable insights into the key drivers of housing construction technology in China's Desakota regions. The tiered relationship between architectural factors, environmental concerns, project management, supply chain efficiency, and financial considerations offers a comprehensive framework for sustainable development. Future research should focus on longitudinal studies to track changes in these factors over time, exploring the impact of specific policies and interventions. Comparative studies across different Desakota regions and other semi-urban areas globally would further enhance understanding and promote best practices.

This study's sample size (120 respondents) might limit the generalizability of the findings. The reliance on the RII approach for data analysis could be complemented by other statistical methods. Future research should include a larger, more diverse sample, employing more sophisticated statistical analyses and incorporating qualitative data to provide a richer understanding of the complexities influencing housing construction technology in these dynamic regions. The study focused primarily on the perspective of those involved in the construction process itself, and future studies could benefit from incorporating the views of residents and other stakeholders.