Measurement and spatiotemporal evolution characteristics analysis for the provincial development level of intelligent construction in China

Intelligent Construction (IC) is emerging as a transformative approach within the architecture, engineering, and construction (AEC) industry, garnering significant global attention. There exist considerable disparities in the development levels of IC across various provinces in China, leading to uneven advancement that complicates precise policy formulation and differential implementation. Previous studies have primarily evaluated IC at the project and enterprise levels, thus lacking a comprehensive measure of the provincial IC development level. To bridge this gap, this study introduces a quantitative method to assess provincial IC development levels in empirical data, analyzing their driving factors and spatiotemporal evolution. Initially, based on the Politics-Economy-Society-Technology (PEST) analysis model, 16 measurement indexes were identified through a combination of literature review and expert interviews. Original data for these indexes were acquired via policy and media news mining, along with literature and patent indexing, etc. Subsequently, a quantification method for each index was established. The “analytic network process (ANP), entropy weight, and game theory” integration method was used to calculate combination weights. Finally, the development level of IC was quantitatively measured based on the cloud matter-element model, and the spatiotemporal evolution characteristics of the provincial development level in China from 2012 to 2022 were analyzed. The results indicate that (1) the development level of IC in China is divided into four levels, and the overall development level is relatively low, with only Beijing, Shanghai, and Shandong ranking at level I. (2) The development level shows a trend of increasing from northwest to southeast, with policy and technological factors being the main driving forces. (3) There is a significant spatial positive correlation between the development levels of provinces, and their spatial agglomeration effects are gradually developing from coastal areas to inland areas. The research results provide a theoretical basis for stakeholders such as governments and enterprises to formulate differentiated development strategies for IC and also provide a reference for measuring the development level of IC and other fields in other countries.

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Publication Details

Journal
Journal of Civil Engineering and Management
Published
2025-05-15
DOI
https://doi.org/10.3846/jcem.2025.23767
Citations
1
Primary Topic
Regional Economic and Spatial Analysis
Type
article
Field-Weighted Citation Impact
3.13

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Measurement and spatiotemporal evolution characteristics analysis for the provincial development level of intelligent construction in China

Yudan Dou, Shengbin Ma, Zhong Liu, Xueya Yan et al.
1 citations
Journal of Civil Engineering and Management
Regional Economic and Spatial Analysis
3.13
article

Measurement and spatiotemporal evolution characteristics analysis for the provincial development level of intelligent construction in China

Yudan Dou, Shengbin Ma, Zhong Liu, Xueya Yan, Xin Guo
article en
1 citations

Abstract

Intelligent Construction (IC) is emerging as a transformative approach within the architecture, engineering, and construction (AEC) industry, garnering significant global attention. There exist considerable disparities in the development levels of IC across various provinces in China, leading to uneven advancement that complicates precise policy formulation and differential implementation. Previous studies have primarily evaluated IC at the project and enterprise levels, thus lacking a comprehensive measure of the provincial IC development level. To bridge this gap, this study introduces a quantitative method to assess provincial IC development levels in empirical data, analyzing their driving factors and spatiotemporal evolution. Initially, based on the Politics-Economy-Society-Technology (PEST) analysis model, 16 measurement indexes were identified through a combination of literature review and expert interviews. Original data for these indexes were acquired via policy and media news mining, along with literature and patent indexing, etc. Subsequently, a quantification method for each index was established. The “analytic network process (ANP), entropy weight, and game theory” integration method was used to calculate combination weights. Finally, the development level of IC was quantitatively measured based on the cloud matter-element model, and the spatiotemporal evolution characteristics of the provincial development level in China from 2012 to 2022 were analyzed. The results indicate that (1) the development level of IC in China is divided into four levels, and the overall development level is relatively low, with only Beijing, Shanghai, and Shandong ranking at level I. (2) The development level shows a trend of increasing from northwest to southeast, with policy and technological factors being the main driving forces. (3) There is a significant spatial positive correlation between the development levels of provinces, and their spatial agglomeration effects are gradually developing from coastal areas to inland areas. The research results provide a theoretical basis for stakeholders such as governments and enterprises to formulate differentiated development strategies for IC and also provide a reference for measuring the development level of IC and other fields in other countries.

Journal of Civil Engineering and ManagementVol. 31(5)
Dalian University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 8%
Regional Economic and Spatial Analysis
3.13
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