Geographical imbalance and influential characteristics of the green building market

Chang, R; He, T; Han, Y; Xue, R and Zhang, W E (2023) Geographical imbalance and influential characteristics of the green building market. Journal of Construction Engineering and Management, 149(10): 04023093, ISSN 0733-9364

Abstract

Green buildings have gained increasing momentum during the past decade, evidenced by an uptick in green building construction worldwide. To facilitate green building development, it is crucial to understand the current geographical distribution of green buildings, thereby identifying emerging markets and opportunities for future growth. However, very few studies investigated the spatial characteristics of the green building market and the factors influencing the distribution of green buildings. By examining the national green building market in the United States, we studied the spatial distribution patterns and significant influencing factors of the county-level US green building markets. Cluster mapping and hot spots of the green building markets were identified through spatial autocorrelation analysis. A spatial regression model with high performance (R2 of 0.83) was developed to identify the significant influencing factors. We found a statistically significant clustering phenomenon of county-level US green building markets. The spatial error model reveals that three factors, namely, the number of housing units, gross domestic product, and the local green building company index, significantly influence the number of green buildings at the county level. We also found that the county-level green building market is influenced by these factors of not only the host county, but also the neighboring counties. Our findings provide a useful reference for stakeholders' decision-making process concerning local green building market development.

Item Type: Article
Uncontrolled Keywords: geographical imbalance; green building market; spatial autocorrelation; spatial distribution; spatial regression
Index terms: hot spot, clustering, markets, regression model, influencing factor, spatial distribution, gross domestic product, decision-making process, mapping, green building, housing, United States, emerging market
Subjects: construction type, risk assessment, economic analysis, environmental science, data science, geographical analysis, Geography, spatial and geospatial analysis, design practice, statistical analysis, decision analysis
Topics: Risk Management, Sustainability, Construction Technology, Business Strategy, Geographical Context, Research Practice, Digital Applications, Design Practice, International Construction
Descriptive scope: 3 PCA

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