Residents' Willingness Based on Principal Component Analysis and Logistic Regression Modeling

Authors

  • Pengfang Gao
  • Nuolin Yu
  • Yuze Gao
  • Tangzhen Li
  • Junhan Sun
  • Zhenhao Gao
  • Jiaxu Wang

DOI:

https://doi.org/10.54097/ng350c28

Keywords:

Green building, Principal component analysis, Logistic regression, Willingness to accept

Abstract

Under the background of the "dual-carbon" target and green transformation of the construction industry, the promotion of green buildings in Shandong Province is facing challenges due to the divergence of residents' perceptions and the insufficient motivation of enterprises. This paper analyzes residents' green building promotion from the dimensions of "utility outcome", "personal perception", "environmental impact", "government effectiveness", and "environmental impact" through 1141 residents' questionnaires using principal component analysis and logistic regression modeling. "government effectiveness" dimensions to analyze residents' willingness to accept green building. The results show that the degree of recognition by friends and relatives, the degree of trust in government policies, the positive role of media publicity and occupational differences are significant driving factors, the first three have a strong positive effect on the willingness to buy, and there are significant differences in the willingness of different occupational groups to accept. This study provides an actionable path for the promotion of green buildings in Shandong Province, which is of great theoretical and practical significance in cracking the bottleneck of promotion, promoting the low-carbon transformation of the construction industry, and helping the realization of the "dual-carbon" goal.

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Published

26-05-2025

Issue

Section

Articles

How to Cite

Gao, P., Yu, N., Gao, Y., Li, T., Sun, J., Gao, Z., & Wang, J. (2025). Residents’ Willingness Based on Principal Component Analysis and Logistic Regression Modeling. Mathematical Modeling and Algorithm Application, 5(1), 57-61. https://doi.org/10.54097/ng350c28