NIMBY Phenomenon and Construction of a Subjective Risk Assessment Framework for Major Engineering Projects: A Study Using the Delphi Method

NIMBYs are an increasingly common phenomenon in major construction projects, and pose significant challenges to project progress and social stability. In this study, the Delphi method was used to develop a methodology for the assessment of the risk of NIMBY in terms of four dimensions, such as environmental safety, psychological stability, rational attitude and government credibility. The study used Python to write a scoring model that combines hierarchical analysis and entropy weighting to determine the importance of each indicator, and also used Monte Carlo methods to optimise the model's performance. The study also involved the development of a web-based assessment tool that is accessible to a number of people at the same time. Experimental results show that this assessment method outperforms the traditional method in terms of accuracy, stability and computational efficiency, providing reliable technical support for risk assessment and decision-making in major engineering projects and playing an important role in ensuring smooth project progress.

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Published
2025-05-16
DOI
https://doi.org/10.1145/3757110.3757113
Primary Topic
Construction Project Management and Performance
Type
article
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article

NIMBY Phenomenon and Construction of a Subjective Risk Assessment Framework for Major Engineering Projects: A Study Using the Delphi Method

Zhengya ZHANG
Construction Project Management and Performance
article

NIMBY Phenomenon and Construction of a Subjective Risk Assessment Framework for Major Engineering Projects: A Study Using the Delphi Method

Zhengya ZHANG
article en

Abstract

NIMBYs are an increasingly common phenomenon in major construction projects, and pose significant challenges to project progress and social stability. In this study, the Delphi method was used to develop a methodology for the assessment of the risk of NIMBY in terms of four dimensions, such as environmental safety, psychological stability, rational attitude and government credibility. The study used Python to write a scoring model that combines hierarchical analysis and entropy weighting to determine the importance of each indicator, and also used Monte Carlo methods to optimise the model's performance. The study also involved the development of a web-based assessment tool that is accessible to a number of people at the same time. Experimental results show that this assessment method outperforms the traditional method in terms of accuracy, stability and computational efficiency, providing reliable technical support for risk assessment and decision-making in major engineering projects and playing an important role in ensuring smooth project progress.

Hainan University (CN), Hainan Agricultural School (CN)
Openalex Percentile: Top 67%
Construction Project Management and Performance
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