基于随机森林的制度同构与安全氛围对建设项目安全投资影响研究OA

Insufficient safety investment on construction projects hinders their safety performance.The present study therefore proposes a theoretical framework of"Institutional Isomorphism,Safety Climate and Safety Investment"by integrating the Institutional Isomorphism Theory and the Safety Climate The-ory.We employed correlation analysis and the random forest machine learning model on data from 953 valid questionnaires.Results demonstrate that safety climate serves as the core determinant of safety in-vestment behavior,with organizational and team safety climate jointly accounting for over 86.00%of the explanatory power.In contrast,institutional isomorphism exerts weak direct effect on safety invest-ment.However,it poses significant mediating effect via safety climate.Its mediating pathway contribu-ting 21.80%to the total impact,with normative isomorphism and mimetic isomorphism demonstrating notable effects.The present random forest model achieves an R2 value of 0.814,outperforming conven-tional linear analysis approaches in unraveling the complex nonlinear coupling relationships across mul-tiple variables.This study probes into the application of machine learning methods in construction safe-ty management and delineates the transmission mechanism underlying"institutional pressure,cultural response and investment behavior".It provides theoretical and practical implications for construction enterprises to synergistically optimize institutional compliance and cultivate safety cultures,enhancing the efficiency of safety resource allocation.