Assessment of Construction Risk Management Practices Through Questionnaire-Based Statistical Analysis
Keywords:
Construction Risk Management, SPSS, T-Test, ANOVA, Correlation Analysis, Regression Analysis, Risk Ranking.Abstract
Construction projects are exposed to various risks that can influence cost, time, quality, safety, and overall project performance. This study investigates major construction risks and the challenges associated with risk management through questionnaire-based statistical analysis. Data were collected from 126 construction professionals and analysed using IBM SPSS Statistics. The study applied descriptive statistics, reliability analysis, independent t-tests, ANOVA, correlation analysis, regression analysis, and risk ranking methods. Reliability analysis confirmed strong internal consistency, with Cronbach’s Alpha values above 0.90. Among the identified risks, safety risks recorded the highest mean score (4.0968), followed by technical and quality risks. Correlation analysis revealed strong positive relationships among the major risk categories, while regression analysis showed that implementation challenges had the strongest influence on overall project risk (β = 0.657, p < 0.001). The findings suggest that although risk management is widely recognised as essential in construction projects, its effective implementation is often constrained by limited awareness, inadequate training, and ineffective communication. The study therefore emphasises the importance of structured and data-driven risk management practices to improve project performance and reduce project uncertainties.
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