Project characteristic-based performance prediction model for school constructions: hierarchical regression approach
DOI:
https://doi.org/10.7764/RDLC.23.2.296Abstract
Project underperformance remains a significant concern in the construction industry. The majority of prior studies have focused on identifying the subjective factors that affect project performance. However, there are currently no in-depth studies evaluating the influence of project characteristics and managerial/organizational obstacles on construction project performance for design-bid-build projects using empirical data. Therefore, this study aims to present a predictive model that illustrates the correlation between project characteristics, managerial/organizational complexity and difficulties, and construction project performance. Project data relating to the construction of 101 public schools within a developing country was collected. Subsequently, the project characteristics were identified, and two performance indicators (schedule performance index and cost performance index) were calculated for each project. A survey was conducted with construction professionals who took part in all of the control and management processes of these school projects to evaluate their managerial and organizational difficulties. Hierarchical regression model approach and correlation analyses were employed to develop the predictor model. The results indicate that factors such as location, school type, and project duration significantly predict both the schedule performance and managerial and organizational difficulties in school construction. An indirect correlation, rather than a direct association, was found between schedule performance and managerial and organizational difficulties. The proposed model will be a helpful guide for construction professionals, engineering managers and government decision-makers seeking to improve the performance of "design-bid-build" school construction projects. We suggest integrating the qualification-based selection (QBS) system into traditional procurement methods for public investments.
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