| description abstract | Construction project productivity can be enhanced by the implementation of good management practices. The purposes of this research are to identify construction equipment management practices that have the potential to improve productivity in multistory building projects, develop a tool for measuring such practices, and on that basis, build a logistic regression model for predicting the probability of exceeding a baseline productivity factor when the levels of implementation of equipment management practices are known. The research adopted a two-phase exploratory sequential mixed-methods design. During Phase I, in-depth interviews were conducted with 19 experts who have been involved in the delivery of multistory building projects. The qualitative data were analyzed, and construction equipment management practices that have the potential to improve productivity were identified. In Phase II, data were collected from 39 principal contractors on 39 projects using questionnaires. The quantitative data were analyzed to prioritize the practices identified in Phase I, and on that basis, a scoring tool for measuring the practices was developed; a logistic regression model was also developed for predicting the probability of exceeding baseline productivity factor using a sigmoid graph when the score of the practices is known. Construction equipment maintenance, construction equipment procurement plans, and construction equipment productivity analysis are identified as the three construction equipment management practices that could improve productivity in multistory building projects. Contractors can use the probability-based predictive model to assess the risk of low productivity for specific levels of implementations of construction equipment management practices. This research contributes to the body of knowledge by developing a construction equipment management practices measuring, planning, monitoring, and evaluating tool in the context of multistory building projects. Also, the logistic regression model can be used to test whether a certain level of implementation of a construction equipment management practice might be associated with higher or lower productivity compared to the baseline. | |
