Gurmu, A T and Aibinu, A A (2017) Construction equipment management practices for improving labor productivity in multistory building construction projects. Journal of Construction Engineering and Management, 143(10): 04017081, ISSN 0733-9364
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Australia; building projects; construction equipment management practices; labor and personnel issues; logistic regression; productivity |
| Index terms: | construction project, management practice, questionnaire, body of knowledge, personnel, interview, principal contractor, equipment management, building construction, monitoring, labour productivity, implementation, construction equipment, logistic regression, productivity, Australia |
| Subjects: | data collection methods, control systems, practitioner, operational management, contractual arrangements, knowledge management, management, construction equipment, Geography, production management, building construction, statistical analysis |
| Topics: | Information Management, Research Practice, Geographical Context, Project Management, Business Strategy, Plant and Equipment, Construction Technology, Procurement, Roles and Professions, Human Resources, Site Management |
| Descriptive scope: | 4 PCEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here