Gurmu, A T and Ongkowijoyo, C S (2020) Predicting construction labor productivity based on implementation levels of human resource management practices. Journal of Construction Engineering and Management, 146(3): 04019115, ISSN 0733-9364
Abstract
The prediction of the odds of achieving higher or lower productivity as compared to some baseline productivity is one of the important steps to consider while analyzing labor productivity in construction projects. The objective of this research is to build a logistic regression model that can be used to estimate the productivity of building projects based on the levels of planning or implementation of human resource management practices. Quantitative data were collected from 39 contractors who worked on multistory building projects completed between 2011 and 2016. Correlation analysis was carried out and the associations between productivity, human resource management (HRM) practices, company profiles, and project characteristics were investigated. Logistic regression analysis was conducted to develop the probability-based labor productivity prediction model. Project delay is found to be negatively correlated with HRM practices, whereas company size is positively associated with HRM practices. A scoring tool to measure the levels of HRM practice implementation on building projects was developed. On that basis, a logistic regression model of HRM practices and productivity was built. This study contributes to the body of knowledge by proposing a tool that can be used to assess the odds of having high productivity based on the implementation levels of HRM practices on a certain building project.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | building project; construction labor productivity; human resource management practices |
| Index terms: | project delay, body of knowledge, construction project, prediction model, human resource management, implementation, estimate, labour productivity, logistic regression analysis, construction labour, correlation analysis, productivity, logistic regression |
| Subjects: | contractual arrangements, knowledge management, prediction and forecasting, financial and cost management, management, production management, project controls, statistical analysis |
| Topics: | Human Resources, Site Management, Time Control, Information Management, Project Management, Research Practice, Business Strategy, Cost Management, Procurement |
| Descriptive scope: | 3 PCA |
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