Modelling masonry labour productivity using multiple regression

Thomas, A V and Sudhakumar, J (2014) Modelling masonry labour productivity using multiple regression. In: Raiden, A and Aboagye-Nimo, E (eds.) Proceedings of 30th Annual ARCOM Conference, 1-3 September 2014, Portsmouth, UK.

Abstract

Construction labour productivity is influenced by a multitude of factors. Productivity models analyze and estimate the impact of the various factors on productivity. In the present research, multiple regression analysis was used to develop a model to quantify the impact of the influential factors on masonry labour productivity, in the context of a developing country. Previous studies to develop productivity models relied on data collected through questionnaires, wherein the influence of various factors was measured on a qualitative scale. The present study, however, utilized quantitative data directly collected from two case study projects, to develop the model. The regression model identified excessive overtime and material delays as the major factors impacting productivity. The mode of employment of labour was also found to have a significant impact on productivity. Sensitivity analysis was also performed to identify trends of the factors. The significant variables identified by the regression model emphasize the importance of efficient resource planning in achieving high labour productivity.

Item Type: Conference Paper (Paper)
Uncontrolled Keywords: labour productivity; modelling; regression
Index terms: case study, construction labour, questionnaire, influential factor, sensitivity analysis, regression model, employment, multiple regression analysis, labour productivity, developing country, multiple-regression, modelling, estimate, productivity, resource planning
Subjects: development economics, financial and cost management, resource management, analytical methods, data collection methods, management, statistical analysis, risk assessment, environmental hazards
Topics: International Construction, Cost Management, Engineering Principles, Human Resources, Business Strategy, Risk Management, Site Management, Research Practice, Sustainability
Descriptive scope: 4 PCEA

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