Model Labor Productivity of Concrete Pouring in Building Construction Projects Using Multiple Regression Analysis: A Case of Selected Public Construction Projects in Adama.

Abstract

Construction industry is considered to be one of the important contributor key factors in the economy of any country, especially the developing countries. The main objective of this thesis is to develop labor productivity model for the building construction industry regarding concrete pouring. Increasing the construction work productivity benefits a contractor/client in several ways. Therefore measuring productivity, identifying factors affecting productivity and use productivity modeling approaches methods should be a major and continual concern for construction sector to increase the probability of projects to be completed as per the budgeted cost and specified time. Data collection method that were employed under this study were primary data from a construction worker(s) at cites.The data were collected by trained data collectors fromMarch 4, 2004 to April 19, 2004 using a standard, structured and pre-tested questionnaire which design to have both qualitative and quantitative data relevant to the study problem. Construction labor productivity is influenced by a multitude of factors. Pearson chi-square test is asymptotically equivalent to the likelihood ratio; hence, it was used in the analysis. The preliminary analysis has been done to know which of the variables appears to have a strong association with labor productivity and the results were described under univariate analysis section. Productivity models analyze and estimate the impact of these various factors on labor productivity. In the research, multiple regression analysis was used to develop a model to quantify the impact of the influential factors on labor productivity. The multiple linear regression analysis showed that ; Rainfall, Labor Physical fatigue, Materials Delay, Lack of required construction materials, Crew size, Poor working condition, Inadequate formwork and/or temporal transport structure during execution, Time lost – rework, and Lack of labor supervision, were major factors that had a significant contribution with labor productivity. Based on results obtained from the model, we observed that some of the assumed factors (nine (9)) factors were found to be influential factors that are assumed to maximizing labor productivity rate of concrete pouring. From the fitted regression model, it has been indicated that the rate of labor productivity varies by the condition of laborer as they becomes tired or not (Fatigue). The odds of being not productive having tired were 3.381 times more likely than those laborers which not/less tired.The other significant variables were also be interpreted based on the odds multiplier or odds ratio with an odds ratio of one for the reference category, and all other groups are compared on the basis of the reference group. Hence, awareness creations have to be made toward these significant predictors’ variables. It is recommended that further studies, involving data collection from more number of construction sites, are carried out to study the impact of labor related and various other factors on productivity of concrete pouring.