Study of relationship between rework and labor productivity in Building Construction Projects
DOI:
https://doi.org/10.7764/RDLC.19.1.30-41Keywords:
Productivity, rework, regression, prediction, buildingsAbstract
The objectives of this study included: (1) identifying the factors affecting construction labor productivity, (2) identifying the causes of rework in building projects, (3) addressing the relationship between labor productivity and rework using regression analysis based on data collected from building projects implemented in Palestine. The following steps were used in this study: (1) Questionnaire survey – stage 1: a questionnaire survey was carried out to identify the main factors affecting labor productivity and the main causes of rework on construction sites, (2) Questionnaire survey – stage 2: after identifying the significant causes of rework using factor analysis, a questionnaire survey was conducted to address the impact of these significant causes on labor productivity, (3) Prediction models: Data collected from 40 building construction projects were used to establish the regression models that describe the relation between rework and labor productivity on construction sites. The study concluded that the top factors affecting labor productivity are: lack of labor experience, payments delay, rework due to labor mistakes, lack of supervisor’s experience and materials shortage. The study also found that the top five rework causes in building projects are: lack of manpower skills, non-compliance with specifications, frequent change orders, inadequate job planning, and inadequate coordination and integration. Using regression analysis for data collected from 40 building construction projects, three predictive models were developed. The models indicated a significant relation between rework cost and labor productivity i.e the higher the rework cost the lower the construction productivity. This study is the first one that investigated the relationship between construction productivity and rework in Palestine, and that is why it is very important. Results would be helpful for researchers and construction professionals.
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