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| dc.contributor.author | Mikiyas, Yazew Berie | |
| dc.date.accessioned | 2024-10-21T07:19:58Z | |
| dc.date.available | 2024-10-21T07:19:58Z | |
| dc.date.issued | 2022-07 | |
| dc.identifier.uri | http://ir.bdu.edu.et/handle/123456789/16046 | |
| dc.description.abstract | Construction sector plays a leading role in economic growth for countries all around the world and since construction is a labor-intensive industry, Productivity taken as a primary driving force for economic development. Enhanced productivity helps contractors not only to be more efficient and profitable but, knowing actual productivity level helps them to estimate and be more competitive during bidding for projects. The main objective of this research was to develop forecasting model that helps construction stakeholders to predict construction labor productivity of block works by using multivariate regression technique. In order to attain the objective, a detailed literature review was done and 32 factors that had tangible impact on construction labor productivity were listed and grouped in 8 groups namely: Manpower related, Motivation related, Materials and tools related, Supervision related, Project related, Time related, Quality related and External factors. A questionnaire survey was conducted on ongoing building construction projects in Bahir Dar city. Simple random sampling technique was used to collect the data’s. Based on the result of the survey, from the 31 factors 8 were selected as most significant factors based on their RII value. These nine factors were then subjected to Principal component analysis method in order to reduce their number, and four factors (Crew size, Labor’s skill, Store location and Construction method) were factored out for the model formulation process. From the collected data 80% were used in the training set or model formulation. Multi-Variate regression was done using SPSS (statistical package for social studies) to generate the forecasting model. A forward selection method was used in developing the model, which resulted in R2 value of 77.7% which indicates a good predicting capability of the model. Finally, the developed model was validated by using the remaining 20% of collected data and resulted in small amount of mean average percentage error (MAPE=5.19%). The developed predicting model helps construction stakeholders mainly contractors in Bahir Dar city in the initial stages of construction by providing them a predicting formula. And also Contractors are advised to give serious attention for the factors listed out in this paper as they have a great impact in affecting construction labor productivity. Keywords: Construction labor productivity, Model formulation, Multi-variate regression, Productivity | en_US |
| dc.language.iso | en_US | en_US |
| dc.title | DEVELOPMENT OF CONSTRUCTION LABOR PRODUCTIVITY ESTIMATION MODEL FOR BLOCK WORK IN BAHIR DAR CITY PUBLIC BUILDING PROJECTS USING MULTI-VARIATE REGRESSION ANALYSIS | en_US |
| dc.type | Thesis | en_US |
