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| dc.contributor.author | MELAKU, ADANE MENGISTU | |
| dc.date.accessioned | 2024-02-05T06:57:46Z | |
| dc.date.available | 2024-02-05T06:57:46Z | |
| dc.date.issued | 2023-06-05 | |
| dc.identifier.uri | http://ir.bdu.edu.et/handle/123456789/15619 | |
| dc.description.abstract | Construction industry is complex in its nature since it involves large number of stakeholders. In Ethiopia the number of road projects is increasing from time to time due to the emphasis given to the sector. However, it has become difficult to complete projects in the allocated cost, time and quality. The main objective of this research was to develop forecasting model that helps construction stakeholders to precisely predict construction performance of a road construction projects by using multi-variate regression technique. Detailed literature review was done and 61 factors that had tangible impact on construction performance were listed and grouped in 7 groups namely: Cost, Time, Quality, Productivity, Client Satisfaction, Health and safety and Innovation and Learning. A questionnaire survey was conducted on ongoing Federal road construction projects in the Central Region. Total population sampling technique was used to collect the data since the population to be studied is limited. Based on the result of the survey, from the 61 factors 9 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 (Delay in payments, Cash flow Problem, Resource Availability and Sequencing Practice according to schedule) 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 to generate the forecasting model. An Enter selection method was used in developing the model, which resulted in R 2 value of 84.9% 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=2.98%). The developed predicting model helps construction stakeholders mainly contractors involving in road constructions in the initial and construction stages 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 performance. Keywords: Construction performance, Model formulation, Multi-variate regression | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Civil and Water Resources Engineering | en_US |
| dc.title | DEVELOPMENT OF A PREDICTIVE REGRESSION MODEL FOR ESTIMATING CONSTRUCTION PERFORMANCE OF ETHIOPIAN FEDERAL ROAD PROJECTS | en_US |
| dc.type | Thesis | en_US |
