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Integrating exploratory factor analysis and fuzzy AHP models for assessing the factors affecting the performance of building construction projects: The case of Ethiopia.

Authors :
Ayalew, Girmay Getawa
Ayalew, Genet Melkamu
Meharie, Meseret Getnet
Source :
Cogent Engineering; 2023, Vol. 10 Issue 1, p1-38, 38p
Publication Year :
2023

Abstract

Project performance is a critical issue for the construction industry. The construction industry is complex in its nature because it contains a large number of parties involved in the planning, execution, and monitoring of all types of civil works. Moreover, construction industries are always unique and heterogeneous; they will always encounter many unforeseen events that will negatively affect the construction everywhere, and the construction projects suffer from many problems and complex issues in the performance of building projects. Therefore, the study was focused on assessing the factors affecting the performance of building projects. The study would employ an integrated methodology of factor analysis and fuzzy AHP methods. First, the factor analysis is used to classify and reduce the input variables and their variable coefficients are determined. Second, fuzzy AHP is used to determine the preference weights of the input variables, and for ranking. To achieve this objective, data were collected from primary and secondary sources. This study used an integrated methodology as a data analysis method, and SPSS software version 23 and Microsoft Excel were used as analysis tools. The study pointed out that project location (0.083), changes in design (0.068), market fluctuation (0.067), financial difficulties (0.066), and size of the project (0.064) are identified as the most significant factors that affect the performance of building construction projects. Finally, it can be recommended that the practitioners take appropriate actions in improving the performance of building projects, and the methodologies can be implemented to demonstrate its practicality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23311916
Volume :
10
Issue :
1
Database :
Complementary Index
Journal :
Cogent Engineering
Publication Type :
Academic Journal
Accession number :
174173102
Full Text :
https://doi.org/10.1080/23311916.2023.2243724