Exploring fuzzy AHP approaches for quality management control practices in public building construction projects

Abstract

The construction industry has a significant multiplier effect on the economy as a whole. It provides the basis upon which other sectors can grow by constructing the physical facilities required for the production and distribution of goods and services. Building construction projects is one of the major development constraints in developing countries since their development highly depends on the growth of their physical infrastructures. Developing countries allocate a considerable amount of their scarce financial resources towards the development of their infrastructure needs. However, most of these infrastructure projects in developing countries encounter considerable quality management controlling problems, especially in public building construction projects. These results in decreasing customer satisfaction, lower productivity, and decreased service delivery times. Thus, the study focuses on exploring fuzzy AHP approaches for quality management control practices in public building construction projects. The data analysis for this study was carried out by using fuzzy AHP methods. This method is used to determine the preference weights of the input variables and for ranking. To achieve the objective, the data were collected from primary and secondary sources. Microsoft Excel was used as an analysis tool. The study revealed that quality management plans and quality management control tools are identified as mostly practiced quality management control systems in public building construction projects. Finally, it can be recommended that the project participants implement and communicate the organization’s mission, vision, strategy, policies, and processes throughout the organization to enhance the productivity of the projects.

Keywords:

• Construction projects
• fuzzy AHP
• quality
• and quality management control

Reviewing editor:

• Sanjay Kumar Shukla, Senior Editor, Edith Cowan University, Australia

Subjects:

• Civil, Environmental and Geotechnical Engineering
• Engineering Economics
• Engineering Management

Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Notes on contributors

Girmay Getawa Ayalew

Girmay Getawa Ayalew is currently working as a lecturer at the Woldia Institute of Technology, Woldia University, P.O. Box 400, Woldia, Ethiopia. He is former a lecturer at the Gondar Institute of Technology, University of Gondar, P.O. Box 196, Gondar, Ethiopia. He received his MSc degree in Construction Engineering and Management from the University of Gondar, Ethiopia. His research interest includes BIM, Fuzzy AHP, Artificial intelligence, Quality Management, and Machine learning algorithm. Email: [email protected] Institutional Email: [email protected]

Lidiya Admasu Alemneh

Lidiya Admasu Alemneh is working as a lecturer at the Gondar Institute of Technology, University of Gondar, P.O. Box 196, Gondar, Ethiopia. She received her MSc degree in Construction Engineering and Management from the University of Gondar, Ethiopia. Her research interest includes Quality Management, Fuzzy AHP, and Project Management. Email: [email protected] Institutional Email: [email protected]

Genet Melkamu Ayalew

Genet Melkamu Ayalew is currently working as a lecturer at the Woldia Institute of Technology, Woldia University, P.O. Box 400, Woldia, Ethiopia. She is former a lecturer at the Gondar Institute of Technology, University of Gondar, P.O. Box 196, Gondar, Ethiopia. She received her MSc degree in Construction Engineering and Management from the University of Gondar, Ethiopia. Her research interest includes Quality Management, Fuzzy AHP, and Regression Modeling. Email: [email protected] Institutional Email: [email protected]