Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 10 results ...
Arif, M, Al Zubi, M, Gupta, A D, Egbu, C, Walton, R O and Islam, R (2017) Knowledge sharing maturity model for Jordanian construction sector. Engineering, Construction and Architectural Management, 24(01), 170-88.
Asiedu, R O, Frempong, N K and Alfen, H W (2017) Predicting likelihood of cost overrun in educational projects. Engineering, Construction and Architectural Management, 24(01), 21-39.
Chang-Richards, Y, Wilkinson, S, Seville, E and Brunsdon, D (2017) Effects of a major disaster on skills shortages in the construction industry: Lessons learned from New Zealand. Engineering, Construction and Architectural Management, 24(01), 2-20.
Davies, K, McMeel, D J and Wilkinson, S (2017) Making friends with Frankenstein: Hybrid practice in BIM. Engineering, Construction and Architectural Management, 24(01), 78-93.
Kärnä, S and Junnonen, J-M (2017) Designers’ performance evaluation in construction projects. Engineering, Construction and Architectural Management, 24(01), 154-69.
Kalutara, P, Zhang, G, Setunge, S and Wakefield, R (2017) Factors that influence Australian community buildings’ sustainable management. Engineering, Construction and Architectural Management, 24(01), 94-117.
Lu, W, Hua, Y and Zhang, S (2017) Logistic regression analysis for factors influencing cost performance of design-bid-build and design-build projects. Engineering, Construction and Architectural Management, 24(01), 118-32.
Lu, W, Li, Z and Wang, S (2017) The role of justice for cooperation and contract’s moderating effect in construction dispute negotiation. Engineering, Construction and Architectural Management, 24(01), 133-53.
Semaan, N and Salem, M (2017) A deterministic contractor selection decision-support system for competitive bidding. Engineering, Construction and Architectural Management, 24(01), 61-77.
- Type: Journal Article
- Keywords: project management; decision making; selection; decision support systems; construction management; performance criteria
- ISBN/ISSN:
- URL: https://doi.org/10.1108/ECAM-06-2015-0094
- Abstract:
Purpose The construction industry today is one of the biggest industries in the world. As projects continue to grow in complexity, project management continues to evolve. Contractor selection is a difficult task that owners and project managers face. Although previously researchers have worked on the subject of contractor selection, a comprehensive decision support system for contractor selection has not yet been developed. Recent reports of major delays and cost overruns in mega projects highlight the need for a model that is able to be flexible and comprehensive becomes evident. The paper aims to discuss these issues. Design/methodology/approach The research focuses on obtaining insights from field experts using both quantitative and qualitative methods. Then, a model was developed in the light of the data collected. Accordingly, the model was tested on a case study. Findings This paper presents a model for contractor selection that is wholesome in its take on the topic. The model incorporates both managerial and technical aspects of the problem. The model was tested on a case study and it was proven to be feasible in real world applications. The contractor selection decision support system serves the needs of both academics and industry managers, as an integral part of project management. Originality/value The model presented in this paper is innovative in its take on the problems. MCDA tools have been uniquely modified in this paper to cater to the needs of the selection problem while accounting for the criteria hierarchy that incorporates aspects that are instrumental for proper evaluation of a contractor’s likelihood of success.
Shahtaheri, M, Haas, C T and Salimi, T (2017) A multi-dimensional joint confidence limit approach to mixed mode planning for round-the-clock projects. Engineering, Construction and Architectural Management, 24(01), 40-60.