Optimum house delivery decision model from the government's and recipients' point-of-view

Mahdi, I M; Al-Reshaid, K and Fereig, S M (2006) Optimum house delivery decision model from the government's and recipients' point-of-view. Engineering, Construction and Architectural Management, 13(4), pp. 413-430. ISSN 09699988

Abstract

Purpose - The purpose of this paper is to look into the mass production of dwelling units and the conflict encountered when the economics versus quality, sometimes resulting in a waste of public funding resources and extra re-building time. Design/methodology/approach - This paper proposes a decision model for deciding the optimum house delivery alternatives for both the recipients and the Government. The decision model is designed using the analytical hierarchy process. Where multiple criteria are incorporated for such as waiting time, citizen satisfaction, and quality of work, house delivery-time, cost, losses and finally, management responsibility. Findings - Partially constructed houses enable the possibility of many alternatives by the recipients, which in turn avoids the drawbacks of rebuilding and at the same time, maintains work quality. The partially constructed housing system is proved to be effective in making a trade-off between the government purposes and recipients desires, but with a variable percentage of partial construction. Originalty/value - The analysis of the surveys stresses the importance of different alternatives within the partially constructed housing system in order to reduce waiting time and construction cost thus increases the satisfaction of occupants. The validity of this study continues to be effective to this date, as the Government's housing policies have not yet changed or streamlined, consequently re-building continues to be the theme of many public houses after hand-over to recipients.

Item Type: Article
Uncontrolled Keywords: analytical hierarchy process; decision making; housing; Kuwait
Date Deposited: 11 Apr 2025 15:08
Last Modified: 11 Apr 2025 15:08