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This paper describes a multiple‐criteria decision support system (MCDSS) for the selection of the most appropriate contractor. The system can accommodate the unique characteristics of a project in addition to the qualifications and capabilities of those contractors assessed. The system first evaluates the list of contractors by matching their qualifications with specific project conditions. A short list of eligible contractors is thus selected and further the MCDSS compares the current capabilities of the short listed contractors and their plans for the project under consideration, to select the most appropriate contractor. The Delphi method was used to evoke expertise and obtain reliable assessment values for all criteria related to the contractor qualification, while the analytic hierarchy process (AHP) was used to assess the specific project conditions. The system can be easily modified to adopt specific conditions of the proposed project and also to facilitate the decision maker in explaining the reasons for the elimination of excluded contractor.

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.

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.

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.

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.

The purpose of this paper is to build a tested model and framework for describing the structure and factors influencing customer satisfaction in the construction industry.

The paper introduces a structural equation model illustrating the interdependencies of the factors influencing customer satisfaction. Data for the model are based on 831 assessments obtained from project customers with regard to the successfulness of the project.

The results show that customer satisfaction in construction is a complex phenomenon in which various factors have a different impact on the quality as perceived by the customer. Management and factors related to skills have a different impact on the factors describing the end result and methods of the project. According to this study, the contractor's ability to cooperate is divided into two directions: managing changes and communication. The result emphasises the significance of communication in project production. In order to improve their level of service, the contractors should focus on developing and improving their central processes. With regard to customer satisfaction, this stresses the significance of the entire selection of services and products the contractor offers.

Customer satisfaction has become a significant tool for measuring performance alongside the traditional, harder measurement tools. Although the demands of customer‐orientation and customer satisfaction have been acknowledged in the field, little attention has been paid to development of customer satisfaction and the factors involved.