Develop a Decision Support System for Determining the Optimal Mark-up bid percent in Construction Projects

Abstract

ABSTRACT The Construction contracting is the ability to bid-successfully. Winning project tenders and making profit is the main contactor’s target to survive in the construction sector. While there are methods to calculate direct and indirect costs, there are fewer tools for estimating mark-ups. Therefore, Optimum bid mark-up decision is an important issue, to maximize possible profits, cover contingency and keeping bids at a competitive level. The bid markup decision in construction projects is a complex adaptive process performed by contractor in the pre-tender stage. Therefore, it requires significant experience and market knowledge. Due to the economic reform initiatives lately undertaken by the Egyptian government coupled with the ambitious development programs of infrastructure and the development of several new cities, there are new variables that add to the complexity of this process. These variables include high inflation, currency exchange changes, economic instability, removal of subsidies (utilities, fuel, etc.) & compressed construction deadlines. Cost Engineering makes it possible to increase profits by revealing qualitative and quantitative factors, so that special attention may be given to strengthening decision analysis, thereby evaluate existent unforeseen risk that absorb part or all of the normal profits. Hence, increase the importance of project management science. The objective of this research is to develop a Decision Support System (DSS) to generate the optimum bid markup for residential building projects. In forming this decision, there are various qualitative and quantitative factors. Thus, factors influencing the decision process identified and evaluated using Delphi technique, two round questionnaire survey to reflect a real decision. Then analyze the retrieved factors with stepwise regression statistical technique to generate highly impact factors. The decision support system consists of three modules; first, the Analytic Network Process (ANP)-Relative Module; second, Rating Module and the third is the financial forecast module. Finally, generate the optimum bid markup.