In the construction industry, the contractors are faced with two critical decisions. The contractors have to decide to bid a project or not. If yes, the contractors must decide on the proper markup size for the lowest bidder with a reasonable profit.
The dilemma of competitive bidding is to bid low enough to win the contract but high enough to make a profit. There are many variables that affect the contractors’ decisions to bid or not to bid, and how much to bid. This study proposes a “Bidding Decision Making for Construction Company Using Multi Criteria Prospect Model” (BD-MCPM) to assist contractors to make decision to bid on a project or not and determine a bid markup furthermore. Such model can optimize the markup size with an acceptable biding price.
This study presents a competitive bidding strategy model in setting a markup for projects in construction industry. The goal of BD-MCPM is to help a company to achieve its objectives in bidding. This study carries out 18 factors (10 factors for biding and 8 factors for markup size) that finally impact on the markup size.
For making decision on bid/no bid and markup size, this study employs Multi Criteria Prospect Model (MCPM) which links Fuzzy Preference Relations (FPR) and Cumulative Prospect Theory (CPT) to figure out proper weights and calculating prospect values. FPR is used to determine the relative weights of influential factors and CPT to evaluate the prospect values of markup size under various bidding situations. In CPT, utility functions reflect the characteristics of the project decision makers. Decision makers can handle a newly tendered project with their requirements and preferences. Besides, BD-MCPM has been implemented in the form of prototype software system (BD-MCPM system, BD-MCPMS).
As aforementioned descriptions, this study concludes:
(1) MCPM can be applied successfully to model the bid/no bid and markup size decision.
(2) BD-MCPM can improve the quality of the decision process used in setting a markup and can help a contractor to gain a competitive edge in bidding.
(3) For practice, BD-MCPM has been validated through actual project bids collected from surveys in Vietnamese construction companies. It brings out outstanding results which are some contributions of this study.

In the construction industry, the contractors are faced with two critical decisions. The contractors have to decide to bid a project or not. If yes, the contractors must decide on the proper markup size for the lowest bidder with a reasonable profit.
The dilemma of competitive bidding is to bid low enough to win the contract but high enough to make a profit. There are many variables that affect the contractors’ decisions to bid or not to bid, and how much to bid. This study proposes a “Bidding Decision Making for Construction Company Using Multi Criteria Prospect Model” (BD-MCPM) to assist contractors to make decision to bid on a project or not and determine a bid markup furthermore. Such model can optimize the markup size with an acceptable biding price.
This study presents a competitive bidding strategy model in setting a markup for projects in construction industry. The goal of BD-MCPM is to help a company to achieve its objectives in bidding. This study carries out 18 factors (10 factors for biding and 8 factors for markup size) that finally impact on the markup size.
For making decision on bid/no bid and markup size, this study employs Multi Criteria Prospect Model (MCPM) which links Fuzzy Preference Relations (FPR) and Cumulative Prospect Theory (CPT) to figure out proper weights and calculating prospect values. FPR is used to determine the relative weights of influential factors and CPT to evaluate the prospect values of markup size under various bidding situations. In CPT, utility functions reflect the characteristics of the project decision makers. Decision makers can handle a newly tendered project with their requirements and preferences. Besides, BD-MCPM has been implemented in the form of prototype software system (BD-MCPM system, BD-MCPMS).
As aforementioned descriptions, this study concludes:
(1) MCPM can be applied successfully to model the bid/no bid and markup size decision.
(2) BD-MCPM can improve the quality of the decision process used in setting a markup and can help a contractor to gain a competitive edge in bidding.
(3) For practice, BD-MCPM has been validated through actual project bids collected from surveys in Vietnamese construction companies. It brings out outstanding results which are some contributions of this study.

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