Applying Friedman’s Bidding Model Towards Lowest-Bid Procurement Utilizing the Monte Carlo Simulation
DOI:
https://doi.org/10.26593/josc.v3i2.7089Keywords:
bid to cost ratio, first order statistics, Friedman’s bidding model, government contracts, Monte Carlo SimulationAbstract
Under the lowest bid procurements, contractors find themselves in a competition in the process of contract bidding. When the rule dictates the lowest price as the contract winner, a high bid value would result in high profits but would have an unlikely chance to win the contract. A low bid would be more likely to win the contract but with lower to no profits. There are methods that solve the uncertainty of optimal bid value, such as Friedman’s model which achieves the optimal bid value using bid to cost ratios. Another method is to utilize the monte carlo simulation to model the prediction of the lowest bid for an upcoming projects. The study purpose is to find the optimal bid to cost value of the contractor based on the contractor’s past bidding records, the contractor’s true bidding cost estimate, and the opposing bidder’s bid value. Results show that the optimal bid to cost ratio for known number of bidders ranges from 1,1 for n=1 and 1,02 for n=8 in which n denotes the number of bidders. For unknown number of bidders, the value of the optimal bid to cost ratio is 1,07 with Gamma distribution and 1,08 with rayleigh distribution.
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