Quantitative Bid or No-Bid Decision-Support Model for Contractors: Fid-Bau Portal

Quantitative Bid or No-Bid Decision-Support Model for Contractors

Chisala, Maxwell L

AbstractThe bidding behavior of contractors in the Malawi contract construction market was investigated using a selected set of 75 bidding factors in a structured questionnaire survey administered to a random representative sample of contractors where contractors were asked to indicate the importance they attach to given bidding factors when making a bid or no-bid decision. A proposed simple additive weighted scoring (SAWS) model was used to generate importance weights of bidding factors and subjective importance scoring of internal (firm-related) and external (project-related and environment-related) factors affecting the bid or no-bid decision for a given bidding situation. Conclusions of contractor bid or no-bid decision behavior from the questionnaire study were corroborated with a semistructured interview study involving senior industry players deemed more familiar with real-life bid or no bid decision problems. Medium-to-large-sized contractors with high bid-win rates were found to have an importance scoring of internal factors not exceeding 50% of the importance scoring of external factors, whereas small contractors with high bid-win rates were found to have an importance scoring of internal factors not exceeding 45% of the importance scoring of external factors and hence offering quantitative criteria for when to pursue a bidding opportunity (bid) or not to pursue a bidding opportunity (no bid) on a new job in the studied contract construction market. The proposed bid or no-bid decision-support model was found to be 86% effective in predicting the actual decisions in 35 real-life bid or no-bid situations in a test study of the model in the Malawian contract construction market. The primary value of this study is the development of an effective and reliable tool for quantifying bid or no-bid decisions that is functional for any studied contract construction market with the potential to facilitate contractors’ establishing in-house procedures and managerial decision support systems likely to improve the quality of decision-making in the construction industry.