Pretendering Decision Model for Contractor Selection of Public Procurement Projects

Abstract

Selection of the most appropriate contractor is critical for a successful project. There has been no practical analytic model for objective determination of the most appropriate contractor selection method (CSM) before the tendering evaluation. Most existing models adopt the posttendering bidding data for a specific procurement project rather than those from all potential bidders who may enter the procurement market. To resolve the long-unsolved problem of the existing models, this paper proposes a pretendering contractor selection analysis model (PreCSAM) based on historical procurement data, which can determine the most appropriate of the three prevailing contractor selection methods, e.g., lowest tender (LT), best value (BV), and prequalified lowest tender (PQLT). The three-stage model validation of the proposed method revealed that the proposed PreCSAM is able to suggest a CSM with 100% correctness compared with those reported in literature; it also achieved a high precision rate (94.12%) of market range prediction for a retrospective analysis of 23 public building construction projects from 2012 to 2018 procurements by the Construction and Planning Agency of the Ministry of Interior, Taiwan. Most importantly, the proposed PreCSAM overcomes the limitations of posttendering analysis of all existing methods in determining CSM.