Bids evaluation and supplier selection (BESS) model: a hybrid MCDM framework for objective, transparent, and value-driven decision-making in public procurement

Public procurement regulations mandate that supplier selection be objective, transparent, and based on both price and non-price criteria. However, procuring agencies frequently face legal challenges due to unchecked discretion, ambiguous expert evaluations, and rank reversal issues that lead to suboptimal awards and bid protests. This study introduces the Bids Evaluation and Supplier Selection (BESS) framework, a hybrid Multi-Criteria Decision-Making (MCDM) approach that operationalizes regulatory requirements and enables auditable supplier selection. The framework contributes a novel methodology that: (i) categorizes evaluation criteria as Objective (Verifiable) and Subjective (Judgment-Dependent), consistent with the UNCITRAL Model Law's "to the extent practicable" standard (Article 11); (ii) employs Cloud Model Theory integrated with DEMATEL and BWM to address linguistic ambiguity in expert judgments, while using AHP with dual consistency checks for objective criteria; and (iii) applies PROBID for rank-stable rankings resistant to rank reversal, supplemented by utility graphs for objective trade-off visualization. The framework was validated on three real-world public tenders (N=22 bidders) representing two-stage, single stage, and emergency procurement methods. Monte Carlo simulations (10,000 iterations per case) confirmed robustness: the BESS framework identified optimal suppliers that traditional price-focused evaluations overlooked and identified stable leading alternatives, although the degree of dominance varied by procurement context and criterion group. Rank stability tests demonstrated that PROBID maintains original rankings when dominated alternatives are added, whereas TOPSIS and VIKOR exhibit rank reversal. The BESS framework provides public agencies with a regulation-aligned, auditable decision support approach for structuring supplier evaluation, improving transparency, and reducing reliance on undocumented discretionary judgments.