Mahmoudi Amin, Javed Saad Ahmed
Department of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing, 210096 China.
School of Business, Nanjing University of Information Science and Technology, Nanjing, 210044 China.
Group Decis Negot. 2022;31(5):1051-1096. doi: 10.1007/s10726-022-09790-1. Epub 2022 Aug 25.
A popular framework of the supplier selection process is usually characterized by problem definition, criteria formulation, supplier screening, and supplier selection. The literature review suggested limitations of this framework as it ignores the screening of criteria (beyond criteria weighing) and evaluators (buyers) and its inability to guide the supplier selection problems where a measure of confidence or trust is needed to confirm the reliability of the selected supplier. While extending de Boer's influential supplier selection framework, the current study argues that the supplier selection problem is not merely about ranking suppliers based on given criteria; instead, it involves evaluating criteria and evaluators as well. Guided by the theory of statistics and the Ordinal Priority Approach (OPA), the study pioneers a probabilistic approach of supplier evaluation and selection under incomplete information using a novel Confidence Level measure. The study suggests, the probability that a supplier shortlisted for selection is actually the optimum choice or not can be explained through a probability distribution, called W-distribution, therefore, confidently preventing the decision-makers from selecting the sub-optimum suppliers. The study presents a novel contribution to the theory of multiple-attribute decision-making through the OPA. The proposed approach can help build intelligent decision support systems to aid managers while providing them with early warning tools and suggestions to improve confidence in their selection.
供应商选择过程的一个流行框架通常具有问题定义、标准制定、供应商筛选和供应商选择等特点。文献综述表明了该框架的局限性，因为它忽略了标准（除标准权重外）和评估者（采购方）的筛选，并且无法指导在需要某种置信度或信任度来确认所选供应商可靠性的情况下的供应商选择问题。在扩展德布尔有影响力的供应商选择框架时，当前研究认为供应商选择问题不仅仅是根据给定标准对供应商进行排名；相反，它还涉及对标准和评估者的评估。在统计学理论和序数优先法（OPA）的指导下，该研究开创了一种在信息不完整情况下使用新颖的置信水平度量进行供应商评估和选择的概率方法。该研究表明，入围选择的供应商实际上是否为最佳选择的概率可以通过一种称为W分布的概率分布来解释，因此，可以自信地防止决策者选择次优供应商。该研究通过OPA对多属性决策理论做出了新颖贡献。所提出的方法可以帮助构建智能决策支持系统，以协助管理人员，同时为他们提供预警工具和建议，以提高他们选择的置信度。
