摘要：
We will talk about network data envelopment analysis (DEA) and performance evaluation of supply chains. In the first part, we introduce multi-stage DEA models and examine limitations of the multi-stage DEA model with additive efficiency decomposition, which has been widely used in the literature. We create taxonomy for the multi-stage DEA models and show when the decomposition weights can be non-increasing. When the decomposition weight for a stage is deemed reflective of the stage's relative importance, this property then implies that upstream stages (regardless the stage efficiency scores) in the model will obtain higher priority inefficiency decomposition. We also find that the non-increasing weights can affect the evaluation of overall and stage efficiency scores and discuss the multi-stage DEA model with constant decomposition weights as an alternative. In the second part, we integrate stochastic multi-criteria acceptability analysis (SMAA) and DEA, and propose a “two-stage SMAA-DEA” for efficiency evaluation and ranking of supply chains with stochastic criteria values. Two stochastic efficiency measures are defined for supply chain efficiency evaluation in the model. In addition, the model provides rank acceptability and holistic acceptability index for the supply chain ranking. The developed model extends two-stage DEA models to handle uncertain or imprecise inputs, intermediate measures, and outputs using stochastic distributions, and allows for variable process weights.
报告人简介：
昂胜，管理科学与工程专业博士，中国科学技术大学特任副研究员。于2015年毕业于中国科学技术大学管理学院，曾在新加坡南洋理工大学南洋商学院（CSC联合培养博士生项目）、美国华盛顿大学Foster商学院等交流访问。主要研究领域为评价理论与决策、供应链管理等。主持国家自然科学基金青年项目、中国博士后科学基金特别资助和面上资助（一等）项目、安徽省自然科学基金面上项目等，并参与国家自然科学基金重点项目和重大项目等研究课题。担任国际学术期刊International Journal of Applied Management Science编委，在EJOR、OMEGA、JORS、ANOR、IJPR、Expert Systems等国际学术期刊上发表学术论文30余篇。入选教育部课程思政教学名师和教学团队（2021），获得中国优选法统筹法与经济数学研究会评价方法与应用分会优秀论文奖（2019）等。
时间：2021年10月21日周四下午14：00
线上腾讯会议：会议号733 139 2055