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6-14 美国Adelphi大学商学院教授黄志民学术讲座:Methodology and Critical Thinking in Modeling-Data Envelopment Analysis (DEA)

题目:Methodology and Critical Thinking in Modeling-Data Envelopment Analysis (DEA)

主讲人:黄志民 教授 (美国Adelphi大学商学院)

时间:2017年6月14日(周三)下午14:30-16:30

地点:主楼六层

主讲人简介:

    黄志民,美国Adelphi大学商学院教授,The University of Texas at Austin运营管理博士 (1991),Journal of Modeling in Management 主编,International Journal of Information Technology and Decision Making,International Journal of Sustainable Society,International Journal of Society Systems Science等杂志的编委,曾担任OMEGA: International Journal of Management Science副主编,主编了包括 Annals of Operations Research等多个杂志的特刊,同时为30多个国际性杂志及许多基金和出版社审阅论文和书稿。黄志民在管理、经济、运筹等一流学术刋 物上共发表文章80多篇,其中,有2篇发表在决策科学学科排名第1的杂志Decision Sciences上,有11篇发表在运筹学学科排名前3、DEA领域排名第1的杂志European Journal of Operational Research上,有1篇收集在由世界著名管理经济学家Cooper等编辑的“数据包络分析手册”(Handbook of DEA)一书中。根据SCI和SSCI的统计数据,到2017年5月,黄志民共有70篇论文被检索,并被5,000多篇论文引用。被引用最多的两篇论文 是:“Polyhedral Cone-Ratio DEA Models with an Illustrative Application to Large Commercial Banks,”(发表在Journal of Econometrics)和“Cone Ratio Data Envelopment Analysis and Multi- objective Programming,” (发表在International Journal of Systems Science),被引用次数分别达到780多次和560多次。 这些文章中涉及到的一个重要领域是数据包络分析,该理论体系是由运筹学泰斗、管理科学创始人Charnes和Cooper在1978年建立 (Charnes是黄志民的博士学位导师, 曾入围1974年诺贝尔经济学奖最终3人角逐名单)。 黄志民和Charnes、Cooper进一步发展了数据包络分析有关理论和模型,他们发表的文章中有5篇创立了经典理论,有2篇建立了经典模型,而以他们 名字命名的“锥比率”Cone Ratio DEA模型和“满意度”Satisficing模型被学术界认为是最有影响的DEA模型之一。在供应链研究方面,黄志民教授是合作广告 (cooperative advertising)这一领域的主要开创者。目前,在合作广告这一领域引用次数最多的3 篇论文(论文引用次数分别达到377, 283, 247次),黄志民教授都是其主要作者。

内容介绍:

    This presentation deals with modeling development of evaluating activities of organizations such as business firms, government agencies, hospitals, educational institutions, etc. Problems and limitations are incurred in traditional attempts to evaluate efficiency when multiple outputs and multiple inputs need to be taken into account. Data Envelopment Analysis (DEA) can be used to deal with some of these problems. The relatively new approach embodied in DEA does not require the user to prescribe weights to be attached to each input and output, as in the usual index number approaches, and it also does not require prescribing the functional forms that are needed in statistical regress approaches to these topics. We are going to provide a systematic presentation of major developments of few important DEA models that have appeared in the literature.  

 

(承办:能源与环境政策研究中心,科研与学术交流中心)