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The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author's years of research and teaching experiences.
It is difficult to evaluate an organization's performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective.
Conventional and new DEA approaches are presented and discussed using Excel spreadsheets - one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets.
DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA's ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores.
This book also provides an easy-to-use DEA software - DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject tothe capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.
List of contents
Chapter 1: Data Envelopment Analysis.- Chapter 2: Envelopment DEA Models.- Chapter 3: Multiplier DEA Model.- Chapter 4: DEA Cross Efficiency.- Chapter 5: Slack-Based DEA Models.- Chapter 6: Measure-Specific DEA Models.- Chapter 7: Non-radical DEA Models and DEA with Preference.- Chapter 8: Modeling Undesirable Measures.- Chapter 9: Context-dependent Data Envelopment Analysis.- Chapter 10: Super Efficiency.- Chapter 11: Sensitivity Analysis.- Chapter 12: Benchmarking Models.- Chapter 13: Returns-to-Scale.- Chapter 14: DEA Models for Two-Stage Network Processes.- Chapter 15: Models for Evaluating Supply Chains and Network Structures.- Chapter 16: Congestion.- Chapter 17: Identifying Critical Measures in DEA.- Chapter 18: Interval and Ordinal Data in DEA.- Chapter 19: DEAFrontier Software.
About the author
JOE ZHU is Associate Professor of Operations in the Department of Management at Worcester Polytechnic Institute. Zhu received his PhD in industrial engineering and operations research from the University of Massachusetts Amherst. Zhu has published two books focusing on performance evaluation using Data Envelopment Analysis and has developed the DEAFrontier software. An associate editor of the Omega journal, he is an expert in methods of performance measurement. Dr. Zhu has published over forty refereed papers in journals such as Management Science, Operations Research, IIE Transactions, and the Journal of Operational Research Society.
Summary
The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of research and teaching experiences.
It is difficult to evaluate an organization’s performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective.
Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets.
DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores.
This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject tothe capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.
