Handbook of Operations Analytics Using Data Envelopment Analysis: 239 (International Series in Operations Research & Management Science) - Tapa blanda

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Shiuh-Nan Hwang is a Professor in the Department of Business Administration, and Dean of the School of Management at Ming Chuan University, Taiwan. He earned his Ph.D. in Management Science at National Chiao Tung University, an M.S. in Industrial Management at National Cheng Kung University, and a B.S. in Agriculture Economics at National Taiwan University. His research interests include Performance Evaluation and Management, Business Research Methods, and General Management.

Hsuan-Shih Lee is a Professor and Vice-President in the Department of Shipping & Transportation Management at the College of Maritime Science and Management, National Taiwan Ocean University, Taiwan. He earned his Ph.D., and M.S. in Information Engineering, and B.S. in Computer Engineering, all at National Chiao Tung University, Taiwan. His research interests include Maritime Management and Policy, Performance management, Management Information Systems, System Analysis and Design, Algorithm Analysis, and Computer Networks.

Joe Zhu is Professor of Operations Analytics in the Foisie School of Business, Worcester Polytechnic Institute. He is an internationally recognized expert in methods of performance evaluation and benchmarking using Data Envelopment Analysis (DEA). He has published and co-edited more than 15 books focusing on performance evaluation and benchmarking using DEA. He has more than 18,000 Google Scholar citations with over 100 peer-reviewed articles. He is recognized as one of the top authors in DEA with respect to research productivity, h-index, and g-index. He is an Area Editor of OMEGA, and on the Editorial Board of European Journal of Operational Research, and Computers and Operations Research. He is the Series Associate Editor of International Series in Operations Research and Management Science.

De la contraportada

This handbook focuses on Data Envelopment Analysis (DEA) applications in operations analytics which are fundamental tools and techniques for improving operation functions and attaining long-term competitiveness. In fact, the handbook demonstrates that DEA can be viewed as Data Envelopment Analytics.

Chapters include a review of cross-efficiency evaluation; a case study on measuring the environmental performance of OECS countries; how to select a set of performance metrics in DEA with an application to American banks; a relational network model to take the operations of individual periods into account in measuring efficiencies; how the efficient frontier methods DEA and stochastic frontier analysis (SFA) can be used synergistically; and how to integrate DEA and multidimensional scaling.

In other chapters, authors construct a dynamic three-stage network DEA model; a bootstrapping based methodology to evaluate returns to scale and convexity assumptions in DEA; hybridizing DEA and cooperative games; using DEA to represent the production technology and directional distance functions to measure band performance; an input-specific Luenberger energy and environmental productivity indicator; and the issue of reference set by differentiating between the uniquely found reference set and the unary and maximal types of the reference set.

Finally, additional chapters evaluate and compare the technological advancement observed in different hybrid electric vehicles (HEV) market segments over the past 15 years; radial measurement of efficiency for the production process possessing multi-components under different production technologies; issues around the use of accounting information in DEA; how to use DEA environmental assessment to establish corporate sustainability; a summary of research efforts on DEA environmental assessment applied to energy in the last 30 years; and an overview of DEA and how it can be utilized alone and with other techniques to investigate corporate environmental sustainability questions.