Data-Enabled Analytics (eBook)

DEA for Big Data

Joe Zhu, Vincent Charles (Herausgeber)

eBook Download: PDF

2021 | 1st ed. 2021
X, 364 Seiten
Springer International Publishing (Verlag)
978-3-030-75162-3 (ISBN)

Infos

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

Joe Zhu is a Professor of Operations Analytics in the Foisie Business School, Worcester Polytechnic Institute. He is an internationally recognized expert in methods of performance evaluation and benchmarking using Data Envelopment Analysis (DEA), and his research interests are in the areas of operations and business analytics, productivity modeling, and performance evaluation and benchmarking. He has published and co-edited several books focusing on performance evaluation and benchmarking using DEA and developed the DEAFrontier software. With more than 130 journal articles, books, and textbooks along with over 20,000 Google Scholar citations, he is recognized as one of the top authors in DEA with respect to research productivity, h-index, and g-index.

Vincent Charles is a Professor of Management Science and the Director of Research at Buckingham Business School, University of Buckingham, UK. He has published over 110 research works with Pearson Education, Cambridge Scholars Publishing, UK and other publishers. His area of research includes productivity, quality, efficiency, effectiveness, competitiveness, innovation, and design thinking. He has the following industry exposure for research and consultancy purposes:  advertising, agriculture & agribusiness, transportation, consumer products, banking, education, electronics, and manufacturing.

Produkt-Details

• Erscheint lt. Verlag: 16.12.2021
• Reihe/Serie: International Series in Operations Research & Management Science
• Reihe/Serie: International Series in Operations Research & Management Science
• Zusatzinfo: X, 364 p. 103 illus.
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Wirtschaft ► Allgemeines / Lexika
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Logistik / Produktion
• Schlagworte: Best-Practice • Big Data • data-enabled analytics • Data envelopment analysis • Data Science • Efficiency • Forecasting • large-scale computations • Performance Evaluation • random forest • Reinforcement Learning
• ISBN-10: 3-030-75162-7 / 3030751627
• ISBN-13: 978-3-030-75162-3 / 9783030751623