Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency

Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency

Release Date: January, 2024|Copyright: © 2024 |Pages: 389
DOI: 10.4018/979-8-3693-0255-2
ISBN13: 9798369302552|EISBN13: 9798369302576
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Description & Coverage
Description:

In today's highly competitive and rapidly evolving global landscape, the quest for efficiency has become a crucial factor in determining the success of organizations across various industries. Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency is a comprehensive guide that delves into the powerful mathematical tool of DEA, is designed to assess the relative efficiency of decision-making units (DMUs), and provides valuable insights for performance improvement. This book presents a systematic overview of DEA models and techniques, from fundamental concepts to advanced methods, showcasing their practical applications through real-world examples and case studies.

Readers will embark on an enlightening journey through the theory, methodology, and practical applications of DEA. The book begins with a solid foundation in the basics of DEA, exploring various models, such as the input-oriented and output-oriented approaches and the constant and variable returns to scale assumptions. Advanced DEA methods, including cross-efficiency evaluation, Malmquist productivity index, and network DEA, are also thoroughly examined. This book illustrates practical applications through real-world examples and case studies, provides guidance for conducting DEA research and analysis, discusses the limitations and challenges of DEA, and explores recent developments and future trends in DEA research.

Catering to a broad audience, this book is designed for students, researchers, consultants, decision-makers, and enthusiasts in the field of efficiency analysis and performance measurement. Consultants and practitioners will gain practical insights for applying DEA in various contexts, and decision-makers will be equipped to make informed decisions for maximizing efficiency. Additionally, individuals with a general interest in data analysis and performance measurement will find this book accessible and informative.

Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency covers a wide range of topics, including mathematical foundations of DEA, DEA models and variations, DEA efficiency and productivity measures, DEA applications in various industries such as healthcare, finance, supply chain management, environmental management, education management, and public sector management. The book also addresses DEA software, implementation issues, empirical studies, and case studies. Furthermore, it explores future developments and emerging trends in DEA research, ensuring readers stay up-to-date with the latest advancements in the field.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Application of Data Envelopment Analysis
  • DEA Aggregation and Disaggregation Techniques
  • Decision Analysis and Uncertainty
  • Efficiency and Productivity Measures
  • Forecasting and Predictive Analytics
  • Industrial Engineering
  • Input and Output Selection
  • Mathematical Foundations
  • Models and Variations
  • Multicriteria Decision Making
  • Nonparametric Frontier Estimation
  • Scale Efficiency and Returns to Scale
  • Sensitivity Analysis and Robustness
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Editor/Author Biographies
Adeyemi Abel Ajibesin is a distinguished academic scholar with over two decades of extensive experience in research, teaching, and leadership, particularly in the field of Electrical and Computer Engineering. Currently serving as the Chair/HoD of Software Engineering at the School of IT & Computing (SITC) at the American University of Nigeria, he was the founding Interim Dean of the School of Engineering, the Interim Dean of SITC, and the Director of the African Centre for ICT Innovation and Training. Already, he has served in various capacities at Simon Fraser University, Canada; University of Cape Town, South Africa; and Pan African University Institute for Basic Sciences, Technology & Innovation, Kenya, among other places. His research interests are diverse, spanning data science, broadband networks, frontier analysis, AI applications for gender equity, community development, leadership, innovation, and transformation. Beyond academia, Dr. Ajibesin holds patents for engineering products and copyrights for computing software, showcasing his commitment to innovation and intellectual contributions in his field.
Narasimha Rao Vajjhala is working as an Associate Professor at the Faculty of Engineering and Architecture at the University of New York Tirana, Albania. He is a senior member of ACM and IEEE. He is the Editor-in-Chief of the International Journal of Risk and Contingency Management (IJRCM). He is also a member of the Risk Management Society (RIMS), and the Project Management Institute (PMI). He has over 20 years of experience teaching programming and database-related courses at both graduate and undergraduate levels in Europe and Africa. He has also worked as a consultant in technology firms in Europe and has experience participating in EU-funded projects. He has supervised several undergraduate senior design projects and graduate theses. He has completed a Doctorate in Information Systems and Technology (United States); holds a Master of Science in Computer Science and Applications (India), and a Master of Business Administration with a specialization in Information Systems (Switzerland), and an undergraduate degree in Computer Science (India).
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