Zhu J. Data-Enabled Analytics. DEA for Big Data 2021

Textbook in PDF format

This book brings Data Envelopment Analysis (DEA) based techniques and big data together to explore the novel uses and potentials of 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.
Data Envelopment Analysis and Big Data: A Systematic Literature Review with Bibliometric Analysis
Acceleration of Large-Scale DEA Computations Using Random Forest Classification
The Estimation of Productive Efficiency Through Machine Learning Techniques: Efficiency Analysis Trees
Hybrid Data Science and Reinforcement Learning in Data Envelopment Analysis
Aggregation of Outputs and Inputs for DEA Analysis of Hospital Efficiency: Economics, Operations Research and Data Science Perspectives
Parallel Processing and Large-Scale Datasets in Data Envelopment Analysis
Network DEA and Big Data with an Application to the Coronavirus Pandemic
Hierarchical Data Envelopment Analysis for Classification of High-Dimensional Data
Dominance Network Analysis: Hybridizing Dea and Complex Networks for Data Analytics
Value Extracting in Relative Performance Appraisal with Network DEA: An Application to U.S. Equity Mutual Funds
Measuring Chinese Bank Performance with Undesirable Outputs: A Slack-Based Two-Stage Network DEA Approach
Using Network DEA and Grey Prediction Model for Big Data Analysis: An Application in the Global Airline Efficiency