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Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis
Details
The combination of DEA and ratio analysis is introduced as a suitable field for evaluating the performance of DMUs. In this regard, DEA-R is also proposed as a hybrid technique for calculating efficiency, ranking DMUs, and finding efficient faces. Therefore, the relationship between DEA and DEA-R provides a suitable field for researchers in the field of evaluating the performance of DMUs. The audience of this book is not limited to researchers in mathematics fields, but experts and students in industrial engineering and management fields also benefit from the topics of this book.
Presents an introduction of comparative efficiency models in ratio analysis and DEA-R Demonstrates the relationship between ratio analysis models and DEA-R with classical data envelopment analysis models Focuses on comparative efficiency models in ratio analysis and DEA-R
Inhalt
Relationship between DEA models without explicit inputs and DEA-R models.- Finding efficient surfaces in DEA-R models.- Cost and revenue efficiency in DEA-R models.- A Novel Slack-Based Model for Efficiency and Super-efficiency in DEA-R.- A Multi-Criteria Ratio-Based Approach for Two-Stage Data Envelopment Analysis.- A novel network DEA-R model for evaluating hospital services supply chain performance.- A novel inverse DEA-R model for inputs/output estimation.- Evaluation of Two-Stage Networks based on Average Efficiency Using DEA and DEA-R with Fuzzy Data.- Stochastic network DEA-R models for two-stage systems.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031431807
- Genre Technology Encyclopedias
- Auflage 2023
- Lesemotiv Verstehen
- Anzahl Seiten 196
- Herausgeber Springer International Publishing
- Größe H241mm x B160mm x T17mm
- Jahr 2023
- EAN 9783031431807
- Format Fester Einband
- ISBN 3031431804
- Veröffentlichung 02.10.2023
- Titel Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis
- Autor Farhad Hosseinzadeh Lotfi , Tofigh Allahviranloo , Javad Gerami , Mohammad Reza Mozaffari , Witold Pedrycz
- Untertitel Studies in Big Data 138
- Gewicht 465g
- Sprache Englisch