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Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis

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  • © 2023

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Authors:
  1. Farhad Hosseinzadeh Lotfi

    1. Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

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  2. Tofigh Allahviranloo

    1. Department of Applied Mathematics, Istinye University, Istanbul, Türkiye

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  3. Witold Pedrycz

    1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

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  4. Mohammad Reza Mozaffari

    1. Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran

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  5. Javad Gerami

    1. Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran

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  • 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

Part of the book series: Studies in Big Data (SBD, volume 138)

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About this book

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.

Keywords

Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Relationship Between Ratio Analysis, DEA-R and DEA Models

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 1-21

  3. Determining the Production Possibility Set for Ratio Data: A Novel Hybrid DEA-R Approach

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 23-52

  4. Incorporating Preference Information in DEA-R and DEA for Efficiency Analysis

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 53-72

  5. Finding Suitable Target in DEA and DEA-R

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 73-88

  6. Cost and Revenue Efficiency Based on MOLP in DEA-R Models

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 89-102

  7. A Slack-Based Model for Efficiency Evaluation in DEA and DEA-R

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 103-116

  8. A Centralized Resource Allocation Approach for Two-Stage Data Envelopment Analysis

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 117-137

  9. The Two-Stage Network Based on Ratio Analysis Models

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 139-155

  10. Calculating Environmental, Social and Economic Efficiencies of a Two-Stage Supply Chain in DEA-R Using Genetic Algorithm

    • Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami
    Pages 157-180
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Authors and Affiliations

  • Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Farhad Hosseinzadeh Lotfi

  • Department of Applied Mathematics, Istinye University, Istanbul, Türkiye

    Tofigh Allahviranloo

  • Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

    Witold Pedrycz

  • Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran

    Mohammad Reza Mozaffari, Javad Gerami

Bibliographic Information

  • Book Title: Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis

  • Authors: Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammad Reza Mozaffari, Javad Gerami

  • Series Title: Studies in Big Data

  • DOI: https://doi.org/10.1007/978-3-031-43181-4

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-43180-7Published: 02 October 2023

  • Softcover ISBN: 978-3-031-43183-8Due: 01 November 2023

  • eBook ISBN: 978-3-031-43181-4Published: 30 September 2023

  • Series ISSN: 2197-6503

  • Series E-ISSN: 2197-6511

  • Edition Number: 1

  • Number of Pages: XIV, 180

  • Number of Illustrations: 3 b/w illustrations, 29 illustrations in colour

  • Topics: Data Engineering, Computational Intelligence, Big Data

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