Extension of Data Envelopment Analysis with Preference Information

Extension of Data Envelopment Analysis with Preference Information
Author :
Publisher : Springer
Total Pages : 196
Release :
ISBN-10 : 9781489975287
ISBN-13 : 1489975284
Rating : 4/5 (87 Downloads)

Book Synopsis Extension of Data Envelopment Analysis with Preference Information by : Tarja Joro

Download or read book Extension of Data Envelopment Analysis with Preference Information written by Tarja Joro and published by Springer. This book was released on 2015-01-02 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to incorporating preference information in Data Envelopment Analysis (DEA) with a special emphasis in Value Efficiency Analysis. In addition to theoretical considerations, numerous illustrative examples are included. Hence, the book can be used as a teaching text as well. Only a modest mathematical background is needed to understand the main principles. The only prerequisites are a) familiarity with linear algebra, especially matrix calculus; b) knowledge of the simplex method; and c) familiarity with the use of computer software. The book is organized as follows. Chapter 1 provides motivation and introduces the basic concepts. Chapter 2 provides the basic ideas and models of Data Envelopment Analysis. The efficient frontier and production possibility set concepts play an important role in all considerations. That's why these concepts are considered more closely in Chapter 3. Since the approaches introduced in this study are inspired by Multiple Objective Linear Programming, the basic concepts of this field are reviewed in Chapter 4. Chapter 5 also compares and contrasts Data Envelopment Analysis and Multiple Objective Linear Programming, providing some cornerstones for approaches presented later in the book. Chapter 6 discusses the traditional approaches to take into account preference information in DEA. In Chapter 7, Value Efficiency is introduced, and Chapter 8 discusses practical aspects. Some extensions are presented in Chapter 9, and in Chapter 10 Value Efficiency is extended to cover the case when a production possibility set is not convex. Three implemented applications are reviewed in Chapter 11.


Extension of Data Envelopment Analysis with Preference Information Related Books

Extension of Data Envelopment Analysis with Preference Information
Language: en
Pages: 196
Authors: Tarja Joro
Categories: Business & Economics
Type: BOOK - Published: 2015-01-02 - Publisher: Springer

DOWNLOAD EBOOK

This book provides an introduction to incorporating preference information in Data Envelopment Analysis (DEA) with a special emphasis in Value Efficiency Analys
Network Data Envelopment Analysis
Language: en
Pages: 447
Authors: Chiang Kao
Categories: Business & Economics
Type: BOOK - Published: 2016-08-23 - Publisher: Springer

DOWNLOAD EBOOK

This book presents the underlying theory, model development, and applications of network Data Envelopment Analysis (DEA) in a systematic way. The field of netwo
Handbook on Data Envelopment Analysis
Language: en
Pages: 513
Authors: William W. Cooper
Categories: Business & Economics
Type: BOOK - Published: 2011-08-23 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field
Financial Risk Management in Banking
Language: en
Pages: 276
Authors: Shahsuzan Zakaria
Categories: Business & Economics
Type: BOOK - Published: 2019-08-08 - Publisher: Routledge

DOWNLOAD EBOOK

As risk-taking is an essential part of the banking industry, banks must practise efficient risk management to ensure survival in uncertain financial climates. B
Data Science and Productivity Analytics
Language: en
Pages: 441
Authors: Vincent Charles
Categories: Business & Economics
Type: BOOK - Published: 2020-05-23 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theor