LEADER 03923nam 22005293 450 001 9910746953003321 005 20231004080221.0 010 $a3-031-43181-2 035 $a(MiAaPQ)EBC30765467 035 $a(Au-PeEL)EBL30765467 035 $a(PPN)272736937 035 $a(CKB)28443963800041 035 $a(Exl-AI)30765467 035 $a(EXLCZ)9928443963800041 100 $a20231004d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis 205 $a1st ed. 210 1$aCham :$cSpringer International Publishing AG,$d2023. 210 4$d©2023. 215 $a1 online resource (192 pages) 225 1 $aStudies in Big Data Series ;$vv.138 311 08$aPrint version: Hosseinzadeh Lotfi, Farhad Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis Cham : Springer International Publishing AG,c2023 9783031431807 327 $aPreface -- Contents -- List of Figures -- List of Tables -- 1 Relationship Between Ratio Analysis, DEA-R and DEA Models -- 1.1 Background -- 1.2 Basic Concepts -- 1.2.1 Efficiency Evaluation of DMUs in the Input and Output Orientated -- 1.2.2 Production Function -- 1.2.3 Approximation of the Production Function -- 1.2.4 Production Possibility Set -- 1.2.5 CCR Model in the Input Oriented -- 1.2.6 CCR Model in the Output Oriented -- 1.2.7 BCC Model in the Input Oriented -- 1.2.8 The BCC Model -- 1.3 Relationship Between Models DEA and DEA-R -- 1.3.1 The DEA Models in Output Oriented and DEA-R Models in Input Oriented -- 1.3.2 The DEA Models in Input Oriented and DEA-R Models in Output Oriented -- 1.4 DEA Models Without Explicit Inputs and DEA-R -- 1.5 A Numerical Example for Commercial Banks -- 1.6 Conclusions -- References -- 2 Determining the Production Possibility Set for Ratio Data: A Novel Hybrid DEA-R Approach -- 2.1 Background -- 2.2 The Novel Hybrid DEA-RA Approach -- 2.2.1 Ratio Analysis (RA) -- 2.2.2 The Inputs and Outputs of DEA-RA Model -- 2.3 DEA-RA Axiomatic Structure -- 2.3.1 DEA-R Space -- 2.3.2 Convexity$7Generated by AI. 330 $aThis book, 'Comparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis,' explores advanced methodologies in data envelopment analysis (DEA) with a focus on ratio analysis. It is part of the 'Studies in Big Data' series and aims to bridge theoretical and practical applications in evaluating the performance of decision-making units (DMUs). The authors, including Farhad Hosseinzadeh Lotfi and others, present hybrid models combining DEA and Ratio Analysis (DEA-R) to enhance efficiency calculations and rankings. The book targets researchers in applied mathematics, industrial engineering, management, and computer engineering, offering insights into DEA-R's applications in various sectors such as banking and supply chain management. The text is a comprehensive resource for those interested in operational research and efficiency evaluation.$7Generated by AI. 410 0$aStudies in Big Data Series 606 $aData envelopment analysis$7Generated by AI 606 $aRatio analysis$7Generated by AI 615 0$aData envelopment analysis. 615 0$aRatio analysis. 676 $a658.4033 700 $aHosseinzadeh Lotfi$b Farhad$01356586 701 $aAllahviranloo$b Tofigh$01077219 701 $aPedrycz$b Witold$021029 701 $aMozaffari$b Mohammad Reza$01431444 701 $aGerami$b Javad$01431445 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746953003321 996 $aComparative Efficiency in Data Envelopment Analysis Based on Ratio Analysis$93573758 997 $aUNINA