LEADER 00000nam a2200517 i 4500 
001    978-81-322-2253-8 
003    DE-He213 
005    20151016113617.0 
006    m     o  d         
007    cr nn 008maaau 
008    150325s2015    ii      s         0 eng d 
020    9788132222538 (electronic bk.) 
020    9788132222521 (paper) 
024 7  10.1007/978-81-322-2253-8|2doi 
040    GP|cGP|erda|dAS 
041 0  eng 
050  4 HD62.15 
082 04 658.4013|223 
245 00 Benchmarking for performance evaluation :|ba production 
       frontier approach /|cedited by Subhash C. Ray, Subal C. 
       Kumbhakar, Pami Dua 
264  1 New Delhi :|bSpringer India :|bImprint: Springer,|c2015 
300    1 online resource (xiv, 281 pages) :|billustrations, 
       digital ;|c24 cm 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
505 0  Introduction – Ray, Subhash; Kumbhakar, Subal & Dua, Pami 
       -- Chapter 1. Estimation of Technical Inefficiency in 
       Production Frontier Models Using Cross-Sectional Data by 
       Kumbhakar, Subal C. & Wang, Hung-Jen -- Chapter 2. Data 
       Envelopment Analysis for Performance Evaluation: A Child's
       Guide by Ray, Subhash C. & Chen, Lei -- Chapter 3. An 
       Introduction to CNLS and StoNED Methods for Efficiency 
       Analysis: Economic Insights and Computational Aspects by 
       Johnson, Andrew L. and Kuosmanen, Timo -- Chapter 4. 
       Dynamic Efficiency Measurement by Forsund, Finn R -- 
       Chapter 5. Efficiency Measures for Industrial Organization
       by Ten Raa, Thijs -- Chapter 6. Multiplicative and 
       Additive Distance Functions: Efficiency Measures and 
       Duality by Pastor, Jesus T. & Aparicio, Juan 
520    This book provides a detailed introduction to the 
       theoretical and methodological foundations of production 
       efficiency analysis using benchmarking. Two of the more 
       popular methods of efficiency evaluation are Stochastic 
       Frontier Analysis (SFA) and Data Envelopment Analysis 
       (DEA), both of which are based on the concept of a 
       production possibility set and its frontier. Depending on 
       the assumed objectives of the decision-making unit, a 
       Production, Cost, or Profit Frontier is constructed from 
       observed data on input and output quantities and prices. 
       While SFA uses different maximum likelihood estimation 
       techniques to estimate a parametric frontier, DEA relies 
       on mathematical programming to create a nonparametric 
       frontier. Yet another alternative is the Convex 
       Nonparametric Frontier, which is based on the assumed 
       convexity of the production possibility set and creates a 
       piecewise linear frontier consisting of a number of 
       tangent hyper planes. Three of the papers in this volume 
       provide a detailed and relatively easy to follow 
       exposition of the underlying theory from neoclassical 
       production economics and offer step-by-step instructions 
       on the appropriate model to apply in different contexts 
       and how to implement them. Of particular appeal are the 
       instructions on (i) how to write the codes for different 
       SFA models on STATA, (ii) how to write a VBA Macro for 
       repetitive solution of the DEA problem for each production
       unit on Excel Solver, and (iii) how to write the codes for
       the Nonparametric Convex Frontier estimation. The three 
       other papers in the volume are primarily theoretical and 
       will be of interest to PhD students and researchers hoping
       to make methodological and conceptual contributions to the
       field of nonparametric efficiency analysis 
650  0 Benchmarking (Management) 
650  0 Production management 
650 14 Economics/Management Science 
650 24 Operation Research/Decision Theory 
650 24 Microeconomics 
650 24 Statistics for Business/Economics/Mathematical Finance/
650 24 Production/Logistics/Supply Chain Management 
650 24 Econometrics 
700 1  Ray, Subhash C.,|eeditor 
700 1  Kumbhakar, Subal C.,|eeditor 
700 1  Dua, Pami,|eeditor 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
856 40 |uhttp://dx.doi.org/10.1007/978-81-322-2253-8