rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Benchmarking for Performance Evaluation
    sub title: A Production Frontier Approach
  name:
    name part: Ray, Subhash C.
    role:
      role term: editor.
  name:
    name part: Kumbhakar, Subal C.
    role:
      role term: editor.
  name:
    name part: Dua, Pami.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: ii
    date issued: 2015
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 281 p. 73 illus. online resource.
  abstract: 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.
  table of contents: 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 Førsund, 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.
  note: edited by Subhash C. Ray, Subal C. Kumbhakar, Pami Dua.
  subject:
    topic: Business
  subject:
    topic: Production management
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Statistics
  subject:
    topic: Econometrics
  subject:
    topic: Microeconomics
  subject:
    topic: Business and Management
  subject:
    topic: Operation Research/Decision Theory
  subject:
    topic: Microeconomics
  subject:
    topic: Statistics for Business/Economics/Mathematical Finance/Insurance
  subject:
    topic: Operations Management
  subject:
    topic: Econometrics
  classification: HD30.23
  classification: 658.40301
  related item:
    title info:
      title: Springer eBooks
  identifier: 9788132222538
  identifier: http://dx.doi.org/10.1007/978-81-322-2253-8
  record info:
    record creation date: 150325
    record change date: 20151204160535.0
    record identifier: 978-81-322-2253-8