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Titlebook: Benchmarking for Performance Evaluation; A Production Frontie Subhash C. Ray,Subal C. Kumbhakar,Pami Dua Book 2015 The Editor(s) (if applic

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发表于 2025-3-21 17:08:10 | 显示全部楼层 |阅读模式
期刊全称Benchmarking for Performance Evaluation
期刊简称A Production Frontie
影响因子2023Subhash C. Ray,Subal C. Kumbhakar,Pami Dua
视频videohttp://file.papertrans.cn/184/183382/183382.mp4
发行地址Rooted in the neoclassical economics of production, presents the analytical tools needed for efficiency analysis.Brings together all key alternative methodologies – Stochastic Frontier Analysis, Data
图书封面Titlebook: Benchmarking for Performance Evaluation; A Production Frontie Subhash C. Ray,Subal C. Kumbhakar,Pami Dua Book 2015 The Editor(s) (if applic
影响因子.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 context
Pindex Book 2015
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An Introduction to CNLS and StoNED Methods for Efficiency Analysis: Economic Insights and Computatiines the virtues of the widely used neoclassic production models, Data Envelopment Analysis (DEA), and Stochastic Frontier Analysis (SFA). Like DEA, StoNED is able to estimate an axiomatic production function relaxing the functional form specification required in most implementations of SFA. However
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Dynamic Efficiency Measurement,cy, explaining the results of efficiency analyses is notoriously more difficult than carrying out the estimations. The literature points to measures of inputs and management as not including quality dimensions as a reason for measured efficiency differences, indicating that more work needs to be don
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Efficiency Measures for Industrial Organization,best practices—and an organization efficiency—which indicates the degree of optimality of the number of firms and their distribution. The latter component provides an efficiency measure for the industrial organization. Economies or diseconomies of scale and of scope play a big role in the determinat
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G. Sganga,G. Brisinda,M. Castagneto problems. We also describe the non-convex free disposal hull (FDH) procedure and the second-stage regression analysis that seeks to account for variation in measured efficiency scores due to external factors.
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Efficiency Measures for Industrial Organization,ing of scale economies will be reviewed. This paper shows in detail how the efficiency of an industrial organization can be measured as a gap between mean firm efficiency and overall industry efficiency. The analysis is extended to dynamic models to measure the role of entry and exit in the efficiency of the industrial organization.
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