Productivity measurement in industrial operations

Abstract Conceptual foundations of productivity measures encompassing technical change, technical efficiency, scale efficiency, and allocative efficiency are discussed. Three principal approaches to productivity measurement — index measurement, programming methods, and econometric estimation — are reviewed. The merits, uses, information requirements, and limitations of methods for the estimation of production and cost frontiers and their derivative productivity measures are assessed.

[1]  K. Laspeyres.  IX. Die Berechnung einer mittleren Waarenpreissteigerung. , 1871 .

[2]  M. Ishaq Nadiri,et al.  Some Approaches to the Theory and Measurement of Total Factor Productivity: A Survey , 1970 .

[3]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[4]  Boaz Golany,et al.  Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions , 1985 .

[5]  C. Lovell,et al.  On the estimation of technical inefficiency in the stochastic frontier production function model , 1982 .

[6]  Abraham Charnes,et al.  Management Science Relations for Evaluation and Management Accountability , 1979 .

[7]  T. Koopmans.  Three Essays on the State of Economic Science , 1958 .

[8]  C. Hulten.  On the "Importance" of Productivity Change , 1979 .

[9]  Walter Diewert,et al.  Exact and superlative index numbers , 1976 .

[10]  Abraham Charnes,et al.  Programming with linear fractional functionals , 1962 .

[11]  R. Shepherd.  Theory of cost and production functions , 1970 .

[12]  A. Charnes,et al.  Chance-Constrained Programming , 1959 .

[13]  R. Solow.  TECHNICAL CHANGE AND THE AGGREGATE PRODUCTION FUNCTION , 1957 .

[14]  W. Diewert.  Fisher ideal output, input, and productivity indexes revisited , 1992 .

[15]  S. Malmquist.  Index numbers and indifference surfaces , 1953 .

[16]  Kenneth C. Land,et al.  Chance‐constrained data envelopment analysis , 1993 .

[17]  D. Aigner,et al.  P. Schmidt, 1977,?Formulation and estimation of stochastic frontier production function models,? , 1977 .

[18]  William W. Cooper,et al.  Chapter 13 Satisficing DEA models under chance constraints , 1996, Ann. Oper. Res..

[19]  L. Törnqvist.  The Bank of Finland's consumption price index , 1936 .

[20]  D. Poirier,et al.  On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function , 1976 .

[21]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[22]  F. Divisia.  L'indice monétaire et la théorie de la monnaie , 1926 .

[23]  On maximum likelihood estimation of stochastic frontier production models , 1983 .

[24]  I. Fisher.  The Best form of Index Number , 1921, Quarterly Publications of the American Statistical Association.

[25]  R. Kopp,et al.  The decomposition of frontier cost function deviations into measures of technical and allocative efficiency , 1982 .

[26]  C. Hulten.  Divisia Index Numbers , 1973 .

[27]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[28]  M. Rothschild,et al.  Testing the Assumptions of Production Theory: A Nonparametric Approach , 1972, Journal of Political Economy.

[29]  H. Vinod.  Canonical ridge and econometrics of joint production , 1976 .

[30]  W. Greene.  Maximum likelihood estimation of econometric frontier functions , 1980 .

[31]  R. Banker.  Estimating most productive scale size using data envelopment analysis , 1984 .

[32]  Jati K. Sengupta,et al.  Data envelopment analysis for efficiency measurement in the stochastic case , 1987, Comput. Oper. Res..

[33]  D. Jorgenson,et al.  TRANSCENDENTAL LOGARITHMIC PRODUCTION FRONTIERS , 1973 .

[34]  Z. Griliches,et al.  The Explanation of Productivity Change , 1967 .

[35]  R. Moorsteen.  On Measuring Productive Potential and Relative Efficiency , 1961 .