Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach

Estimation of efficiency of firms in a non-competitive market characterized by heterogeneous inputs and outputs along with their varying prices is questionable when factor-based technology sets are used in data envelopment analysis (DEA). In this scenario, a value-based technology becomes an appropriate reference technology against which efficiency can be assessed. In this contribution, the value-based models of Tone (2002) are extended in a directional DEA set up to develop new directional cost- and revenue-based measures of efficiency, which are then decomposed into their respective directional value-based technical and allocative efficiencies. These new directional value-based measures are more general, and include the existing value-based measures as special cases. These measures satisfy several desirable properties of an ideal efficiency measure. These new measures are advantageous over the existing ones in terms of (1) their ability to satisfy the most important property of translation invariance; (2) choices over the use of suitable direction vectors in handling negative data; and (3) flexibility in providing the decision makers with the option of specifying preferable direction vectors to incorporate their preferences. Finally, under the condition of no prior unit price information, a directional value-based measure of profit inefficiency is developed for firms whose underlying objectives are profit maximization. For an illustrative empirical application, our new measures are applied to a real-life data set of 50 US banks to draw inferences about the production correspondence of banking industry.

[1]  R. Shephard Cost and production functions , 1953 .

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

[3]  J. Paradi,et al.  Best practice analysis of bank branches: An application of DEA in a large Canadian bank , 1997 .

[4]  Timo Kuosmanen,et al.  Measuring economic efficiency with incomplete price information: With an application to European commercial banks , 2001, Eur. J. Oper. Res..

[5]  A. Mostafaee,et al.  A simplified version of the DEA cost efficiency model , 2008, Eur. J. Oper. Res..

[6]  Jesús T. Pastor,et al.  Units invariant and translation invariant DEA models , 1995, Oper. Res. Lett..

[7]  R. Färe,et al.  Benefit and Distance Functions , 1996 .

[8]  R. Robert Russell,et al.  Aggregation of Efficiency Indices , 1999 .

[9]  Biresh K. Sahoo,et al.  A generalized multiplicative directional distance function for efficiency measurement in DEA , 2014, Eur. J. Oper. Res..

[10]  Yasunori Ishii,et al.  On the Theory of the Competitive Firm under Price Uncertainty: Note , 1977 .

[11]  Kaoru Tone,et al.  A strange case of the cost and allocative efficiencies in DEA , 2001, J. Oper. Res. Soc..

[12]  Ali Emrouznejad,et al.  A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA , 2010, Eur. J. Oper. Res..

[13]  Emmanuel Thanassoulis,et al.  Malmquist-type indices in the presence of negative data: An application to bank branches , 2010 .

[14]  Biresh K. Sahoo,et al.  Returns to growth in a nonparametric DEA approach , 2012, Int. Trans. Oper. Res..

[15]  Toshiyuki Sueyoshi,et al.  Measuring efficiencies and returns to scale of Nippon telegraph & telephone in production and cost analyses , 1997 .

[16]  Robert G. Dyson,et al.  A generalisation of the Farrell cost efficiency measure applicable to non-fully competitive settings , 2008 .

[17]  Juan Aparicio,et al.  Translation Invariance in Data Envelopment Analysis , 2015 .

[18]  Emmanuel Thanassoulis,et al.  Negative data in DEA: a directional distance approach applied to bank branches , 2004, J. Oper. Res. Soc..

[19]  Jesús T. Pastor,et al.  Chapter 3 Translation invariance in data envelopment analysis: A generalization , 1996, Ann. Oper. Res..

[20]  Kristiaan Kerstens,et al.  Negative data in DEA: a simple proportional distance function approach , 2011, J. Oper. Res. Soc..

[21]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[22]  Hirofumi Fukuyama,et al.  Profit Inefficiency of Japanese Securities Firms , 2008 .

[23]  Kaoru Tone,et al.  Radial and non-radial decompositions of profit change: With an application to Indian banking , 2009, Eur. J. Oper. Res..

[24]  R. Färe,et al.  The measurement of efficiency of production , 1985 .

[25]  M. Farrell The Measurement of Productive Efficiency , 1957 .

[26]  Biresh K. Sahoo,et al.  An alternative approach to monetary aggregation in DEA , 2010, Eur. J. Oper. Res..

[27]  Hirofumi Fukuyama,et al.  Economic inefficiency measurement of input spending when decision-making units face different input prices , 2004, J. Oper. Res. Soc..

[28]  Joan V. Robinson Economics of imperfect competition , 1969 .

[29]  William W. Cooper,et al.  Chapter 1 Introduction: Extensions and new developments in DEA , 1996, Ann. Oper. Res..

[30]  Timo Kuosmanen,et al.  Measuring economic efficiency with incomplete price information , 2003, Eur. J. Oper. Res..

[31]  Subhash C. Ray,et al.  Cost efficiency in the US steel industry: A nonparametric analysis using data envelopment analysis , 1995 .

[32]  Emmanuel Thanassoulis,et al.  A cost Malmquist productivity index , 2004, Eur. J. Oper. Res..

[33]  E. Chamberlin The theory of monopolistic competition : a re-orientation of the theory of value , 1947 .

[34]  Hirofumi Fukuyama,et al.  OUTPUT SLACKS-ADJUSTED COST EFFICIENCY AND VALUE-BASED TECHNICAL EFFICIENCY IN DEA MODELS( Operations Research for Performance Evaluation) , 2009 .

[35]  Timo Kuosmanen,et al.  The law of one price in data envelopment analysis: Restricting weight flexibility across firms , 2003, Eur. J. Oper. Res..

[36]  Jati K. Sengupta,et al.  Efficiency Models in Data Envelopment Analysis: Techniques of Evaluation of Productivity of Firms in a Growing Economy , 2006 .

[37]  Jaume Puig-Junoy,et al.  Partitioning input cost efficiency into its allocative and technical components: an empirical DEA application to hospitals , 2000 .

[38]  W. Cooper,et al.  RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA , 1999 .

[39]  Biresh K. Sahoo,et al.  Evaluating cost efficiency and returns to scale in the Life Insurance Corporation of India using data envelopment analysis , 2005 .

[40]  R. G. Dyson,et al.  Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments , 2005, Eur. J. Oper. Res..

[41]  Kristiaan Kerstens,et al.  Returns to growth in a nonparametric DEA approach , 2012, Int. Trans. Oper. Res..

[42]  R. Färe,et al.  Profit, Directional Distance Functions, and Nerlovian Efficiency , 1998 .

[43]  Biresh K. Sahoo,et al.  Radial and non-radial decompositions of Luenberger productivity indicator with an illustrative application , 2011 .

[44]  A. Mostafaee,et al.  Cost efficiency measures in data envelopment analysis with data uncertainty , 2010, Eur. J. Oper. Res..

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

[46]  K. Sam Park,et al.  Pro-efficiency: Data speak more than technical efficiency , 2011, Eur. J. Oper. Res..

[47]  Kaoru Tone,et al.  Non-parametric measurement of economies of scale and scope in non-competitive environment with price uncertainty , 2013 .

[48]  Kaoru Tone,et al.  Decomposing capacity utilization in data envelopment analysis: An application to banks in India , 2009, Eur. J. Oper. Res..

[49]  Biresh K. Sahoo,et al.  Alternative measures of environmental technology structure in DEA: An application , 2011, Eur. J. Oper. Res..

[50]  Rolf Färe,et al.  Resolving a strange case of efficiency , 2006, J. Oper. Res. Soc..

[51]  C. Engel,et al.  How Wide is the Border? , 1994 .

[52]  Joan Robinson,et al.  The Economics of Imperfect Competition. , 1933 .

[53]  Kaoru Tone,et al.  Re-examining scale elasticity in DEA , 2006, Ann. Oper. Res..

[54]  J. J. McCall,et al.  Competitive Production for Constant Risk Utility Functions , 1967 .