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Practical Aspects of Value Efficiency Analysis

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  • P. Korhonen
  • A. Siljamaeki
  • M. Soismaa

Abstract

In this paper, we consider practical aspects for measuring Value Efficiency in Envelopment Analyis. Value efficiency is an efficiency concept that takes into account the decision maker's preferences.It was developed by Halme, Joro, Korhonen, Salo and Wallenius [1998]. The decision maker is asumed to compare alternatives using an implicitly known value function which reaches its maximum at the most preferred point on the efficient frontier. The unknown value function is assumed to be pseudoconcave and strictly increasing for outputs and strictly decreasing for inputs. The purpose of value effiiency analysis is to estimate a need to increase outputs and/or decrease inputs for reaching the indifference contour of the value function at the optimum. Because the value function is unknown, the indifference contours cannot be defined precisely. Value efficiency analysis never results in more pessimistic evaluation than in the case of a known function. To carry out value efficiency analysis, we have to locate the most preferred solution of the decision maker. In practice, this phase cannot be too complicated. We propose a few alternative ways to locate it and discuss the use of those ways in practical application.

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Bibliographic Info

Paper provided by International Institute for Applied Systems Analysis in its series Working Papers with number ir98042.

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Date of creation: Jun 1998
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Handle: RePEc:wop:iasawp:ir98042

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  1. P. Korhonen, 1998. "Multiple Objective Programming Support," Working Papers ir98010, International Institute for Applied Systems Analysis.
  2. Korhonen, Pekka J. & Laakso, Jukka, 1986. "A visual interactive method for solving the multiple criteria problem," European Journal of Operational Research, Elsevier, vol. 24(2), pages 277-287, February.
  3. P. Korhonen, 1997. "Searching the Efficient Frontier in Data Envelopment Analysis," Working Papers ir97079, International Institute for Applied Systems Analysis.
  4. M. Halme & T. Joro & P. Korhonen & S. Salo & J. Wallenius, 1998. "Value Efficiency Analysis for Incorporating Preference Information in Data Envelopment Analysis," Working Papers ir98054, International Institute for Applied Systems Analysis.
  5. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
  6. Tarja Joro & Pekka Korhonen & Jyrki Wallenius, 1998. "Structural Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming," Management Science, INFORMS, vol. 44(7), pages 962-970, July.
  7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
  8. Korhonen, Pekka, 1988. "A visual reference direction approach to solving discrete multiple criteria problems," European Journal of Operational Research, Elsevier, vol. 34(2), pages 152-159, March.
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Cited by:
  1. Marshall, Elizabeth P. & Shortle, James S., 2005. "Using DEA and VEA to Evaluate Quality of Life in the Mid-Atlantic States," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 34(2), October.
  2. Joro, Tarja & Korhonen, Pekka & Zionts, Stanley, 2003. "An interactive approach to improve estimates of value efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 149(3), pages 688-699, September.
  3. Eduardo González & Ana Cárcaba & Juan Ventura, 2011. "The Importance of the Geographic Level of Analysis in the Assessment of the Quality of Life: The Case of Spain," Social Indicators Research, Springer, vol. 102(2), pages 209-228, June.

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