Restricting weights in value efficiency analysis

Abstract

In this paper, we consider the problem of incorporating additional preference information into Value Efficiency Analysis by using the "price" information of inputs and outputs. This is done to improve the accuracy of the estimation of the Value Efficiency Scores. Value Efficiency developed by Halme et al [1998] is an efficiency concept, which takes into account the decision maker's preferences. Value Efficiency Analysis is based on the assumption that an implicitly known value function reaches its maximum at the Most Preferred Solution on the efficient frontier. The Most Preferred solution is an input-output vector preferred to all other possible input-output vectors. The ultimate goal is to measure a need to improve (radially) the values of inputs and/or outputs to make them equally preferred to the Most Preferred Solution. Because we do not know the value function, we approximate the indifference curves of all possible value functions satisfying certain assumptions by their tangents at the Most Preferred Solution. The resulting cone of the tangents consists of points less or equally preferred tothe Most Preferred Solution. However, in addition to the Most Preferred Solution information about the "prices" of inputs and outputs may be available as well. We show how this information can be incorporated into the analysis and illustrate the approach by an example on the performance of municipal dental units in Finland.

Internet Based Benchmarking

“…By imposing the user's preferences to all DMUs we use the following index to rank unit A: |0D| |0A BM | . The idea corresponds with the literature on so-called value efficiency in DEA, see e.g., Halme and Korhonen (2000) and Korhonen et al (2002). The idea is based on the assumptions that the user have a pseudoconcave utility function and that the benchmark selected by the user is the most preferred benchmark.…”

Optimal weights in DEA models with weight restrictions

“…From the technology perspective, the incorporation of weight restrictions results in the expansion of the model of technology (Charnes et al 1989, Roll et al 1991, Halme and Korhonen 2000. Podinovski (2004b) shows that this expansion is caused by the dual terms in the envelopment model generated by weight restrictions, and that DMU o is projected on the boundary of the expanded technology.…”

DEA Models with Production Trade-offs and Weight Restrictions

“…Charnes et al (1989), Roll et al (1991) and Halme and Korhonen (2000) show that the incorporation of weight restrictions in multiplier models induce dual terms that change the technology but do not explore this relation as a basis for the assessment of weight restrictions that have a production meaning.…”