Chance-constrained Data Envelopment Analysis Research Articles

Determining relative efficiency of slightly non-homogeneous decision making units by data envelopment analysis: a case study in IROST

The assumption of classical Data Envelopment Analysis (DEA) models is based on complete homogeneity of Decision Making Units (DMUs). The objective of this paper is to propose a method of determining relative efficiency of slightly non-homogeneous DMUs by using DEA. First missing values are inserted by series mean. Then relative weights of DMUs are measured by Analytic Hierarchy Process (AHP) and finally relative efficiency of DMUs is computed by chance-constrained DEA. A case study demonstrates the application of the proposed method.

A comparison of chance-constrained DEA and stochastic frontier analysis: bank efficiency in Taiwan

We employed both chance-constrained data envelopment analysis (CCDEA) and stochastic frontier analysis (SFA) to measure the technical efficiency of 39 banks in Taiwan. Estimated results show that there are significant differences in efficiency scores between chance-constrained DEA and stochastic frontier production function. The advanced setting of the chance-constrained mechanism of DEA does not change the instinctive differences between DEA and SFA approaches. We further find that the ownership variable is still a significant variable to explain the technical efficiency in Taiwan, irrespective of whether a DEA, CCDEA or SFA approach is used.

A comparison of chance-constrained DEA and stochastic frontier analysis: bank efficiency in Taiwan

We employed both chance-constrained data envelopment analysis (CCDEA) and stochastic frontier analysis (SFA) to measure the technical efficiency of 39 banks in Taiwan. Estimated results show that there are significant differences in efficiency scores between chance-constrained DEA and stochastic frontier production function. The advanced setting of the chance-constrained mechanism of DEA does not change the instinctive differences between DEA and SFA approaches. We further find that the ownership variable is still a significant variable to explain the technical efficiency in Taiwan, irrespective of whether a DEA, CCDEA or SFA approach is used.

Productive efficiency under capitalism and state socialism:: An empirical inquiry using chance-constrained data envelopment analysis

In this paper we undertake a comparison of the productive efficiency of a set of West European market economies and a set of East European planned economies. We employ the techniques of chance-constrained data envelopment analysis to conduct the comparison. These techniques are particularly appropriate when the performance of producers depends on their ability to make resource allocation decisions in the presence of technological and market uncertainties. We find the market economies to have been much more efficient in their allocation of resources.