Construct a composite indicator based on integrating Common Weight Data Envelopment Analysis and principal component analysis models: An application for finding development degree of provinces in Iran

Balanced development of regions requires the fair distribution of facilities and services. Hence, it is necessary to find and estimate the development degree of regions for policy makers. This paper presents an integrated Common Weight Data Envelopment Analysis (CWDEA) – Principal Component Analysis (PCA) model to find out the development degree of provinces in Iran. First, 131 suitable indicators are selected and then, the indicators are classified in fourteen different classes. In classical DEA model, each Decision Making Unit (DMU) is free to set its weights to reach the efficient frontier. In this paper, to restrict flexibility in indicator weights, development degree of provinces in each class is calculated using CWDEA model. Since, the proposed CWDEA model is not capable of fully ranking of provinces with all indicators, hence, the development degrees generated by CWDEA model are considered as indicators of PCA and the final ranks are obtained using PCA model. The results of proposed CWDEA-PCA model show that Yazd, Semnan and Bushehr are top three provinces in Iran.     

The efficient use of enterprise information for strategic advantage: A data envelopment analysis

A majority of manufacturers make use of some form of enterprise systems (ES), yet on average, the financial impact of ES adoption is essentially neutral. We propose that in an ES environment of easy information access, competitive success depends, in part, on the policies regulating enterprise information use. To explore this proposition, we examine the efficient use of different types of enterprise information in the realization of strategic performance. Efficient firms will devote fewer resources to information use to achieve the same strategic performance as less efficient firms.     

An application of data envelopment analysis to evaluate the efficiency level of the operational cost of Brazilian electricity distribution utilities

This paper shows efficiency indices for 60 Brazilian electricity distribution utilities. The efficiency scores are gauged by three DEA models. For both models, these quantities are evaluated under different contexts. One treats with respect to the regulator perspective. The others examine an alternative approach based on cluster analysis and restrictions on factor weights. It is worth pointing out that these developments can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental in incentive regulation schemes.     

A non-parametric index of corporate governance in the banking industry: An application to Indian data

This paper presents a methodological framework for constructing a non-parametric index of corporate governance for banks. The index is constructed by aggregating six distinct dimensional indices capturing different dimensions of corporate governance, namely board effectiveness, audit function, risk management, remuneration, shareholder rights and information, and disclosure and transparency. For aggregation, a tailored version of data envelopment analysis (DEA) approach which is popularly known as constrained ‘Benefit-of-the-Doubt (BoD)’ model is employed. This approach is unique and distinctive in the sense that it requires no a priori knowledge of weights, and assigns endogenous weights obtained from actual data to individual dimensions of bank governance in order to construct a composite index of corporate governance. This methodological framework has illustrated by applying it for a data set of 40 Indian banks operating in the year 2017. The data set has been compiled using 58 governance regulations as defined by relevant jurisdictions.