Input/Output Variables Selection in Data Envelopment Analysis: A Shannon Entropy Approach

Abstract

The purpose of this study is to provide an efficient method for the selection of input–output indicators in the data envelopment analysis (DEA) approach, in order to improve the discriminatory power of the DEA method in the evaluation process and performance analysis of homogeneous decision-making units (DMUs) in the presence of negative values and data. For this purpose, the Shannon entropy technique is used as one of the most important methods for determining the weight of indicators. Moreover, due to the presence of negative data in some indicators, the range directional measure (RDM) model is used as the basic model of the research. Finally, to demonstrate the applicability of the proposed approach, the food and beverage industry has been selected from the Tehran stock exchange (TSE) as a case study, and data related to 15 stocks have been extracted from this industry. The numerical and experimental results indicate the efficacy of the hybrid data envelopment analysis–Shannon entropy (DEASE) approach to evaluate stocks under negative data. Furthermore, the discriminatory power of the proposed DEASE approach is greater than that of a classical DEA model.

Construction of power system evaluation system oriented to common prosperity based on entropy weight method

“…At this time, if the entropy of the indicator is the smallest, the weight will be large, and if the entropy of the indicator is the largest, the weight will be small. The calculation steps of the weight determination method of the entropy value method [10] :…”

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces

“…The selection of inputs and outputs in DEA, a non-parametric method, determines the production or operational process under evaluation [ 64 ]. Incorrect or unrelated options can result in skewed efficiency outcomes, impeding the capacity to pinpoint areas for enhancement in the assessed firms [ 65 ]. Hence, it is crucial to carefully choose inputs and outputs relevant to the unique situation to get meaningful and practical efficiency estimates using DEA [ 66 ].…”

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

“…These four major categories of financial ratios represent the underlying financial strengths of a firm. Based on the literature (Edirisinghe & Zhang, 2007, 2008Kuo et al, 2021;Lim et al, 2014;Peykani et al, 2022;Rahiminezhad Galankashi et al, 2020;Wu et al, 2022;Xidonas et al, 2009), expert opinions (from fund managers and financial advisors), and the Delphi method (utilizing questionnaires), we select a total of 14 critical financial parameters that encompass all of these perspectives to serve as inputs and outputs for our DEA model, as presented in Table 2. In the DEA model, parameters that follow the 'the more, the better' principle are used as outputs, while those adhering to 'the fewer, the better' principle are classified as inputs (Cook et al, 2014).…”

“…On the other hand, there are various ways to implement FA, one of which is Data Envelopment Analysis (DEA) (Abad et al, 2004;Edirisinghe & Zhang, 2007, 2008Lim et al, 2014). DEA is a data-enabled performance evaluation technique that evaluates the relative efficiency of decision-making units (DMUs) considering several inputs and outputs (Emrouznejad & Yang, 2018;Zhu, 2022) and can be leveraged in the process of financial portfolio construction to measure assets' efficiencies, thereby specifying the best assets for investment (Edirisinghe & Zhang, 2007, 2008Lim et al, 2014;Peykani et al, 2020Peykani et al, , 2022. Consequently, DEA approaches can be used as a means of FA in the portfolio selection context in order to fundamentally assess a firm's investment worthiness based on comparison to the market as a whole, rather than evaluating it in isolation, thus contributing to the identification of financially healthy firms.…”