scholarly journals EVALUATION OF FINANCIAL HEALTH OF COMPANIES THROUGH DATA ENVELOPMENT ANALYSIS: SELECTION OF VARIABLES FOR THE DEA MODEL IN R

2020 ◽  
Author(s):  
Emil Exenberger ◽  
Michaela Kavčáková
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Financial Health ◽  
Dea Model ◽  
Selection Of Variables ◽  
Selection Of

scholarly journals Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 160
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Data Envelopment Analysis ◽  
Logit Model ◽  
Estimation Accuracy ◽  
Data Envelopment Analysis Model ◽  
Type I ◽  
Data Envelopment ◽  
Financial Health ◽  
Error Type ◽  
Suitable Alternative ◽  
Dea Model

This paper focuses on business financial health evaluation with the use of selected mathematical and statistical methods. The issue of financial health assessment and prediction of business failure is a widely discussed topic across various industries in Slovakia and abroad. The aim of this paper was to formulate a data envelopment analysis (DEA) model and to verify the estimation accuracy of this model in comparison with the logit model. The research was carried out on a sample of companies operating in the field of heat supply in Slovakia. For this sample of businesses, we selected appropriate financial indicators as determinants of bankruptcy. The indicators were selected using related empirical studies, a univariate logit model, and a correlation matrix. In this paper, we applied two main models: the BCC DEA model, processed in DEAFrontier software; and the logit model, processed in Statistica software. We compared the estimation accuracy of the constructed models using error type I and error type II. The main conclusion of the paper is that the DEA method is a suitable alternative in assessing the financial health of businesses from the analyzed sample. In contrast to the logit model, the results of this method are independent of any assumptions.

Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance

2021 ◽  
pp. 0258042X2110025
Author(s):  
B. Senthil Arasu ◽  
Desti Kannaiah ◽  
Nancy Christina J. ◽  
Malik Shahzad Shabbir
Keyword(s):  
Data Envelopment Analysis ◽  
Stock Exchange ◽  
Secondary Market ◽  
Data Envelopment ◽  
Stock Performance ◽  
The Past ◽  
Financial Strength ◽  
Selection Of Variables ◽  
Selection Of ◽  
Past Price

Data envelopment analysis (DEA) is a relative measurement technique used to evaluate the efficiencies of a homogeneous group of samples with multiple inputs and/or outputs. DEA can be highly effective when right variables are chosen. The objective of this study is to identify the most appropriate variables for DEA to evaluate stock performance and find the efficient ones from a pool of stocks. Evaluation of stocks are carried out either by assessing their financial strength or by assessing their past price behaviour in the secondary market or both. In any case, it is imperative to use suitable variables to evaluate the performance of stocks. For this purpose, three different combinations of variables were tested on 69 non-financial stocks listed in the National Stock Exchange (NSE), which were selected based on their market capitalization. The results obtained suggest that all the three sets of variables taken for the study help in the identification of efficient stocks. The average returns of the stocks selected in all the three cases are higher than the market return. Among the three sets, stocks identified using the past price behaviour give a higher return when compared to the other two sets. The study can help academicians and investors to percolate efficient stocks from a large pool of stocks. The selected stocks can be further analysed to construct an effective portfolio.

scholarly journals ANALYTICAL HIERARCHY PROCESS METHOD AND DATA ENVELOPMENT ANALYSIS APPLICATION IN TERRAIN VEHICLE SELECTION

Transport ◽  
2019 ◽  
Vol 34 (5) ◽  
pp. 600-616 ◽  
Author(s):  
Slobodan Starčević ◽  
Nebojša Bojović ◽  
Raimundas Junevičius ◽  
Viktor Skrickij
Keyword(s):  
Data Envelopment Analysis ◽  
Analytical Hierarchy Process ◽  
Data Envelopment ◽  
Ahp Method ◽  
Dea Model ◽  
Consistency Model ◽  
Analysis Application ◽  
Ranking Of Alternatives ◽  
Hierarchy Process ◽  
Selection Of

Selection of a terrain vehicle for performing different tasks is an important factor, which influences the mobility of a user through the quality of conducting transport activities. This paper is dealing with the problem of the terrain vehicle selection for the equipping of military units which, are to be engaged in multinational operations, using the Analytical Hierarchy Process (AHP) method and Data Envelopment Analysis (DEA). Determination of the relative importance of criteria, which are used for evaluation of potential alternatives is conducted through AHP method. The results proposed by the AHP method are used as multiple outputs of the defined DEA model for the selection of the terrain vehicle. Based on the DEA model the efficiencies of alternatives are defined and also the final ranking of alternatives is determined. Besides the hybrid model AHP-DEA, which is the integral part of a basic multicriteria model in this paper the possible applications of Best Worst Method (BWM) and FUll COnsistency Model (FUCOM) are presented through validation of models. The validation is conducted through statistical data obtained by application of different multicriteria techniques, using Spearman’s Correlation Coefficient (SCC).

scholarly journals Operational Efficiency of Chinese Provincial Electricity Grid Enterprises: An Evaluation Employing a Three-Stage Data Envelopment Analysis (DEA) Model

2018 ◽  
Vol 10 (9) ◽  
pp. 3168 ◽  
Author(s):  
Haoran Zhao ◽  
Huiru Zhao ◽  
Sen Guo
Keyword(s):  
Data Envelopment Analysis ◽  
Environmental Variables ◽  
Market Competition ◽  
Environmental Values ◽  
Operational Efficiency ◽  
Data Envelopment ◽  
Electricity Grid ◽  
Frontier Analysis ◽  
Dea Model ◽  
Statistical Noise

With the implementation of new round electricity system reform in China, the provincial electricity grid enterprises (EGEs) of China should focus on improving their operational efficiency to adapt to the increasingly fierce market competition and satisfy the requirements of the electricity industry reform. Therefore, it is essential to conduct operational efficiency evaluation on provincial EGEs. While considering the influences of exterior environmental variables on the operational efficiency of provincial EGEs, a three-stage data envelopment analysis (DEA) methodology is first utilized to accurately assess the real operational efficiency of provincial EGEs excluding the exterior environmental values and statistical noise. The three-stage DEA model takes the amount of employees, the fixed assets investment, the 110 kV and below distribution line length, and the 110 kV and below transformer capacity as input variables and the electricity sales amount, the amount of consumers, and the line loss rate as output variables. The regression results of the stochastic frontier analysis model indicate that the operational efficiencies of provincial EGEs are significantly affected by exterior environmental variables. Results of the three-stage DEA model imply that the exterior environmental values and statistical noise result in the overestimation of operational efficiency of provincial EGEs, and the exclusion of exterior environmental values and statistical noise has provincial-EGE-specific influences. Furthermore, 26 provincial EGEs are divided into four categories to better understand the differences of operational efficiencies before and after the exclusion of exterior environmental values and statistical noise.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

scholarly journals Sustainability Evaluation of Product Packaging System with a Three-Stage Network Data Envelopment Analysis Methodology

2019 ◽  
Vol 9 (2) ◽  
pp. 246 ◽  
Author(s):  
Yong Xie ◽  
Yafang Gao ◽  
Shihao Zhang ◽  
Hailong Bai ◽  
Zhenghao Liu
Keyword(s):  
Life Cycle ◽  
Data Envelopment Analysis ◽  
Empirical Test ◽  
Environmentally Friendly ◽  
Network Data ◽  
Data Envelopment ◽  
Packaging System ◽  
Product Packaging ◽  
Dea Model ◽  
Network Data Envelopment Analysis

This study presents a method that is based on the three-stage network Data Envelopment Analysis (DEA) to evaluate the sustainability of packaging systems for a product. This method facilitates the selection of better product packaging alternatives from an environmentally friendly point of view and it comprises the following four steps: (i) the definition of packaging sustainability indicator (PSI) based on environmental efficiency and impact indicator of three-stage in packaging life cycle, (ii) modeling a three-stage Network DEA model for a packaging system, (iii) computing PSI based on the DEA model, and (iv) result analysis. An empirical test has been progressed to prove the feasibility of the proposed method by selecting the three types of milk packaging systems. The results indicated that the PSI value of PrePack is the maximum and the Tetra Pak minimum. According to these results, the study provides an environmentally friendly evaluation method for product packaging systems, which is more intuitive than Life Cycle Assessment (LCA).

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