A robust cross-efficiency data envelopment analysis model with undesirable outputs

2020 ◽  
pp. 114117
Author(s):  
Madjid Tavana ◽  
Mehdi Toloo ◽  
Nazila Aghayi ◽  
Aliasghar Arabmaldar
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Analysis Model ◽  
Efficiency Data

Evaluation of Supply Chain Efficiency Based on a Novel Network of Data Envelopment Analysis Model

2015 ◽  
Vol 25 (14) ◽  
pp. 1540036 ◽  
Author(s):  
Li Fang Fu ◽  
Jun Meng ◽  
Ying Liu
Keyword(s):  
Supply Chain ◽  
Data Envelopment Analysis ◽  
Decision Makers ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Analysis Model ◽  
Multilayer Network ◽  
Supply Chain Efficiency ◽  
Proposed Model

Performance evaluation of supply chain (SC) is a vital topic in SC management and inherently complex problems with multilayered internal linkages and activities of multiple entities. Recently, various Network Data Envelopment Analysis (NDEA) models, which opened the “black box” of conventional DEA, were developed and applied to evaluate the complex SC with a multilayer network structure. However, most of them are input or output oriented models which cannot take into consideration the nonproportional changes of inputs and outputs simultaneously. This paper extends the Slack-based measure (SBM) model to a nonradial, nonoriented network model named as U-NSBM with the presence of undesirable outputs in the SC. A numerical example is presented to demonstrate the applicability of the model in quantifying the efficiency and ranking the supply chain performance. By comparing with the CCR and U-SBM models, it is shown that the proposed model has higher distinguishing ability and gives feasible solution in the presence of undesirable outputs. Meanwhile, it provides more insights for decision makers about the source of inefficiency as well as the guidance to improve the SC performance.

scholarly journals Efektywność akademickich klubów sportowych funkcjonujących w szkolnictwie wyższym

Ekonomia ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 9-20
Author(s):  
Łukasz Brzezicki
Keyword(s):  
Data Envelopment Analysis ◽  
Empirical Models ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Sports Clubs ◽  
Sports Events ◽  
Efficiency Data

Efficiency of academic sports clubs operating in higher educationIn the article, the efficiency of 29 academic sports clubs in 2017 was measured using the NR-DEA non-radial-efficiency data envelopment analysis model. Two empirical models characterizing two different areas of activity of academic sports clubs were used in the study. The first model M1 fo­cused on club productivity, it includes the number of people practicing in the club and the total number of points obtained in the Polish Academic Championships. The second model M2 focused on club activity, it takes into account the number of organized events and participants taking part in the events. The results obtained show that sports clubs of technical universities were more often effective in terms of productivity than in terms of activity. A different situation occurs in university clubs, which were more often effective in terms of the activity of sports events, sporadically in terms of productivity.

Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model

2016 ◽  
Vol 16 (04) ◽  
pp. 1043-1068 ◽  
Author(s):  
Wei-Hsin Kong ◽  
Tsu-Tan Fu ◽  
Ming-Miin Yu
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Analysis Model ◽  
Negative Data ◽  
Two Stage ◽  
Data Set ◽  
Dea Model ◽  
Domestic Banks

This paper develops a range directional distance data envelopment analysis (DEA) model to simultaneously deal with the problems of negative data and undesirable outputs in the study of performance measurement with two-stage DEA. We report on the development of this model to handle both positive and negative data in a DEA framework and accommodate the problem of undesirable intermediate outputs in the first stage of operational processes. Unlike previous two-stage DEA models we allow for a nonuniform abatement factor imposing on stage 1’ production technology. Such a model is then applied to evaluate Taiwanese bank efficiencies both at the operational stage and profitability stage in banking activities based on a data set consisting of 35 domestic banks in Taiwan in the period 2007. The results indicate that, by the range directional two-stage data envelopment analysis model, the operational efficiency was smaller than the profitability efficiency. Many banks generated too many performing loans in which independent banks should reduce more performing loans than financial holding company subsidiary banks. Both the ratio of investments to loans and the ratio of nonperforming loans to performing loans did not have significant contributions to the efficiency. This paper is able to provide information for bank operators and researchers on the managerial and strategic implications of how negative data and undesirable outputs affect efficiency and how to measure efficiency appropriately.

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