Data Envelopment Analyses
Parisa Nankali; Fatemeh Rakhshan; Mohammad Reza Alirezaee
Abstract
Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due ...
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Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due to the corona virus pandemic.Methodology: In this study, first, by considering the appropriate loyalty codes at the level of bank branches, we define the appropriate weight constraints of the type of confidence zone constraints of the first type and add them to the basic model of data envelopment analysis. The new size obtained from this mathematical model is due to the effect of loyalty constraints and will have more resolution than the basic model. The loyalty factor of each branch is then defined as the ratio of the size of the new model to the base model, which will be a number between zero and one. Then, the proposed model is implemented in a case study consisting of 195 branches of the Housing Bank and the results of the model are analyzed.Findings: The results show that the loyalty factor is directly related to the quality of in-person services and a new measure of efficiency is obtained to monitor customer loyalty.Originality/Value: The data envelopment analysis method can be a suitable technique to evaluate the role of non-personal bank services in the level of customer loyalty and can help banks to retain customers.
Data Envelopment Analyses
Mohammad Reza Alirezaee; Fatemeh Rakhshan; Bahareh Banaye khoyi
Abstract
One of the problems in portfolio selection, is choosing a stock with conflicting and incomparable objectives such as return and risk. DEA cross efficiency is one of the most useful tools in assessing performance and prioritize a number of firms that makes it possible to determine efficient units in portfolio ...
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One of the problems in portfolio selection, is choosing a stock with conflicting and incomparable objectives such as return and risk. DEA cross efficiency is one of the most useful tools in assessing performance and prioritize a number of firms that makes it possible to determine efficient units in portfolio selection from different industries. Although cross efficiency is an approach for evaluating performance, it application is improved in portfolio selection. The method used in this research, calculates the (average) cross efficiency scores and considers its changes and then incorporates two statistics of cross efficiency into the mean-variance (MV) formulation of portfolio selection. This method has two advantages: One is selection of portfolios well-diversified in terms of their performance on multiple evaluation criteria, and the other is alleviation of the so-called ‘‘ganging together’’ phenomenon of DEA cross-efficiency evaluation in portfolio selection. This procedure is applied on stock portfolio selection in the Iranian stock market consist of 20 reputable companies and efficiency changes with causes over this period is examined. It is demonstrated in this paper that the selected portfolio yields higher risk-adjusted returns than two stock market index for a 9-year sample period.