Tsolas, I., Charles, V. and Gherman, T. (2020) Supporting Better Practice Benchmarking: A DEA-ANN Approach to Bank Branch Performance Assessment. Expert Systems with Applications. 160, pp. 1-12. 0957-4174.
| Item Type: | Article |
|---|---|
| Abstract: | The quest for best practices may lead to an increased risk of poor decision-making, especially when aiming to attain best practice levels reveals that efforts are beyond the organization’s present capabilities. This situation is commonly known as the “best practice trap”. Motivated by such observation, the purpose of the present paper is to develop a practical methodology to support better practice benchmarking, with an application to the banking sector. In this sense, we develop a two-stage hybrid model that employs Artificial Neural Network (ANN) via integration with Data Envelopment Analysis (DEA), which is used as a preprocessor, to investigate the ability of the DEA-ANN approach to classify the sampled branches of a Greek bank into predefined efficiency classes. ANN is integrated with a family of radial and non-radial DEA models. This combined approach effectively captures the information contained in the characteristics of the sampled branches, and subsequently demonstrates a satisfactory classification ability especially for the efficient branches. Our prediction results are presented using four performance measures (hit rates): percent success rate of classifying a bank branch’s performance exactly or within one class of its actual performance, as well as just one class above the actual class and just one class below the actual class. The proposed modeling approach integrates the DEA context with ANN and advances benchmarking practices to enhance the decision-making process for efficiency improvement. |
| Uncontrolled Keywords: | Artificial Neural Network, Data Envelopment Analysis, Banking, Performance, Best Practice, Benchmarking, Artificial Intelligence |
| Creators: | Tsolas, Ioannis, Charles, Vincent and Gherman, Tatiana |
| Faculties, Divisions and Institutes: |
Faculties > Faculty of Business & Law > International Strategy & Business University Faculties, Divisions and Research Centres - OLD > Research Centre > China and Emerging Economies Centre Research Centres > China and Emerging Economies Centre |
| Date: | 25 May 2020 |
| Date Type: | Acceptance |
| Page Range: | pp. 1-12 |
| Journal or Publication Title: | Expert Systems with Applications |
| Volume: | 160 |
| Number of Pages: | 12 |
| Language: | English |
| DOI: | https://doi.org/10.1016/j.eswa.2020.113599 |
| ISSN: | 0957-4174 |
| Status: | Published / Disseminated |
| Refereed: | Yes |
| Related URLs: | |
| URI: | http://nectar.northampton.ac.uk/id/eprint/13191 |
Actions (login required)
 |
Edit Item |
Altmetric
Altmetric