Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank

Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks

“…This being the case, several researchers (Cooper et al, 1999;Despotis and Smirlis, 2002;Guo and Tanaka, 2001;Jahanshahloo et al, 2004;Kao and Liu, 2000b) started structuring FDEA models, allowing for the measurement of outputs and inputs as fuzzy numbers. Particularly with respect to FDEA applications on banking, studies to assess efficiency in the financial sector still remain scarce, and their major focus tends to relate to ranking of DMUs based on computed fuzzy efficiencies rather than predicting or explaining efficiency levels in terms of contextual variables (Chen et al, 2013;Puri & Yadav, 2014;Puri & Yadav, 2013;Wang et al, 2014;Hsiao et al, 2011;Wu et al, 2006). According to Hatami-Marbini et al (2011a), the huge dissemination of different models within a large scope of applications in terms of efficiency measurement demonstrates that FDEA models represent an effective path for handling uncertainty and vagueness when inputs/outputs are imprecise (Kao & Liu, 2000b).…”

“…Thus far, applications of FDEA to measure bank efficiency have been scarce and focused on ranking DMUs rather than predicting their efficiency levels based on a set of contextual variables (Chen et al, 2013;Puri & Yadav, 2014;Puri & Yadav, 2013;Wang, Lu & Liu, 2014;Hsiao et al, 2011;Wu, Yang, & Liang, 2006). This paper innovates first by focusing on Mozambican banks and second by simultaneously adopting three major FDEA models based on the α-level approach in combination with the conditional bootstrapped truncated regression, proposed…”

The Impact of Service Quality on Customer Loyalty: A Study of Banks in Penang, Malaysia

“…The key objective of NPM, for instance, is to improve the delivery of service quality by taking a customer-oriented approach (Mwita, 2000). Wu et al (2006) integrates data envelopment analysis (DEA) and neural network (NNs) to examine the relative branch efficiency. The use of the DEA technique in performance benchmarking of bank branches has evolved from relative benchmarking of performance in terms of operating efficiency (service quality) and profitability (Manandhar & Tang, 2002).…”

A Novel Electric Power Plants Performance Assessment Technique Based on Genetic Programming Approach

“…The ANN implementation is needed to be done by a computer program. The new hybrid approach combining DEA and ANNs (Athanassopoulos & Curram, 1996) has been applied in many fields (Mostafa, 2009;Pendharka, 2010;Çelebi & Bayraktar, 2008;Wu, 2009;Wu et al, 2006;Wang et al, 2009 (Kaboudan, 2003) such as forecasting electricity demand (Lee et al, 1997); forecasting long term energy consumption (Karabulut et al, 2008) in real-time runoff (Khu et al, 2001); predicting financial data (Iba & Sasaki, 2002); predicting stock prices (Kaboudan, 2000) in fault analysis of the diesel engine fuel (Sun et al, 2004); prediction of ski-jump bucket spillway scour (Azamathulla et al, 2008); river pipeline scour (Azamathulla & Ghani, 2010) and longitudinal dispersion coefficients in streams (Azamathulla & Ghani, 2011) and etc. This study presents a genetic programming procedure for performance evaluating of a set of homogeneous steam power plants and benchmarking.…”