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

By Desheng Dash Wu, Zijiang Yang, Liang Liang. Expert systems with applications, 2006

349 citations recorded by the source corpus.

Subfields: Accounting, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/200a6a981f3c336c74e02079789d6a42992f8fd3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. Nan Li
2. Thurasamy Ramayah
3. Desheng Dash Wu

In Management Science and Operations Research

1. Nan Li
2. Thurasamy Ramayah
3. Desheng Dash Wu

In Strategy and Management

1. Nan Li
2. Desheng Dash Wu

Citations in the corpus

• Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2010, neutral): “There are studies however, which evaluate bank branch performance with DEA and compare the results with other methodologies, i.e. FDH (Portela et al., 2003), Malmquist indices (Camanho and Dyson, 2006), log-linear frontier method (Giokas, 2008a), ABC Plus (Kantor and Maital, 1999), OCRA (Parkan and ”
• The Impact of Service Quality on Customer Loyalty: A Study of Banks in Penang, Malaysia (2010, background): “Wu et al. (2006) integrates data envelopment analysis (DEA) and neural network (NNs) to examine the relative branch efficiency.”
• Using text mining and sentiment analysis for online forums hotspot detection and forecast (2010, methodology): “Application of SVM includes text classification [15], image processing [24], and time series analysis [25] [32].”