Bank branch operational performance: A robust multivariate and clustering approach
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- 作者：Oscar Herrera-Restrepoa ; oscar84@vt.edu" class="auth_mail" title="E-mail the corresponding author ; Konstantinos Triantisa ; triantis@vt.edu" class="auth_mail" title="E-mail the corresponding author ; William L. Seaverb ; wseaver@utk.edu" class="auth_mail" title="E-mail the corresponding author ; Joseph C. Paradic ; paradi@mie.utoronto.ca" class="auth_mail" title="E-mail the corresponding author ; Haiyan Zhud ; haiyanzhu29@gmail.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Data envelopment analysis ; Influential observations ; Robust principal component analysis ; Meta-frontier ; Cluster-frontier ; Bank branch performance
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：15 May 2016
- 年：2016
- 卷：50
- 期：Complete
- 页码：107-119
- 全文大小：1230 K
文摘
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Integration of robust clustering analysis and DEA to study bank branch performance.
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Detection of influential branches, i.e., exhibiting extreme operating behaviors.
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Detection of influential branches affecting the clustering and efficiency performance.
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Exploration of how peer selection is affected by influential branches.
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Influential-based and cluster profiles that inform network design decisions.