Bank branch operational performance: A robust multivariate and clustering approach
作者：
Highlights：
• Integration of robust clustering analysis and DEA to study bank branch performance.
• Detection of influential branches, i.e., exhibiting extreme operating behaviors.
• Detection of influential branches affecting the clustering and efficiency performance.
• Exploration of how peer selection is affected by influential branches.
• Influential-based and cluster profiles that inform network design decisions.
摘要
•Integration of robust clustering analysis and DEA to study bank branch performance.•Detection of influential branches, i.e., exhibiting extreme operating behaviors.•Detection of influential branches affecting the clustering and efficiency performance.•Exploration of how peer selection is affected by influential branches.•Influential-based and cluster profiles that inform network design decisions.
论文关键词：Data envelopment analysis,Influential observations,Robust principal component analysis,Meta-frontier,Cluster-frontier,Bank branch performance
论文评审过程：Received 12 October 2015, Revised 22 December 2015, Accepted 23 December 2015, Available online 29 December 2015, Version of Record 15 January 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.12.025
