The Contribution of Data Analysis in Bank Branch Classification. Case Study:« Société Générale Algeria »

المؤلفون

  • akila lanseur
  • sabrina boukellal

الكلمات المفتاحية:

Keywords: Quantitative methods, PCA, HCA, performance, bank branches.

الملخص

This study employs Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to evaluatebankbranch performance within Société Générale Algeria's network. Conducted at the bank's headquarters in Algiers, this research aims to provide marketing managers with a scientifically rigorous framework for assessing and categorizing branch performance across Algeria's national territory. The methodology combines PCA to identify key performance dimensions among variables, followed by HCA to segment 81 surveyed branches into homogeneous clusters. The findings reveal two primary performance dimensions, profitability and market orientationand establish three distinct branch categories ranked according to their overall performance levels.

JEL Classification Codes: M31, M39

مشاهدات الملخص: 50 pdf (الإنجليزية) التنزيلات: 12

المراجع

التنزيلات

منشور

2025-09-30

إصدار

القسم

المقالات

كيفية الاقتباس

The Contribution of Data Analysis in Bank Branch Classification. Case Study:« Société Générale Algeria ». (2025). مجلة إضافات إقتصادية, 9(2), 852-867. https://journals.univ-ghardaia.edu.dz/idafat/article/view/1884

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