A multivariate model of integrated branch performance and potential focusing on personal banking

Avkiran, Necmi Kemal (1995) A multivariate model of integrated branch performance and potential focusing on personal banking. PhD thesis, Victoria University of Technology.

Abstract

Existing methodologies of bank branch performance analysis are dominated by accounting and financial measures that inherently generate information of a retrospective nature. The outcomes are a possible misleading assessment of a branch's economic viability and misguided planning decisions in reconfiguring a branch. ... This study develops three principal models for an integrated analysis of personal banking performance, based on data collected from branches of a major Australian trading bank. In conclusion, the study delivers a model of overall performance comprised of eight variables; a model of overall potential also comprised of eight variables,- and, a discriminant model comprised of five predictors and two functions with validated coefficients, and a cross-validated correct classification rate. In addition, scales developed for such constructs as customer service quality and managerial competence can be applied independent of regression analysis and discriminant analysis models. It is submitted that the findings of the study can be used in decisions concerning reconfiguring, closing, or opening branches. Furthermore, the study could assist in minimising the gap between current branch performance and branch potential, by focusing attention on the treatment of variables that are controllable by bank management.

Additional Information

Includes bibliographical references: pp.305-327

Item type Thesis (PhD thesis)
URI https://vuir.vu.edu.au/id/eprint/15434
Subjects Historical > Faculty/School/Research Centre/Department > School of Economics and Finance
Historical > FOR Classification > 1402 Applied Economics
Keywords Branch banks, Evaluation, customer services
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login