Monitoring and Improving Greek Banking Services Using Bayesian Networks: an Analysis of Mystery Shopping Data
Mystery shopping is a well known marketing technique used by companies and marketing analysts to measure quality of service, and gather information about products and services. In this article, we analyse data from mystery shopping surveys via Bayesian networks in order to examine and evaluate the quality of service offered by the loan departments of Greek banks. We use mystery shopping visits to collect information about loan products and services and, by this way, evaluate the customer satisfaction and plan improvement strategies that will assist Banks to reach their internal standards. Bayesian Networks not only provide a pictorial representation of the dependence structure between the characteristics of interest but also allow to evaluate, interpret and understand the effects of possible improvement strategies.
|Date of creation:||Jan 2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://dipartimenti.unipv.eu/on-dip/epmq/Home.html
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lauritzen, Steffen L., 1995. "The EM algorithm for graphical association models with missing data," Computational Statistics & Data Analysis, Elsevier, vol. 19(2), pages 191-201, February.
- John Mylonakis, 2009. "Customer Relationship Management Functions: A Survey of Greek Bank Customer Satisfaction Perceptions," The IUP Journal of Bank Management, IUP Publications, vol. 0(2), pages 7-31, May.
- Mihelis, G. & Grigoroudis, E. & Siskos, Y. & Politis, Y. & Malandrakis, Y., 2001. "Customer satisfaction measurement in the private bank sector," European Journal of Operational Research, Elsevier, vol. 130(2), pages 347-360, April.
- Silvia Salini & Ron Kenett, 2009.
"Bayesian networks of customer satisfaction survey data,"
Journal of Applied Statistics,
Taylor & Francis Journals, vol. 36(11), pages 1177-1189.
- Silvia SALINI & Ron S. KENETT, 2007. "Bayesian networks of customer satisfaction survey data," Departmental Working Papers 2007-33, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
When requesting a correction, please mention this item's handle: RePEc:pav:wpaper:160. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paolo Bonomolo)
If references are entirely missing, you can add them using this form.