Applying Multi-objective Optimization for Variable Selection to Analyze User Trust in Electronic Banking

  • F. Liébana-Cabanillas
  • R. Nogueras
  • F. Muñoz-Leiva
  • I. Rojas
  • A. Guillén
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 171)


The potential fraud problems, international economic crisis and the crisis of confidence in markets have affected financial institutions, which have tried to maintain customer trust in many different ways. To maintain the trust level in financial institutions, the implementation of electronic banking for customers has been considered a successful strategy. However, the parameters that define user trust have not been analysed in detail due to the lack of experience and the recent use of e-banking. This paper aims to determine which variables are relevant to user trust by applying machine learning techniques as multi-objective genetic algorithms for the preparation of business strategies to improve confidence and profitability. The algorithms have been tuned following the indications given by experts and their results have been validated by them, setting a level of reliability. There is also a comparison among different fitness functions used in the evolution process that are able to rank the subset of variables encoded by the individuals.


Mutual Information Variable Selection Pareto Front Decision Vector User Trust 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Álvarez, J.M.: La banca española ante la actual crisis financiera. Estabilidad Financiera 15, 23–38 (2008)Google Scholar
  2. 2.
    Karjaluoto, H., Mattila, M., Pento, T.: Factors underlying attitude formation toward online banking in Finland. International Journal of Bank Marketing 20(6), 261–272 (2002)CrossRefGoogle Scholar
  3. 3.
    Hsu, S.H.: Developing an index for online customer satisfaction: Adaptation of American Customer Satisfaction Index. Expert Systems with Applications 34, 3033–3042 (2008)CrossRefGoogle Scholar
  4. 4.
    Berrocal, M.: Fidelización y Venta Cruzada. Informe Caja Castilla La Mancha (2009)Google Scholar
  5. 5.
    Delgado, J., Nieto, M.J.: Incorporación de la tecnología de la información a la actividad bancaria en España: La banca por Internet. Estabilidad financiera, Banco de España 3, 85–105 (2002)Google Scholar
  6. 6.
    Muñoz-Leiva, F.: La adopción de una innovación basada en la Web. Tesis Doctoral. Departamento de Comercialización e Investigación de Mercados, Universidad de Granada (2008)Google Scholar
  7. 7.
    Lam, S.Y., Shankar, V., Murthy, M.K.: Customer Value, Satisfaction, Loyalty, and Switching Costs: An Illustration from a Business-to-Business Service Context. Journal of the Academy of Marketing Science 32(3), 293–311 (2004)CrossRefGoogle Scholar
  8. 8.
    García, N., Sanzo, M.J., Trespalacios, J.A.: Can a good organizational climate compensate for a lack of top management commitment to new product development? Journal of Business Research 61, 118–131 (2008)CrossRefGoogle Scholar
  9. 9.
    Ha, H.Y.: Factors Influencing Consumer Perceptions of Brand Trust Online. Journal of Product and Brand Management 13(5), 329–342 (2004)CrossRefGoogle Scholar
  10. 10.
    Laroche, M., Yang, Z., Mcdougall, G.H.G., Bergeron, J.: Internet Versus Bricks-and- Mortar Retailers: An Investigation Into Tangibility and Its Consequences. Journal of Retailing 81(4), 251–267 (2005)CrossRefGoogle Scholar
  11. 11.
    Muñoz-Leiva, F., Luque-Martínez, T., Sanchez-Fernandez, J.: How to improve trust toward electronic banking. Online Information Review 34(6), 907–934 (2010)CrossRefGoogle Scholar
  12. 12.
    Flavián, C., Guinalíu, M.: Un análisis de la influencia de la confianza y del riesgo percibido sobre la lealtad a un sitio web: el caso de la distribución de servicios gratuitos. Revista Europea de Dirección y Economía de la Empresa 16(1), 159–178 (2007)Google Scholar
  13. 13.
    Flavián, C., Guinalíu, M., Gurrea, R.:: Análisis empírico de la influencia ejercida por la usabilidad percibida, la satisfacción y la confianza del consumidor sobre la lealtad a un sitio web. In: XVI Encuentros de Profesores Universitarios de Marketing, pp. 209–226. Esic (2004)Google Scholar
  14. 14.
    Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2) (2002)Google Scholar
  15. 15.
    Srinivas, N., Deb, K.: Multi-objective Optimization using Nondominated sorting in Genetic Algorithms. Evolutionary Computation 2(3), 221–248 (1994)CrossRefGoogle Scholar
  16. 16.
    Eirola, E., Liitiainen, E., Lendasse, A., Corona, F., Verleysen, M.: Using the Delta Test for Variable Selection. In: ESANN 2008 Proceedings, European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, Bruges, Belgium (2008)Google Scholar
  17. 17.
    Gallant, S.I.: Perceptron-based learning algorithms. IEEE Transactions on Neural Networks 1(2), 179–191Google Scholar
  18. 18.
    Guillen, A., Sovilj, D., Lendasse, A., Mateo, F., Rojas, I.: Minimising the Delta Test for Variable Selection in Regression Problems. International Journal High Performance Systems Architecture 1(4) (2008)Google Scholar
  19. 19.
    Pi, H., Peterson, C.: Finding the Embedding Dimension and Variable Dependencies in Time Series. Neural Computation 6(3), 509–520 (1994)CrossRefGoogle Scholar
  20. 20.
    Lendasse, A., Corona, F., Hao, J., Reyhani, N., Verleysen, M.: Determination of the Mahalanobis matrix using nonparametric noise estimations. In: ESANN, pp. 227–232 (2006)Google Scholar
  21. 21.
    Kraskov, A., Stögbauer, H., Grassberger, P.: Estimating mutual information. Physics Review (June 2004)Google Scholar
  22. 22.
    Kwak, N., Choi, C.H.: Input Feature Selection by Mutual Information Based on Parzen Window. IEEE Trans. Pattern Analysis and Machine Intelligence 24(12), 1667–1671 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • F. Liébana-Cabanillas
    • 1
  • R. Nogueras
    • 2
  • F. Muñoz-Leiva
    • 3
  • I. Rojas
    • 1
  • A. Guillén
    • 2
  1. 1.Distribution Channels in Caja Rural Granada, Dpt. of Marketing, and Market ResearchUniversity of GranadaGranadaSpain
  2. 2.Dpt. of Computer Technology and ArchitectureUniversity of GranadaGranadaSpain
  3. 3.Dpt. of Marketing and Market ResearchUniversity of GranadaGranadaSpain

Personalised recommendations