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An algorithmic approach for modelling customer expectations

Author

Listed:
  • Nicolae POP

    (Academy of Economic Studies, Bucharest)

  • Adriana AGAPIE

    (Academy of Economic Studies, Bucharest)

  • Nicolae TEODORESCU

    (Academy of Economic Studies, Bucharest)

Abstract

The scope of this article is to discuss the dynamics of formatting customer expectations in financial services-under two models for assessing cumulative learning in customer expectations. The first model is a classical Bayesian one, the second model is an entirely new application of the Repetitive Stochastic Guesstimation (RSG) algorithm. The traditional assumption of postulating that empirical data have been generated from an underlying probability has been questioned even by orthodox theorists. Our research strategy is to cast this problem in the form of an optimization problem and show that RSG algorithm will produce a relevant solution for the original economic problem.

Suggested Citation

  • Nicolae POP & Adriana AGAPIE & Nicolae TEODORESCU, 2009. "An algorithmic approach for modelling customer expectations," Management & Marketing, Economic Publishing House, vol. 4(1), Spring.
    • Handle: RePEc:eph:journl:v:4:y:2009:i:1:n:5
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    References listed on IDEAS

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    3. Charemza, Wojciech W, 2002. "Guesstimation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(6), pages 417-433, September.
    4. Albert Marcet, 1991. "Solving non-linear stochastic models by parameterizing expectations: An application to asset pricing with production," Economics Working Papers 5, Department of Economics and Business, Universitat Pompeu Fabra.
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