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An algorithmic approach for modelling customer expectations

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  • 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.

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File URL: http://www.managementmarketing.ro/pdf/articole/127.pdf
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Bibliographic Info

Article provided by Economic Publishing House in its journal Management & Marketing.

Volume (Year): 4 (2009)
Issue (Month): 1 (Spring)
Pages:

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Handle: RePEc:eph:journl:v:4:y:2009:i:1:n:5

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Related research

Keywords: Bayesian updating; Computational economics; Customer expectations; Repetitive Stochastic Guesstimation.;

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  1. Wojciech W. Charemza, 1998. "Guesstimation," Discussion Papers in Economics 98/1, Department of Economics, University of Leicester, revised Sep 1998.
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