An algorithmic approach for modelling customer expectations
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.
Volume (Year): 4 (2009)
Issue (Month): 1 (Spring)
|Contact details of provider:|| |
References listed on IDEAS
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.:
When requesting a correction, please mention this item's handle: RePEc:eph:journl:v:4:y:2009:i:1:n:5. 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: (Simona Vasilache)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.