Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/18919
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dc.contributor.authorSoon, Wan Mei Amanda-
dc.contributor.authorAng, Keng Cheng-
dc.contributor.authorTeo, Kok Ming-
dc.date.accessioned2017-07-27T05:16:28Z-
dc.date.available2017-07-27T05:16:28Z-
dc.date.issued2014-
dc.identifier.citationSoon, W. M. A., Ang, K. C., & Teo, K. M. (2014). Comparison of pricing models with simulated demand data. The Electronic Journal of Mathematics and Technology, 8(3), 195-210. Retrieved from https://php.radford.edu/~ejmt/ContentIndex.php#v1n2en
dc.identifier.issn1933-2823-
dc.identifier.urihttp://hdl.handle.net/10497/18919-
dc.description.abstractMany types of pricing models incorporating different forms of demand functions have emerged in the past years. In an earlier work, a piecewise-defined Complementarity-Constrained Demand Function (CCDF) was discussed to correct certain weaknesses in commonly used demand functions. The authors introduced a Complementarity-Constrained (CC) pricing model incorporating the CCDF in that same work. However, there was a lack of numerical implementations therein. Hence in a separate work, we developed an algorithm using MATLAB to compare a generic pricing model and a CC pricing model. Experiments were performed to compare the revenues from the two models for certain ranges of parameters defining the demand function. In this work, we conduct further numerical testing by simulating the bidding behaviours of different types of customers and using simulated demand data to compare the models. We find that the use of the CC model leads to higher revenues for certain simulated scenarios.en
dc.description.urihttps://php.radford.edu/~ejmt/ContentIndex.php#v2n1-
dc.language.isoenen
dc.titleComparison of pricing models with simulated demand dataen
dc.typeArticleen
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