Comparing Mobile Phone Price Estimators in the IranMarket: Hedonic Regression and Artificial Neural Network

Mohsen Nazari, Seyed Vahid Tabatabaie Kalejahi

Abstract


The purpose of this paper is to develop two price estimator functions and compare the performance and accurateness of them.After gathering mobile phone features from their manufacturers’ websites and their prices from “Donyaye-Eqtesad” newspaper, Hedonic regression and Artificial Neural Network models developed.The most effective feature of mobile phones in their prices are theirs brand, being touch screen, camera quality in mega pixel, battery life in calling and wireless network connectivity, and Also ANN model is better estimator than hedonic regression function.Because all of the mobile phones in the Iran market are imported from other countries, importers can import mobile phones that have those features that have more value to customers and reach a higher market share.The major contribution of this paper is specifying the most important determinants of mobile phone prices in the Iran market and comparing the two price estimator functions. This paper is of value to mobile phone importers, mobile phone manufactures, advertisers and pricing researchers.


Full Text:

PDF


DOI: https://doi.org/10.5296/bms.v3i1.1083

Copyright (c) 2011 Mohsen Nazari, Seyed Vahid Tabatabaie Kalejahi

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Business Management and Strategy  ISSN 2157-6068

Copyright © Macrothink Institute 

To make sure that you can receive messages from us, please add the 'macrothink.org' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.

If you have any questions, please contact bms@macrothink.org.

------------------------------------------------------------------------------------------------------------------------------------------------------