Mobile Phone Price Research Articles

Comparing mobile phone price estimators in the Iran Market: Hedonic Regression and Artificial Neural Network

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.

Functionality development dynamism in a diffusion trajectory: A case of Japan's mobile phones development

While it is generally accepted that Information Technology (IT) has a self-propagating function which ensures that the more widespread its use, the greater its functionality, its emerging dynamism remains a black box. This paper attempts to shed some light on this dynamism through utilizing monthly trend data for the number of Japan's mobile phone subscribers over the last 12 years. A bi-logistic growth model demonstrating the diffusion trajectory initiated by both generations of mobile phones was constructed, with the goal of identifying the increase in the functionality development in the transition from traditional mobile phones with a simple communication function (1st wave mobile phone) to mobile phones with an Internet protocol function (2nd wave mobile phone). Through an empirical analysis utilizing the bi-logistic growth model, it was determined that the 2nd wave mobile phone emerged at an earlier stage of diffusion trajectory than the 1st stage mobile phone, which enabled a sustainable functionality development in Japan's mobile phones over the decade. Factors governing a dramatic decrease in mobile phones prices were analyzed, utilizing the result of the measurement of functionality development. This led to the discovery that while an increase in functionality development enhanced the price of mobile phones, this increase accelerated self-propagating diffusion, thereby enabling a dramatic reduction in prices through the effects of learning exercise and economies of scale. Based on the foregoing findings, the driving forces of self-propagating functionality development were analyzed, and it was determined that effective utilization of potential resources in innovation (e.g., assimilation of spillover technology and learning effects) is the key driving forces behind self-propagating functionality development.