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Author:Vesselkov, Alexandr
Title:Forecasting of mobile handset feature diffusion: supply-related aspects
Publication type:Master's thesis
Publication year:2014
Pages:vii + 65      Language:   eng
Department/School:Tietoliikenne- ja tietoverkkotekniikan laitos
Main subject:Network Economics   (ETA3003)
Supervisor:Hämmäinen, Heikki
Instructor:Riikonen, Antti
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201409012575
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto  1692   | Archive
Keywords:diffusion
product feature
mobile handset
dissemination
Abstract (eng):Mobile handsets gradually evolve into computer-like devices.
Hence, contemporary smartphones are capable of running complicated mobile applications, many of which are enabled by different mobile handset components, or features.
Therefore, mobile application and service providers are increasingly interested to know the corresponding market potential for their applications and services, that is, diffusion of related handset components.
Feature diffusion depends on a primarily supply-driven process of the component penetration in sales, which is referred to as feature dissemination.
This thesis analyses the phenomenon of mobile handset feature dissemination and investigates the ways in which forecasting of feature dissemination and diffusion can be improved.
First, the evolution of mobile handset population in Finland was studied based on operators' data in order to obtain a better understanding of the focus market.
Then, dissemination of mobile handset features was analysed quantitatively based on handset sales information.
Finally, the processes underlying the phenomenon of feature dissemination were studied qualitatively using a method of expert interviews.
Quantitative analysis revealed that dissemination of some features is interdependent and relationships between the features have a hierarchical pattern.
Expert interviews showed that the feature dissemination is a complicated phenomenon, affected by different factors and decisions of industry stakeholders.
Furthermore, based on the interview outcomes, it was concluded that the forecasting of feature dissemination can be improved by considering the costs of hardware components, effects of chipset integration and demand for feature-enabled mobile applications.
ED:2014-09-21
INSSI record number: 49714
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