DocumentCode :
159912
Title :
Which phone will you get next: Observing trends and predicting the choice
Author :
Yi Wang ; Hui Zang ; Devineni, Pravallika ; Faloutsos, Michalis ; Janakiraman, K. ; Motahari, Sara
Author_Institution :
Bourns Coll. of Eng., UC Riverside, Riverside, CA, USA
fYear :
2014
fDate :
5-9 May 2014
Firstpage :
1
Lastpage :
7
Abstract :
As the smartphone/cellphone market has exploded, the war on which smartphone platform will dominate has become fiercer than ever. In that vain, the goal of this paper is to answer two fundamental questions: What are the adoption trends for smartphones? And how can we estimate the demand for new smartphones? We answer these two questions by collecting a dataset of 3 million subscribers from a nationwide telecom operator. A key aspect of our work is that we have demographic information per user, such as income level, and age, which we correlate with phone usage patterns. Interestingly, we find that in all demographic groups, Android is leading platform top in all age groups and income levels. A key question is whether the “social influence” affects the choice of phone, which we find more pronounced in business plans. Finally, we develop a predictor to infer the phone a user will switch to considering: (a) the type of previous phone, (b) the social influence, and (c) the demographics of the user. Compared with the reference method, our predictor is effective in: (a) reducing the prediction error in number of phones by 1/3, and (b) in the case of minimizing phone costs, the monetary cost by half. Apart from its interest in observations, our work could help telecom operator forecast their inventory more accurately by pointing to the right properties to consider.
Keywords :
Android (operating system); demand forecasting; inventory management; probability; smart phones; Android; cell phone market; demographic information; inventory forecast; prediction error; smart phone choice; smart phone market; smart phone trends; social influence; telecom operator; user demographics; Bayes methods; Correlation; Market research; Smart phones; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Operations and Management Symposium (NOMS), 2014 IEEE
Conference_Location :
Krakow
Type :
conf
DOI :
10.1109/NOMS.2014.6838293
Filename :
6838293
Link To Document :
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