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Key Factors of In-App Purchase for Game Applications

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In game market, mobile applications (App) will reach to 20% revenue. Related researchers also pointed out that game Apps are the largest source of revenue compared to other Apps. In order to attract more customers to use, App developers made a number of ways, for example, free or trial Apps, prepayment which can obtain more services, providing complete free App but customers need to do in-App purchases if they have advanced needs, or click on the ads to get extra content and services. Game Apps developers need to design products to satisfy customers' demands and attract more mobile device users to download, and consumption within the App. Recent surveys reported that in-App purchases will be the major trend. Therefore, game App manufacturers need to know which factor is crucial for increasing in-App purchase behaviors. Therefore, this study attempts to define potential factor set of game Apps and then use back-propagation neural network (BPN) based feature selection method to identify crucial important factors of influencing in-app purchases for game App users. The extracted factors can help game developers to improve their design for increasing the revenue.

Original languageEnglish
Title of host publicationProceedings - 2015 7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015
PublisherIEEE Computer Society
Pages91-95
Number of pages5
ISBN (Electronic)9781467383059
DOIs
StatePublished - 3 Mar 2016
Event7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015 - Kobe, Japan
Duration: 18 Nov 201520 Nov 2015

Publication series

NameInternational Conference on Emerging Trends in Engineering and Technology, ICETET
Volume2016-March
ISSN (Print)2157-0477
ISSN (Electronic)2157-0485

Conference

Conference7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015
Country/TerritoryJapan
CityKobe
Period18/11/1520/11/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • Back-propagation neural network
  • feature selection
  • Game App

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