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Early Expansion of the User Base for Mobile Applications: Evidence from the US Apple App Store
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.ORCID iD: 0000-0002-7928-2607
2023 (English)In: International Journal of Innovation and Technology Management (IJITM), ISSN 0219-8770, Vol. 20, no 7, article id 2350044Article in journal (Refereed) Published
Abstract [en]

Mobile applications (apps) have grown drastically since their birth in 2008. Acquiring more app users as quickly as possible after the app is released in the app stores is one of the key rules for app developers to survive in this emerging and competitive digital market. This paper uses cumulative weekly downloading data from the US Apple App Store during a two-year period of 2015 and 2016 to study the early expansion curves and diffusion patterns of mobile apps in the app market. Downloading payment methods (free or paid to download an app) and hedonic or utilitarian value-orientated app types (games and productivity apps) are considered when we study the diffusion pattern of mobile apps. The Bass model is used as the baseline model, and the logistic model and Gompertz model are used to conduct a robustness check. Nonlinear least squares (NLS) is the measurement to obtain parameters of diffusion models. The results show that the Bass model is the best-fitting model compared with the other two models, and the diffusion pattern of mobile apps is S-shaped at the market level. The first 35 weeks are essential for the app developers to attract app users' downloads. More app data from different app stores and more diffusion models can be tested for mobile app diffusion and early expansion patterns in future research.

Place, publisher, year, edition, pages
World Scientific, 2023. Vol. 20, no 7, article id 2350044
Keywords [en]
Mobile applications, early expansion, diffusion pattern, Bass model, Apple App Store
National Category
Business Administration Other Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-25236DOI: 10.1142/S021987702350044XISI: 001025937400002Scopus ID: 2-s2.0-85175810944OAI: oai:DiVA.org:bth-25236DiVA, id: diva2:1787355
Available from: 2023-08-14 Created: 2023-08-14 Last updated: 2023-11-17Bibliographically approved

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Wang, Shujun

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CiteExportLink to record
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  • apa
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