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The Impact of App Revenue Model Choices for App Revenues: A Study of Apps Since Their Initial App Store Launch
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.ORCID iD: 0000-0003-0493-7450
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.ORCID iD: 0000-0002-9787-7620
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.ORCID iD: 0000-0002-7928-2607
2022 (English)In: Economic Analysis and Policy, ISSN 0313-5926, Vol. 76, p. 325-336Article in journal (Refereed) Published
Abstract [en]

When launching a new app in one of the major app stores, the developer must decide how to generate revenues from that app. The decision includes whether to charge an upfront payment from the customer or make it free to download and whether to include in-app payments. In this study, we analysed the effect of these decisions on the amount of revenue an app generates and if it differs for gaming (hedonic value-orientation) and productivity (utilitarian value-orientation) apps. To analyse this effect, we used approximately two years of mobile app panel data from 330 newly launched US Apple App Store gaming and productivity apps. Based on random effects regression analysis, we report that free downloads combined with in-app payments are superior in revenue generation for gaming apps. By contrast, for productivity apps, relying only on either upfront payment for the app or on in-app payments generates the highest revenues. For gaming app developers, offering free to download apps is thus recommended. For productivity app developers, charging for either downloading or in-app features is more successful. This study complements existing literature by investigating revenue generation of new apps and the performance effect of specific revenue model options that developers must make in app store settings.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 76, p. 325-336
Keywords [en]
Mobile app, Revenue model, App revenue, Apple’s App Store, New release app
National Category
Business Administration
Research subject
Industrial Economics a nd Managemen
Identifiers
URN: urn:nbn:se:bth-23657DOI: 10.1016/j.eap.2022.08.010ISI: 000863324500005Scopus ID: 2-s2.0-85137308181OAI: oai:DiVA.org:bth-23657DiVA, id: diva2:1696255
Note

open access

Available from: 2022-09-16 Created: 2022-09-16 Last updated: 2023-01-18Bibliographically approved
In thesis
1. Essays on Mobile Application Performance in the Market
Open this publication in new window or tab >>Essays on Mobile Application Performance in the Market
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The mobile application has experienced rapid growth since its emergence in 2008. The mobile app platform, as the two-sided market for mobile apps, enables app developers and app users to make transactions in it. In this competitive market, app developers face different factors that influence the success of apps. This dissertation deals with mobile app performance in the market and studies the determinants of mobile app performance from app users’ and app developers’ perspectives. 

This dissertation consists of four essays and an introductory part. Each essay is a separate study, but all of them aim to explore the factors that impact mobile app performance in the market. Essay I investigates the combinatory effects of ratings and reviews from app users on new mobile app downloads. Ratings and reviews have been found to have direct and interaction effects on mobile app downloads. Essay II analyzes the effects of different revenue model choices from app developers on app revenue performance in the market. The findings show that free downloads combined with in-app payments are a superior revenue model for gaming apps, but either charging for downloading or in-app purchases is better for productivity apps. Essay III discovers the diffusion pattern of new mobile apps in the market. The Bass model is used to test the diffusion parameters, and the logistic model and the Gompertz model are used to do the robustness check. The results show that the Bass model is the best-fitting model for mobile app data compared with the other two models, and newly launched mobile apps follow the S-curve diffusion pattern, and the early expansion of the mobile app should achieve in the first 35 weeks. Essay IV studies how the launch timing of new apps affects app downloads. The backward launch competition, cross-category launch competition, and release-date launch competition are factors that impact app downloads. For all four essays, the US Apple App Store data is adopted because the Apple App Store is one of the leading app stores worldwide. Different empirical analysis methods are applied in the four essays. Hedonic and utilitarian consumption values are considered in differentiating app types in all four essays. 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2022. p. 191
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 6
Keywords
mobile applications, market performance, ratings and reviews, revenue models, diffusion
National Category
Economics and Business Other Computer and Information Science
Research subject
Industrial Economics a nd Managemen
Identifiers
urn:nbn:se:bth-23658 (URN)978-91-7295-443-4 (ISBN)
Public defence
2022-10-27, J1630, Karlskrona, 13:15 (English)
Opponent
Supervisors
Available from: 2022-09-16 Created: 2022-09-16 Last updated: 2022-10-05Bibliographically approved

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Numminen, EmilSällberg, HenrikWang, Shujun

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