IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v127y2021icp332-345.html
   My bibliography  Save this article

Switching decision, timing, and app performance: An empirical analysis of mobile app developers’ switching behavior between monetization strategies

Author

Listed:
  • Lee, Young-Jin
  • Ghasemkhani, Hossein
  • Xie, Karen
  • Tan, Yong

Abstract

Mobile application developers switch their monetization strategies for strategic purposes. We investigate the determinants and consequences of app developers’ switching behavior between paid and free strategies over time. Using large-scale daily app rank data from the iOS App Store, our estimations reveal that the prior performance of an app and its duration of staying in a monetization strategy significantly impact the developers’ decision of switching. We also find that better-performing apps tend to have longer stays in the paid strategy, whereas developers tend to switch their monetization strategy to free when the performance of a paid app declines. Furthermore, app developers’ switching behavior and duration of the app in each strategy have significant effects on the subsequent app performance in the App Store. Finally, we find the impact of switching behavior varies by app category. Managerial implications with estimated economic outcomes on strategic moves by app developers towards higher app performance are provided.

Suggested Citation

  • Lee, Young-Jin & Ghasemkhani, Hossein & Xie, Karen & Tan, Yong, 2021. "Switching decision, timing, and app performance: An empirical analysis of mobile app developers’ switching behavior between monetization strategies," Journal of Business Research, Elsevier, vol. 127(C), pages 332-345.
  • Handle: RePEc:eee:jbrese:v:127:y:2021:i:c:p:332-345
    DOI: 10.1016/j.jbusres.2021.01.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014829632100031X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2021.01.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shen, George Chung-Chi, 2015. "Users' adoption of mobile applications: Product type and message framing's moderating effect," Journal of Business Research, Elsevier, vol. 68(11), pages 2317-2321.
    2. Park, Hyun Jung & Kim, Sang-Hoon, 2013. "A Bayesian network approach to examining key success factors of mobile games," Journal of Business Research, Elsevier, vol. 66(9), pages 1353-1359.
    3. Euy-Young Jung & Chulwoo Baek & Jeong-Dong Lee, 2012. "Product survival analysis for the App Store," Marketing Letters, Springer, vol. 23(4), pages 929-941, December.
    4. Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
    5. Dave Wooldridge & Michael Schneider, 2010. "The Business of iPhone App Development," Springer Books, Springer, number 978-1-4302-2734-2 edited by Clay Andres & Steve Anglin & Mark Beckner & Ewan Buckingham & Gary Cornell & Jonathan Gennick & Jona, November.
    6. Anindya Ghose & Sang Pil Han, 2014. "Estimating Demand for Mobile Applications in the New Economy," Management Science, INFORMS, vol. 60(6), pages 1470-1488, June.
    7. Picoto, Winnie Ng & Duarte, Ricardo & Pinto, Inês, 2019. "Uncovering top-ranking factors for mobile apps through a multimethod approach," Journal of Business Research, Elsevier, vol. 101(C), pages 668-674.
    8. Hyeokkoo Eric Kwon & Hyunji So & Sang Pil Han & Wonseok Oh, 2016. "Excessive Dependence on Mobile Social Apps: A Rational Addiction Perspective," Information Systems Research, INFORMS, vol. 27(4), pages 919-939, December.
    9. Cheng, Hsing Kenneth & Tang, Qian Candy, 2010. "Free trial or no free trial: Optimal software product design with network effects," European Journal of Operational Research, Elsevier, vol. 205(2), pages 437-447, September.
    10. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    11. Andrew D. Gershoff & Ran Kivetz & Anat Keinan, 2012. "Consumer Response to Versioning: How Brands' Production Methods Affect Perceptions of Unfairness," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(2), pages 382-398.
    12. Carmon, Ziv & Ariely, Dan, 2000. "Focusing on the Forgone: How Value Can Appear So Different to Buyers and Sellers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(3), pages 360-370, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Biraglia, Alessandro & Bowen, Karen T. & Gerrath, Maximilian H.E.E. & Musarra, Giuseppe, 2022. "How need for closure and deal proneness shape consumers’ freemium versus premium price choices," Journal of Business Research, Elsevier, vol. 143(C), pages 157-170.
    2. Davazdahemami, Behrooz & Kalgotra, Pankush & Zolbanin, Hamed M. & Delen, Dursun, 2023. "A developer-oriented recommender model for the app store: A predictive network analytics approach," Journal of Business Research, Elsevier, vol. 158(C).
    3. Numminen, Emil & Sällberg, Henrik & Wang, Shujun, 2022. "The impact of app revenue model choices for app revenues: A study of apps since their initial App Store launch," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 325-336.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lara Stocchi & Naser Pourazad & Nina Michaelidou & Arry Tanusondjaja & Paul Harrigan, 2022. "Marketing research on Mobile apps: past, present and future," Journal of the Academy of Marketing Science, Springer, vol. 50(2), pages 195-225, March.
    2. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    3. Zhuolan Bao & Wenwen Li & Pengzhen Yin & Michael Chau, 2021. "Examining the impact of review tag function on product evaluation and information perception of popular products," Information Systems and e-Business Management, Springer, vol. 19(2), pages 517-539, June.
    4. Jinyang Zheng & Zhengling Qi & Yifan Dou & Yong Tan, 2019. "How Mega Is the Mega? Exploring the Spillover Effects of WeChat Using Graphical Model," Information Systems Research, INFORMS, vol. 30(4), pages 1343-1362, December.
    5. Shivendu Shivendu & Zhe (James) Zhang, 2015. "Versioning in the Software Industry: Heterogeneous Disutility from Underprovisioning of Functionality," Information Systems Research, INFORMS, vol. 26(4), pages 731-753, December.
    6. Ismagilova, Elvira & Dwivedi, Yogesh K. & Slade, Emma, 2020. "Perceived helpfulness of eWOM: Emotions, fairness and rationality," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    7. Davazdahemami, Behrooz & Kalgotra, Pankush & Zolbanin, Hamed M. & Delen, Dursun, 2023. "A developer-oriented recommender model for the app store: A predictive network analytics approach," Journal of Business Research, Elsevier, vol. 158(C).
    8. Zhanfei Lei & Dezhi Yin & Han Zhang, 2021. "Focus Within or On Others: The Impact of Reviewers’ Attentional Focus on Review Helpfulness," Information Systems Research, INFORMS, vol. 32(3), pages 801-819, September.
    9. Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
    10. Ni Huang & Tianshu Sun & Peiyu Chen & Joseph M. Golden, 2019. "Word-of-Mouth System Implementation and Customer Conversion: A Randomized Field Experiment," Information Systems Research, INFORMS, vol. 30(3), pages 805-818, September.
    11. Yingjie Zhang & Beibei Li & Xueming Luo & Xiaoyi Wang, 2019. "Personalized Mobile Targeting with User Engagement Stages: Combining a Structural Hidden Markov Model and Field Experiment," Information Systems Research, INFORMS, vol. 30(3), pages 787-804, September.
    12. Aydin Gokgoz, Zeynep & Ataman, M. Berk & van Bruggen, Gerrit H., 2021. "There’s an app for that! understanding the drivers of mobile application downloads," Journal of Business Research, Elsevier, vol. 123(C), pages 423-437.
    13. Patel, Vipul & Das, Kallol & Chatterjee, Ravi & Shukla, Yupal, 2020. "Does the interface quality of mobile shopping apps affect purchase intention? An empirical study," Australasian marketing journal, Elsevier, vol. 28(4), pages 300-309.
    14. Li, Yiming & Li, Gang & Tayi, Giri Kumar & Cheng, T.C.E., 2019. "Omni-channel retailing: Do offline retailers benefit from online reviews?," International Journal of Production Economics, Elsevier, vol. 218(C), pages 43-61.
    15. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
    16. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    17. Guha Majumder, Madhumita & Dutta Gupta, Sangita & Paul, Justin, 2022. "Perceived usefulness of online customer reviews: A review mining approach using machine learning & exploratory data analysis," Journal of Business Research, Elsevier, vol. 150(C), pages 147-164.
    18. Ketron, Seth, 2017. "Investigating the effect of quality of grammar and mechanics (QGAM) in online reviews: The mediating role of reviewer crediblity," Journal of Business Research, Elsevier, vol. 81(C), pages 51-59.
    19. Meek, Stephanie & Wilk, Violetta & Lambert, Claire, 2021. "A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews," Journal of Business Research, Elsevier, vol. 125(C), pages 354-367.
    20. Henrik Sällberg & Shujun Wang & Emil Numminen, 2023. "The combinatory role of online ratings and reviews in mobile app downloads: an empirical investigation of gaming and productivity apps from their initial app store launch," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 426-442, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:127:y:2021:i:c:p:332-345. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.