IDEAS home Printed from https://ideas.repec.org/a/pal/jmarka/v11y2023i3d10.1057_s41270-022-00171-w.html
   My bibliography  Save this article

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

Author

Listed:
  • Henrik Sällberg

    (Blekinge Institute of Technology)

  • Shujun Wang

    (Blekinge Institute of Technology)

  • Emil Numminen

    (Blekinge Institute of Technology)

Abstract

Mobile app ratings and reviews are important due to their influence on consumer behavior and the financial consequences for app developers and app platform providers. This paper contributes to prior work by analyzing how rating and review information in combination impact mobile app downloads. To achieve these ends, we utilize daily panel data of 341 gaming (hedonic consumption value-oriented) and productivity (utilitarian consumption value-oriented) apps tracked for almost two years from their release in the Apple App Store. Hence, we contribute to how ratings and reviews matter for the larger majority of apps, whereas previous research has mainly focused on either ratings’ or reviews’ impact on app performance for top-ranked apps. Results of fixed-effects regression analysis reveal different combinatory impacts of text review information (polarity, subjectivity, and review length) and rating information (average rating score, volume of ratings, and dispersion of ratings) on gaming versus productivity app downloads. Important implications of the findings for app developers and platform providers, and for future research into online ratings and reviews, are discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jmarka:v:11:y:2023:i:3:d:10.1057_s41270-022-00171-w
    DOI: 10.1057/s41270-022-00171-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41270-022-00171-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/s41270-022-00171-w?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. Bidyut Hazarika & Kuanchin Chen & Muhammad Razi, 2021. "Are numeric ratings true representations of reviews? A study of inconsistency between reviews and ratings," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 38(1), pages 85-106.
    2. Lutz, Bernhard & Pröllochs, Nicolas & Neumann, Dirk, 2022. "Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation," Journal of Business Research, Elsevier, vol. 144(C), pages 888-901.
    3. Jieun Kim & Yongtae Park & Chulhyun Kim & Hakyeon Lee, 2014. "Mobile application service networks: Apple’s App Store," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 1-27, March.
    4. Das, Gopal & Mukherjee, Amaradri & Smith, Ronn J., 2018. "The Perfect Fit: The Moderating Role of Selling Cues on Hedonic and Utilitarian Product Types," Journal of Retailing, Elsevier, vol. 94(2), pages 203-216.
    5. Akdim, Khaoula & Casaló, Luis V. & Flavián, Carlos, 2022. "The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    6. Xitong Li, 2018. "Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold," Information Systems Research, INFORMS, vol. 29(3), pages 739-754, September.
    7. Gottschalk, Sabrina A. & Mafael, Alexander, 2017. "Cutting Through the Online Review Jungle — Investigating Selective eWOM Processing," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 89-104.
    8. Jie Ren & Jeffrey V. Nickerson, 2019. "Arousal, valence, and volume: how the influence of online review characteristics differs with respect to utilitarian and hedonic products," European Journal of Information Systems, Taylor & Francis Journals, vol. 28(3), pages 272-290, May.
    9. Tafesse, Wondwesen, 2021. "The effect of app store strategy on app rating: The moderating role of hedonic and utilitarian mobile apps," International Journal of Information Management, Elsevier, vol. 57(C).
    10. Alberto Lopez & Eva Guerra & Beatriz Gonzalez & Sergio Madero, 2020. "Consumer sentiments toward brands: the interaction effect between brand personality and sentiments on electronic word of mouth," Journal of Marketing Analytics, Palgrave Macmillan, vol. 8(4), pages 203-223, December.
    11. 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.
    12. Manqi (Maggie) Li & Yan Huang & Amitabh Sinha, 2020. "Data-Driven Promotion Planning for Paid Mobile Applications," Information Systems Research, INFORMS, vol. 31(3), pages 1007-1029, September.
    13. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2019. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print hal-03511270, HAL.
    14. Anthony D. Miyazaki & Dhruv Grewal & Ronald C. Goodstein, 2005. "The Effect of Multiple Extrinsic Cues on Quality Perceptions: A Matter of Consistency," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(1), pages 146-153, June.
    15. Zhang, Yi-Lu & Guo, Qiang & Ni, Jing & Liu, Jian-Guo, 2015. "Memory effect of the online rating for movies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 261-266.
    16. Runyu Chen & Wei Xu, 2017. "The determinants of online customer ratings: a combined domain ontology and topic text analytics approach," Electronic Commerce Research, Springer, vol. 17(1), pages 31-50, March.
    17. Roma, Paolo & Vasi, Maria, 2019. "Diversification and performance in the mobile app market: The role of the platform ecosystem," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 123-139.
    18. Khare, Adwait & Labrecque, Lauren I. & Asare, Anthony K., 2011. "The Assimilative and Contrastive Effects of Word-of-Mouth Volume: An Experimental Examination of Online Consumer Ratings," Journal of Retailing, Elsevier, vol. 87(1), pages 111-126.
    19. Shyam Gopinath & Jacquelyn S. Thomas & Lakshman Krishnamurthi, 2014. "Investigating the Relationship Between the Content of Online Word of Mouth, Advertising, and Brand Performance," Marketing Science, INFORMS, vol. 33(2), pages 241-258, March.
    20. 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.
    21. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2021. "Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals," Post-Print hal-03511351, HAL.
    22. Liu, Feng & Zhao, Shaoqiong & Li, Yang, 2017. "How many, how often, and how new? A multivariate profiling of mobile app users," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 71-80.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Yajie Hu & Huiwen Zhou & Yuangao Chen & Jianrong Yao & Jiangwu Su, 2023. "The influence of patient-generated reviews and doctor-patient relationship on online consultations in China," Electronic Commerce Research, Springer, vol. 23(2), pages 1115-1141, June.
    4. 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.
    5. Wondwesen Tafesse, 2023. "The differential effects of developers’ app store strategy on the performance of niche and popular mobile apps," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 317-330, September.
    6. Takumi Kato, 2022. "Rating valence versus rating distribution: perceived helpfulness of word of mouth in e-commerce," SN Business & Economics, Springer, vol. 2(11), pages 1-24, November.
    7. Anuja Shukla & Anubhav Mishra, 2023. "Role of Review Length, Review Valence and Review Credibility on Consumer’s Online Hotel Booking Intention," FIIB Business Review, , vol. 12(4), pages 403-414, December.
    8. Das, Gopal & Spence, Mark T. & Agarwal, James, 2021. "Social selling cues: The dynamics of posting numbers viewed and bought on customers' purchase intentions," International Journal of Research in Marketing, Elsevier, vol. 38(4), pages 994-1016.
    9. 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.
    10. Jifeng Luo & Ying Rong & Huan Zheng, 2020. "Impacts of logistics information on sales: Evidence from Alibaba," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 646-669, December.
    11. Zheng, Lili, 2021. "The classification of online consumer reviews: A systematic literature review and integrative framework," Journal of Business Research, Elsevier, vol. 135(C), pages 226-251.
    12. Wang, Yuqiu & Ngai, Eric W.T. & Li, Kai, 2024. "Effects of sentiment quantity, dispersion, and dissimilarity on online review forwarding behavior: An empirical analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    13. Zhai, Mengfan & Wang, Xinyue & Zhao, Xijie, 2024. "The importance of online customer reviews characteristics on remanufactured product sales: Evidence from the mobile phone market on Amazon.com," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    14. Li, Yuanshuo & Zhang, Zili & Pedersen, Susanne & Liu, Xudong & Zhang, Ziqiong, 2023. "The influence of relative popularity on negative fake reviews: A case study on restaurant reviews," Journal of Business Research, Elsevier, vol. 162(C).
    15. Langan, Ryan & Besharat, Ali & Varki, Sajeev, 2017. "The effect of review valence and variance on product evaluations: An examination of intrinsic and extrinsic cues," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 414-429.
    16. Nima Jalali & Sangkil Moon & Moon-Yong Kim, 2023. "Profiling diverse reviewer segments using online reviews of service industries," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 130-148, June.
    17. Barta, Sergio & Gurrea, Raquel & Flavián, Carlos, 2023. "Consequences of consumer regret with online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    18. Shobhit Kakaria & Aline Simonetti & Enrique Bigne, 2024. "Interaction between extrinsic and intrinsic online review cues: perspectives from cue utilization theory," Electronic Commerce Research, Springer, vol. 24(4), pages 2469-2497, December.
    19. Rosillo-Díaz, Elena & Muñoz-Rosas, Juan Francisco & Blanco-Encomienda, Francisco Javier, 2024. "Impact of heuristic–systematic cues on the purchase intention of the electronic commerce consumer through the perception of product quality," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    20. Li, Hui & Xu, Yunjie & Huang, Lihua, 2021. "When less is more? The contingent effect of product supply limitation in the release of new electronic products," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).

    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:pal:jmarka:v:11:y:2023:i:3:d:10.1057_s41270-022-00171-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.