VALUE PERCEPTION AND CONSUMER BEHAVIOUR IN FREEMIUM MOBILE GAMING: EXAMINING THE INFLUENCE OF ENJOYMENT, SOCIAL AND ECONOMIC VALUE ON CONTINUED USAGE AND PURCHASE INTENTIONS AMONG INDIAN YOUTH GAMERS

Authors

  • Gourav Bareja Mittal School of Business, Lovely Professional University, Phagwara, Punjab, India Author
  • Shabnam Gulati Mittal School of Business, Lovely Professional University, Phagwara, Punjab, India Author

DOI:

https://doi.org/10.29121/ShodhPrabandhan.v2.i1.2025.101

Keywords:

Freemium Business Model, Youth Gamers, Enjoyment Value, Social Value, Economic Value, Continued Use Intention, Purchase Intention, Pls-Sem, Mobile Gaming

Abstract

The proliferation of digital game applications has resulted in the transformation of the entertainment industry in terms of usage of the freemium business model. Unlike paid game models where consumers have to pay to use an application, in case of freemium models, gamers get access to games for free, and make payment within the game through in-app purchases, virtual goods, subscription, ads and premium functionalities. While allowing companies to gain wide customer base, the main problem with such a model is the difficulty in converting free users into paying customers. Therefore, it has become crucial to comprehend the factors that determine users' intentions for continued use and purchase of games.

The proposed study aims at exploring the impact of the three aspects of perceived value on continued use intention and purchase intention in freemium gaming application among youth gamers in India. According to the consumer value theory and technology adoption perspective, it is believed that youth gamers' perceptions related to entertainment, social and economic values play a major role in shaping their behavior towards freemium gaming applications. A quantitative approach will be used in the research, and data collected from youth gamers will be analyzed using PLS-SEM.

The results can have great significance for gaming companies and marketers in creating effective strategies for enhancing user engagement, fostering customer relationship, and making premium buys.

References

Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327 DOI: https://doi.org/10.1007/BF02723327

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 DOI: https://doi.org/10.2307/249008

Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104 DOI: https://doi.org/10.1177/002224378101800104

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., and Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Springer. https://doi.org/10.1007/978-3-030-80519-7 DOI: https://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203 DOI: https://doi.org/10.1108/EBR-11-2018-0203

Hamari, J., and Keronen, L. (2017). Why do people buy virtual goods? A meta-analysis. Computers in Human Behavior, 71, 59–69. https://doi.org/10.1016/j.chb.2017.01.042 DOI: https://doi.org/10.1016/j.chb.2017.01.042

Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8 DOI: https://doi.org/10.1007/s11747-014-0403-8

Holbrook, M. B. (1999). Consumer value: A framework for analysis and research. Routledge.

Kim, H. W., Chan, H. C., and Gupta, S. (2007). Value-based adoption of mobile internet. Decision Support Systems, 43(1), 111–126. https://doi.org/10.1016/j.dss.2005.05.009 DOI: https://doi.org/10.1016/j.dss.2005.05.009

Kotler, P., and Keller, K. L. (2016). Marketing management (15th ed.). Pearson.

Nambisan, S., and Baron, R. A. (2007). Interactions in virtual customer environments. Journal of Interactive Marketing, 21(2), 42–62. https://doi.org/10.1002/dir.20077 DOI: https://doi.org/10.1002/dir.20077

Ryu, H. S. (2018). What makes users willing to pay for digital content? Telematics and Informatics, 35(5), 1248–1260.

Sweeney, J. C., and Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0 DOI: https://doi.org/10.1016/S0022-4359(01)00041-0

Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., and Xu, X. (2012). Consumer acceptance and use of information technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412 DOI: https://doi.org/10.2307/41410412

Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302 DOI: https://doi.org/10.1177/002224298805200302

Downloads

Published

2025-06-30