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Network externalities in online video games: an empirical analysis utilizing online product ratings

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Abstract

Video games have become a major contributor to the USA and global economy. This paper studies network externalities in the online video game industry. Even though network externalities are recognized as a major driver of new product diffusion, testing the existence and the impact of network externalities at the individual level has been a challenge. By employing online product ratings in the estimation, we find that for online video games: (1) a larger installed base generates higher product ratings by individuals; (2) network externalities exhibit nonlinear dynamics over product life cycle—nonsignificant initially, highly significant next, and less significant in the later period; and (3) network externalities differ across consumer segments: the impact of the installed base is stronger on less-experienced consumers than on more-experienced ones. Our results suggest that network externalities should be treated as a dynamic rather than a time-invariant phenomenon and heterogeneous rather than homogeneous across consumers.

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Notes

  1. Huffington Post (2015), Video Game Industry Adds Billions to US Economy, http://www.huffingtonpost.com/rich-taylor/the-billion-dollar-video-game-industry_b_6148684.html. Accessed July 1, 2015.

  2. http://www.dfcint.com/wp/dfc-intelligence-forecasts-global-video-game-industry-to-reach-96b-in-2018-2/. Accessed July 1, 2015.

  3. When aggregate data are employed, it is often a methodological challenge to distinguish network externalities from confounding factors such as technology development, herding behavior, and local information spillover (Goolsbee and Klenow 2002).

  4. Consumer reviews in video game communities suggest that congestion is an important issue for online video games. For instance, a player commented about the game World of Warcraft, “… the population of WoW is extremely large. Depending on your server and the time of the day you might enter a queue to access the realm you play on. Congestion on a server can create lag and a lot of downtime.”

  5. Although we needed to test the dynamics of network externalities over different time periods, it is not our purpose to precisely identify the cutoff points between these time periods. Nor is it a critical issue to the research questions of this paper. Rather, the overall nonlinear pattern of hypothesis 2 is our focus.

  6. We further conducted the estimation using lagged subscriptions as instruments and obtained similar results. We thank an anonymous reviewer for these suggestions.

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Acknowledgments

The authors are listed alphabetically and contributed equally to this research. Part of the work was done when Yong Liu was a Visiting Professor at Tianjin University of Technology, Tianjin, China.

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Authors and Affiliations

  1. Department of Marketing, Eller College of Management, The University of Arizona, Tucson, AZ, 85721, USA

    Yong Liu

  2. Department of Marketing and Supply Chain Management, East Carolina University, Greenville, NC, 27858, USA

    Enping Shirley Mai

  3. Discipline of Marketing, School of Business Administration, The University of Houston Victoria, 14000 University Blvd, Sugar Land, TX, 77479, USA

    Jun Yang

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  1. Yong Liu
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  2. Enping Shirley Mai
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  3. Jun Yang
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Correspondence to Yong Liu.

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Liu, Y., Mai, E.S. & Yang, J. Network externalities in online video games: an empirical analysis utilizing online product ratings. Mark Lett 26, 679–690 (2015). https://doi.org/10.1007/s11002-015-9390-x

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