Analysis Of the Correlation Between Game Price, Distribution Company, And Rating

Yuncong Xu

doi:10.54097/ej3czn81

Authors

Yuncong Xu Bachelor of Liberal Arts and Science, The University of Sydney, Sydney, Australia

DOI:

https://doi.org/10.54097/ej3czn81

Keywords:

Game launch price; Metascore and user score; COVID shock; Platform strategy.

Abstract

This study investigates the correlation between game’s launch price, Metascore and user score using a set of data including the top 100 rated games from 2015 to 2025. Prices were recorded as the release price to ensure consistency in all comparison inside the analysis. The writer examines whether price can be seen as an important signal of game quality and explore differences between critics and player scores and identifies some platform-based pricing strategy. Correlation analysis showed a weak positive relation between price and Metascore. Further analysis showed there is a significant difference between user scores and Metascore. On platform base data, there is a difference between game prices on each platform when released. By using Locally Estimated Scatterplot Smoothing (LOESS), the writer identified that there is a price drop around 2020 likely caused by the COVID pandemic. Overall, the finding suggests that price is influenced by many other aspects, including economy, publishing, strategy, and market positioning. It is also important to notice that user scores are another important aspect game companies need to consider.

Downloads

Download data is not yet available.

References

[1] Choi H S, Ko M S, Medlin D, & Chen C. The effect of intrinsic and extrinsic quality cues of digital video games on sales: An empirical investigation. Decision Support Systems, 2018, 106: 86-96.

[2] Kraemer T, Weiger W H, & Heidenreich S. Do all-stars shine the same? Investigating the nonlinear effects of user and critic reviews on video game sales. Journal of Business Research, 2025, 188: 115034.

[3] Hamari J, & Keronen L. Why do people buy virtual goods: A meta-analysis. Computers in Human Behavior, 2017, 71: 59-69.

[4] Kerr A. Global games: Production, circulation and policy in the networked era. Routledge, 2017.

[5] Cox J, & Kaimann D. How do reviews from professional critics interact with other signals of product quality? Evidence from the video game industry. Journal of Consumer Behaviour, 2015, 14(6): 366-377.

[6] Santos T, Lemmerich F, Strohmaier M, & Helic D. What's in a review: Discrepancies between expert and amateur reviews of video games on metacritic. Proceedings of the ACM on Human-Computer Interaction, 2019, 3(CSCW): 1-22.

[7] Marchand A, & Hennig-Thurau T. Value creation in the video game industry: Industry economics, consumer benefits, and research opportunities. Journal of Interactive Marketing, 2013, 27(3): 141-157.

[8] Cleveland W S, & Devlin S J. Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association, 1988, 83(403): 596-610.

[9] Liu H. Dynamics of pricing in the video game console market: skimming or penetration? Journal of Marketing Research, 2010, 47(3): 428-443.

[10] Arora A, Greenwald A, Kannan K, & Krishnan R. Effects of information-revelation policies under market-structure uncertainty. Management Science, 2007, 53(8): 1234-1248.