@article{Zendle:2022:osf.io/mwrva,
author = {Zendle, D and Flick, C and Cutting, J and Deterding, S and Petrovskaya, E and Drachen, A},
doi = {osf.io/mwrva},
title = {The Many Faces of Monetisation: Understanding the diversity and extremity of spending in mobile games via massive-scale transactional analysis},
url = {http://dx.doi.org/10.31234/osf.io/mwrva},
year = {2022}
}

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TY  - JOUR
AB  - <p>With the rise of microtransactions, particularly in the mobile games industry, there has been ongoing concern that  games reliant on these obtain substantial revenue from a small proportion of heavily involved individuals, to an extent that may be financially burdensome to these individuals. Yet despite substantive grey literature and speculation on this topic, there is little robust data available. We explore the revenue distribution in microtransaction-based mobile games using a transactional dataset of USD 4.7bn in in-game spending drawn from 69,144,363 players of 2,873 mobile games over the course of 624 days.   We find diverse revenue distribution in mobile games, ranging from a ‘uniform’ cluster, in which all spenders invest approximately similar amounts, to ‘hyper-pareto’ games, in which a large proportion of revenue (~38%) stems from 1% of spenders alone. Specific kinds of games are typified by higher spending: the more a game relies on its top 1% for revenue generation, the more these individuals tend to spend, with simulated gambling products (‘social casinos’) at the top. We find a small subset of games across all genres, clusters, and age ratings in which the top 1% of gamers are highly financially involved– spending an average of USD 66,285 each in the 624 days under evaluation in the most extreme case. We discuss implications for future studies on links between gaming and wellbeing.</p>
AU  - Zendle,D
AU  - Flick,C
AU  - Cutting,J
AU  - Deterding,S
AU  - Petrovskaya,E
AU  - Drachen,A
DO  - osf.io/mwrva
PY  - 2022///
TI  - The Many Faces of Monetisation: Understanding the diversity and extremity of spending in mobile games via massive-scale transactional analysis
UR  - http://dx.doi.org/10.31234/osf.io/mwrva
ER  - 

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