Despite the enormous revenues generated by the video game industry in recent years, relatively little research has been undertaken into consumer preferences and the determinants of video game consumption. This study addresses this deficiency through the analysis of data from a popular online video game that includes historic behavioural information for 1,408 consumers participating in 728,811 unique rounds of gameplay. We analyse these data with the goal of estimating determinants of the aggregate amount of time that a consumer spends playing the game. Through the estimation of duration models, we show that less experienced consumers are less likely to continue playing the game at any given point, possibly due to having achieved mastery and becoming bored. However, we also find that consumers tend to play the game for longer periods when using a wider range of character roles and vehicles, implying that a consumer's interest can be maintained through exposure to greater variety. Our results represent the first such evidence on in‐game consumer preferences, which has important implications for video game consumption through optimisation of gameplay experiences to satisfy these preferences.

Multiplayer video games are high-involvement products with multiplatform and multiplayer characteristics which aim to enhance player retention by optimizing the matching of teams in accordance with their skills and attributes. However, relatively little academic research has been conducted into the ways in which player attributes can be used to optimize the formation of teams in multiplayer video games. Our study addresses this deficiency in the literature by analyzing a dataset from a popular online multiplayer game that includes historic behavioral data of 6.9 million players participating in 862,664 unique game rounds. We analyze the observable factors associated with longer duration of participation in each round, finding that player retention improves in the presence of player-versus-player combat, variety and heterogeneity. We also show that player retention diminishes as a result of the absence of particular role or vehicle use within a given round. Based on the findings of the analysis, we develop a novel approach called nested matching to assign players to teams with an optimal mixture of skills and inherent and complementary attributes.

JEL Classification: C33; C55; D12; L82; M21This study analyzes the effect of variety on consumer utility using historical behavioral information for 1,397 consumers participating in 729,049 unique rounds of play. We show that consumers generally exhibit a preference for variety as part of their gameplay utility. The relationship between variety and utility is nonlinear and follows, at least for some types of variety, an inverted u-shape as predicted by the Wundt curve. Our results represent the first such evidence on the importance of variety in video gaming, which has significant implications for consumption through optimization of gameplay utility to satisfy the demand for variety.

In actual school choice applications the theoretical underpinnings of the Boston School Choice Mechanism (BM) (complete information and rationality of the agents) are often not given. We analyze the actual behavior of agents in such a matching mechanism, using data from the matching mechanism currently used in a clearinghouse at a faculty of Business Administration and Economics at a German university, where a variant of the BM is used, and supplement this data with data generated in a survey among students who participated in the clearinghouse. We find that under the current mechanism over 70% of students act strategically. Controlling for students' limited information, we find that they do act rationally in their decision to act strategically. While students thus seem to react to the incentives to act strategically under the BM, they do not seem to be able to use this to their own advantage. However, those students acting in line with their beliefs manage a significantly better personal outcome than those who do not. We also run simulations by using a variant of the deferred acceptance algorithm, adapted to our situation, to show that the use of a different algorithm may be to the students' advantage.

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