The Trojan classification system represents a modern way of measuring player motivation. It was created in 2015 by a team of seventeen scientists who aimed to overcome the shortcomings of earlier systems. These older systems often focused only on specific types of games or solely on players from Europe and America. The Trojan model takes a different approach - it was designed to work across various game genres and cultures, which researchers confirmed through testing in both America and China.
First, the researchers compiled 246 different statements expressing possible reasons why people play games. They drew both on their own gaming experience and on earlier questionnaires. After a joint review, they selected the 104 most important statements, which were then rated by hundreds of players in an online survey. Using advanced mathematical methods, they ultimately identified six main pillars that form player motivation. The entire questionnaire was then gradually refined and shortened until the final version was created.
To ensure that their model was not merely theoretical, the authors tested it on very large groups of participants. In America, more than 18,000 players of the popular game League of Legends took part in the study. This game belongs to the MOBA (Multiplayer Online Battle Arena) genre, in which two teams compete against each other in an arena. In China, a similarly large number of players of the online world Chevalier’s Romance Online 3 completed the questionnaire. This game belongs to the MMO (Massively Multiplayer Online) genre, in which thousands of people interact simultaneously within one vast world. These large-scale data confirmed that the division into six motivational groups is meaningful regardless of the part of the world in which a player lives.
The researchers also went beyond questionnaire responses alone. They collaborated with the game company Riot Games and compared what players reported about themselves in the test with how they actually behaved in the game. This confirmed that the questionnaire predicts real in-game behavior very accurately. For example, individuals who placed strong emphasis on social interaction in the test demonstrably had many more friends in the game and communicated with other players more frequently.
