Motivations for Play in Online Games NICK YEE ABSTRACT An empirical model of player motivations in online games provides the foundation to under- stand and assess how players differ from one another and how motivations of play relate to age, gender, usage patterns, and in-game behaviors. In the current study, a factor analytic ap- proach was used to create an empirical model of player motivations. The analysis revealed 10 motivation subcomponents that grouped into three overarching components (achievement, social, and immersion). Relationships between motivations and demographic variables (age, gender, and usage patterns) are also presented. 772 CYBERPSYCHOLOGY & BEHAVIOR Volume 9, Number 6, 2006 © Mary Ann Liebert, Inc. INTRODUCTION E VERY DAY , millions of people 1 interact with each other in online environments known as Mas- sively-Multiplayer Online Role-Playing Games (MMORPGs). MMORPG players, who on average are 26 years old, typically spend 22 h per week in these environments. 2 Asking MMORPG players why they play reveals a wide variation of motives: Currently, I am trying to establish a working corpo- ration within the economic boundaries of the vir- tual world—primarily, to learn more about how real world social theories play out in a virtual econ- omy [male, age 30]. The fact that I was able to immerse myself in the game and relate to other people or just listen in to the “chatter” was appealing [female, age 34]. Indeed, the variation suggests that MMORPGs may appeal to many players because they are able to cater to many different kinds of play styles. Being able to articulate and quantify these motivations provides the foundation to explore whether different sections of the player demographic are motivated differently, and whether certain motivations are more highly cor- related with usage patterns or other in-game behav- iors. Such a model has value for both researchers and game designers. For researchers, findings may clarify whether certain kinds of players are more susceptible to problematic usage, for example. For game develop- ers, findings may clarify how certain game mechanics may attract or alienate certain kinds of players. While Bartle’s Player Types 3 is a well-known player taxonomy of Multi-User Dungeon (MUD) users, the underlying assumptions of the model have never been empirically tested. For example, Bartle assumed that preference for one type of play (e.g., achievement) suppressed other types of play (e.g., socializing or exploring). Also, it has never been empirically shown that the four player types are indeed independent types. In other words, sev- eral of the types may correlate to a high degree. In essence, it would be hard to use Bartle’s model on a practical basis unless it was validated with and grounded in empirical data. In the following work, I describe a factor analytic approach to creating an empirically grounded player motivation model. Department of Communication, Stanford University, Palo Alto, California. Rapid Communication