Keywords

1 Introduction

Video games are fun. However oversimplified this argument may be, it gets continuously repeated both in the ongoing cultural discourse on video games as well as in industrial and academic accounts of them. It is very commonplace to just state that “I play games just for fun” or that “games are nothing but good fun”. Just to give an example of the importance of fun in the academic discussion, in his book about game-based learning, Marc Prensky [6] has listed twelve characteristics of video games that contribute to their ability to be engaging. The very first of them states that games are essentially a form of fun. However, as an academic concept, “fun” is highly ambiguous in its meaning, and the understanding of the concept rarely gets elaborated in papers discussing or utilizing this concept in research [14]. Our focus in this work-in-progress paper is on shedding more light on fun as a reason to play games. While also acknowledging how the concept might refer to certain types of games and features of gameplay, we are here primarily interested in describing fun in motivational terms. Instead of settling for a singular concept of fun, our intention is to discover the motivational constitution of this concept. That is, what kind of motives to play games and motivational factors of gameplay are associated with fun.

Already at the dawn of video game research, Chris Crawford [2] has discussed the potential differences between asking “why do people play games in general?” and “what makes a game more fun than another?” According to Crawford, the key difference lies between the motivating and enjoyment factors of games. Admitting an inevitable dependence between the two, motivating factors refer to the reasons for approaching games (even the ones without much enjoyment but, e.g., a good exercise) while enjoyment factors help people to choose between games on the basis of fun, that is, the gameplay and sensory based gratification it offers. However, in order to be fun, a game must sufficiently satisfy the approach motivations of the player [2]. On the basis of such a formulation, fun clearly is a criterion for game choice and for continued play, but it is not necessarily to be seen as a genuine approach motivation to play games. This formulation, however, leaves much room for clarifying the relationship between motivation and fun, especially in regards to studying what kind of things in gameplay constitute fun in terms of motivational approach towards games.

The terms “fun” and “enjoyment” are frequently considered synonyms in the literature [14]. In particular, enjoyment and pleasure emphasize positive connotations of fun. But such a meaning should not be restricted to superficial aspects of the concept, as even the most serious things in life (especially the ones we are passionate about) give us enjoyment and make us return to the corresponding activities [6]. On the other hand, “fun” can also promote negative connotations, for example, when understood in more frivolous terms of amusement or ridicule [6]. However, one should note that in regard to play, pleasures are merely not submissive to (superficial) fun and happiness, since engagement with play opens up a whole spectrum of variations of pleasure in the world [10]. How should we then conceptualize these engaging things in life that promote substantial pleasure and enjoyment for people? We may look for answers to this question in Ryan and Deci’s [7] influential Self-Determination Theory (SDT). It is a macro-theory of human motivation and organismic growth, with a focus on curiosity and explorative behavior as a manifestation of intrinsic motivation.

According to the SDT [7], three basic psychological needs (autonomy, competence and relatedness) energize motivational processes and promote harmonious development of the human organism within the world. Satisfaction of the basic need for actualizing one’s autonomic self is considered to be the primary element of this theory, essentially referring to activities that embrace one’s spontaneous curiosity, interest and free will. This seems to align well with notions that the disposition of having “fun” is essentially a voluntary (intrinsically motivated) attitude of perceiving situations as enjoyable (e.g., [1]), as well as with game research literature emphasizing players’ participation in game experiences as being characteristically voluntary and autonomous (e.g., [4, 5, 12]). The models of game motivation research are also typically built upon the premise of an autonomous player (e.g., [9, 15]). In addition to autonomy, the basic needs of competence and relatedness also provide potential approaches. For example, as the flow-theory [3] proposes, the balance between a player’s skills and a game’s challenges should arguably result in pleasurable experiences relating to one’s competence. Tamborini et al. [13] have established that enjoyment indeed derives from the satisfaction of SDT needs, which however, do not necessarily include a purely pleasure-driven search for enjoyment.

Fig. 1.
figure 1

The circle of fun, incorporating the perspectives of Motivation, Gameplay experience and Self-Determination.

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In this study we conceptualize the SDT basic needs satisfaction as the self-reflective ways how fun is in general constituted in personal life. Self-determination thus provides an approach for scrutinizing both the varieties of pleasure afforded by gameplay and fun as a motivational disposition (see Fig. 1). Furthermore, this approach opens up a possibility to utilize three “lenses” in conceptualizing fun in terms of (1) motivation, (2) situated gameplay experience, and (3) reflective constitution of the self. On the basis of two survey datasets, we will next report a brief empirical investigation of how “fun” appears as a factor of gameplay motives and preferences through these three lenses.

2 Methods

Two large survey samples were collected within the ongoing project from Finland (N = 879) and from South-Korea (N = 1519) in cooperation with two market research companies. Both of the data collection processes were designed to produce samples that would represent the age (ages from 18 to 65) and gender distribution of the said countries. Prior to making any analyses, a total of 52 survey responses were removed from the Finnish sample and 131 from the Korean sample as these respondents were identified as outliers. After the data cleaning process, the Finnish sample consisted of 827 respondents (49.0% male, 51.0% female, mean age 41.4) and the Korean sample of 1,388 respondents (50.4% male, 49.6% female, mean age 39.1).

Both of the surveys included the Intrinsic Motivations to Gameplay (IMG) inventory, the Gameplay Activity inventory (GAIN), a 17-item inventory on video game genre play, a five-item inventory on preferred game modes (e.g., single-player computer games, multiplayer mobile games), and demographic questions. The 15-IMG is a SDT compatible five-factor inventory on motives to play digital games [15]. It assesses general gaming motives of Autonomy (\(\alpha \) = 0.92), Competence (\(\alpha \) = 0.89), Relatedness (\(\alpha \) = 0.89), Immersion (\(\alpha \) = 0.91), and Fun (\(\alpha \) = 0.90). The 15-GAIN is a five-factor construct that measures players’ preferences in gameplay activity types of Aggression (\(\alpha \) = 0.88), Caretaking (\(\alpha \) = 0.83), Coordinate (\(\alpha \) = 0.83), Exploration (\(\alpha \) = 0.85), and Management (\(\alpha \) = 0.88). The GAIN was applied in the study as it informs us about game choice and game enjoyment [16], whereas the IMG instrument has been developed and validated precisely for investigating approach motivations to play video games at large.

We made an exploratory cluster analysis with Stata 16.2 software in order to explore how the motivational factor of Fun was related to other play motives (i.e., approach factors) and furthermore to gameplay preferences (i.e., enjoyment factors), genre play habits, and player demographics. For this purpose, we generated factor sum variables for each of the five IMG dimensions and proceeded to do a cluster analysis based on these motive factors. The number (k) of clusters was identified by investigating scree plots generated from the within sum of squared (WSS) and its logarithm [\(\log \)(WSS)] for cluster solutions between 2 and 20 clusters. A solution of eight clusters was found to be the most prominent, and therefore we conducted a nonhierarchical k-means cluster analysis with Euclidean distance for k = 8.

3 Results

As a result of the cluster analysis, it was first found that Fun had the highest mean sum of the five IMG-based motive factors across all clusters. We then standardized the values for all of the five factor sums by each cluster and found that the effect size between the Fun factor and the second most highest ranged from small (d = 0.23) to huge (d = 1.94) and that this approach generated, in principle, player clusters that were very motivated, reasonably motivated, slightly motivated, and amotivated to play videogames. Differently put, by initially generating clusters based on sum variables, the results did not inform us much about the motivational profiles as the k-means procedure identified the clusters based on how motivated players were instead of being able to generate insight into what motivates them to play games.

To overcome this issue, another approach to k-means clustering was taken. Prior to making the analysis, the five factor sum variables were now standardized for each survey participant. By doing so, we excluded from the cluster analysis information about to what degree a participant was motivated to play games in general and based the analysis only on what factors motivated them the most and the least in comparison to their own motivation mean value. The scree plots suggested a solution of six clusters, and a k-means clustering was made accordingly. The six clusters are reported in Table 1.

Table 1. The six-cluster solution. Reporting standardized factor sums and direct factors sum.
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Of the six clusters, only Cluster 4 was identified as based on its players desire to play video games because of Fun. Participants of Cluster 1 were grouped together, because of the Immersion and Autonomy motive whereas Autonomy and Competence were both relatively high motives for the second player cluster. The Competence motive was the most important motivational factor for Cluster 3. And finally both Cluster 5 and Cluster 6 were motivated by Relatedness. Cluster 6 had the lowest value for Fun of the six clusters.

However, when we observed the non-standardized factor sums it was revealed that Fun had the highest mean value not only for Cluster 4 but also for Cluster 2. The significance of the Fun motive was evident also when taking into account that Cluster 2 and Cluster 4 were clearly the two largest clusters with 623 and 566 participants. Next we calculated GAIN factor sums, genre playing habit means, game mode preferences, and descriptive statistics for demographics for the six clusters (Table 2).

Table 2. Descriptive GAIN, genre play, game mode, and playtime statistics for the six clusters.
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Participants of the Immersive cluster had the highest mean preference for Exploration, Aggression, Caretaking, and Management of the six player clusters. They also had the highest mean value for genre play, meaning that they played more genres than players of the other clusters. They played action games, action-adventure games, role-playing games, simulations, and platform games more than other players. The Immersive players had the highest weekly mean play hours on console play (1.8 h), and lowest mean age (35.9 years, 57% male). The cluster was under-represented in the Finnish sample.

The Autonomous players had the second highest preference average for Exploration, and they reported the highest preference for single-player computer and console play, and single-player mobile play. The puzzle genre was their favorite. They were the oldest player cluster (42.6 years, 50% male), and they were over-represented in Finland. The Challenger player type (40.1 years, 54% female) had the highest preference for the puzzle genre and they played mobile games each week for 4.4 h, which was the highest value of the player clusters. They were equally represented in both countries.

The Fun-Seeker was only motivated to play because of Fun. They also did not prefer any of the gameplay activity types but instead had the lowest preferences for all of the five factors of the six player clusters. Furthermore, they had the lowest game genre average, but they played puzzle games almost as much as the Challenger type. They also had the second highest weekly play hours for mobile gaming, and the second highest preference average for single-player mobile games after the Autonomous type. A total of 57% of this player type were female players. It was equally represented in both countries, and the mean age of the cluster was 40.5 years.

Finally, the Social and the Competitive player clusters were both motivated by Relatedness. They both enjoyed Exploration to a similar extent, and they both reported high scores for the racing game genre. The Competitive also had a relatively high score for sports games, and the highest score for strategy games of the six clusters. They both enjoyed multiplayer computer and console games more than the other clusters. The Social player type had the highest weekly computer play hours of the clusters, followed by the second highest hours of the Competitive type. Both of these clusters were over-represented in South-Korea. A total of 56% of the Social cluster were male players, but this was overshadowed by the Competitive player type which consisted of 60% of males.

If we consider together the two clusters (Autonomous and Fun-Seeker) that had the highest mean sums for the Fun motive, we can note that these two clusters covered 53.8% of all players included in the study. These two clusters shared similar game preferences and interests as both of them preferred the puzzle genre and single-player experiences. On the same note, the clusters that had the highest Relatedness motive for game play had notably lower Fun motive scores. This raises a question about a possible tension between the social motive to play when compared to playing just for Fun.

4 Concluding Statements

To a large part, the results of the present investigation seem to agree with the general expectations that playing games is fun, people play games because of the fun, and that such fun associates with the voluntariness of gameplay. In the results of the first cluster analysis, fun in particular appeared as an all-encompassing and ubiquitous motivational orientation, which would arguably incorporate expectations of gameplay gratifications and motivational factors in a diffuse manner. Due to this ubiquitous nature, following Crawford’s [2] line of thought, it seems difficult to treat fun as the same level of motive as the more discrete need-based IMG motives overtaken by it. Rather, fun could be considered as more like a general game gratification orientation.

The second cluster analysis, however, offered much more defined results revealing a six cluster solution, in which only one of the clusters (25.6% of the players) was solely based on a general fun-seeking game gratification orientation. Thus, the players represented by this Fun-seeker cluster appear purely as gratification seekers, while with the other clusters, fun appears to be more defined and needs-based. The results support Tamborini et al.’s [13] model that makes a distinction between the deeper, SDT needs-based and the more superficial and hedonistic-driven orientations towards enjoyment. Furthermore, the results are in line with Ryan et al.’s [8] conceptual distinction between hedonistic and eudaimonic approaches to human well-being, which in particular proposes that the latter approach indeed can be characterized in SDT-based motivational terms.

The question remains: what are the qualities of game gratification that are preferred by the Fun-Seekers? Our results indicate that they prefer logical problem solving and other game mechanics and interaction types typical of mobile puzzle games. In future studies this issue could be further investigated by including scrutiny of gameplay challenge dimensions, as well as focusing more on the performative ways of pleasure constitution. The latter approach could, for example, include a particular focus on the vitality forms [11] of the actions of gameplay as an immediate arousal of pleasure within sensory-motor interaction experience.