Elsevier

Computers in Human Behavior

Volume 68, March 2017, Pages 538-546
Computers in Human Behavior

Full length article
Why do players buy in-game content? An empirical study on concrete purchase motivations

https://doi.org/10.1016/j.chb.2016.11.045Get rights and content

Highlights

  • Inventory/questionnaire of in-game purchase motivations (19) was formed.

  • Motivational dimensions of in-game purchases were investigated via survey (N = 519).

  • Nineteen motivations converged onto six main dimensions:

    • Unobstructing, Social, Competition, Economical, Children, and Unlocking content.

    • Unobstructing, Social and Economical motivations predicted in-game purchases.

Abstract

Selling in-game content has become a popular revenue model for game publishers. While prior research has investigated latent motivations as determinants of in-game content purchases, the prior literature has not focused on more concrete reasons to purchase in-game content that stem from how the games are being designed. We form an inventory of reasons (19) to buy in-game content via triangulating from analyses of top-grossing free-to-play games, from a review of existing research, and from industry expert input. These reasons were operationalized into a survey (N = 519). Firstly, we explored how these motivations converged into categories. The results indicated that the purchasing reasons converged into six dimensions: 1) Unobstructed play, 2) Social interaction, 3) Competition, 4) Economical rationale, 5) Indulging the children, and 6) Unlocking content. Secondly, we investigated the relationship between these factors and how much players spend money on in-game content. The results revealed that the purchase motivations of unobstructed play, social interaction, and economical rationale were positively associated with how much money players spend on in-game content. The results imply that the way designers implement artificial limitations and obstacles as well as social interaction affects how much players spend money on in-game content.

Introduction

Virtual goods and other forms of in-game content have rapidly become one of the biggest forms of online consumption for gamers and de facto revenue model for game publishers (Alha et al., 2016, Hamari, 2015, Lehdonvirta, 2009). Selling virtual goods has especially been an integral part of the free-to-play/freemium business model that has rapidly spread to online services in general but perhaps most prominently to online games. In the free-to-play model the core game is offered for free for the user in order to acquire as many users as possible. The game publisher then attempts to upsell various pieces of in-game content in order to generate revenue. For instance, an analysis of the top 300 apps in the Apple's App Store reveals that the majority of downloadable apps are games that employ the free-to-play model (Brockmann, Stieglitz, & Cvetkovic, 2015).

One of the main consequences of selling in-game content has been its impact on the design philosophy of games (Hamari and Lehdonvirta, 2010, Hamari, 2011, Lin and Sun, 2011, Nieborg, 2015). Developers are no longer simply trying to create the best possible game they can in the artistic sense, but rather, in order to sell in-game content, the game developers attempt to craft the game in a way that it would entice users to purchase in-game content as frequently as possible. This is commonly done by tweaking the game according to player behavior and introducing new content periodically (Alves and Roque, 2007, Hamari and Järvinen, 2011, Hamari and Lehdonvirta, 2010, Hamari, 2011, Nieborg, 2015, Oh and Ryu, 2007). Therefore, purchase decisions for in-game content are not only affected by people's existing general attitudes, consumption values, and motivations but also by the design decisions and the needs built into the game by the developers (Alha et al., 2014, Hamari and Järvinen, 2011, Hamari and Keronen, 2016, Hamari and Lehdonvirta, 2010, Hamari, 2010, Harviainen and Hamari, 2015, Lin and Sun, 2011, Paavilainen et al., 2013).

While there has been a clear increase in studies investigating purchases of in-game content and virtual goods during the last decade (see e.g. Hamari & Keronen, 2016 for a review), the related quantitative literature has commonly focused on latent psychological constructs rather than being concerned with possible purchase motivations that stem from how the game has been designed. The quantitative vein of literature has been interested in predicting virtual good or in-game content (re-)purchases from perspectives of different affective experiences in the game (Chou and Kimsuwan, 2013, Hamari, 2015, Lee et al., 2012, Luo et al., 2011), customer lifetime value (Hanner & Zarnekow, 2015), content visibility (Jankowski, Bródka, & Hamari, 2016), cultural and demographic aspects (Lee and Wohn, 2012, Wohn, 2014), tele/social presence (Animesh, Pinsonneault, Yang, & Oh, 2011), playfulness (Han & Windsor, 2013), flow/cognitive involvement (Huang, 2012, Liu and Shiue, 2014), transaction cost theory (Guo and Barnes, 2011, Guo and Barnes, 2012), satisfaction (Kim, 2012), perceived value (Chou and Kimsuwan, 2013, Park and Lee, 2011), critical reception (Alha et al., 2016), technology acceptance (Cha, 2011, Domina et al., 2012, Hamari and Keronen, 2016), theories of planned behavior and reasoned action (Gao, 2014, Kaburuan et al., 2009), and expectancy-disconfirmation model (Wang and Chang, 2013, Wang and Chang, 2014). Qualitative efforts mapping the phenomenon, on the other hand, have been more successful in identifying more specific and concrete purchase motivations that pertain to the nature of the business models and its related effect on game design (Hamari and Järvinen, 2011, Hamari and Lehdonvirta, 2010, Hamari, 2011, Zagal et al., 2013), user experiences (Alha et al., 2014, Cleghorn and Griffiths, 2015, Lin and Sun, 2011, Paavilainen et al., 2013), and features of virtual goods (Lehdonvirta, 2009). While the quantitative body of literature has focused on relatively abstract psychological factors, and has therefore been unable to provide knowledge on more specific reasons for purchases that stem from how the game is designed, the contributions of the qualitative studies sphere, on the other hand, have not yet been harnessed in quantitative efforts to systematize the measurement and understanding of purchase motivators for in-game content. Therefore, the efforts on measuring purchase motivations stemming from the design of the game are currently lacking.

To this end, we aim to investigate reasons for purchasing in-game content from a bottom-up perspective that is informed by data and observations rather than from a top-down confirmatory perspective. Firstly, we form a measurement instrument for measuring the different reasons for buying in-game content by triangulating the findings of analyzing top-grossing free-to-play games, existing research on purchase motivations, in-depth discussions with game industry specialists, and literature related to gaming motivations. The resulting inventory of reasons (19) to buy in-game content was operationalized into a survey and was administered to free-to-play game players (N = 519) that had purchased in-game content. Next, the factorial properties of the measurement instrument are investigated. Finally, we investigate which purchase motivation factors predict how much players spend real money on in-game content.

Section snippets

Questionnaire development

We developed a set of items corresponding to reasons for making purchases in free-to-play games. The aim was to focus on concrete reasons for buying in-game content that players are faced with in free-to-play games. To comprise a comprehensive list, we analyzed one hundred top-grossing free-to-play games (excluding casino games) according to AppAnnie (a prominent data analysis tool used in mobile markets). From each genre, the typical in-app purchases and in-game spending mechanics were

Data

The data was gathered by an online survey through websites and social media pages of three major Finnish games-related magazines. The link to the survey was posted on the websites and in some cases also on the Facebook pages of the magazines. In all cases, the link was accompanied by a short introduction and invitation to participate in the study. The survey was active for 17 days. All the respondents who entered their contact information at the end of the survey were entered in a prize raffle

Exploratory factor analysis

We conducted an exploratory factor analysis using the PCA extraction method and the Varimax rotation. The factorial structure converged in 11 iterations. The resulting factorial structure explained 57.3% of the variance and all of the factors exceeded Eigenvalue of 1.

The first factor (named unobstructed play) includes purchase motivations related to being able to smoothly continue playing without obstructions or distractions: speeding timers, avoiding repetition, reaching completion, continuing

The relationship between reasons to purchase and the amount of money spent on in-game content

While the motivations describe which reasons have been important to respondents when they have purchased in-game content, the means do not inform us about the relationship between the motivations and how much the players are spending money on in-game content. Therefore, we conducted a multiple regression analysis on how the purchase motivation constructs were associated with a latent variable on how much money players use via four items: 1) total money used on free-to-play games, 2) money spent

Discussion

The results of the present study highlight that in games that employ the business model of selling in-game goods, the demand for those goods is, to some extent, dictated by how the game is designed and by the rules that govern how the items function in relation to the game's rules. Therefore, developers can be seen to create value for the in-game products through a careful configuration of the interplay between the game and the products sold therein (e.g. see Alha et al., 2014, Hamari and

Conclusion

In this paper, we set out to measure more concrete motivations to buy in-game content than majority of related literature so far. Firstly, we composed a measurement instrument for identifying between different motivations and reasons to purchase in-game content by triangulating from top-grossing games, existing research, and from discussions with game industry specialists. These reasons were operationalized into a survey which was further administered to free-to-play game players (N = 519) that

Acknowledgements

The research has been carried out as part of research projects (40134/13, 40111/14, 40107/14) funded by the Finnish Funding Agency for Innovation (TEKES). Moreover, we wish to thank Dome, Pelaaja and V2.fi.

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