From the Hands of an Early Adopter’s Avatar to Virtual Junkyards: Analysis of Virtual Goods’ Lifetime Survival

Virtual worlds and games have been postulated to provide unprecedented possibilities for research in general [1,2], but especially for the study of economics [3] due to their ability to systematically track every event in that reality, but also due to the possibility of creating controllable environments while having people exhibit natural behaviors.

Perhaps one of the most prominent veins of study related to virtual economies has been the study of consumer behavior related to adopting and purchasing virtual goods in virtual worlds and games [4–7]. This has especially been the case since games and virtual world operators have been the forerunners in implementing the so-called freemium or free-to-play business model ([8–10]), where playing or using the virtual environment is free of charge, but the operator generates revenue through different manifold marketing strategies combining classical sales tactics imbued with platform design that further encourages virtual-goods purchases [11–13].

Virtual goods mostly take up the forms of in-game items related to the theme of the game, such as avatar clothing, gear, vehicles, pets, emoticons, and other customization options [5,14], as well as different types of items related to the recent proliferation of ”gamblification”, where acquiring virtual goods is increasingly based on gambling-like mechanics, effectively blurring the line between gaming and gambling [15].

The largest vein of research in this continuum has been the investigation into why people purchase virtual goods [4,5] in primary or secondary markets within the virtual world. Popularly, this question was initially motivated by the sheer anecdotal amazement of why people would spend considerable amount of real money on products that “do not exist” [11,16]. However, since the initial combination of hype and disillusionment, virtual and game economies have entered into the realm of everyday consumer-facing services. Studying the question of why people purchase and trade virtual goods has primarily focused on latent psychological factors such as motivations, attitudes, experiences, and belief, and how they predict virtual-goods transactions as well as the internal design of the environment (see, for example, Reference [4] for a review of the area). However, the limitation within this sphere of research is that it can only provide a glimpse of the reasons why users purchase virtual goods as a singular event since it is focused on the consumer rather than the object of consumption and trade—the virtual good itself. Only few studies [17] have taken the initiative in an attempt to map the longer lifespan of virtual goods from their inception to circulation and to their ultimate end, destroyed from the virtual world, forgotten in a user’s virtual bag, or existing in an account of a user who has stopped visiting the virtual world.

Additionally, one of the major hurdles in governing and maintaining virtual economies, in addition to increasing consumer demand for virtual goods [11], has been the balancing act between “sources” and “sinks” [18] of virtual goods within a virtual economy. There is no practical or technical reason why any virtual good could not exist in complete abundance within the virtual economy. However, this would create problems both in relation to the meaningfulness of acting within the virtual world due to extreme inflation, which would also effectively void any need for users to purchase or trade virtual goods. Therefore, the lifetime management of virtual goods is of vital importance for any virtual-economy operator (see References [6,11,18]). Some of the methods in the game-operator palette have been, for example, contrived durability and planned obsolescence of virtual goods (see, for example, Reference [19]).

Game developers are confronted with issues identified with the ideal recurrence of virtual-product updates, their volumes, and intensity, with an emphasis on ceaseless development [20]. Reduced recurrence of updates can result in user churn, while the consistent improvement of new content increases operational expenses. From another perspective, users may have a constrained capacity for digital content used when content is updated as often as possible. This might be regarded as unwise budget allocation when content production is fundamentally higher than demand. The life expectancy of web-based gaming items is generally shorter than that of traditional items, and users always expect system updates and new content [21,22]. Another issue is the habituation impact resulting from the short life expectancy of virtual products, and the limited time in which the item can attract online users. This opens up new research directions since, so far, it has principally been researched for traditional markets [23].

To address this research problem, the present study is focused on the characteristics of early-stage adopters of virtual goods and how they predict the lifespan of the goods. Rogers [24] treats 2.5% of users as innovators, 13.5% of users as early adopters, 34% as an early majority, and 34% and 16% as the late majority and laggards, respectively. This research shows how characteristics of early-stage adopters affect user engagement and product lifespan. The main contributions include the identification of the role of early adopters of virtual goods for product lifespan, and building a predictive model for product life with the use of data.

The empirical study is followed by analysis based on survival prediction models and identification of the role of the characteristics of early-stage adopters for product lifespan. Decision trees showed the ability to predict product lifespan with the use of product-adopter characteristics. The rest of the paper is organized as follows. The Methodology section contains the conceptual framework, dataset description, and methodological background. The Results section includes descriptive statistics and results from the lifespan models based on user characteristics. This is followed by results from product classification in terms of their lifespan and user characteristics with an accuracy higher than 80%. The study is concluded in the final section.

From the Hands of an Early Adopter’s Avatar to Virtual Junkyards: Analysis of Virtual Goods’ Lifetime Survival

Kamil Bortko
Patryk Pazura
Juho Hamari
Piotr Bartków
Jarosław Jankowski

Citation: Bortko, K., Pazura, P., Hamari, J., Bartków, P., & Jankowski, J. (2019). From the Hands of an Early Adopter’s Avatar to Virtual Junkyards: Analysis of Virtual Goods’ Lifetime Survival. Applied Sciences, 9(7), 1268.

Please see the paper for full details: 
Journal
ResearchGate

Abstract: 

One of the major questions in the study of economics, logistics, and business forecasting is the measurement and prediction of value creation, distribution, and lifetime in the form of goods. In ”real” economies, a perfect model for the circulation of goods is impossible. However, virtual realities and economies pose a new frontier for the broad study of economics, since every good and transaction can be accurately tracked. Therefore, models that predict goods’ circulation can be tested and confirmed before their introduction to ”real life” and other scenarios. The present study is focused on the characteristics of early-stage adopters for virtual goods, and how they predict the lifespan of the goods. We employ machine learning and decision trees as the basis of our prediction models. Results provide evidence that the prediction of the lifespan of virtual objects is possible based just on data from early holders of those objects. Overall, communication and social activity are the main drivers for the effective propagation of virtual goods, and they are the most expected characteristics of early adopters.

Reference:

[1]Bainbridge, W.S. The scientific research potential of virtual worlds. Science 2007, 317, 472–476.
[2]Lazer, D.; Pentland, A.; Adamic, L.; Aral, S.; Barabási, A.L.; Brewer, D.; Christakis, N.; Contractor, N.; Fowler, J.; Gutmann, M.; et al. Computational social science. Science 2009, 323, 721–723.
[3]Horton, J.J.; Rand, D.G.; Zeckhauser, R.J. The online laboratory: Conducting experiments in a real labor market. Exp. Econ. 2011, 14, 399–425.
[4]Hamari, J.; Keronen, L. Why do people buy virtual goods: A meta-analysis. Comput. Hum. Behav. 2017, 71, 59–69.
[5]Lehdonvirta, V. Virtual item sales as a revenue model: Identifying attributes that drive purchase decisions. Electron. Commer. Res. 2009, 9, 97–113.
[6]Lehdonvirta, V.; Castronova, E. Virtual Economies: Design and Analysis; MIT Press: Cambridge, MA, USA, 2014.
[7]Lin, H.; Sun, C.T. Cash trade in free-to-play online games. Games Cult. 2011, 6, 270–287.
[8]Alha, K.; Koskinen, E.; Paavilainen, J.; Hamari, J.; Kinnunen, J. Free-to-play games: Professionals’ perspectives. In Proceedings of the 2014 International DiGRA Nordic Conference, May 29-30, Upsalla, Sweden, 2014.
[9]Alha, K.; Koskinen, E.; Paavilainen, J.; Hamari, J. Critical Acclaim and Commercial Success in Mobile Free-to-Play Games. In Proceedings of the First International Joint Conference of DiGRA and FDG, August 1-6, Dundee, Scotland, UK, 2016.
[10]Hamari, J.; Hanner, N.; Koivisto, J. Service quality explains why people use freemium services but not if they go premium: An empirical study in free-to-play games. Int. J. Inf. Manag. 2017, 37, 1449–1459.
[11]Hamari, J.; Lehdonvirta, V. Game design as marketing: How game mechanics create demand for virtual goods. Int. J. Bus. Sci. Appl. Manag. 2010, 5, 14–29.
[12]Hamari, J.; Järvinen, A. Building customer relationship through game mechanics in social games. In Business, Technological, and Social Dimensions of Computer Games: Multidisciplinary Developments;IGI Global: Hershey, PA, USA, 2011; pp. 348–365.
[13]Heimo, O.I.; Harviainen, J.T.; Kimppa, K.K.; Mäkilä, T. Virtual to virtuous money: A virtue ethics perspective on video game business logic. J. Bus. Ethics 2018, 153, 95–103.
[14]Fairfield, J.A. Virtual property. B.U.L. Rev. 2005, 85, 1047.
[15]Macey, J.; Hamari, J. eSports, skins and loot boxes: Participants, practices and problematic behaviour associated with emergent forms of gambling. New Media Soc. 2019, 21, 20–41.
[16]Taylor, T.L. Living digitally: Embodiment in virtual worlds. In The Social Life of Avatars; Springer-Verlag, London, 2002; pp. 40–62.
[17]Jankowski, J.; Kolomvatsos, K.; Kazienko, P.; Watróbski, J. Fuzzy Modeling of User Behaviors and Virtual Goods Purchases in Social Networking Platforms. J. UCS 2016, 22, 416–437.
[18]Lehdonvirta, V. Virtual economics: Applying economics to the study of game worlds. In Proceedings of the 2005 Conference on Future Play (Future Play 2005), Lansing, MI, USA, 13–15 October 2005.
[19]Orbach, B.Y. The durapolist puzzle: Monopoly power in durable-goods markets. Yale J. Regul. 2004, 21, 67.
[20]Lu, H.P.; Wang, S.m. The role of Internet addiction in online game loyalty: An exploratory study. Internet Res. 2008, 18, 499–519.
[21]Kwong, J.A. Getting the goods on virtual items: A fresh look at transactions in multi-user online environments. William Mitchell Law Rev. 2010, 37, 1805.
[22]Kaplan, A.M.; Haenlein, M. Consumer use and business potential of virtual worlds: The case of second life. Int. J. Media Manag. 2009, 11, 93–101.
[23]Wathieu, L. Consumer habituation. Manag. Sci. 2004, 50, 587–596.
[24]Rogers, E.M. Diffusion of Innovations, 4th ed.; Free Press: New York, NY, USA, 1962.