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Pricing of Games As a Service: an Analytical Model for Interactive Digital Services with Hedonic Properties

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Pricing of Games As a Service: an Analytical Model for Interactive Digital Services with Hedonic Properties University of Texas Rio Grande Valley ScholarWorks @ UTRGV Information Systems Faculty Publications and Robert C. Vackar College of Business & Presentations Entrepreneurship 1-2018 Pricing of Games as a Service: An Analytical Model for Interactive Digital Services with Hedonic Properties Tayfun Keskin The University of Texas Rio Grande Valley Follow this and additional works at: https://scholarworks.utrgv.edu/is_fac Part of the Business Commons, and the Computer Sciences Commons Recommended Citation Keskin, T. (2018, January 3). Pricing of Games as a Service: An Analytical Model for Interactive Digital Services with Hedonistic Properties. Proceedings of the 51st Hawaii International Conference on System Sciences 2018. Hawaii International Conference on System Sciences 2018, Manoa, HI. https://doi.org/ 10.24251/HICSS.2018.165 This Article is brought to you for free and open access by the Robert C. Vackar College of Business & Entrepreneurship at ScholarWorks @ UTRGV. It has been accepted for inclusion in Information Systems Faculty Publications and Presentations by an authorized administrator of ScholarWorks @ UTRGV. For more information, please contact [email protected], [email protected]. Proceedings of the 51st Hawaii International Conference on System Sciences j 2018 Pricing of Games as a Service: An Analytical Model for Interactive Digital Services with Hedonic Properties Tayfun Keskin The University of Texas Rio Grande Valley [email protected] Abstract One of the most important motives for the game This study explores optimal pricing strategies in developer to release new contents of the game is to games and other interactive digital goods under balance between getting desirable content delivered incomplete information, when bundling is an option. and minimizing the annoyance caused to players. It is Drawing from research on the pricing of information obvious that game developers have the incentive to goods, we propose a pattern of optimal pricing deliver desirable content to players. Frequent release strategies in which hedonic characteristics affect the of new content provides new excitement to players, utility of interactive digital goods and services. This is and invoke in game purchasing. For the annoyance a new approach to games, to treat them as a service to caused to players, it is not only referring to the hassle determine pricing strategies. Findings reveal that caused by frequency update notifications, it also there is an optimal pricing solution for firms in the includes the cost incurred when players are trying to gaming industry. This finding holds both in bundling get used to the new contents or user interfaces. In and non-bundling cases. addition, frequent additions could complicate the Utilizing analytical modeling methodology, we game. It could potentially harm in game social propose pricing-inspired business strategies to the interactions and deter new players [1]. firms operating in the digital gaming industry. Our findings could also be applied to other hedonic interactive digital goods and services. Overall, this study contributes to the existing pricing theories in digital services and information goods. 1. Introduction Content release strategy of the gaming industry was almost identical to the physical goods prior to the Figure 1: Super Mario Series Cartridges internet era. For example, once Super Mario is released, all the game content is packed into a fixed package, and the players did not get any new content Our study aims to model this trade-off caused until Super Mario 2 cartridge is released (see figure 1.) frequent updates to generate revenue. We also This strategy seems to be constrained by technology investigate how social interactions among gamers of the game production rather than by business could affect the developers’ optimal decision. Of motives. Moreover, connecting a digital service to a course, in practice, this analytical model should be physical good made it easier to utilize conventional tested with empirical estimates so that we can know pricing models. Nowadays, game developers can more about how exactly the model works for different release new content to players whenever they want. types of games or different player pools. Many mobile apps or online games release new updates in a matter of weeks, or even days. Given this The main contribution of this research study is to flexibility, determining optimized pricing and content clarify how several important mechanisms, which are release strategies based on business motives has well known to the game developers, work together in become an important decision. an economic model. For example, the game difficulty URI: http://hdl.handle.net/10125/50052 Page 1340 ISBN: 978-0-9981331-1-9 (CC BY-NC-ND 4.0) has to be at the correct level because if the game is too to our knowledge, this is the first paper investigating difficult, it could deter new players. On the other hand, pricing strategies games as a service. if it is too easy, competitive players may leave. Also, if the developers release new content too frequently 2. Literature Review user do not have enough time to get used to them. Yet, without new releases, the developer cannot response to user’s preference accordingly. Leveraging the Contemporary games typically utilize cloud- nature of social interaction in the game makes it easier computing technologies. The gaming industry has for the players to learn about the new content and gain been embracing cloud computing because of its the most out of it. None of these mechanisms is foreign reduced operational costs, flexibility, scalability, rapid to the game industry. However, it is because these deployment, remote access and mobility, access to mechanisms interact and affect each other, putting innovation, efficient use of computing resources, and them together makes the whole system very green computing [2]. Cloud computing has three complicated to analysis without a formal model. By service models: Infrastructure as a Service (IaaS), building an economic model with rational agent, we Platform as a Service (PaaS), and Software as a can apply the tools we use in economics to learn about Service (SaaS). Conventional digital games are to how the above mechanisms work. moving from away from physical software packages (i.e., Cartridges and disks) to SaaS platforms. The new Our analytical model also provides insight to SaaS based gaming platform is called cloud gaming, operational decisions (such as when and how much a or games as a service (GaaS) [3]. game developer should release new content.) In addition, if they can release new content to a particular SaaS is not only a popular for gaming services, but group of players, how they should pick those players. it also drives the overall growth of the cloud We hope that the model will provide us with a tool to computing industry. In 2016, SaaS applications hint the answer to these questions and hint how the generated more than half of the cloud computing decision be affected by the nature of player pool, size industry revenue [4]. of game, nature of game, companies’ fame, and the cost of producing new contents. This study investigates the impact of interactive digital goods pricing strategies on the sales revenues Understanding the optimal content release of GaaS products. Therefore, this section discusses the frequency is important for the game developers prior studies on price discount-based pricing and provide good user experience for players. Our bundling strategies. preliminary investigation revealed that there is substantial amount of comments in Google Play and 2.1 SaaS – GaaS Intersection Apple App Store declaring the annoyance caused by too frequent updates. In addition, there are even more Cloud computing, particularly SaaS, has been a comments concerning not enough new content when popular research topic in the last decade [5, 6, 7, 8, 9, we are looking at the game-associated forums. 10]. Numerous studies have presented definitions of major concepts, systems structures, stakeholders, and Finally, our analytical model hints the direction of technologies, as well as potential future research how making use of game data to improve bundling topics in the cloud computing area [2, 4, 9]. However, decisions. As mentioned before, social interaction GaaS is rarely discussed in cloud computing research plays an important role in determining optimal content primarily because it is covered under SaaS and other release strategy. Therefore, with the proper measure of emerging technology categories. Discussion of these the degree of social interactions and other “emerging technology” classifications is essential for characteristics of the game, we can determine the information systems research as the managerial strategy better. Big-data researchers in the gaming aspects of cloud computing enhances capabilities and industry can also benefit from this model. The insight performance of the information technology (IT) we get from an economic model can help us to narrow artifact [11]. down what we should be looking at in the sea of game data. An alternative key study pillar of cloud computing research is to discuss new gaming technologies that In the recent years, online games and software as a can be offered through SaaS category. The overview service have been popular research topics. However, of GaaS is essential to investigate these new technologies and capabilities related to cloud Page 1341 computing and provide an overarching picture for the 3. Model pricing of these emerging technologies [2, 12]. We characterize game markets with a competitive Prior research has already addressed perception, classical two period model with a j number of adoption, privacy and security issues regarding the offerings. Initially, competing firms start with SaaS concept [13, 14, 15], yet we were not able to asymmetric market shares, which is more realistic than identify any studies on business models or pricing identical market shares. Next, we use this model to research on SaaS. investigate how prices and market shares would change over time and to explain strategies for 2.2 Pricing Strategies advanced strategies that include bundling of GaaS offerings.
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