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In the past decade, online gaming service has undergone exponential growth due to an Internet revolution where websites can use streaming video, audio, and a whole new set of user interactivity. This explosive growth has made the online gaming industry a highly profitable e-commerce business. According to DFC Intelligence, a strategic market research and consulting firm, online game players worldwide was 124 million in 2005 and nearly tripled to 376 million in 2009. The firm also estimates that the overall worldwide revenue for online games was $1.9 billion in 2003, and the revenue increased to $15.7 billion in 2010 and is expected to grow to nearly $29 billion in 2016 (DFC Intelligence, 2011).
To compete in this fast-growing market, online gaming service providers strive to offer attractive games and reduce subscription fee. Some new vendors in the market even compete by not charging subscription fee and allowing individuals to play for free. Although subscription fee may influence players’ initial choices of gaming service, player satisfaction should be the central concern for online gaming service providers. This is because satisfied players are likely to stay longer with a vendor, play games more often, and tend to contribute to word-of-mouth branding (Anderson & Srinivasan, 2003; Ding, Hu, Verma, & Wardell, 2010). Thus, the increasing proliferation of online gaming service and the fierce competition in online game market warrant investigation of the core research question of this study: What drives online game player satisfaction?
Past research finds that people play online games for various reasons such as overcoming challenge, alleviating tension, making friends, and killing time, but the most basic goal is to enjoy (Davis, Steury, & Pagulayan, 2005; Kim, Park, Kim, Moon, & Chun, 2002). That is, they primarily use online gaming service to derive a hedonic experience (Wu, Li, & Rao, 2008). Researchers in Information Systems (IS) field have indeed shown that enjoyable experience is fundamental to a positive attitude toward playing online games (Hsu & Lu, 2004). IS researchers also find that optimal user experience has a significant effect on both attitude toward and acceptance of online games (Lee, 2009). The brief overview of several articles cited above suggests that we need to take a close look at hedonic experience with respect to player satisfaction. However, based on our knowledge, very few studies have systematically examined the role of hedonic experience in online game player satisfaction.
To fill this gap and address the core research question stated above, the current study investigates the effect of hedonic experience on player satisfaction using an adapted technology acceptance model (TAM). Given that online gaming service is enabled by Internet-based information technology, TAM should fit in this e-commerce business environment and can serve as a good starting point as we attempt to better understand player satisfaction (Cayir, Basoglu, & Daim, 2010). To provide a sound theoretical basis for our research model, the current study also draws on a key marketing theory—the hedonic consumption perspective, which emphasizes the importance of hedonic experience to consumer behavior. By combining the perspective with TAM, the current study contributes not only to an interdisciplinary approach to model development, but also to an improved understanding of user satisfaction with an IT-based service. Moreover, this study also contributes by comparing the predictive power of TAM variables with that of hedonic experience constructs, and thus helps to ascertain which ones play a more important role in online gaming service context. This particular issue is of profound theoretical and practical importance, but so far, it has not been directly and systematically investigated.
This study tests the research model using questionnaire responses from 402 online game players, and analyzes the data by employing a structural equation modeling tool. Next, we provide theoretical background, followed by a section in which we present the research model and hypotheses for this study. We then report research design and the results of data analysis. Finally, we conclude with a discussion of important insights, implications, and limitations of this study.