Skip to main content
SpringerLink
Log in

Determining Satisfaction from Gameplay by Discussing Flow States Related to Relaxation and Excitement

  • Research
  • Published:
The Computer Games Journal

Abstract

Currently, people use the Internet for both work and leisure. The hedonic features of a website are as crucial as its functional features. In recent years, website researches have begun paying attention to user experience because people immerse games on websites. This study examined how satisfaction differs in different flow states. This study investigated the flow experience of online game players in states of excitement and relaxation and explored how flow states influence website satisfaction and actual use time. Because motivations engendered by goal or behavior orientation moderates the relationship between flow states and website satisfaction, the optimal flow pattern may differ between goal- and behavior-oriented website game players. This study used clustering analysis and a t test to divide and compare the groups. The total number of respondents was 340. Among these, 175 players (51.47%) were male. The results revealed that the goal-oriented players were more satisfied in the relaxation flow state, and the behavior-oriented players were substantially satisfied at an exciting flow experience. However, both goal- and behavior-oriented players demonstrated no significant difference in the time spent on playing games when they were immersed in a flow state. From a theoretical perspective, this study demonstrated that different balances between challenge and skill result in different experiences and satisfaction levels. This study provided a novel finding that the spending time playing games did not mean that the players were more satisfied. Game developers should thoroughly evaluate the balance between challenges and skills based on their target players and company strategies when designing games.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Apter, M. J. (1982). The experience of motivation: The theory of psychological reversals. New York: Academic Press.

    Google Scholar 

  • Apter, M. J. (1992). The dangerous edge: The psychology of excitement. New York: Free Press.

    Google Scholar 

  • Apter, M. J. (2007). Reversal theory: The dynamics of motivation. London: Oxford Oneworld Publications.

    Google Scholar 

  • Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421–458.

    Google Scholar 

  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS quarterly, 25, 351–370.

    Google Scholar 

  • Bilgihan, A., Cobanoglu, C., Nusair, K., Okumus, F., & Bujisic, M. (2013). A quantitative study exploring the difference between gaming genre preferences. The Computer Games Journal, 2, 19–40.

    Google Scholar 

  • Castaneda, J. A., Munoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44, 384–396.

    Google Scholar 

  • Chang, Y.-W. (2016). Influence of the principle of least effort across disciplines. Scientometrics, 106, 1117–1133.

    Google Scholar 

  • Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of Web activities. Computers in Human Behavior, 15, 585–608.

    Google Scholar 

  • Coll, R., & Wingertsman, J. C., III. (1990). The effect of screen complexity on user preference and performance. International Journal of Human-Computer Interaction, 2, 255–265.

    Google Scholar 

  • Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper Perennial.

    Google Scholar 

  • Csikszentmihalyi, M. (1997). Finding flow: The psychology of engagement with everyday life. New York: Basic Books.

    Google Scholar 

  • Csikszentmihalyi, M., & Csikszentmihalyi, I. S. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass.

    Google Scholar 

  • Csikszentmihalyi, M., Larson, R., & Prescott, S. (1977). The ecology of adolescent activity and experience. Journal of youth and adolescence, 6, 281–294.

    Google Scholar 

  • Csikszentmihalyi, M., & Lefevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56, 815–822.

    Google Scholar 

  • Deng, L., & Scott, P. M. (2010). Affect in web interfaces: A study of the impacts of web page visual complexity and order. Mis Quarterly, 34, 711–A10.

    Google Scholar 

  • Doolin, B., Dillon, S., Thompson, F., & Corner, J. L. (2005). Perceived risk, the Internet shopping experience and online purchasing behavior: A New Zealand perspective. Journal of Global Information Management (JGIM), 13, 66–88.

    Google Scholar 

  • Engeser, S., & Rheinberg, F. (2008). Flow, performance and moderators of challenge-skill balance. Motivation and Emotion, 32, 158–172.

    Google Scholar 

  • Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.

    Google Scholar 

  • Fox, L. (2009). Transforming your mind. Maitland: Xulon Press.

    Google Scholar 

  • Gefen, D. (2000). E-commerce: the role of familiarity and trust. Omega, 28, 725–737.

    Google Scholar 

  • Gefen, D., Karahanna, E., & Straub, D. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50, 307–321.

    Google Scholar 

  • Gupta, R., & Kabadayi, S. (2010). The relationship between trusting beliefs and web site loyalty: The moderating role of consumer motives and flow. Psychology & Marketing, 27, 166–185.

    Google Scholar 

  • Hampton-Sosa, W. (2017). An exploration of essential factors that influence music streaming adoption and the intention to engage in digital piracy. International Journal of Electronic Commerce Studies, 8, 97–134.

    Google Scholar 

  • Hausman, A. V., & Siekpe, J. S. (2009). The effect of web interface features on consumer online purchase intentions. Journal of Business Research, 62, 5–13.

    Google Scholar 

  • Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60, 50–68.

    Google Scholar 

  • Jeong, S. W., Fiore, A. M., Niehm, L. S., & Lorenz, F. O. (2009). The role of experiential value in online shopping the impacts of product presentation on consumer responses towards an apparel. Internet Research, 19, 105–124.

    Google Scholar 

  • Kent, M. (2006). The Oxford dictionary of sports science and medicine. Oxford: Oxford University Press.

    Google Scholar 

  • Kim, D., Ferrin, D., & Rao, R. (2009). Trust and satisfaction, two stepping stones for successful E-commerce relationships: A longitudinal exploration. Information Systems Research, 20, 237–257.

    Google Scholar 

  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13, 205–223.

    Google Scholar 

  • Lalomia, M. J., & Sidowski, J. B. (1990). Measurements of computer satisfaction, literacy, and aptitudes: A review. International Journal of Human-Computer Interaction, 2, 231–253.

    Google Scholar 

  • Lee, D., Rhee, Y., & Dunham, R. B. (2009). The role of organizational and individual characteristics in technology acceptance. International Journal of Human-Computer Interaction, 25, 623–646.

    Google Scholar 

  • Liang, C.-C. (2018). Discontinuous adoption of social media platform. International Journal of Electronic Commerce Studies, 9, 71–92.

    Google Scholar 

  • Lippert, S. K., & Volkmar, J. A. (2007). Cultural effects on technology performance and utilization: A comparison of US and Canadian users. Journal of Global Information Management, 15, 56–90.

    Google Scholar 

  • Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52, 599–607.

    Google Scholar 

  • Lu, Y. B., Zhou, T., & Wang, B. (2009). Exploring Chinese users' acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25, 29–39.

    Google Scholar 

  • Mackenzie, S. H., Hodge, K., & Boyes, M. (2011). Expanding the flow model in adventure activities: A reversal theory perspective. Journal of Leisure Research, 43, 519–544.

    Google Scholar 

  • Moon, J., & Kim, Y. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38, 217–230.

    Google Scholar 

  • Nakamura, J., & Csikszentmihalyi, M. (2009). Flow Theory and research. In C. R. Snyder & S. J. Lopez (Eds.), Oxford handbook of positive psychology (2nd ed.). New York: Oxford University Press.

    Google Scholar 

  • Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13, 3–16.

    Google Scholar 

  • Novak, T. P., Hoffman, D. L., & Yung, Y.-F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19, 22–42.

    Google Scholar 

  • Plotnik, R., & Kouyoumjian, H. (2011). Introduction to psychology. Belmont: CA, Wadsworth.

    Google Scholar 

  • Reid, G. (2012). Motivation in video games: A literature review. The Computer Games Journal, 1, 70–81.

    Google Scholar 

  • Rice, M. (2002). What makes users revisit a Web site. MarketingNews, 31, 12.

    Google Scholar 

  • Richard, M. O., Chebat, J. C., Yang, Z. Y., & Putrevu, S. (2010). A proposed model of online consumer behavior: Assessing the role of gender. Journal of Business Research, 63, 926–934.

    Google Scholar 

  • Rouibah, K., & Hamdy, H. (2009). Factors affecting information communication technologies usage and satisfaction: Perspective from instant messaging in Kuwait. Journal of Global Information Management, 17(2), 8–29.

    Google Scholar 

  • Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors' flow experience while browsing a Web site: Its measurement, contributing factors and consequences. Computers in Human Behavior, 20, 403–422.

    Google Scholar 

  • Snyder, C. R., & Lopez, S. J. (2009). Oxford handbook of positive psychology. USA: Oxford University Press.

    Google Scholar 

  • Thatcher, A., Wretschko, G., & Fridjhon, P. (2008). Online flow experiences, problematic Internet use and Internet procrastination. Computers in Human Behavior, 24, 2236–2254.

    Google Scholar 

  • van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28, 695–704.

    Google Scholar 

  • Williamson Smith, M., Sun, W., Sutherland, J., & Mackie, B. (2014). Game advertising: A conceptual framework and exploration of advertising prevalence. The Computer Games Journal, 3, 95–124.

    Google Scholar 

  • Yang, Y.-J., Wang, C.-C., & Chen, C.-C. (2017). Recent development trend of electronic commerce research: 2000 to 2016. Contemporary Management Research, 13(2), 131–142.

    Google Scholar 

  • Yu, C.-S., Chantatub, W., & Mendi, B. (2017). Factors for user intention to switch browsers: A cross-national survey. International Journal of Electronic Commerce Studies, 8, 146–172.

    Google Scholar 

  • Zipf, G. K. (1949). Human behavior and the principle of least effort. Oxford: England, Addison-Wesley Press.

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Ministry of Science and Technology, Taiwan (MOST 109-2410-H-034-002).

Author information

Authors and Affiliations

  1. Department of Advertising, Chinese Culture University, No.55, Hwa-Kang Rd., Yang-Ming-Shan, Taipei, 11114, Taiwan, ROC

    Shu-Chen Chang & Yu-Ping Chiu

  2. MetaEdge Corporation, Taipei, Taiwan, ROC

    Jiann-Chyau Hwang

Authors
  1. Shu-Chen Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu-Ping Chiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiann-Chyau Hwang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yu-Ping Chiu.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chang, SC., Chiu, YP. & Hwang, JC. Determining Satisfaction from Gameplay by Discussing Flow States Related to Relaxation and Excitement. Comput Game J 9, 369–382 (2020). https://doi.org/10.1007/s40869-020-00113-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40869-020-00113-5

Keywords

Search

Navigation