Flow (FCF) theory has received considerable attention in recent decades. In addition to flow, FCF theory proposed three influential factors, that is, boredom, frustration, and apathy. While these factors have received relatively less attention than flow, Internet applications have grown exponentially, warranting a closer reexamination of the applicability of the FCF theory. Thus, this study tested the theory that high/low levels of skill and challenge lead to four channels of flow. The study sample included 253 online gamers who provided valid responses to an online survey. Analytical results support the FCF theory, although a few exceptions were noted. First, skill was insignificantly related to apathy, possibly because low-skill users can realize significant achievements to compensate for their apathy. Moreover, in contrast with the FCF theory, challenge was positively related to boredom, revealing that gamers become bored with difficult yet repetitive challenges. Two important findings suggest new directions for FCF theory. 1. Introduction The application of flow theory to multiple Internet contexts [1–4] reflects its prominent role in information systems research. In their pioneering work, Csikszentmihalyi [5] proposed the four channels of flow (FCF) theory, that is, flow, boredom, frustration, and apathy, and also posited that skill and challenge are major components in each of those channels. Flow refers to the involvement of individuals in activities with full concentration and their subsequent enjoyment [6], whereas those individuals experience flow through high degree of skills to control challenges [1]. Such highly enjoyable experiences cause individuals to become more involved in related activities, allowing them to perceive enjoyment, control, and intrinsic enjoyment [2]. Therefore, high levels of skills and challenges create the perception of flow. Boredom occurs when a person experiences monotony, insipidity, and a lack of stimuli [7]. Individuals may feel disinterested and lacking in concentration for an activity, resulting in unpleasant emotions [8]. Moreover, boredom creates a passive perception towards stimuli [9]. Enhanced skills likely shift individuals from involvement to boredom [8]. Therefore, highly skilled individuals are more likely to familiarize themselves with the stimuli related to an activity, subsequently giving rise to boredom. Frustration refers to the inability of individuals to solve problems or satisfy demand involving discontent or insecure perceptions [7]. Although frustration may produce negative emotions under
References
[1]
D. L. Hoffman and T. P. Novak, “Marketing in hypermedia computer-mediated environments: conceptual foundations,” Journal of Marketing, vol. 60, no. 3, pp. 50–68, 1996.
[2]
C. L. Hsu and H. P. Lu, “Why do people play on-line games? An extended TAM with social influences and flow experience,” Information and Management, vol. 41, no. 7, pp. 853–868, 2004.
[3]
C. Mathwick and E. Rigdon, “Play, flow, and the online search experience,” Journal of Consumer Research, vol. 31, no. 2, pp. 324–332, 2004.
[4]
C. I. Teng, L. S. Huang, S. P. Jeng, Y. J. Chou, and H. H. Hu, “Who are loyal customers in online games?” in Proceedings of the International Consortium for Electronic Business, pp. 312–313, ICEB Press, Waikoloa, Hawaii, USA, 2008.
[5]
M. Csikszentmihalyi and I. S. Csikszentmihalyi, Optimal Experience: Psychological Studies of Flow in Consciousness, Cambridge University Press, Cambridge, UK, 1988.
[6]
M. Csikszentmihalyi, “Happiness and creativity: going with flow,” The Futurist, vol. 31, no. 5, pp. 8–12, 1997.
[7]
Merriam-Webster Online Dictionary, “Frustration and apathy,” January 2011, http://www.merriam-webster.com/.
[8]
G. Chanel, C. Rebetez, M. Bétrancourt, and T. Pun, “Boredom, engagement and anxiety as indicators for adaptation to difficulty in games,” in Proceedings of the 12th International MindTrek Conference: Entertainment and Media in the Ubiquitous Era (MindTrek '08), pp. 13–17, ACM Press, October 2008.
[9]
C. D. Fisherl, “Boredom at work: a neglected concept,” Human Relations, vol. 46, no. 3, pp. 395–417, 1993.
[10]
L. D. Goodstein and R. I. Lanyon, “The process of adjustment,” in Adjustment, Behavior, and Personality, L. D. Goodstein and R. I. Lanyon, Eds., pp. 155–189, Addison Wesley, 1975.
[11]
K. M. Gilleade and A. Dix, “Using frustration in the design of adaptive videogames,” in Proceedings of theACM SIGCHI International Conference on Advances in Computer Entertainment Technology (ACE '04), pp. 228–232, ACM Press, 2004.
[12]
M. L. Korzaan, “Going with the flow: predicting online purchase intentions,” Journal of Computer Information Systems, vol. 43, no. 4, pp. 25–31, 2003.
[13]
M. J. Sánchez-Franco, “Exploring the influence of gender on the web usage via partial least squares,” Behaviour and Information Technology, vol. 25, no. 1, pp. 19–36, 2006.
[14]
Y. X. Skadberg and J. R. Kimmel, “Visitors' flow experience while browsing a Web site: its measurement, contributing factors and consequences,” Computers in Human Behavior, vol. 20, no. 3, pp. 403–422, 2004.
[15]
E. Bridges and R. Florsheim, “Hedonic and utilitarian shopping goals: the online experience,” Journal of Business Research, vol. 61, no. 4, pp. 309–314, 2008.
[16]
M. O. Richard and R. Chandra, “A model of consumer web navigational behavior: conceptual development and application,” Journal of Business Research, vol. 58, no. 8, pp. 1019–1029, 2005.
[17]
T. P. Novak, D. L. Hoffman, and Y. F. Yung, “Measuring the customer experience in online environments: a structural modeling approach,” Marketing Science, vol. 19, no. 1, pp. 22–42, 2000.
[18]
D. L. Hoffman and T. P. Novak, “Flow online: lessons learned and future prospects,” Journal of Interactive Marketing, vol. 23, no. 1, pp. 23–34, 2009.
[19]
L. E. Nacke and C. A. Lindley, “Affective ludology, flow and immersion in a first-person shooter: measurement of player experience,” Loading…The Journal of the Canadian Game Studies Association, vol. 3, no. 5, 2009.
[20]
A. Dietrich, “Neurocognitive mechanisms underlying the experience of flow,” Consciousness and Cognition, vol. 13, no. 4, pp. 746–761, 2004.
[21]
D. H. Choi, J. Kim, and S. H. Kim, “ERP training with a web-based electronic learning system: the flow theory perspective,” International Journal of Human Computer Studies, vol. 65, no. 3, pp. 223–243, 2007.
[22]
M. Zaman, M. Anandarajan, and Q. Dai, “Experiencing flow with instant messaging and its facilitating role on creative behaviors,” Computers in Human Behavior, vol. 26, no. 5, pp. 1009–1018, 2010.
[23]
C. Klimmt, A. Rizzo, P. Vorderer, J. Koch, and T. Fischer, “Experimental evidence for suspense as determinant of video game enjoyment,” Cyberpsychology and Behavior, vol. 12, no. 1, pp. 29–31, 2009.
[24]
D. Choi and J. Kim, “Why people continue to play online games: in search of critical design factors to increase customer loyalty to online contents,” Cyberpsychology and Behavior, vol. 7, no. 1, pp. 11–24, 2004.
[25]
R. Weber, R. Tamborini, A. Westcott-Baker, and B. Kantor, “Theorizing flow and media enjoyment as cognitive synchronization of attentional and reward networks,” Communication Theory, vol. 19, no. 4, pp. 397–422, 2009.
[26]
M. Csikszentmihalyi, Beyond Boredom and Anxiety, Jossey-Bass, San Francisco, Calif, USA, 1975.
[27]
T. P. Novak, D. L. Huffman, and A. Duhachek, “The influence of goal-directed and experiential activities on online flow experiences,” Journal of Consumer Psychology, vol. 13, no. 1-2, pp. 3–16, 2003.
[28]
R. Agarwal and E. Karahanna, “Time flies when you're having fun: cognitive absorption and beliefs about information technology usage,” MIS Quarterly, vol. 24, no. 4, pp. 665–694, 2000.
[29]
H. Chen, R. T. Wigand, and M. S. Nilan, “Optimal experience of Web activities,” Computers in Human Behavior, vol. 15, no. 5, pp. 585–608, 1999.
[30]
J. Chung and F. B. Tan, “Antecedents of perceived playfulness: an exploratory study on user acceptance of general information-searching websites,” Information and Management, vol. 41, no. 7, pp. 869–881, 2004.
[31]
A. Rollings and E. Adams, Andrew Rollings and Ernest Adams on Game Design, New Riders, Indianapolis, Ind, USA, 2003.
[32]
C. I. Teng, “Customization, immersion satisfaction, and online gamer loyalty,” Computers in Human Behavior, vol. 26, no. 6, pp. 1547–1554, 2010.
[33]
D. Weibel, B. Wissmath, S. Habegger, Y. Steiner, and R. Groner, “Playing online games against computer- vs. human-controlled opponents: effects on presence, flow, and enjoyment,” Computers in Human Behavior, vol. 24, no. 5, pp. 2274–2291, 2008.
[34]
C. L. Hsu and H. P. Lu, “Consumer behavior in online game communities: a motivational factor perspective,” Computers in Human Behavior, vol. 23, no. 3, pp. 1642–1659, 2007.
[35]
D. Williams, N. Yee, and S. E. Caplan, “Who plays, how much, and why? Debunking the stereotypical gamer profile,” Journal of Computer-Mediated Communication, vol. 13, no. 4, pp. 993–1018, 2008.
[36]
R. Kammann and R. Flett, “Affectometer 2: a scale to measure current level of general happiness,” Australian Journal of Psychology, vol. 35, no. 2, pp. 259–265, 1983.
[37]
A. Kozma and M. J. Stones, “The measurement of happiness: development of the Memorial University of Newfoundland Scale of Happiness (MUNSH),” Journals of Gerontology, vol. 35, no. 6, pp. 906–912, 1980.
[38]
C. K. J. Wang, A. Khoo, W. C. Liu, and S. Divaharan, “Passion and intrinsic motivation in digital gaming,” Cyberpsychology and Behavior, vol. 11, no. 1, pp. 39–45, 2008.
[39]
C. I. Teng, S. S. Chang, and K. H. Hsu, “Emotional stability of nurses: impact on patient safety,” Journal of Advanced Nursing, vol. 65, no. 10, pp. 2088–2096, 2009.
[40]
C. I. Teng, Y. I. L. Shyu, W. K. Chiou, H. C. Fan, and S. M. Lam, “Interactive effects of nurse-experienced time pressure and burnout on patient safety: a cross-sectional survey,” International Journal of Nursing Studies, vol. 47, no. 11, pp. 1442–1450, 2010.
[41]
R. P. Bagozzi and Y. Yi, “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science, vol. 16, no. 1, pp. 74–94, 1988.
[42]
J. C. Anderson and D. W. Gerbing, “Structural equation modeling in practice: a review and recommended two-step approach,” Psychological Bulletin, vol. 103, no. 3, pp. 411–423, 1988.
[43]
C. Fornell and D. F. Larcker, “Evaluating structural equation models with unobservable variables and measurement errors,” Journal of Marketing Research, vol. 18, no. 1, pp. 39–50, 1981.
[44]
M. W. Browne and R. Cudeck, “Single sample cross-validation indices for covariance structures,” Multivariate Behavioral Research, vol. 24, no. 4, pp. 445–455, 1989.
[45]
M. W. Browne and R. Cudeck, “Alternative ways of assessing model fit,” in Testing Structural Equation Models, K. A. Bollen and J. S. Long, Eds., pp. 136–162, 1993.
[46]
J. H. Steiger, “Point estimation, hypothesis testing, and interval estimation using the RMSEA: some comments and a reply to Hayduk and Glaser,” Structural Equation Modeling, vol. 7, no. 2, pp. 149–162, 2000.
[47]
R. P. Bagozzi, “Structural equation models are modelling tools with many ambiguities: comments acknowledging the need for caution and humility in their use,” Journal of Consumer Psychology, vol. 20, no. 2, pp. 208–214, 2010.
[48]
K. A. Bollen, Structural Equations with Latent Variable, John Wiley & Sons, New York, NY, USA, 1989.
[49]
P. M. Podsakoff, S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff, “Common method biases in behavioral research: a critical review of the literature and recommended remedies,” Journal of Applied Psychology, vol. 88, no. 5, pp. 879–903, 2003.
[50]
C. A. Steinkuehler and D. Williams, “Where everybody knows your (screen) name: online games as ‘third places’,” Journal of Computer-Mediated Communication, vol. 11, no. 4, pp. 885–909, 2006.
[51]
D. Weibel, B. Wissmath, and F. W. Mast, “Immersion in mediated environments: the role of personality traits,” Cyberpsychology, Behavior, and Social Networking, vol. 13, no. 3, pp. 251–256, 2010.
[52]
R. T. A. Wood, M. D. Griffiths, D. Chappell, and M. N. O. Davies, “The structural characteristics of video games: a psycho-structural analysis,” Cyberpsychology and Behavior, vol. 7, no. 1, pp. 1–10, 2004.
[53]
C. I. Teng, “Personality differences between online game players and nonplayers in a student sample,” Cyberpsychology and Behavior, vol. 11, no. 2, pp. 232–234, 2008.
[54]
C. I. Teng, “Online game player personality and real-life need fulfillment,” International Journal of Cyber Society and Education, vol. 2, no. 2, pp. 39–50, 2009.
[55]
C. I. Teng, “Who are likely to experience flow? Impact of temperament and character on flow,” Personality and Individual Differences, vol. 50, no. 6, pp. 863–868, 2011.
[56]
C. I. Teng and S. H. Lin, “Examination of four channels of flow,” in Proceedings of the 9th International Consortium for Electronic Business, pp. 99–102, 2009.