The Concept of Flow in Online Consumer Behavior

  • Irene Esteban-Millat
  • Francisco J. Martínez-López
  • David Luna
  • Inma Rodríguez-Ardura
Part of the Progress in IS book series (PROIS)


The concept of flow has become increasingly relevant in the field of online navigation and specifically in explaining consumer behaviour in electronic markets. Not only can it be used to characterize the user’s interactive relationship with virtual environments, but it can also have a positive and desirable impact on the individuals’ consumption experiences and also on the performance of the companies’ websites which induce flow state in their customers. The purpose of this conceptual article is to analyse in-depth the concept of flow and elucidate its relevance to the context of online consumer behaviour. It contains a comprehensive and critical analysis of the literature and highlights the potential for businesses to generate flow experiences in their online environments. It also identifies the ambiguities and inconsistencies regarding the conceptualisation and operationalisation of flow in online commercial websites. Finally, we stress the importance of conducting further research in this area, with particular focus on the role of flow within the prevailing social web context.


Flow E-commerce Internet Online consumer behavior 


  1. Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694.CrossRefGoogle Scholar
  2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–511.CrossRefGoogle Scholar
  3. Bagozzi, R. P., & Warshaw, P. R. (1990). Trying to consume. Journal of Consumer Research, 17(2), 127–141.CrossRefGoogle Scholar
  4. Bakker, A. B. (2008). The work-related flow inventory: construction and initial validation of the WOLF. Journal of Vocational Behavior, 72(3), 400–414.CrossRefGoogle Scholar
  5. Barki, H., & Hartwick, J. (1989). Rethinking the concept of user involvement. MIS Quarterly, 13(1), 53–63.CrossRefGoogle Scholar
  6. Bettman, J. R. (1979). An information processing theory of consumer choice. Massachussets: Addison-Weley.Google Scholar
  7. Bridges, E., & Florsheim, R. (2008). Hedonic and utilitarian shopping goals: The online experience. Journal of Business Research, 61(4), 309–314.CrossRefGoogle Scholar
  8. Chang, H. H., & Wang, I. C. (2008). An investigation of user communication behaviour in computer mediated environments. Computers in Human Behavior, 24(5), 2.336–2.356.CrossRefGoogle Scholar
  9. Celsi, R. L., & Olson, J. C. (1988). The role of involvement in attention and comprehension processes. Journal of Consumer Research, 15(2), 210–224 Google Scholar
  10. Chan, T. S., & Repman, J. (1999). Flow in web based instructional activity: an exploratory research project. International Journal of Educational Telecommunications, 5(3), 225–237.Google Scholar
  11. Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal Experience of Web Activities. Computers in Human Behavior, 15(5), 585–608Google Scholar
  12. Chen, L., Gillenson, M.L., & Sherrell, D. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39(8), 705–719.Google Scholar
  13. Chen, H. (2006). Flow on the net–detecting Web users’ positive affects and their flow states. Computers in Human Behavior, 22(2), 221–233.CrossRefGoogle Scholar
  14. Chen, J. (2007). Flow in games, and everything else. Communications of the ACM, 50(4), 31–34.CrossRefGoogle Scholar
  15. Chen, H., Wigand, R. T., & Nilan, M. S. (2000). Exploring web users’ optimal flow experiences. Information Technology and People, 3(4), 263–281.CrossRefGoogle Scholar
  16. Chou, T. J., & Ting, C. C. (2003). The role of flow experience in cyber-game addiction. Cyberpsychology and Behavior, 6(6), 663–675.CrossRefGoogle Scholar
  17. Chung, J., & Tang, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information and Management, 41(7), 869–881.CrossRefGoogle Scholar
  18. Clarke, S. G., & Haworth, J. T. (1994). Flow experience in the daily lives of sixth-form college students. British Journal of Psychology, 85(4), 511–523.CrossRefGoogle Scholar
  19. Cowley, B., Charles, D., Black, M., & Hickey, R. (2008). Toward an understanding of flow in video games. ACM Computers in Entertainment, 6(2), 1–27.CrossRefGoogle Scholar
  20. Coyle, J. R., & Thorson, E. (2001). The effects of progressive levels of interactivity and vividness in Web marketing sites. Journal of Advertising, 30(3), 65–77.CrossRefGoogle Scholar
  21. Csikszentmihalyi, M. (1975). Beyond boredom and anxiety (1ª ed.). San Francisco (California): Jossey-Bass.Google Scholar
  22. Csikszentmihalyi, M. (1977). Beyond boredom and anxiety (2ª ed.). San Francisco (California): Jossey-Bass.Google Scholar
  23. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Nueva York: Harper and Row.Google Scholar
  24. Csikszentmihalyi, M. (1997). Happiness and creativity. The Futurist, 31(5), 8–12.Google Scholar
  25. Csikszentmihalyi, M., & Csikszentmihalyi, I. S. (1988). Optimal Experience: Psychological studies of flow in consciousness. Cambridge (Massachusetts): Cambridge University Press.CrossRefGoogle Scholar
  26. Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56(5), 815–822.CrossRefGoogle Scholar
  27. Dailey, L. (2004). Navigational web atmospherics. Explaining the influence of restrictive navigation cues. Journal of Business Research, 57(7), 795–803.CrossRefGoogle Scholar
  28. Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.CrossRefGoogle Scholar
  29. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.CrossRefGoogle Scholar
  30. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 111–132.CrossRefGoogle Scholar
  31. Day, H. I. (1981). Advances in intrinsic motivation and aesthetics. Nueva York: Plenum press.CrossRefGoogle Scholar
  32. Delle Fave, A., & Massimini, F. (1988). Modernization and the changing contexts of flow in work and leisure. In M. Csikszentmihalyi & I. S. Csikszentmihalyi (Eds.), Optimal experience: Psychological studies of flow in consciousness. Nueva York: University Press.Google Scholar
  33. Engel, J. F., Kollat, D. T., & Blackwell, R. D. (1968). Consumer behaviour (1ª ed.). Nueva York: Holt, Rinehart & Winston.Google Scholar
  34. Ghani, J. A. (1991). Flow in human-computer interactions: Test of a model. In J. Carey (Ed.), Factors in management information systems: an organizational perspective. Norwood (Nueva Jersey): Ablex Publishing Corp.Google Scholar
  35. Ghani, J. A. (1995). Flow in human-computer interactions: Test of a model. In J. Carey (Ed.), Human factors in information systems: Emerging theoretical bases. Norwood (Nueva Jersey): Ablex Publishing Corp.Google Scholar
  36. Finneran, C. M., & Zhang, P. (2003). A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments. International Journal of Human-Computer Studies, 59(4), 475–496.Google Scholar
  37. Ghani, J. A., & Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human-computer interaction. The Journal of Psychology, 128(4), 381–391.CrossRefGoogle Scholar
  38. Guo, Y. M., & Poole, M. S. (2009). Antecedents of flow in online shopping: A test of alternative models. Information Systems Journal, 19(4), 369–390.CrossRefGoogle Scholar
  39. Havitz, M. E., & Mannell, R. C. (2005). Enduring involvement, situational. Involvement, and flow in leisure and non-leisure activities. Journal of Leisure, 37(2), 152–177.Google Scholar
  40. Held, R. M., & Durlach, N. I. (1992). Telepresence. Presence: Teleoperators and Virtual Environments, 1(1), 109–112.Google Scholar
  41. Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computermediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50–68.CrossRefGoogle Scholar
  42. Howard, J. (1989). Consumer behavior in marketing strategy. Upper Saddle River (Nueva Jersey): Prentice Hall.Google Scholar
  43. Howard, J., & Sheth, J. N. (1969). The theory of buyer behavior. Nueva York: Wiley.Google Scholar
  44. Hsu, C. L., & Lu, H. P. (2004). Why do people play online games? an extended TAM with social influences and flow experience. Information and Management, 41(7), 853–868.CrossRefGoogle Scholar
  45. Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). Flow experience and internet shopping behavior: Investigating the moderating effect of consumer characteristics. Systems Research and Behavioral Science, 29(3), 317–332.CrossRefGoogle Scholar
  46. Huang, M. H. (2003). Designing website attributes to induce experiential encounters. Computers in Human Behavior, 19(4), 425–442.CrossRefGoogle Scholar
  47. Huang, M. H. (2006). Flow, enduring, and situational involvement in the web environment: A tripartite second-order examination. Psychology and Marketing, 23(5), 383–411.CrossRefGoogle Scholar
  48. Igbaria, M., Schiffman, S. J., & Wieckowski, T. J. (1994). The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behaviour and Information Technology, 13, 349–361.CrossRefGoogle Scholar
  49. Igbaria, M., Guimaraes, T., & Davis, G. (1995). Testing the determinants of microcomputer usage via a structured equation model. Journal of Management Information Systems, 11(4), 87–114.Google Scholar
  50. Inal, Y., & Cagiltay, K. (2007). Flow experiences of children in an interactive social game environment. British Journal of Educational Technology, 38(3), 455–464.CrossRefGoogle Scholar
  51. Jiang, Z., & Benbasat, I. (2004). Virtual product experience: effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 21(3), 111–147.Google Scholar
  52. Jiang, Z., & Benbasat, I. (2005). Virtual product experience: effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 2(3), 111–147.Google Scholar
  53. Korzaan, M. L. (2003). Going with the flow: Predicting online purchase intentions. Journal of Computer Information Systems, 43(4), 25–31.Google Scholar
  54. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 3(2), 205–223.CrossRefGoogle Scholar
  55. Laurent, G., & Kapferer, J. (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22(1), 41–53.Google Scholar
  56. Laurel, B. (1990). Interface agents: Metaphors with character. In B. Laurel (Ed.), The art of human-computer interface design. Reading (Massachusetts): Addison-Wesley.Google Scholar
  57. Lee, S. M., & Chen, L. (2010). The impact of flow on online consumer behavior. Journal of Computer Information Systems, 50(4), 1–10. Google Scholar
  58. Liu, S. H., Liao, H.L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599–607. Google Scholar
  59. Liu, Z., & Liu, Y. (2009). Research on personalization e-learning system based on agent technology. Proceedings of the 3rd WSEAS International Conference on Circuits, Systems, Signal and Telecommunications. Ningbo (China).Google Scholar
  60. Luna, D., Peracchio, L. A., & de Juan, M. D. (2003). Flow in individual web sites: Model estimation and cross-cultural validation. Advances in Consumer Research, 30(1), 280–281.Google Scholar
  61. Martínez-López, F. J., Luna, P., & Martínez, F. J. (2005). Online shopping, the standard learning hierarchy, and consumers′ internet expertise. Internet Research, 15(3), 312–334.CrossRefGoogle Scholar
  62. Martínez-López, F. J., Luna, P., & Martínez, F. J. (2006). Motivations for consumption behaviours on the web: A conceptual model based on a holistic approach. International Journal of Electronic Marketing and Retailing, 1(1), 3–20.CrossRefGoogle Scholar
  63. Martínez-López, F. J., Rodríguez-Ardura, I., Gázquez-Abad, J. C., Sánchez-Franco, M., & Cabal, C. (2010). Psychological elements explaining the consumer’s adoption and use of a website recommendation system. Internet Research, 20(3), 316–341.CrossRefGoogle Scholar
  64. Martínez-López, F. J., Gázquez-Abad, J. C., Rodríguez-Ardura, I., & Cabal, C. (2011). An integrative framework on the psychological variables explaining the consumers’ use of e-commerce-based recommendation systems. In M. M. Cruz-Cunha & J. Varajao (Eds.), e-business issues, challenges and opportunities for SMEs: Driving competitiveness (pp. 350–364). Hershey: IGI Global.Google Scholar
  65. Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of Consumer Research, 31(2), 324–332.CrossRefGoogle Scholar
  66. Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217–230.CrossRefGoogle Scholar
  67. Nel, D., Niekerk, R., Berthon, J. P., & Davies, T. (1999). Going with the flow: Web sites and customer involvement. Internet Research: Electronic Networking Applications and Policy, 9(2), 109–116.CrossRefGoogle Scholar
  68. Nicosia, F. (1966). Consumer decision processes: Marketing and advertising implications. Englewood Cliffs (Nueva Jersey): Prentice Hall.Google Scholar
  69. Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42.CrossRefGoogle Scholar
  70. 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, 3(2), 3–16.Google Scholar
  71. Ornstein, R. (1977). The psychology of consciousness (2ª ed.). Nueva York: Harcourt, Brace.Google Scholar
  72. Pace, S. (2004). A grounded theory of the flow experiences of web users. International Journal of Human-Computer Studies, 60(3), 327–363.CrossRefGoogle Scholar
  73. Pearce, J. (2005). Engaging the learner: how can the flow experience support e-learning?. In Proceedings of world conference on E-Learning in corporate, government, healthcare, and higher education. Chesapeake (Virginia).Google Scholar
  74. Pilke, E. M. (2004). Flow experiences in information technology use. International Journal of Human-Computer Studies, 61(3), 347–357.Google Scholar
  75. Rathunde, K. (2003). A comparison of montessori and traditional middle schools: motivation, quality of experience, and social context. The NAMTA Journal, 28(3), 13–52.Google Scholar
  76. Rathunde, K., & Csikszetnmihalyi, M. (2005). Middle school students’ motivation and quality of experience: A comparison of Montessori and traditional school environments. American Journal of Education, 111(3), 341–371.CrossRefGoogle Scholar
  77. Reeve, M. J. (1994). Motivación y Emoción. Madrid: Mc Graw Hill.Google Scholar
  78. Rettie, R. (2001). An exploration of flow during Internet use. Internet Research: Electronic Networking Applications and Policy, 11(2), 103–113.CrossRefGoogle Scholar
  79. Richard, M. O., & Chandra, R. (2005). A model of consumer web navigational behavior: Conceptual development and application. Journal of Business Research, 58(8), 1.019–1.029.CrossRefGoogle Scholar
  80. Rodríguez-Ardura, I., & Martínez-López, F. J. (2008). Playing cat and mouse: Consumers empowerment and marketing interactions on the Internet. International Journal of Business Environment, 2(2), 201–214.CrossRefGoogle Scholar
  81. Rodríguez-Ardura, I., Martínez-López, F. J., & Luna, P. (2010). Going with the consumer towards the social web environment: a review of extant knowledge. International Journal of Electronic Marketing and Retailing, 3(4), 415–440.CrossRefGoogle Scholar
  82. Rossin, D., Ro, Y. K., Klein, B. D., & Guo, Y. M. (2009). The effects of flow on learning outcomes in an online information management course. Journal of Information Systems Education, 20(1), 87–98.Google Scholar
  83. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development and well-being. American Psychologist, 55(1), 68–78. Google Scholar
  84. Salanova, M., Bakker, A. B., & Llorens, S. (2006). Flow at work: evidence for an upward spiral of personal and organizational resources. Journal of Happiness Studies, 7(1), 1–22.CrossRefGoogle Scholar
  85. Sánchez-Franco, M. J. (2005). El comportamiento del usuario en la web: Un análisis del estado de flujo. Revista española de investigación de marketing, 9(1), 65–98.Google Scholar
  86. Sánchez-Franco, M. J., & Roldán, J. L. (2005). Web acceptance and usage model. A comparison between goal-directed and experiential web users. Internet Research, 15(1), 21–48.CrossRefGoogle Scholar
  87. Sánchez-Franco, M. J., Rondán, F. J., & Villarejo, Á. F. (2007). Un modelo empírico de adaptación y uso de la Web. Utilidad, facilidad de uso y flujo percibidos. Cuadernos de economía y dirección de la empresa, Núm., 30, 153–180.CrossRefGoogle Scholar
  88. Schifter, D. B., & Ajzen, I. (1985). Intention, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology, 49(3), 842–851.CrossRefGoogle Scholar
  89. Sénécal, S., Nantel, J., & Gharbi, J. E. (2002). The influence of flow on hedonic and utilitarian shopping values. Advances in Consumer Research, 29(1), 483–484.Google Scholar
  90. Sharafi, P., Hedman, L., & Montgomery, H. (2006). Using information technology: Engagement modes, flow experience, and personality orientations. Computers in Human Behavior, 22(5), 899–916.CrossRefGoogle Scholar
  91. Shernoff, D. J., Czikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of row theory. School Psychology Quarterly, 18(2), 158–176.CrossRefGoogle Scholar
  92. Shih, C. F. (1998). Conceptualizing consumer experiences in cyberspace. European Journal of Marketing, 32(7/8), 655–663.CrossRefGoogle Scholar
  93. Shoham, A. (2004). Flow experiences and image making: An online chat-room ethnography. Psychology and Marketing, 21(10), 855–882.CrossRefGoogle Scholar
  94. Sicilia, M., Ruiz, S., & Munuera, J. L. (2005). Effects of interactivity in a web site. The moderating effect of need for cognition. Journal of Advertising, 34(3), 31–45.CrossRefGoogle Scholar
  95. Siekpe, J. S. (2005). An examination of the multidimensionality of flow construct in a computer-mediated environment. Journal of Electronic Commerce Research, 6(1), 31–43.Google Scholar
  96. 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(3), 403–422.CrossRefGoogle Scholar
  97. Smith, D. N., & Sivakumar, K. (2004). Flow and internet shopping behaviour. A conceptual model and research propositions. Journal of Business Research, 57(10), 1.199–1.208.CrossRefGoogle Scholar
  98. Srivastava, K., Shukla, A., & Sharma, N. K. (2010). Online flow experiences: the role of need for cognition, self-efficacy, and sensation seeking tendency“. International Journal of Business Insights & Transformation, 3(2), 93–100.Google Scholar
  99. Steele, J. P., & Fullagar, C. J. (2009). Facilitators and outcomes of student engagement in a college setting. The Journal of Psychology, 143(1), 5–27.CrossRefGoogle Scholar
  100. Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73–93.CrossRefGoogle Scholar
  101. Sweetser, P., & Wyeth, P. (2005). “GameFlow: A model for evaluating player enjoyment in games. ACM Computers in Entertainment, 3(3), 1–24.CrossRefGoogle Scholar
  102. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.CrossRefGoogle Scholar
  103. Trevino, L. K., & Webster, J. (1992). Flow in computer mediated communication. Communication Research, 9(5), 539–573.CrossRefGoogle Scholar
  104. Thatcher, A., Wretschko, G., & Fridjhon, P. (2008). Online flow experiences, problematic Internet use and Internet procrastination. Computers in Human Behavior, 24(5), 2.236–2.254. Google Scholar
  105. Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.Google Scholar
  106. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.CrossRefGoogle Scholar
  107. Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: toward an integrated model. Decision Sciences, 33(2), 297–316.CrossRefGoogle Scholar
  108. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478. Google Scholar
  109. Wan, C. S., & Chiou, W. B. (2006). Psychological motives and online games addiction: A test of flow theory and humanistic needs theory for taiwanese adolescents. Cyberpsychology and Behavior, 9(3), 317–324.CrossRefGoogle Scholar
  110. Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human computer interactions. Computers in Human Behavior, 9(4), 411–426.CrossRefGoogle Scholar
  111. Woszczynskia, A. B., Roth, P. L., & Segarsc, A. H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18(4), 369–388.CrossRefGoogle Scholar
  112. Wu, G. (2000). The role of perceived interactivity in interactive ad processing. Unpublished Doctoral Dissertation. Austin (Texas): The University of Texas.Google Scholar
  113. Wu, J. J., & Chang, Y. S. (2005). Towards understanding members’ interactivity, trust, and flow in online travel community. Industrial Management and Data Systems, 105(7), 937–954.CrossRefGoogle Scholar
  114. Yu, J., Ha, I., Choi, M., & Rho, J. (2005). Extending the TAM for t-commerce. Information and Management, 42(7), 965–976.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Irene Esteban-Millat
    • 1
  • Francisco J. Martínez-López
    • 2
  • David Luna
    • 3
  • Inma Rodríguez-Ardura
    • 4
  1. 1.Open University of CataloniaBarceloneSpain
  2. 2.University of Granada; and Open University of CataloniaBarcelonaSpain
  3. 3.City University of New YorkNew YorkUSA
  4. 4.Internet Interdisciplinary InstituteOpen University of CataloniaCataloniaSpain

Personalised recommendations