Electronic Markets

, Volume 28, Issue 1, pp 111–122 | Cite as

On the way to understanding binge watching behavior: the over-estimated role of involvement

  • Jani MerikiviEmail author
  • Antti Salovaara
  • Matti Mäntymäki
  • Lilong Zhang
Research Paper


Watching television shows using online television streaming services, such as Netflix, Hulu, and Youku, has mushroomed in the recent years. Along with these services, binge watching, defined as an act of consuming more than one episode of a television show in quick succession, has become a widespread behavior. Yet, it has received very little attention from academics. This study conceptualizes binge watching and examines its effect on satisfaction. We present binge watching as a two-dimensional system usage concept, including behavioral and cognitive involvement components. Using these components, we then study their impact on user satisfaction. We test our explorative approach with a sample of 227 respondents using Partial Least Squares modeling. The results support heterogeneous view of online television streaming service use. That is, involvement with binge watching is over-estimated and does not define user satisfaction. Our study contributes to online consumer behavior research as well as the information systems literature by investigating binge watching as a distinct form of technology use.


Binge watching online television service satisfaction system usage involvement 

JEL classification



  1. Abbott, A. (2014). The problem of excess. Sociological Theory, 32(1), 1–26.CrossRefGoogle Scholar
  2. 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
  3. Arris Investors. (2015). Press release. Retrieved from
  4. Baker, A. E. (1854). Glossary of Northamptonshire words and phrases: With examples of their colloquial use, and illustrations from various authors: To which are added, the customs of the county. London: J.R. Smith.Google Scholar
  5. Barki, H., Titah, R., & Boffo, C. (2007). Information system use-related activity: An expanded behavioral conceptualization of individual-level information system use. Information Systems Research, 18(2), 173–192.CrossRefGoogle Scholar
  6. Barkin, S. R., & Dickson, G. W. (1977). An investigation of information system utilization. Information Management, 1(1), 35–45.CrossRefGoogle Scholar
  7. Berridge, V., Herring, R., & Thom, B. (2009). Second opinions on binge drinking: A confused concept and its contemporary history. Social History of Medicine, 22(3), 597–607.CrossRefGoogle Scholar
  8. Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.CrossRefGoogle Scholar
  9. Bhattacherjee, A. (2001b). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370.CrossRefGoogle Scholar
  10. Black, D. W. (2007). A review of compulsive buying disorder. World Psychiatry, 6(1), 14–18.Google Scholar
  11. Bokhari, R. H. (2005). The relationship between system usage and user satisfaction: A meta-analysis. Journal of Enterprise Information Management, 18(2), 211–234.CrossRefGoogle Scholar
  12. Burns, J. J., & Anderson, D. R. (1991). Cognition and watching television. In D. E. Tupper & K. D. Cicerone (Eds.), The neuropsychology of everyday life: Issues in development and rehabilitation (pp. 93–108). Boston: Springer.CrossRefGoogle Scholar
  13. Burton-Jones, A. (2005). New perspectives on the system usage construct. (Unpublished Doctoral dissertation). Department of Computer Information System, Georgia State University, Atlanta, GA.Google Scholar
  14. Burton-Jones, A., & Straub, D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246.CrossRefGoogle Scholar
  15. Chiu, C., Chiu, C., & Chang, H. (2007). Examining the integrated influence of fairness and quality on learners' satisfaction and web-based learning continuance intention. Information Systems Journal, 17(3), 271–287.CrossRefGoogle Scholar
  16. Csikszentmihalyi, M. (1991). Flow, the psychology of optimal experience. New York: HarperPerennial.Google Scholar
  17. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95.CrossRefGoogle Scholar
  18. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.CrossRefGoogle Scholar
  19. Doll, W. J., & Torkzadeh, G. (1998). Developing a multidimensional measure of system-use in an organizational context. Information Management, 33(4), 171–185.CrossRefGoogle Scholar
  20. Elie-Dit-Cosaque, C. M., & Straub, D. W. (2011). Opening the black box of system usage: User adaptation to disruptive IT. European Journal of Information Systems, 20(5), 589–607.CrossRefGoogle Scholar
  21. Faber, R. J., Christenson, G. A., De Zwaan, M., & Mitchell, J. (1995). Two forms of compulsive consumption: Comorbidity of compulsive buying and binge eating. Journal of Consumer Research, 22(3), 296–304.CrossRefGoogle Scholar
  22. Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consistency. In L. Berkowitz (Ed.), Advances in experimental social psychology (6) (pp. 161–202). New York: Academic Press.Google Scholar
  23. Folkes, V. S. (1984). Consumer reactions to product failure: An attributional approach. Journal of Consumer Research, 10(4), 398–409.CrossRefGoogle Scholar
  24. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar
  25. Fowler Jr., F. J. (1995). Improving survey questions: Design and evaluation. Thousand Oaks: Sage Publications.Google Scholar
  26. Glebatis Perks, L. (2014). Media marathoning: Immersions in morality. New York: Lexington Books.Google Scholar
  27. Guimaraes, T., Yoon, Y., & Clevenson, A. B. (1996). Factors important to expert systems success a field test. Information Management, 30(3), 119–130.CrossRefGoogle Scholar
  28. Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.CrossRefGoogle Scholar
  29. Harris Interactive. (2013). Americans taking advantage of ability to watch TV on their own schedule. Retrieved from
  30. Hornshaw, P., & Rosenberg, S. (2017). TV shows you should binge-watch right now, from 'OITNB' to 'better caul Saul'. Retrieved from
  31. Hu, T., & Zhang, P. (2016). Social media usage as a formative construct: Conceptualization, validation, and implication. Journal of Information Technology Management, 27(4), 151–168.Google Scholar
  32. Hunt, H. K. (1977). Conceptualization and measurement of consumer satisfaction and dissatisfaction. In H. K. Hunt (Ed.), CS/D - overview and future research directions (pp. 455–488). Cambridge: Marketing Science Institute.Google Scholar
  33. Hunt, D., Geiger-Oneto, S., & Varca, P. E. (2012). Satisfaction in the context of customer co-production: A behavioral involvement perspective. Journal of Consumer Behaviour, 11(5), 347–356.CrossRefGoogle Scholar
  34. Iivari, J. (2005). An empirical test of the DeLone-McLean model of information system success. ACM SIGMIS Database, 36(2), 8–27.CrossRefGoogle Scholar
  35. Jellinek, E. M. (1952). Phases of alcohol addiction. Quarterly Journal of Studies on Alcohol, 13(4), 673–684.CrossRefGoogle Scholar
  36. Jenner, M. (2016). Is this TVIV? On Netflix, TVIII and binge-watching. New Media & Society, 18(2), 257–273.CrossRefGoogle Scholar
  37. Jenner, M. (2017). Binge-watching: Video on demand, quality TV and mainstreaming fandom. International Journal of Cultural Studies, 20(3), 304–320.CrossRefGoogle Scholar
  38. Jurgensen, J. (2012). Binge viewing: TV's lost weekends. Retrieved from
  39. Karmakar, M., Sloan Kruger, J., Elhai, J., & Kramer, A. (2015). Viewing patterns and addiction to television among adults who self-identify as binge-watchers. APHA Annual Meeting & Expo. Retrieved from
  40. Kellett, S., & Bolton, J. V. (2009). Compulsive buying: A cognitive–behavioural model. Clinical Psychology & Psychotherapy, 16(2), 83–99.CrossRefGoogle Scholar
  41. Khalifa, M., & Liu, V. (2004). The state of research on information system satisfaction. Journal of Information Technology, Theory and Applications, 5(4), 37–49.Google Scholar
  42. Locke, E. A. (1967). Relationship of success and expectation to affect on goal-seeking tasks. Journal of Personality and Social Psychology, 7(2), 125–134.CrossRefGoogle Scholar
  43. Mathes, W. F., Brownley, K. A., Mo, X., & Bulik, C. M. (2009). The biology of binge eating. Appetite, 52(3), 545–553.CrossRefGoogle Scholar
  44. Matrix, S. (2014). The Netflix effect: Teens, binge watching, and on-demand digital media trends. Jeunesse: Young People, Texts, Cultures, 6(1), 119–138.CrossRefGoogle Scholar
  45. McGill, A. L., & Iacobucci, D. (1992). The role of post-experience comparison standards in the evaluation of unfamiliar services. Advances in Consumer Research, 19, 570–578.Google Scholar
  46. McIlwraith, R. D. (1998). "I'm addicted to television": The personality, imagination, and TV watching patterns of self-identified TV addicts. Journal of Broadcasting & Electronic Media, 42(3), 371–386.CrossRefGoogle Scholar
  47. Netflix. (2013). Netflix declares binge watching is the new normal. Retrieved from
  48. Nielsen. (2013). "Binging" is the new viewing for over-the-top streamers. Retrieved from
  49. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469.CrossRefGoogle Scholar
  50. Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418–430.CrossRefGoogle Scholar
  51. Oliver, R. L., & Gerald, L. (1981). Effect of satisfaction and its antecedents on consumer preference and intention. Advances in Consumer Research, 8(1), 88–93.Google Scholar
  52. Patterson, P., Yu, T., & de Ruyter, K. (2006). Understanding customer engagement in services. Proceedings of ANZMAC 2006 Conference: Advancing Theory, Maintaining Relevance, Brisbane, Australia.Google Scholar
  53. Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236–263.CrossRefGoogle Scholar
  54. Pittman, M., & Sheehan, K. (2015). Sprinting a media marathon: Uses and gratifications of binge-watching television through Netflix. First Monday, 20(10). Retrieved from
  55. Podsakoff, P. M., MacKenzie, S. B., Lee, J., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.CrossRefGoogle Scholar
  56. J.D. Power. (2016). Streaming video customer satisfaction highest when paired with pay TV subscription, J.D. power finds. Retrieved from
  57. Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50–69.CrossRefGoogle Scholar
  58. Ringle, C. M., Wende, S. & Will, S. (2005). SmartPLS 2.0 (M3) beta. Retrieved from
  59. Rothbard, N. P. (2001). Enriching or depleting? The dynamics of engagement in work and family roles. Administrative Science Quarterly, 46(4), 655–684.CrossRefGoogle Scholar
  60. Salovaara, A., Öörni, A., & Sokura, B. (2013). Heterogeneous use for multiple purposes: A point of concern to IS use models' validity. In Proceedings of the 34 Th International Conference on Information Systems (ICIS 2013). Milano: Italy.Google Scholar
  61. Schweidel, D. A., & Moe, W. W. (2016). Binge watching and advertising. Journal of Marketing, 80(September), 1-19.CrossRefGoogle Scholar
  62. Seddon, P. (1997). A respecification and extension of the DeLone and McLean. Information Systems Research, 8(3), 240–253.CrossRefGoogle Scholar
  63. Spangler, T. (2015). Netflix far outstrips rivals on hours viewed, satisfaction, survey: Retrieved from
  64. Straub, D., Limayem, M., & Evaristo-Karahanna, E. (1995). Measuring system usage: Implications for IS theory testing. Management Science, 41(8), 1328–1343.CrossRefGoogle Scholar
  65. Stunkard, A. J. (1959). Eating patterns and obesity. Psychiatric Quarterly, 33(2), 284–295.CrossRefGoogle Scholar
  66. Subramani, M. (2004). How do suppliers benefit from information technology use in supply chain relationships? MIS Quarterly, 28(1), 45–73.CrossRefGoogle Scholar
  67. Sung, Y. H., Kang, E. Y., & Lee, W. (2015). A bad habit for your health? An exploration of psychological factors for binge-watching behavior. 65 th ICA Annual Conference, Puerto Rico.Google Scholar
  68. Trouleau, W., Ashkan, A., Ding, W., & Eriksson, B. (2016). Just one more: Modeling binge watching behavior. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 1224.Google Scholar
  69. Walton-Pattison, E., Dombrowski, S. U., & Presseau, J. (2016). 'Just one more episode': Frequency and theoretical correlates of television binge watching. Journal of Health Psychology, xx(xx), xx–xx.Google Scholar
  70. Wechsler, H., Davenport, A., Dowdall, G., Moeykens, B., & Castillo, S. (1994). Health and behavioral consequences of binge drinking in college: A national survey of students at 140 campuses. The Journal of the American Medical Association, 272(21), 1672–1677.CrossRefGoogle Scholar
  71. Westbrook, R. A., & Reilly, M. D. (1983). Value-percept disparity: An alternative to the disconfirmation of expectations theory of consumer satisfaction. Advances in Consumer Research, 10(1), 256–261.Google Scholar
  72. Withington, P. (2011). Intoxicants and society in early modern England. The Historical Journal, 54(3), 631–657.CrossRefGoogle Scholar
  73. ZenithOptimedia. (2014). China media & digital scene 2014. Retrieved from

Copyright information

© Institute of Applied Informatics at University of Leipzig 2017

Authors and Affiliations

  1. 1.National Research Center of Cultural StudiesCentral China Normal UniversityWuhan, HubeiChina
  2. 2.Department of Information and Service EconomyAalto University, School of Business00100 HelsinkiFinland

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