Journal of the Academy of Marketing Science

, Volume 44, Issue 5, pp 568–585 | Cite as

Procrastinators’ online experience and purchase behavior

  • Shabnam H. A. ZanjaniEmail author
  • George R. Milne
  • Elizabeth G. Miller
Original Empirical Research


This paper seeks to understand how marketers might capitalize on consumers’ increasing time spent online and convert online procrastination tendencies into purchase behavior. More specifically, the authors explore whether the propensity to use the Internet to avoid work tasks (online procrastination) leads to purchase behavior, and if so, what the mechanism underlying such an effect might be. Through two studies, the authors find that online procrastination positively impacts purchase, which in turn is indirectly affected by the consumers’ propensity to delay their decisions. The authors further find different likelihoods of purchase based on degrees of tendency to delay decisions, online users’ age, and type of online activities. Implications of these findings for informing managers about the ways to increase purchases for decisive and indecisive consumers who waste time online and raising online procrastinators’ awareness about their vulnerability to marketers are discussed.


Procrastination Flow Internet Indecision Purchase 


  1. Adler, Emily (2014). Social media engagement: The surprising facts about how much time people spend on the major social networks. Accessed 20 Jan 2015.
  2. Ainslie, G. (1975). Specious reward: a behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82(4), 463–496.CrossRefGoogle Scholar
  3. Pew Internet & American Life Project (2010). The percentage of Internet users who have “ever done” an online activity. Retrieved February 10, 2011 from
  4. Andrade, E. B. (2005). Behavioural consequences of affect: combining evaluative and regulatory mechanisms. Journal of Consumer Research, 32(12), 355–362.CrossRefGoogle Scholar
  5. Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656.CrossRefGoogle Scholar
  6. Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.CrossRefGoogle Scholar
  7. Bagozzi, R., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34.CrossRefGoogle Scholar
  8. Beatty, S. E., & Ferrell, M. E. (1998). Impulse buying: modeling its precursors. Journal of Retailing, 74(2), 169–191.CrossRefGoogle Scholar
  9. Bridges, E., & Florsheim, R. (2008). Hedonic and utilitarian shopping goals: the online experience. Journal of Business Research, 61(4), 309–314.CrossRefGoogle Scholar
  10. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.Google Scholar
  11. Bui, M., Krishen, A. S., & Bates, K. (2011). Modelling regret effects on consumer post-purchase decisions. European Journal of Marketing, 45(7), 1068–1090.CrossRefGoogle Scholar
  12. 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
  13. Choi, J. N., & Moran, S. V. (2009). Why not procrastinate? Development and validation of a new active procrastination scale. Journal of Social Psychology, 149(2), 195–212.CrossRefGoogle Scholar
  14. Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass Publishers.Google Scholar
  15. Dailey, L. (2004). Navigational web atmospherics: explaining the influence of restrictive navigation cues. Journal of Business Research, 57(7), 795–803.CrossRefGoogle Scholar
  16. Dholakia, R. R., & Zhao, M. (2009). Retail website interactivity: how does it influence customer satisfaction and behavioural intentions? International Journal of Retail & Distribution Management, 37(10), 821–838.CrossRefGoogle Scholar
  17. eMarketer (2014). Mobile Continues to Steal Share of US Adults’ Daily Time Spent with Media, Accessed 20 Jan 2015.
  18. Ferrari, J. R., Johnson, J., & McCown, W. G. (1995). Procrastination and task avoidance: Theory, research, and treatment. New York: Plenum Press.CrossRefGoogle Scholar
  19. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research, 18(3), 382–388.CrossRefGoogle Scholar
  20. Garg, N., Wansink, B., & Inman, J. J. (2007). The influence of incidental affect on consumers’ food intake. Journal of Marketing, 71(1), 194–206.CrossRefGoogle Scholar
  21. Ghani, J. A., & Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human-computer interaction. Journal of Psychology, 128(4), 381–391.CrossRefGoogle Scholar
  22. Goodman, J. K., Cryder, C. E., & Cheema, A. (2013). Data collection in a flat world: the strengths and weaknesses of mechanical turk samples. Journal of Behavioral Decision Making, 26(3), 213–224.CrossRefGoogle Scholar
  23. Griffiths, M. (2003). Internet gambling: issues, concerns, and recommendations. CyberPsychology and Behavior, 6(6), 557–568.CrossRefGoogle Scholar
  24. Hoffman, D. L., & Novak, T. P. (1996a). A new market paradigm for electronic commerce. The Information Society, 13(1), 43–54.Google Scholar
  25. Hoffman, D. L., & Novak, T. P. (1996b). Marketing in hypermedia computer-mediated environments: conceptual foundations. Journal of Marketing, 60(7), 50–68.CrossRefGoogle Scholar
  26. Huang, M. (2003). Designing website attributes to induce experiential encounters. Computers in Human Behavior, 19(4), 425–442.CrossRefGoogle Scholar
  27. Huang, L., Hsieh, Y., & Wu, Y. J. (2014). Gratifications and social network service usage: the mediating role of online experience. Information and Management, 51(6), 774–782.CrossRefGoogle Scholar
  28. Kang, M. (2009). Retail therapy: A qualitative investigation of scale development. unpublished doctoral dissertation, University of Minnesota, [].
  29. Korzaan, M. L. (2003). Going with the flow: predicting online purchase intentions. Journal of Computer Information Systems, 43(4), 25–31.Google Scholar
  30. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–220.CrossRefGoogle Scholar
  31. Krishen, A. S., Bui, M., & Peter, P. (2010). Retail kiosks: how regret and variety influence consumption. International Journal of Retail & Distribution Management, 38(3), 173–189.CrossRefGoogle Scholar
  32. Kukar-Kinney, M., & Close, A. G. (2010). The determinants of consumers’ online shopping cart abandonment. Journal of the Academy of Marketing Science, 38(2), 240–250.CrossRefGoogle Scholar
  33. Lavoie, J. A. A., & Pychyl, T. A. (2001). Cyberslacking and the procrastination superhighway. Social Science Computer Review, 19(4), 431–444.CrossRefGoogle Scholar
  34. 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
  35. Leung, L. (2004). Net-generation attributes and seductive properties of the internet as predictors of online activities and internet addiction. CyberPsychology and Behavior, 7(3), 333–348.CrossRefGoogle Scholar
  36. Luna, D., Peracchio, L. A., & de Juan, M. D. (2002). Cross-cultural and cognitive aspects of web site navigation. Journal of the Academy of Marketing Science, 30(4), 397–410.CrossRefGoogle Scholar
  37. 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, 280–281.Google Scholar
  38. Mann, L. (1982). Decision making questionnaires I and II. Unpublished scales, Flinders University of South Australia, Flinders, South Australia.Google Scholar
  39. MarketingCharts (2013). Millenials up their time online, Accessed 13 Apr 2015.
  40. Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of Consumer Research, 31(2), 324–332.CrossRefGoogle Scholar
  41. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge: M.I.T. Press.Google Scholar
  42. Noort, G. V., Voorveld, H. A. M., & Reijmersdal, E. A. V. (2012). Interactivity in brand web sites: cognitive, affective, and behavioral responses explained by consumers’ online flow experience. Journal of Interactive Marketing, 26(4), 223–234.CrossRefGoogle Scholar
  43. Novak, T. P., Hoffman, D. L., & Yung, Y. (2000). Measuring the customer experience in online environments: a structural modeling approach. Marketing Science, 19(1), 22–24.CrossRefGoogle Scholar
  44. 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(1–2), 3–16.CrossRefGoogle Scholar
  45. O’Guinn, T. C., & Faber, R. J. (1989). Compulsive buying: a phenomenological exploration. Journal of Consumer Research, 16(2), 147–157.CrossRefGoogle Scholar
  46. O’Cass, A., & Carlson, J. (2010). Examining the effects of website-induced flow in professional sporting team websites. Internet Research, 20(2), 115–134.CrossRefGoogle Scholar
  47. Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on amazon mechanical turk. Judgment and Decision Making, 5(5), 411–419.Google Scholar
  48. Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of website characteristics on a consumer’s urge to buy impulsively. Information Systems Research, 20(1), 60–78.CrossRefGoogle Scholar
  49. Perreault, W. D., Jr., & Leigh, L. E. (1989). Reliability of nominal data based on qualitative judgments. Journal of Marketing Research, 26(2), 135–148.CrossRefGoogle Scholar
  50. Pew Research Center (2015). Internet user demographics, Accessed 13 Apr 2015.
  51. Pychyl, T. A., Lee, J. M., Thibodeau, R., & Blunt, A. (2000). Five days of emotion: an experience sampling study of undergraduate student procrastination. Journal of Social Behavior and Personality, 15(5), 239–254.Google Scholar
  52. Richard, M., & Chandra, R. (2005). A model of consumer web navigational behavior: conceptual development and application. Journal of Business Research, 58(8), 1019–1029.CrossRefGoogle Scholar
  53. Rodgers, S., Wang, Y., Rettie, R., & Alpert, F. (2007). The web motivation inventory: replication, extension and application to internet advertising. International Journal of Advertising, 26(4), 447–476.Google Scholar
  54. Sanchez-Franco, M. J. (2006). Exploring the influence of gender on web usage via partial least squares. Behavior and Information Technology, 25(1), 19–36.CrossRefGoogle Scholar
  55. Scarpi, D. (2012). Work and fun on the internet: the effects of utilitarianism and hedonism online. Journal of Interactive Marketing, 26(1), 53–67.CrossRefGoogle Scholar
  56. Schor, J. B. (1998). The overspent american: Why we want what we don’t need. New York: Harper Perennial.Google Scholar
  57. Senecal, C., Lavoie, K., & Koestner, R. (1997). Trait and situational factors in procrastination: an interactional model. Journal of Social Behavior and Personality, 12(4), 889–903.Google Scholar
  58. Senecal, S., Gharbi, J., & Nantel, J. (2002). The influence of flow on hedonic and utilitarian shopping values. Advances in Consumer Research, 29, 483–84.Google Scholar
  59. Seock, Y., & Bailey, L. R. (2008). The influence of college students’ shopping orientations and gender differences on online information searches and purchase behaviours. International Journal of Consumer Studies, 32(2), 113–121.CrossRefGoogle Scholar
  60. Silver, M., & Sabini, J. (1981). Procrastinating. Journal for the Theory of Social Behaviour, 11(2), 207–221.CrossRefGoogle Scholar
  61. Spada, M. M., Hiou, K., & Nikcevic, A. V. (2006). Metacognitions, emotions, and procrastination. Journal of Cognitive Psychotherapy, 20(3), 319–326.CrossRefGoogle Scholar
  62. Srinivasan, R. (2014), (2014), “Online Social Media and Networks: Impact on Marketing Practice,” Accessed 20 Jan 2015.
  63. Steel, P. (2007). The nature of procrastination: a meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94.CrossRefGoogle Scholar
  64. Thatcher, A., Wretschko, G., & Fridjhon, P. (2008). Online flow experiences, problematic internet use and internet procrastination. Computers in Human Behavior, 24(5), 2236–2254.CrossRefGoogle Scholar
  65. Thayer, R. E., Newman, J. R., & McClain, T. M. (1994). Self-regulation of mood: strategies for changing a bad mood, raising energy, and reducing tension. Journal of Personality and Social Psychology, 67(5), 910–925.CrossRefGoogle Scholar
  66. Umeh, K., & Omari-Asor, L. (2011). Emotional vulnerability and coping styles for resolving decisional conflict. The Journal of Psychology, 145(4), 297–312.CrossRefGoogle Scholar
  67. Underhill, P. (1999). Why we buy: The science of shopping. New York: Simon & Schuster.Google Scholar
  68. van Eerde, W. (2003). A meta-analytically derived nomological network of procrastination. Personality and Individual Differences, 35, 1401–1418.CrossRefGoogle Scholar
  69. Wang, L. C., Baker, J., Wagner, J., & Wakefield, K. (2007). Can a retail website be social? Journal of Marketing, 71(3), 143–157.CrossRefGoogle Scholar
  70. Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: myths and truths about mediation analysis. Journal of Consumer Research, 37(08/01), 197–206.CrossRefGoogle Scholar

Copyright information

© Academy of Marketing Science 2015

Authors and Affiliations

  • Shabnam H. A. Zanjani
    • 1
    Email author
  • George R. Milne
    • 2
  • Elizabeth G. Miller
    • 2
  1. 1.Management and Marketing Department, College of Business and ManagementNortheastern Illinois UniversityChicagoUSA
  2. 2.Marketing Department, Isenberg School of ManagementUniversity of Massachusetts AmherstAmherstUSA

Personalised recommendations