Skip to main content
SpringerLink
Log in

Procrastinators’ online experience and purchase behavior

  • Original Empirical Research
  • Published:
Journal of the Academy of Marketing Science Aims and scope Submit manuscript

Abstract

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.

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
Fig. 3

Similar content being viewed by others

References

  • Adler, Emily (2014). Social media engagement: The surprising facts about how much time people spend on the major social networks. http://www.businessinsider.com/social-media-engagement-statistics-2013-12. Accessed 20 Jan 2015.

  • Ainslie, G. (1975). Specious reward: a behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82(4), 463–496.

    Article  Google Scholar 

  • Pew Internet & American Life Project (2010). The percentage of Internet users who have “ever done” an online activity. Retrieved February 10, 2011 from http://pewinternet.org/Data-Tools/Download-Data/Trend-Data.aspx.

  • Andrade, E. B. (2005). Behavioural consequences of affect: combining evaluative and regulatory mechanisms. Journal of Consumer Research, 32(12), 355–362.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.

    Article  Google Scholar 

  • Bagozzi, R., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34.

    Article  Google Scholar 

  • Beatty, S. E., & Ferrell, M. E. (1998). Impulse buying: modeling its precursors. Journal of Retailing, 74(2), 169–191.

    Article  Google Scholar 

  • Bridges, E., & Florsheim, R. (2008). Hedonic and utilitarian shopping goals: the online experience. Journal of Business Research, 61(4), 309–314.

    Article  Google Scholar 

  • Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.

    Google Scholar 

  • Bui, M., Krishen, A. S., & Bates, K. (2011). Modelling regret effects on consumer post-purchase decisions. European Journal of Marketing, 45(7), 1068–1090.

    Article  Google Scholar 

  • Chen, H. (2006). Flow on the net–detecting web users’ positive affects and their flow states. Computers in Human Behavior, 22(2), 221–233.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

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

    Google Scholar 

  • Dailey, L. (2004). Navigational web atmospherics: explaining the influence of restrictive navigation cues. Journal of Business Research, 57(7), 795–803.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • eMarketer (2014). Mobile Continues to Steal Share of US Adults’ Daily Time Spent with Media, http://www.emarketer.com/Article/Mobile-Continues-Steal-Share-of-US-Adults-Daily-Time-Spent-with-Media/1010782. Accessed 20 Jan 2015.

  • Ferrari, J. R., Johnson, J., & McCown, W. G. (1995). Procrastination and task avoidance: Theory, research, and treatment. New York: Plenum Press.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Garg, N., Wansink, B., & Inman, J. J. (2007). The influence of incidental affect on consumers’ food intake. Journal of Marketing, 71(1), 194–206.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Griffiths, M. (2003). Internet gambling: issues, concerns, and recommendations. CyberPsychology and Behavior, 6(6), 557–568.

    Article  Google Scholar 

  • Hoffman, D. L., & Novak, T. P. (1996a). A new market paradigm for electronic commerce. The Information Society, 13(1), 43–54.

    Google Scholar 

  • Hoffman, D. L., & Novak, T. P. (1996b). Marketing in hypermedia computer-mediated environments: conceptual foundations. Journal of Marketing, 60(7), 50–68.

    Article  Google Scholar 

  • Huang, M. (2003). Designing website attributes to induce experiential encounters. Computers in Human Behavior, 19(4), 425–442.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Kang, M. (2009). Retail therapy: A qualitative investigation of scale development. unpublished doctoral dissertation, University of Minnesota, [http://conservancy.umn.edu/bitstream/52142/1/Kang_umn_0130E_10394.pdf].

  • Korzaan, M. L. (2003). Going with the flow: predicting online purchase intentions. Journal of Computer Information Systems, 43(4), 25–31.

    Google Scholar 

  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–220.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Lavoie, J. A. A., & Pychyl, T. A. (2001). Cyberslacking and the procrastination superhighway. Social Science Computer Review, 19(4), 431–444.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • Mann, L. (1982). Decision making questionnaires I and II. Unpublished scales, Flinders University of South Australia, Flinders, South Australia.

  • MarketingCharts (2013). Millenials up their time online, http://www.marketingcharts.com/online/millennials-up-their-time-online-26405/. Accessed 13 Apr 2015.

  • Mathwick, C., & Rigdon, E. (2004). Play, flow, and the online search experience. Journal of Consumer Research, 31(2), 324–332.

    Article  Google Scholar 

  • Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge: M.I.T. Press.

    Google Scholar 

  • Millward Brown Digital (2015). Getting audiences right, http://www.millwardbrown.com/global-navigation/news/press-releases/full-release/2015/02/06/generations-divided-on-device-preferences. Accessed 4 Apr 2015.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  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(1–2), 3–16.

    Article  Google Scholar 

  • O’Guinn, T. C., & Faber, R. J. (1989). Compulsive buying: a phenomenological exploration. Journal of Consumer Research, 16(2), 147–157.

    Article  Google Scholar 

  • O’Cass, A., & Carlson, J. (2010). Examining the effects of website-induced flow in professional sporting team websites. Internet Research, 20(2), 115–134.

    Article  Google Scholar 

  • Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on amazon mechanical turk. Judgment and Decision Making, 5(5), 411–419.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Perreault, W. D., Jr., & Leigh, L. E. (1989). Reliability of nominal data based on qualitative judgments. Journal of Marketing Research, 26(2), 135–148.

    Article  Google Scholar 

  • Pew Research Center (2015). Internet user demographics, http://www.pewinternet.org/data-trend/internet-use/latest-stats/. Accessed 13 Apr 2015.

  • 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 

  • Richard, M., & Chandra, R. (2005). A model of consumer web navigational behavior: conceptual development and application. Journal of Business Research, 58(8), 1019–1029.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

  • Scarpi, D. (2012). Work and fun on the internet: the effects of utilitarianism and hedonism online. Journal of Interactive Marketing, 26(1), 53–67.

    Article  Google Scholar 

  • Schor, J. B. (1998). The overspent american: Why we want what we don’t need. New York: Harper Perennial.

    Google Scholar 

  • 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 

  • 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 

  • 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.

    Article  Google Scholar 

  • Silver, M., & Sabini, J. (1981). Procrastinating. Journal for the Theory of Social Behaviour, 11(2), 207–221.

    Article  Google Scholar 

  • Spada, M. M., Hiou, K., & Nikcevic, A. V. (2006). Metacognitions, emotions, and procrastination. Journal of Cognitive Psychotherapy, 20(3), 319–326.

    Article  Google Scholar 

  • Srinivasan, R. (2014), (2014), “Online Social Media and Networks: Impact on Marketing Practice,” https://www.ama.org/publications/E-publications/Pages/ama-journal-reader-july-14-social-media.aspx. Accessed 20 Jan 2015.

  • Steel, P. (2007). The nature of procrastination: a meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65–94.

    Article  Google Scholar 

  • Thatcher, A., Wretschko, G., & Fridjhon, P. (2008). Online flow experiences, problematic internet use and internet procrastination. Computers in Human Behavior, 24(5), 2236–2254.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Umeh, K., & Omari-Asor, L. (2011). Emotional vulnerability and coping styles for resolving decisional conflict. The Journal of Psychology, 145(4), 297–312.

    Article  Google Scholar 

  • Underhill, P. (1999). Why we buy: The science of shopping. New York: Simon & Schuster.

    Google Scholar 

  • van Eerde, W. (2003). A meta-analytically derived nomological network of procrastination. Personality and Individual Differences, 35, 1401–1418.

    Article  Google Scholar 

  • Wang, L. C., Baker, J., Wagner, J., & Wakefield, K. (2007). Can a retail website be social? Journal of Marketing, 71(3), 143–157.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Management and Marketing Department, College of Business and Management, Northeastern Illinois University, 5500 North St. Louis Avenue, Chicago, IL, 60625, USA

    Shabnam H. A. Zanjani

  2. Marketing Department, Isenberg School of Management, University of Massachusetts Amherst, Amherst, MA, 01003, USA

    George R. Milne & Elizabeth G. Miller

Authors
  1. Shabnam H. A. Zanjani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. George R. Milne
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elizabeth G. Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shabnam H. A. Zanjani.

Appendix

Appendix

Measures

Trait Decisional Procrastination (Mann 1982)

(5-Point, 1 = not like me, 5 = just like me)

People may use the following statements to describe themselves. Decide how well each of the statements characterizes you:

  1. 1.

    I waste a lot of time on trivial matters before getting to the final decision.

  2. 2.

    Even after I make a decision I delay acting upon it.

  3. 3.

    I don’t make decisions unless I really have to. (dropped after convergent validity test)

  4. 4.

    I delay making decisions until it’s too late.

  5. 5.

    I put off making decisions.

Online Procrastination (Thatcher et al. 2008)

(5-point, 1 = strongly disagree, 5 = strongly agree)

Consider your experience with the Web. Please rate the degree you agree with each of the following statements:

  1. 1.

    When I am online I don’t think about my responsibilities.

  2. 2.

    When I have nothing better to do, I go online. (dropped after convergent validity test)

  3. 3.

    I find that I go online more when I have something else I am supposed to do.

  4. 4.

    When I am online, I don’t need to think about offline problems. (dropped after convergent validity test)

  5. 5.

    I sometimes use the Internet to procrastinate.

  6. 6.

    I often use the Internet to avoid doing unpleasant things.

  7. 7.

    Using the Internet is a way to forget about the things I must do but don’t really want to do.

Online Shopping Behavior (Bridges and Florsheim 2008; Seock and Bailey 2008)

  1. 1.

    How often do you purchase online?

  2. 2.

    How frequently over the past 12 months you participated in online shopping?

  3. 3.

    How frequently over the last 3 years you have purchased a product or service online?

Online Flow Experience (Novak et al. 2000)

Instructions: The word “flow” is used to describe a state of mind sometimes experienced by people who are deeply involved in some activity. One example of flow is the case where a professional athlete is playing exceptionally well and achieves a state of mind where nothing else matters but the game; he or she is completely and totally immersed in it. The experience is not exclusive to athletics: Many people report this state of mind when playing games, engaging in hobbies, or working. Activities that lead to flow completely captivate a person for some period of time. When one is in flow, time may seem to stand still, and nothing else seems to matter. Flow may not last for a long time on any particular occasion, but it may come and go over time. Flow has been described as an intrinsically enjoyable experience. Thinking about your own use of the Web:

  1. 1.

    In general, how frequently would you say you have experienced “flow” when you use the Web? (5-Point, 1 = never, 5 = very often)

  2. 2.

    Most of the time I use the Web I feel that I am in flow (5-Point, 1 = strongly disagree, 5 = strongly agree)

*One additional item was dropped due to low factor loading.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zanjani, S.H.A., Milne, G.R. & Miller, E.G. Procrastinators’ online experience and purchase behavior. J. of the Acad. Mark. Sci. 44, 568–585 (2016). https://doi.org/10.1007/s11747-015-0458-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11747-015-0458-1

Keywords

Search

Navigation