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Extremely Frequent Behavior in Consumer Research: Theory and Empirical Evidence for Chronic Casino Gambling

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Abstract

The present study informs understanding of customer segmentation strategies by extending Twedt’s heavy-half propositions to include a segment of users that represent less than 2% of all households—consumers demonstrating extremely frequent behavior (EFB). Extremely frequent behavior (EFB) theory provides testable propositions relating to the observation that few (2%) consumers in many product and service categories constitute more than 25% of the frequency of product or service use. Using casino gambling as an example for testing EFB theory, an analysis of national survey data shows that extremely frequent casino gamblers do exist and that less than 2% of all casino gamblers are responsible for nearly 25% of all casino gambling usage. Approximately 14% of extremely frequent casino users have very low-household income, suggesting somewhat paradoxical consumption patterns (where do very low-income users find the money to gamble so frequently?). Understanding the differences light, heavy, and extreme users and non-users can help marketers and policymakers identify and exploit “blue ocean” opportunities (Kim and Mauborgne, Blue ocean strategy, Harvard Business School Press, Boston, 2005), for example, creating effective strategies to convert extreme users into non-users or non-users into new users.

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References

  • American Psychiatric Association. (1985). Diagnostic and statistical manual of mental disorders. Washington, DC: American Psychiatric Association.

    Google Scholar 

  • Armstrong, J. S., & Andress, J. G. (1970). Exploratory analysis of marketing data: Tree vs. regression. Journal of Marketing Research, 7(4), 487–492.

    Article  Google Scholar 

  • Barton, A. H. (1955). The concept of property-space in social research. In P. F. Lazarsfeld & M. Rosenberg (Eds.), Language of social research (pp. 40–53). Glencoe: Free.

    Google Scholar 

  • Bass, F., Tigert, D. T., & Lonsdale, R. (1968). Market segmentation: Group versus individual behavior. Journal of Marketing Research, 5(3), 264–270.

    Article  Google Scholar 

  • Bearden, W. O., & Etzel, M. J. (1982). Reference group influence on product and brand purchase decision. Journal of Consumer Research, 9(March), 183–194.

    Article  Google Scholar 

  • Belk, R. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15, 139–168.

    Article  Google Scholar 

  • Belk, R. W., Mayer, R., & Bahn, K. (1982). The eye of the beholder: Individual differences in perceptions of consumption symbolism. In A. Mitchell (Ed.), Advances in consumer research (Vol. 9, pp. 523–530). Ann Arbor: Association for Consumer Research.

    Google Scholar 

  • Bennett, A., & Elman, C. (2006). Complex causal relations and case study methods: The example of path dependence. Political Analysis, 14(3), 250–267.

    Article  Google Scholar 

  • Bjelde, K., Chromy, B., & Pankow, D. (2008). Casino gambling among older adults in North Dakota. Journal of Gambling Studies, 24(4), 423–440.

    Article  PubMed  Google Scholar 

  • Campbell, D. T. (1969). Reforms as experiments. American Psychologist, 24, 409–429.

    Article  Google Scholar 

  • Cerino, V. (1998). UNMC study reveals growing gambling addiction among Omaha’s older adults. University of Nebraska Medical Center, UNMC Public Affairs.

  • Cocanougher, A. B., & Bruce, G. D. (1971). Socially distant reference groups and consumer aspirations. Journal of Marketing Research, 8(August), 79–81.

    Google Scholar 

  • Cook, T., & Campbell, D. T. (1979). Quasi-experimentation: Design & analysis issues for field settings. Dallas, TX: Houghton Mifflin Company.

    Google Scholar 

  • Cook, V, Jr., & Mindak, W. (1984). A search for constants: the “heavy user” revisited!. Journal of Consumer Marketing, 1(Spring), 79–81.

    Google Scholar 

  • Cooper, M. (2005). Sit and spin. Atlantic Monthly, December (http://www.theatlantic.com/doc/200512/slot-machines).

  • Elman, C. (2005). Explanatory typologies in qualitative studies of international politics. International Organization, 59(2), 293–326.

    Article  Google Scholar 

  • Englis, B., & Solomon, M. (1995). To be and not to be: Lifestyle imagery, reference groups, and the clustering of America. Journal of Advertising, 24(Spring), 13–28.

    Google Scholar 

  • Frank, R. (1967). Correlates of buying behavior for grocery products. Journal of Marketing, 31(October), 48–53.

    Article  Google Scholar 

  • Frank, R., Massy, W., & Boyd, H. (1967). Correlates of grocery product consumption rates. Journal of Marketing Research, 4(2), 184–190.

    Article  Google Scholar 

  • George, A. L., & Bennett, A. (2005). Case studies and theory development in the social sciences. Cambridge, MA: MIT Press.

    Google Scholar 

  • Goldsmith, R. (2000). Characteristics of the heavy user of fashionable clothing. Journal of Marketing Theory and Practice, 8(4), 21.

    Google Scholar 

  • Goldsmith, R., & d’Hauteville, F. (1998). Heavy wine consumption: Empirical and theoretical perspectives. British Food Journal, 100(4), 184–190.

    Article  Google Scholar 

  • Goldsmith, R., & Litvin, S. (1999). Heavy users of travel agents: A segmentation analysis of vacation travelers. Journal of Travel Research, 38(2), 127–133.

    Article  Google Scholar 

  • Haley, R. I. (1968). Benefit segmentation: A decision oriented research tool. Journal of Marketing, 32(1), 30–35.

    Google Scholar 

  • Hollander, E., Buchalter, A., & DeCaria, C. (2000). Pathological gambling. The Psychiatric Clinics of North America, 23(3), 629–642.

    Article  PubMed  CAS  Google Scholar 

  • Holman, R. M. (1980). Clothing as communications: An empirical investigation. In J. Olson (Ed.), Advances in consumer research (Vol. 7, pp. 372–377). Ann Arbor: Association for Consumer Research.

    Google Scholar 

  • Holman, R. M. (1981). Product use as communication: An appraisal of a venerable topic. In B. Enis & K. Roering (Eds.), Review of marketing (pp. 250–272). Chicago, IL: American Marketing Association.

    Google Scholar 

  • Hope, J., & Havir, L. (2002). You bet they’re having fun! Older Americans and casino gambling. Journal of Aging Studies, 16(2), 177–197.

    Article  Google Scholar 

  • Johansson, A., Grant, J. E., Kim, S. W., Odlaug, B. L., & Götestam, K. G. (2009). Risk factors for problematic gambling: A critical literature review. Journal of Gambling Studies, 25(1), 67–92.

    Article  PubMed  Google Scholar 

  • Kim, W. C., & Mauborgne, R. (2005). Blue ocean strategy. Boston: Harvard Business School Press.

    Google Scholar 

  • Kusyszyn, I. (1984). The psychology of gambling. Annals of the American Academy of Political and Social Science, 474(July), 133–145.

    Article  Google Scholar 

  • Lazarsfeld, P. (1965). Qualitative measurement in social science: Classification, typologies, and indices. In D. Lerner & H. D. Lasswell (Eds.), The policy sciences (pp. 155–192). Stanford: Stanford University Press.

    Google Scholar 

  • Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144, 1184–1188.

    PubMed  CAS  Google Scholar 

  • Lehrer, J. (2007). The neuroscience of gambling. ScienceBlogs. http://scienceblogs.com/cortex/2007/07/the_neuroscience_of_gambling.php#more.

  • Levy, S. (1959). Symbols for sale. Harvard Business Review, 37(July–August), 117–124.

    Google Scholar 

  • Levy, S. (1964). Symbolism and life style. In S. A. Greyser (Ed.), Toward scientific marketing (pp. 140–150). Chicago: American Marketing Association.

    Google Scholar 

  • Loudon, D., & Bitta, A. D. (1993). Consumer behavior: Concepts and applications. New York: McGraw Hill.

    Google Scholar 

  • Lowrey, T., Englis, B., Shavitt, S., & Solomon, M. (2001). Response latency verification of consumption constellations: Implications for advertising. Journal of Advertising, 30(1), 29–39.

    Google Scholar 

  • MacLaurin, D. J., & Wolstenholme, S. (2008). An analysis of the gaming industry in the Niagara region. International Journal of Contemporary Hospitality Management, 20(3), 320–331.

    Article  Google Scholar 

  • Marshall, K. (2007). Gambling. Perspectives on Labor and Income, Statistics Canada, Catalogue No. 75-001-XIE, May online edition.

  • Moufakkir, O., Singh, A. J., Moufakkir-van der Woud, A., & Holecek, D. (2004). Impact of light, medium and heavy spenders on casino destinations: Segmenting gaming visitors based on amount of non-gaming expenditures. UNLV Gaming Research & Review Journal, 8(1), 59–71.

    Google Scholar 

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

    Article  Google Scholar 

  • Palmgreen, P., Lorch, E., Donohew, L., Harrington, N., D’Silva, M., & Helm, D. (1995). Reaching at-risk populations in a mass media drug abuse prevention campaign: Sensation seeking as a targeting variable. Drugs & Society, 8(34), 29–45.

    Google Scholar 

  • Petry, N. M., Stinson, F. S., & Grant, B. F. (2005). Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: Results form the national epidemiologic survey on alcohol and related conditions. Journal of Clinical Psychiatry, 66(5), 564–574.

    Article  PubMed  Google Scholar 

  • Ragin, C. C. (2000). Fuzzy-set social science. Chicago: The University of Chicago Press.

    Google Scholar 

  • Reichardt, C. (1979). The design and analysis of the non-equivalent group quasi-experiment. Unpublished doctoral dissertation, Northwestern University, Chicago.

  • Shavitt, S., & Nelson, M. (2000). The social identity function in person perceptions: Communicated meanings of product preferences. In G. R. Maio & J. M. Olson (Eds.), Why we evaluate: Function of attitudes (pp. 37–57). Mahwaj, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Solomon, M. (1988). Mapping product constellations: A categorization approach to symbolic consumption. Psychology & Marketing, 5(3), 233–258.

    Google Scholar 

  • Solomon, M., & Assael, H. (1987). The forest or the trees? A gestalt approach to symbolic consumptions. In J. Umiker-Sebeok (Ed.), Marketing and semiotics: New directions in the study of sings for sale (pp. 189–218). Berlin: Mouton de Gruyter.

    Google Scholar 

  • Spotts, D., & Mahoney, E. (1991). Segmenting visitors to a destination region based on volume of their expenditures. Journal of Travel Research, 29(4), 24–31.

    Article  Google Scholar 

  • Stafford, J. E. (1966). Effects of group influences on consumer brand preferences. Journal of Marketing Research, 3(1), 68–75.

    Article  Google Scholar 

  • Sujan, M., & Bettman, J. (1989). The effects of brand positioning strategies on consumers’ brand and category perceptions: Some insights from schema research. Journal of Marketing Research, 26(4), 454–467.

    Article  Google Scholar 

  • Tigert, D., Lathrope, R., & Bleeg, M. (1971). The fast food franchises; Psychographic and demographic segmentation analysis. Journal of Retailing, 47(Spring), 81–90.

    Google Scholar 

  • Twedt, D. W. (1964). How important is the “heavy-user”? Journal of Marketing, 28(1), 71–72.

    Article  Google Scholar 

  • Ward, J., & Loken, B. (1986). The quintessential snack food: Measurement of product prototypes. In R. J. Lutz (Ed.), Advances in consumer research (Vol. 13, pp. 126–131). Provo, UT: Association for Consumer Research.

    Google Scholar 

  • Wolfgang, A. (1988). Gambling as a function of gender and sensation seeking. Journal of Gambling Behavior, 4(2), 71–77.

    Article  Google Scholar 

  • Woodside, A., Cook, V., & Mindak, W. (1987). Profiling the heavy travel segment. Journal of Travel Research, 25(4), 9–14.

    Article  Google Scholar 

  • Woodside, A., & Soni, P. (1991). Customer portfolio analysis for strategic development in direct marketing. Journal of Direct Marketing, 5(2), 6–19.

    Article  Google Scholar 

  • Woodside, A., & Trappey, R. (1996). Customer portfolio analysis among competing retail stores. Journal of Business Research, 35, 189–200.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. University of Rhode Island, Ballentine Hall, Suite 216, Kingston, RI, 02881, USA

    Ralph Perfetto

  2. Department of Marketing, Boston College, Carroll School of Management, 140 Commonwealth Avenue, Chestnut Hill, MA, 02467, USA

    Arch G. Woodside

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  1. Ralph Perfetto
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  2. Arch G. Woodside
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Correspondence to Ralph Perfetto.

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Perfetto, R., Woodside, A.G. Extremely Frequent Behavior in Consumer Research: Theory and Empirical Evidence for Chronic Casino Gambling. J Gambl Stud 25, 297–316 (2009). https://doi.org/10.1007/s10899-009-9130-3

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