Skip to main content
SpringerLink
Log in

An Analysis of Switching and Non-switching Slot Machine Player Behaviour

  • Original Paper
  • Published:
Journal of Gambling Studies Aims and scope Submit manuscript

Abstract

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study’s absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

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

Similar content being viewed by others

References

  • Abbott, M. W. (2001). Problem and non-problem gamblers in New Zealand: A report on phase two of the 1999 national prevalence survey. Report number six of the New Zealand gaming survey. Wellington: Department of Internal Affairs.

  • Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97, 487–499.

    Article  PubMed  Google Scholar 

  • Blaszczynski, A., Sharpe, L., Walker, M., Shannon, K., & Coughlan, M. (2005). Structural characteristics of electronic gaming machines and satisfaction of play among recreational and problem gamblers. International Gambling Studies, 5, 187–198.

    Article  Google Scholar 

  • Brandt, A. E., & Pietras, C. J. (2008). Gambling on a simulated slot machine under conditions of repeated play. The Psychological Record, 58, 405–426.

    Google Scholar 

  • Breen, R. B., & Zimmerman, M. (2002). Rapid onset of pathological gambling in machine gamblers. Journal of Gambling Studies, 18(1), 31–43.

    Article  PubMed  Google Scholar 

  • Chóliz, M. (2010). Experimental analysis of the game in pathological gamblers: Effect of the immediacy of the reward in slot machines. Journal of Gambling Studies, 26, 249–256.

    Article  PubMed  Google Scholar 

  • Cyders, M. A., & Smith, G. T. (2008). Clarifying the role of personality dispositions in risk for increased gambling behavior. Personality and Individual Differences, 45, 503–508.

    Article  PubMed  Google Scholar 

  • Cyders, M. A., Smith, G. T., Spillane, N. S., Fischer, S., Annus, A. M., & Peterson, C. (2007). Integration of impulsivity and positive mood to predict risky behavior: Development and validation of a measure of positive urgency. Psychological Assessment, 19, 107–118.

    Article  PubMed  Google Scholar 

  • Delfabbro, P., Falzon, K., & Ingram, T. (2005). The effects of parameter variations in electronic gambling simulations: Results of a laboratory-based pilot intervention. Gambling Research, 17(1), 7–25.

    Google Scholar 

  • Delfabbro, P., Lahn, J., & Grabosky, P. (2006). It’s not what you know, but how you use it: Statistical knowledge and adolescent problem gambling. Journal of Gambling Studies, 22, 179–193.

    Article  PubMed  Google Scholar 

  • Dickerson, M. G. (1979). FI schedules and persistence at gambling in the UK betting office. Journal of Applied Behaviour Analysis, 12, 315–323.

    Article  CAS  Google Scholar 

  • Dickerson, M., & Baron, E. (2000). Contemporary issues and future directions for research into pathological gambling. Addiction, 95(8), 1145–1159.

    Article  PubMed  CAS  Google Scholar 

  • Dixon, M. R., Harrigan, K. A., Sandhu, R., Collins, K., & Fugelsang, J. A. (2010). Losses disguised as wins in modern multi-line video slot machines. Addiction, 105, 1819–1824.

    Article  PubMed  Google Scholar 

  • Dixon, M. R., MacLin, O. H., & Daugherty, D. (2006). An evaluation of response allocations to concurrently available slot machine simulations. Behavior Research Methods, 38, 232–236.

    Article  PubMed  Google Scholar 

  • Dowling, N., Smith, D., & Thomas, T. (2005). Electronic gaming machines: Are they the ‘crack-cocaine’ of gambling? Addiction, 100, 33–45.

    Article  PubMed  Google Scholar 

  • Fischer, S., & Smith, G. T. (2008). Binge eating, problem drinking, pathological gambling: Linking behaviour to shared traits and social learning. Personality and Individual Differences, 44, 789–800.

    Article  Google Scholar 

  • Gilliland, J. A., & Ross, N. A. (2005). Opportunities for video lottery terminal gambling in Montréal: An environmental analysis. Canadian Journal of Public Health, 96, 55–59.

    PubMed  Google Scholar 

  • Gillis, A., McDonald, J. D., & Weatherly, J. N. (2008). American Indians and non-Indians playing a slot-machine simulation: Effects of sensation seeking and payback percentage. American Indian and Alaska Native Mental Health Research, 15, 18–32.

    Article  PubMed  Google Scholar 

  • Götestam, K. G., & Johansson, A. (2003). Characteristics of gambling and problematic gambling in the Norwegian context: A DSM-IV-based telephone interview study. Addictive Behaviors, 28, 189–197.

    Article  PubMed  Google Scholar 

  • Griffiths, M. (1999). Gambling technologies: Prospects for problem gambling. Journal of Gambling Studies, 15, 265–283.

    Article  PubMed  Google Scholar 

  • Habib, R., & Dixon, M. R. (2010). Neurobehavioral evidence for the “near-miss” effect in pathological gamblers. Journal of the Experimental Analysis of Behavior, 93, 313–328.

    Article  PubMed  Google Scholar 

  • Harrigan, K. A. (2007). Slot machine structural characteristics: Distorted player views of payback percentages. Journal of Gambling Issues, 20, 215–234.

    Article  Google Scholar 

  • Harrigan, K. A., & Dixon, M. (2009). PAR Sheets, probabilities, and slot machine play: Implications for problem and non-problem gambling. Journal of Gambling Studies, 23, 159–174.

    Google Scholar 

  • Harrigan, K. A., & Dixon, M. (2010). Government sanctioned “tight” and “loose” slot machines: How having multiple versions of the same slot machine game may impact problem gambling. Journal of Gambling Studies, 26(1), 159–174.

    Article  PubMed  Google Scholar 

  • Haw, J. (2008a). Random-ratio schedules of reinforcement: The role of early wins and unreinforced trials. Journal of Gambling Issues, 21, 56–67.

    Article  Google Scholar 

  • Haw, J. (2008b). The relationship between reinforcement and gaming machine choice. Journal of Gambling Studies, 24, 55–61.

    Article  PubMed  Google Scholar 

  • Herrnstein, R. J. (1970). On the law of effect. Journal of the Experimental Analysis of Behavior, 13, 243–266.

    Article  PubMed  CAS  Google Scholar 

  • Horne, P. J., & Lowe, C. F. (1993). Determinants of human performance on concurrent schedules. Journal of Experimental Analysis of Behavior, 59, 29–60.

    Article  CAS  Google Scholar 

  • Jackson, A. C., Thomas, S. A., Thomason, N., Holt, T. A., & McCormack, J. (2000). Analysis of clients presenting to break even problem gambling services, July 1 1998 to June 20 1999. Client and Service Analysis Report no 5. Melbourne, VIC: Victorian Department of Human Services.

  • 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, 67–92.

    Article  PubMed  Google Scholar 

  • Lambos, C., & Delfabbro, P. (2007). Numerical reasoning ability and irrational beliefs in problem gambling. International Gambling Studies, 7, 157–171.

    Article  Google Scholar 

  • Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328.

    Article  Google Scholar 

  • Le Pelley, M. E. (2004). The role of associative history in models of associative learning: A selective review and hybrid model. The Quarterly Journal of Experimental Psychology, 57B(3), 193–243.

    Article  Google Scholar 

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

    Google Scholar 

  • Linnet, J., Thomsen, K. R., Møller, A., & Callesen, M. B. (2010). Event frequency, excitement and desire to gamble, among pathological gamblers. International Gambling Studies, 10(2), 177–188.

    Article  Google Scholar 

  • Livingstone, C., Woolley, R., Zazryn, T., Bakacs, L., & Shami, R. (2008). The relevance and role of gaming machine games and game features on the play of problem gamblers. Adelaide, SA: Independent Gambling Authority of South Australia.

    Google Scholar 

  • Loba, P., Stewart, S. H., Klein, R. M., & Blackburn, J. M. (2002). Manipulations of the features of standard video lottery terminal (VLT) games: Effects in pathological and non-pathological gamblers. Journal of Gambling Studies, 17(4), 297–320.

    Article  Google Scholar 

  • Lund, I. (2006). Gambling and problem gambling in Norway: What part does the gambling machine play? Addiction Research and Theory, 14, 475–491.

    Article  Google Scholar 

  • MacLin, O. H., Dixon, M. R., & Hayes, L. J. (1999). A computerized slot machine simulation to investigate the variables involved in gambling behaviour. Behavior Research Methods, Instruments, & Computers, 31, 731–734.

    Article  CAS  Google Scholar 

  • McMillen, J., Marshall, D., Ahmed, E., & Wenzel, M. (2004). Victorian longitudinal community attitudes survey. Melbourne: Victorian Gambling Research Panel.

    Google Scholar 

  • Monaghan, S. (2008). Responsible gambling strategies for internet gambling: The theoretical and empirical base of using pop-up messages to encourage self-awareness. Computers in Human Behavior, 25, 202–207.

    Article  Google Scholar 

  • Morgan, M. J. (1974). Effects of random reinforcement sequences. Journal of the Experimental Analysis of Behavior, 22, 301–310.

    Article  PubMed  CAS  Google Scholar 

  • Peters, H., Hunt, M., & Harper, D. (2010). An animal model of slot machine gambling: The effect of structural characteristics on response latency and persistence. Journal of Gambling Studies, 26, 521–531.

    Article  PubMed  Google Scholar 

  • Productivity Commission. (2009). Australia’s gambling industries. Canberra: Commonwealth of Australia.

    Google Scholar 

  • Skinner, B. F. (1938). The behavior of organisms. New York: Appleton-Century-Crofts.

    Google Scholar 

  • Steel, Z., & Blaszczynski, A. (1996). The factorial structure of pathological gambling. Journal of Gambling Studies, 12, 3–20.

    Article  Google Scholar 

  • Steenbergh, T. A., Meyers, A. W., May, R. K., & Whelan, J. P. (2002). Development and validation of the gambler’s belief questionnaire. Psychology of Addictive Behaviors, 16, 143–149.

    Article  PubMed  Google Scholar 

  • Turner, N., & Horbay, R. (2004). How do slot machines and other electronic gaming machines actually work? Journal of Gambling Issues, 11, 10–50.

    Google Scholar 

  • Urbanoski, K. A., & Rush, B. R. (2006). Characteristics of people seeking treatment for problem gambling in Ontario: Trends from 1998 to 2002. Issues: Journal of Gambling. 16.

    Google Scholar 

  • Volberg, R. A., & Abbott, M. W. (1994). Lifetime prevalence estimates of pathological gambling in New Zealand. International Journal of Epidemiology, 23, 976–983.

    Article  PubMed  CAS  Google Scholar 

  • Walker, M. B. (1992). The psychology of gambling. Oxford: Pergamon Press.

    Google Scholar 

  • Walker, M. B. (2003). The seductiveness of poker machines. In Proceedings of the 13th annual conference of the National Association for Gambling Studies (pp. 12–26), Canberra.

  • Weatherly, J. N., & Brandt, A. E. (2004). Participants’ sensitivity to percentage payback and credit value when playing a slot-machine simulation. Behavior and Social Issues, 13, 33–50.

    Article  Google Scholar 

  • Weatherly, J. N., & Dixon, M. (2007). Toward an integrative behavioral model of gambling. Analysis of Gambling Behavior, 1, 4–18.

    Google Scholar 

  • Weatherly, J. N., & Flannery, K. A. (2008). Facing the challenge: The behavioral analysis of gambling. The Behavior Analyst Today, 9, 130–142.

    Google Scholar 

  • Weatherly, J. N., Thompson, B. J., Hodny, M., & Meier, E. (2009). Choice behavior of non-pathological women playing concurrently available slot machines: Effect of changes in payback percentages. Journal of Applied Behavioral Analysis, 42, 895–900.

    Article  Google Scholar 

  • Whiteside, S. P., & Lynam, D. R. (2001). The five factor model and impulsivity: Using a structural model of personality to understand impulsivity. Personality and Individual Differences, 30, 669–689.

    Article  Google Scholar 

  • Williamson, A., & Walker, M. (2000). Strategies for solving the insoluble: Playing to win Queen of the Nile (pp. 218–226). Lessons of the Past, Mildura: National Association for Gambling Studies.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Psychology (A18), The University of Sydney, Sydney, NSW, 2006, Australia

    Ewan Coates & Alex Blaszczynski

Authors
  1. Ewan Coates
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alex Blaszczynski
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alex Blaszczynski.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Coates, E., Blaszczynski, A. An Analysis of Switching and Non-switching Slot Machine Player Behaviour. J Gambl Stud 29, 631–645 (2013). https://doi.org/10.1007/s10899-012-9329-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10899-012-9329-6

Keywords

Search

Navigation