Mathematics Interdisciplinary Research

Mathematics Interdisciplinary Research

Economic Determinants and Social Influences on Gambling‎ ‎in‎ ‎South‎ ‎Africa:‎ ‎A‎ ‎Mathematical Modeling Approach

Document Type : Original Scientific Paper

Authors
Tichaona Chikore
Farai Nyabadza
Department of Mathematics and Applied Mathematics, ‎South Africa
10.22052/mir.2026.257798.1549
Abstract
‎Gambling in South Africa‎, ‎propelled by casinos‎, ‎sports betting‎, ‎and a growing online sector‎, ‎is increasingly influenced by economic pressures and accessibility‎. ‎This study presents a {partially data-informed} mathematical model to {analyze} gambling participation‎, ‎focusing on the impact of economic indicators (unemployment‎, ‎inflation‎, ‎GDP per capita‎, ‎and poverty) on gambling behaviours‎. ‎Integrating these factors with social influences‎, ‎we employ a non-linear differential equation framework to evaluate the perceived utility of gambling in varying economic scenarios‎. ‎Using Monte Carlo simulations and scenario analysis‎, ‎our results reveal a significant association between high unemployment‎, ‎poverty‎, ‎and increased gambling participation‎, ‎particularly in socially cohesive environments‎. ‎Results indicate that higher unemployment and poverty levels significantly correlate with increased gambling‎, ‎with social influence amplifying this trend‎. ‎Unemployment and peer effects emerge as primary predictors‎, ‎highlighting economic hardship's role in gambling behaviour‎. ‎These findings suggest targeted interventions for economically vulnerable populations‎, ‎such as educational campaigns and support services‎, ‎to mitigate gambling-related risks during economic downturns‎.
Keywords
Gambling dynamics
Economic conditions
Predictive modeling
Utility function
Social influences
Subjects
[1] Sporting Post, The Rise And Rise Of Gambling In South Africa: A Trillion Rand Business in SA in 2024!, 2024, https://www.sportingpost.co.za/the-riseand-rise-of-gambling-in-south-africa/, Accessed: 2024-10-08.
[2] Statistics South Africa, Census 2022: South Africa’s population increases to 62 million, 2023, https://www.sanews.gov.za/south-africa/sa-populationgrows-517-million-62-million, Accessed: 2025-05-03.
[3] A. Catalano, L. Milani, M. Franco, F. Buscema, I. Giommarini, B. Sodano, W. Gilcrease, L. Mondo, M. Marra, C. D. Girolamo, A. Bena and F. Ricceri, The impact of COVID-19 pandemic on gambling: a systematic review, Addict. Behav. 155 (2024) #108037, https://doi.org/10.1016/j.addbeh.2024.108037.
[4] A. Quinn, J. E. Grant and S. R. Chamberlain, COVID-19 and resultant restrictions on gambling behaviour, Neurosci. Biobehav. Rev. 143 (2022) #104932, https://doi.org/10.1016/j.neubiorev.2022.104932.
[5] R. Davies, Record revenues at UK gambling firms amid rise of online slot machines, The Guardian (2023), https://www.theguardian.com/society/2023/nov/30/record-revenues-at-uk-gambling-firms-amid-rise-of-online-slot-machines, Accessed 10 October 2024.
[6] Victorian Responsible Gambling Foundation, Latest edition of Australian Gambling Statistics, 2023, https://responsiblegambling.vic.gov.au/aboutus/news-and-media/latest-edition-of-australian-gambling-statistics/, Accessed: 2023-10-14.
[7] M. Mazoochi, S. Yousefikhah and L. Rabiei, A socio-economic analysis of the online gambling, J. inf. technol. manage. 16 (2024) 62-90, https://doi.org/10.22059/jitm.2023.353397.3241.
[8] T. Grönroos, A. Kouvonen, J. Kontto and A. H. Salonen, Sociodemographic factors, gambling behaviour, and the level of gambling expenditure: a population-based study, J. Gambl. Stud. 38 (2022) 1093–1109, https://doi.org/10.1007/s10899-021-10075-6.
[9] T. A. Latvala, T. P. Lintonen, M. Browne, M. Rockloff and A. H. Salonen, Social disadvantage and gambling severity: a population-based study with register-linkage, Eur. J. Public Health. 31 (2021) 1217–1223, https://doi.org/10.1093/eurpub/ckab162.
[10] R. J. Williams, J. Rehm and R. M. G. Stevens, The Social and Economic Impacts of Gambling, Canadian Consortium for Gambling Research, 2011.
[11] T. Latvala, T. Lintonen and A. Konu, Public health effects of gambling– debate on a conceptual model, BMC Public Health. 19 (2019)#1077,https://doi.org/10.1186/s12889-019-7391-z.
[12] D. T. Olason, T. Hayer, G. Meyer and T. Brosowski, Economic recession affects gambling participation but not problematic gambling: results from a population-based follow-up study, Front. Psychol. 8 (2017) #1247, https://doi.org/10.3389/fpsyg.2017.01247.
[13] G. Blalock, D. R. Just and D. H. Simon, Hitting the jackpot or hitting the skids: entertainment, poverty, and the demand for state lotteries, Am. J. Econ. Sociol. 66 (2007) 545-570, https://doi.org/10.1111/j.1536-7150.2007.00526.x.
[14] M. J. A. Wohl, N. R. Branscombe and J. J. Lister, When the going gets tough: economic threat increases financial risk taking in games of chance, Soc. Psychol. Pers. Sci. 5 (2013) 211-217, https://doi.org/10.1177/1948550613490964.
[15] A. Sirola, J. Nyrhinen and T. A. Wilska, Psychosocial perspective on problem gambling: the role of social relationships, resilience, and COVID-19 worry, J. Gambl. Stud. 39 (2023) 1467-1485, https://doi.org/10.1007/s10899-022-10185-9.
[16] National Research Council (US) Committee on the Social and Economic Impact of Pathological Gambling, Pathological Gambling: A Critical Review, National Academies Press (US), Washington, DC, 1999, https://www.ncbi.nlm.nih.gov/books/NBK230628/.
[17] National Gambling Board, Socio-economic Impact of Gambling in South Africa,2017,https://www.ngb.org.za/SiteResources/documents/2017/Research/Socioeconomic.
[18] C. Barboianu, Mathematical models of games of chance: epistemological taxonomy and potential in problem-gambling research, UNLV Gaming Res. Rev. J. 19 (2015) 17-30.
[19] Y. S. Lee and T. S. Do, A mathematical modeling approach to gambling among older adults, Appl. Math. Comput. 221 (2013) 403-410, https://doi.org/10.1016/j.amc.2013.05.075.
[20] T. S. Do and Y. S. Lee, A differential equation model for the dynamics of youth gambling, Osong Public Health Res. Perspect. 5 (2014) 233-241, https://doi.org/10.1016/j.phrp.2014.06.008.
[21] R. A. Armour and L. A. Bizo, Modeling gambling: an application of the mathematical principles of reinforcement, Anal. Gambl. Behav. 8 (2014) 23-37.
[22] J. C. Lang, D. M. Abrams and H. De Sterck, The influence of societal individualism on a century of tobacco use: modelling the prevalence of smoking,
BMC Public Health. 15 (2015) #1280, https://doi.org/10.1186/s12889-015-2576-6.
[23] S. Castrén, J. Kontto, H. Alho and A. H. Salonen, The relationship between gambling expenditure, socio-demographics, health-related correlates and gambling behaviour-a cross-sectional population-based survey in Finland, Addiction 113 (2018) 91-106, https://doi.org/10.1111/add.13929.
[24] M. Prasertsiwaporn and T. Chomtohsuwan, Poverty, gambling, and law in the digital economy, Corp. Law Gov. Rev. 5 (2023) 109-116, https://doi.org/10.22495/clgrv5i2p12.
[25] J. Conlisk, The utility of gambling, J. Risk Uncertain. 6 (1993) 255 -275.
[26] M. Friedman and L. J. Savage, The utility analysis of choices involving risk, J. Polit. Econ. 56 (1948) 279-304.
[27] L. Cameron, J. Ride and N. Devlin, An economic model of gambling behaviour: a two-stage approach, J. Gambl. Stud. 40 (2024) 65-81, https://doi.org/10.1007/s10899-022-10146-2.
[28] T. Robertson and F. T. Wright, On measuring the conformity of a parameter set to a trend, with applications, Ann. Statist. 10 (1982) 1234-1245, http://doi.org/ 10.1214/aos/1176345988.
[29] J. M. Burger, Social Influence, Psychology of, in: N. J. Smelser, P. B. Baltes (Eds.), International Encyclopedia of the Social & Behavioral Sciences, Pergamon, Oxford, 2001, pp. 14320-14325, https://doi.org/10.1016/B0-08-043076-7/01805-2.
[30] D. Rensen, Understanding the Appeal of Online Gambling: Opportunities and Risks Associated with the Affordances, motivations and Gratifications of Gamblers, Master’s thesis, Tilburg University, Tilburg, 2018.
[31] A. Parrado-González, F. Fernández-Calderón and J. C. León-Jariego, Perceived gambling availability and adolescent gambling behavior: the moderating role of self-efficacy, Int. J. Ment. Health Addict. 21 (2023) 2737-2750, https://doi.org/10.1007/s11469-021-00749-y.
[32] Á. García-Pérez, A. Krotter and G. Aonso-Diego, The impact of gambling advertising and marketing on online gambling behavior: an analysis based on Spanish data, Public Health 234 (2024) 170-177, https://doi.org/10.1016/j.puhe.2024.06.025.
[33] S. Badji, N. Black and D. W. Johnston, economic, health and behavioural consequences of greater gambling availability, Econ. Model. 123 (2023)#106285, https://doi.org/10.1016/j.econmod.2023.106285.
[34] M. Guillou-Landreat, K. Gallopel-Morvan, D. Lever, D. Le Goff and J. Y. Le Reste, Gambling marketing strategies and the internet: what do we know? a systematic review, Front. Psychiatry. 12 (2021) #583817, https://doi.org/10.3389/fpsyt.2021.583817.
[35] R. Hartley and L. Farrell, Can Expected Utility Theory Explain Gambling?,Am. Econ. Rev. 92 (2002) 613-624, https://doi.org/10.1257/00028280260136426.
[36] S. Marko, S. L. Thomas, H. Pitt and M. Daube, The impact of responsible gambling framing on people with lived experience of gambling harm, Front. Sociol. 8 (2023) #1074773, https://doi.org/10.3389/fsoc.2023.1074773.
[37] T. St Quinton and L. Monacis, A reasoned action approach to gambling behavior, Cogent Psychol. 7 (2020) #1857104, https://doi.org/10.1080/23311908.2020.1857104.
[38] A. M. T. Russell, E. Langham and N. Hing, Social influences normalize gambling-related harm among higher risk gamblers, J. Behav. Addict. 7 (2018) 1100-1111, https://doi.org/10.1556/2006.7.2018.139.
Mathematics Interdisciplinary Research
Volume 11, Issue 4
Autumn 2026
Pages 435-461