The analysis of default in a fan membership program: the use of credit scoring as sports management tool
DOI:
https://doi.org/10.5585/podium.v11i1.20124Keywords:
Loyalty Program, Fan membership, Soccer, Default, Credit scoring.Abstract
Research aim: Fan membership programs are examples of how clubs adapted successful tools from corporate world to boost their brands, seeking for a perennial revenue alternative. However, the environment of passionate volatility of the fans becomes a challenge for the sports management. In this way, the aim of the work consists of implementing a Credit Scoring methodology to assess the default behavior in a fan membership program.
Methodological approach: The Credit Scoring is traditionally widespread in bank institutions to study the default behavior of customers, using registration and relationship profiles to assign scores that measure the risk of default.
Originality and relevance: Understanding the fan’s behavior is essential for the manager to implement the promotional measures that aim to enhance the loyalty.
Main results: The results indicate that members with more expensive plans, with older ages, that live in the same city that the games are played and their proximity to the stadium, significantly reduce their probabilities to default. Even if it is a male-majority environment, the female gender presents itself as a profile with a lower probability of default. The fact that the member account holder has dependents linked reduces the probability of default, counterposing the banking Credit Scoring literature, in which the number of dependents increases the probability of default.
Theoretical and methodological contributions: The work uses georeferencing techniques to calculate the distance of each member to the stadium and uses a two-stage Credit Scoring estimation technique, based on active and inactive profiles.
Downloads
References
Albuquerque, P. H. M., Medina, F. A. S., & Silva, A. R. D. (2017). Regressão Logística Geograficamente Ponderada Aplicada a Modelos de Credit Scoring. Revista Contabilidade & Finanças, 28, 93-112.: https://doi.org/10.1590/1808-057x201703760
Azevedo, A. G. D. (2013). O desenvolvimento de estratégia do programa Sócio-torcedor relacionado com a visão Gerencial do futebol profissional no Distrito Federal. (Dissertação de mestrado, Universidade de Brasília). https://repositorio.unb.br/handle/10482/14362
Bandarra, T. M. D. S. (2017). Sport Club Internacional: uma análise de seus torcedores com uma abordagem de CRM. (Trabalho de conclusão de curso, Universidade Federal do Rio Grande do Sul). https://www.lume.ufrgs.br/handle/10183/170502
Biscaia, R., Ross, S., Yoshida, M., Correia, A., Rosado, A., & Marôco, J. (2016). Investigating the role of fan club membership on perceptions of team brand equity in football. Sport Management Review, 19(2), 157-170. https://doi.org/10.1016/j.smr.2015.02.001
Bücker, M., van Kampen, M., & Krämer, W. (2013). Reject inference in consumer credit scoring with nonignorable missing data. Journal of Banking & Finance, 37(3), 1040-1045. https://doi.org/10.1016/j.jbankfin.2012.11.002
Carvalho, W. G., Molletta, S. R., Stinghen, F. M., & Knaut, C. M. F. (2013). Estudo sobre a satisfação do sócio-torcedor do Paraná Clube. Revista Intercontinental de Gestão Desportiva, 3. https://doi.org/10.51995/2237-3373.v11i1e110011
Chen, M. C., & Huang, S. H. (2003). Credit scoring and rejected instances reassigning through evolutionary computation techniques. Expert Systems with Applications, 24(4), 433-441. https://doi.org/10.1016/S0957-4174(02)00191-4
Cunha, Michele Aparecida. (2021). Finanças e Regionalidade: um modelo de Credit Scoring com uso da Regressão Logística Geograficamente Ponderada no Programa Minha Casa Minha Vida em Minas Gerais. 2021. 95 f. Dissertação (Mestrado em Administração) - Universidade Federal de Uberlândia, Uberlândia, 2021. DOI http://doi.org/10.14393/ufu.di.2021.73
DeSarbo, W. S. (2010). A spatial multidimensional unfolding choice model for examining the heterogeneous expressions of sports fan avidity. Journal of Quantitative Analysis in Sports, 6(2). https://doi.org/10.2202/1559-0410.1232
Derbaix, C., & Decrop, A. (2011). Colours and scarves: an ethnographic account of football fans and their paraphernalia. Leisure Studies, 30(3), 271-291. https://doi.org/10.1080/02614367.2010.527356
Dinh, T. H. T., & Kleimeier, S. (2007). A credit scoring model for Vietnam's retail banking market. International Review of Financial Analysis, 16(5), 471-495. https://doi.org/10.1016/j.irfa.2007.06.001
Fleury, F. A., Brashear-Alejandro, T., & Feldmann, P. R. (2014). Considerações teóricas acerca do composto de marketing esportivo. PODIUM Sport, Leisure and Tourism Review, 3(1), 01-11. https://doi.org/10.5585/podium.v3i1.82
Gomes, E. F. C. (2014). O que se pode extrair da média de público histórica do clube. Almanaque do Ferrão. https://almanaquedoferrao.net/2014/11/26/o-que-se-pode-extrair-da-media-de-publico-historica-do-ferrao/
Greene, W. (1998). Sample selection in credit-scoring models. Japan and the world economy, 10(3), 299-316. https://doi.org/10.1016/S0922-1425(98)00030-9
Greene, W. H. (2003). Econometric analysis. Pearson Education India.
Hamil, S., Walters, G., & Watson, L. (2013). The model of governance at FC Barcelona: balancing member democracy, commercial strategy, corporate social responsibility and sporting performance. Who Owns Football? 143-172. Routledge. https://doi.org/10.1080/14660971003780446
Khemais, Z., Nesrine, D., & Mohamed, M. (2016). Credit scoring and default risk prediction: A comparative study between discriminant analysis & logistic regression. International Journal of Economics and Finance, 8(4), 39. https://doi.org/10.5539/ijef.v8n4p39
Leal, D. (2011). Vasco luta contra inadimplência de 83% dos sócios. Portal Lance. https://www.lance.com.br/todos-esportes/vasco-luta-inadimplencia-socios.html
Lei nº 9.615, de 24 março de 1998. Institui normas gerais sobre desporto e dá outras providências. http://www.planalto.gov.br/ccivil_03/leis/l9615consol.htm
Lei nº 10.671, de 15 de maio de 2003. Dispõe sobre o Estatuto de Defesa do Torcedor e dá outras providências. http://www.planalto.gov.br/ccivil_03/leis/2003/l10.671.htm
Li, Z., Tian, Y., Li, K., Zhou, F., & Yang, W. (2017). Reject inference in credit scoring using semi-supervised support vector machines. Expert Systems with Applications, 74, 105-114. https://doi.org/10.1016/j.eswa.2017.01.011
Llopis-Goig, R. (2012). From “socios” to “hyper-consumers”: an empirical examination of the impact of commodification on Spanish football fans. Soccer & Society, 13(3), 392-408. https://doi.org/10.1080/14660970.2012.655508
Macri, M. (2011). Pasión y gestión: Claves del ciclo Macri en Boca. Aguilar.
Moreira, M. V., & Hijós, N. (2013). Clubes deportivos, fútbol y mercantilización: los casos de Boca Juniors e Independiente en la Argentina. Question, 1(37), 149-162. https://www.perio.unlp.edu.ar/ojs/index.php/question/article/view/1728/1473
Mulheres são menos inadimplentes do que homens. (2016). Consumidor Moderno. https://www.consumidormoderno.com.br/2016/03/08/mulheres-sao-menos-inadimplentes-do-que-homens/
Pereira, G. H. D. A. (2004). Modelos de risco de crédito de clientes: Uma aplicação a dados reais. (Dissertação de doutorado, Universidade de São Paulo). https://doi.org/10.11606/D.45.2004.tde-28122004-224257
Ribeiro, L. C. (2012). Futebol: por uma história política da paixão nacional. História: Questões & Debates, 57(2). http://dx.doi.org/10.5380/his.v57i2.30570
Rosolino, T. (2020). As dívidas dos times brasileiros: veja ranking com balanço dos maiores clubes. Portal Terra. https://www.goal.com/br/not%C3%ADcias/as-dividas-dos-times-brasileiros-veja-ranking-com-balanco/14a81mxtoco6i1irhwp9kec53x
Silva Leal, G., Furin, L. M., Conejero, M. A., André, P., & Bougleux, V. (2017) Programas Sócio-Torcedor no Brasil-Análise comparativa entre clubes selecionados e o Volta Redonda Futebol Clube. Revista Gestão e Negócios do Esporte.
Souza Dias, P., Monteiro, P. R. R., & Ribeiro, E. M. S. (2019). Aplicação de Redes Bayesianas para análise de programas sócio torcedor. Revista Pensamento Contemporâneo em Administração, 13(2), 49-66. https://doi.org/10.12712/rpca.v13i2.27526
Thomas, L. C. (2000). A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers. International journal of forecasting, 16(2), 149-172. https://doi.org/10.1016/S0169-2070(00)00034-0
Umbelino, W. L., Silva, R. B., Ponte, V. M. R., & Lima, M. C. (2019). Disclosure em Clubes de Futebol: Estudo sobre os Reflexos da Lei do PROFUT. Revista Evidenciação Contábil & Finanças, 7(1), 112-132. https://doi.org/10.22478/ufpb.2318-1001.2019v7n1.38074
Xavier, F. (2010). O Programa “Sócio-Torcedor” do Sport Club Internacional. Aurora. Revista de Arte, Mídia e Política, (9), 128-138. https://revistas.pucsp.br/aurora/article/view/3788
Yang S, Yu SL(K), Bruwer J. (2017) The effectof relational benefits in loyalty programmes: Evidence from Chinese milk formula customer clubs. J Consumer Behav.2018;1–10. https://doi.org/10.1002/cb.1705
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 PODIUM Sport, Leisure and Tourism Review
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.