O Papel da Inteligência Competitiva no Aprimoramento do Desempenho Organizacional na Indústria do Esporte
PDF (English)

Palavras-chave

Inteligência Competitiva
Organizações Esportivas
IA no Esporte
Análise de Dados
Engajamento de Fãs
Recrutamento de Jogadores
Crescimento de Receitas
Análise Sistemática

Como Citar

Ling, W. (2026). O Papel da Inteligência Competitiva no Aprimoramento do Desempenho Organizacional na Indústria do Esporte. Revista Inteligência Competitiva, 16, e0637. https://doi.org/10.37497/eagleSustainable.v16i.637

Resumo

Objetivo: Explorar o papel que a Inteligência Competitiva (CI) tem desempenhado no apoio ao desempenho de organizações esportivas. O estudo analisa o uso de ferramentas de CI, como IA, análise preditiva e big data, no recrutamento de jogadores, na melhoria da experiência dos fãs e no crescimento das receitas.

Metodologia/abordagem: A pesquisa baseia-se em uma abordagem de métodos mistos, incorporando dados quantitativos (survey com 120 profissionais do esporte) e dados qualitativos (18 entrevistas semiestruturadas com profissionais de CI e gestores esportivos). A correlação entre o uso de CI e o crescimento das receitas foi determinada por regressão e correlação de Pearson, sendo encontrada forte correlação entre CI no recrutamento de jogadores e crescimento das receitas (r = 0,82).

Originalidade/Relevância: O estudo apresenta a mudança de paradigma da CI nas organizações esportivas. A CI está se tornando cada vez mais um instrumento-chave de vantagem competitiva, à medida que a adoção de decisões orientadas por dados tem melhorado o desempenho em campo e o desempenho financeiro fora de campo.

Principais Resultados: O artigo conclui que as ferramentas de CI podem contribuir especialmente para o aprimoramento do recrutamento de jogadores e do engajamento dos fãs, e ambas as direções indicam forte efeito positivo sobre a taxa de crescimento das receitas.

Contribuições Teóricas/Metodológicas: O presente artigo oferece uma revisão aprofundada do conhecimento existente sobre CI em organizações esportivas. Contribui para a literatura de gestão esportiva ao combinar ferramentas de CI com medidas de desempenho organizacional, oferecendo um framework abrangente para estudos futuros sobre implementação e efeitos da CI no esporte.

https://doi.org/10.37497/eagleSustainable.v16i.637
PDF (English)

Referências

Akram, H., Khan, A. U., Naveed, F., & Khalid, A. (2022). The role of athletic knowledge management in obtaining a competitive advantage in the sports work environment. Jurnal Aplikasi Manajemen, Ekonomi dan Bisnis, 7(1), 33–42. https://doi.org/10.51263/jameb.v7i1.152

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108

Byrne, D. (2022). A worked example of Braun and Clarke’s approach to reflexive thematic analysis. Quality & Quantity, 56(3), 1391–1412. https://doi.org/10.1007/s11135-021-01182-y

Calof, J. L., & Wright, S. (2008). Competitive intelligence: A practitioner, academic and inter-disciplinary perspective. European Journal of Marketing, 42(7/8), 717–730. https://doi.org/10.1108/03090560810877114

Christodoulou, A., & Cullinane, K. (2019). Identifying the main opportunities and challenges from the implementation of a port energy management system: A SWOT/PESTLE analysis. Sustainability, 11(21), 6046. https://doi.org/10.3390/su11216046

Corona, R. (2025). The application of artificial intelligence metrics in the National Basketball Association (NBA). Scientia Moralitas: International Journal of Multidisciplinary Research, 10(1), 312–354.

Cronk, B. C. (2016). How to use IBM SPSS statistics: A step-by-step guide to analysis and interpretation. Routledge. https://doi.org/10.4324/9781315266428

Davenport, T. H. (2014). Analytics in sports: The new science of winning. International Institute for Analytics.

Dishman, P. L., & Calof, J. L. (2008). Competitive intelligence: A multiphasic precedent to marketing strategy. European Journal of Marketing, 42(7/8), 766–785. https://doi.org/10.1108/03090560810877141

Dufera, A. G., Liu, T., & Xu, J. (2023). Regression models of Pearson correlation coefficient. Statistical Theory and Related Fields, 7(2), 97–106. https://doi.org/10.1080/24754269.2023.2164970

Fannon, S. R., Munive-Hernandez, J. E., & Campean, F. (2022). Mastering continuous improvement (CI): The roles and competences of mid-level management and their impact on the organisation’s CI capability. The TQM Journal, 34(1), 102–124. https://doi.org/10.1108/TQM-03-2021-0083

Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage Publications. https://books.google.com.pk/books?hl=en&lr=&id=83L2EAAAQBAJ&oi

FIFA. (2023). AI and its application in football: The future of player performance analysis. https://www.fifa.com

Gába, A., Hartwig, T. B., Jašková, P., Sanders, T., Dygrýn, J., Vencálek, O., & Lonsdale, C. (2025). Reallocating time between 24-h movement behaviors for obesity management across the lifespan. Sports Medicine, 55(3), 641–654. https://doi.org/10.1007/s40279-024-02148-4

Guedri, A. (2023). The role of competitive intelligence in achieving participatory management within sports organizations. Business & Management Studies: An International Journal, 11(4), 1386–1409.

Hung, Y. L., Jiang, K. L., Chen, Y. L., & Chang, C. W. (2026). Development of an AI-driven comprehensive performance index for selecting the basketball annual first team. Journal of Mechanics in Medicine and Biology. https://doi.org/10.1142/S0219519426400440

Jeyanthi, P. M., Cvetkoska, V., & Kitanovikj, B. (2024). Decision intelligence in sports marketing. In Sports analytics: Data-driven sports and decision intelligence (pp. 35–53). Springer. https://doi.org/10.1007/978-3-031-63573-1_3

Laursen, G. H., & Thorlund, J. (2016). Business analytics for managers: Taking business intelligence beyond reporting. John Wiley & Sons.

Lee, J. T. (2019). Book review: Designing and conducting mixed methods research. https://doi.org/10.1177/1937586719832223

Liu, F., Wu, S., Zhou, J., Fan, M., & Tian, F. (2026). Understanding spectator loyalty in the Chinese Super League. Frontiers in Psychology, 17, 1776215. https://doi.org/10.3389/fpsyg.2026.1776215

Matović, N., & Ovesni, K. (2023). Interaction of quantitative and qualitative methodology in mixed methods research. International Journal of Social Research Methodology, 26(1), 51–65. https://doi.org/10.1080/13645579.2021.1964857

Mănescu, D. C. (2025). Big data analytics framework for decision-making in sports performance optimization. Data, 10(7), 116. https://doi.org/10.3390/data10070116

McKinsey Global Institute. (2021). The state of AI in 2021. https://www.mckinsey.com

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill. https://doi.org/10.1037/018882

Papadimitriou, S., & Virvou, M. (2025). Computer games for entertainment and education: A literature review and exploration on artificial intelligence integration. In Artificial intelligence–based games as novel holistic educational environments to teach 21st century skills (pp. 25–62). https://doi.org/10.1007/978-3-031-77464-5_2

Puce, L., Żmijewski, P., Cotellessa, F., Schenone, C., Ceylan, H. I., Bragazzi, N. L., & Trompetto, C. (2025). The role of artificial intelligence in sports training. Biology of Sport, 43(1), 355–367. https://doi.org/10.5114/biolsport.2026.152352

Queiroz-Ribeiro, F. D. F. M., Ferreira, C. A. A., Costa, M. D. S. S., Batista, R. C. G., & Costa, S. (2025). Emotional intelligence and decision making. Management (IJSM), 24(3), 1–43. https://doi.org/10.5585/2025.27859

Reddy, S. (2023). The role of data analytics in enhancing decision-making in sports management. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 4(2), 9–16.

Salimi, M., & Nazarian, A. (2022). The effect of organisational agility as mediator in the relationship between knowledge management, competitive advantage, and innovation in sport organisations. International Journal of Knowledge Management Studies, 13(3), 231–256. https://doi.org/10.1504/IJKMS.2022.123712

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7

Tilley, J. (2025). Dogs as a gateway to the good life: Using thematic analysis to explore the mechanisms underpinning dog ownership and human well-being. Qualitative Research in Psychology, 22(1), 15–36. https://doi.org/10.1080/14780887.2024.2364330

Van den Berg, L., Coetzee, B., & Mearns, M. (2020). Establishing competitive intelligence process elements in sport performance analysis and coaching. International Journal of Information Management, 52, 102071. https://doi.org/10.1016/j.ijinfomgt.2020.102071

Vollero, A., Sardanelli, D., & Manoli, A. E. (2025). Exploring the influence of football fan tokens on engagement. Journal of Interactive Marketing, 60(4), 421–435. https://doi.org/10.1177/10949968241305642

Watkins, R., & Leigh, D. (Eds.). (2009). Handbook of improving performance in the workplace: The handbook of selecting and implementing performance interventions (Vol. 2). John Wiley & Sons.

Wilson, P. J., & Kiely, J. (2023). Developing decision-making expertise in professional sports staff. Sports Medicine–Open, 9(1), 100. https://doi.org/10.1186/s40798-023-00629-w

Creative Commons License
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.

Copyright (c) 2026 Revista Inteligência Competitiva

Downloads

Não há dados estatísticos.