Digital Logistics Management in Olympic-Scale Sports Events: The Role of Sensor Data and Integration Potential

Abstract

Olympic-scale sporting events have evolved beyond mere showcases of athletic performance into complex, multi-stakeholder organizations driven by digitalization and integrated logistics systems. In this context, sensor-based technologies have become increasingly critical to digital logistics planning. In particular, the sensor systems implemented during the Rio 2016, Tokyo 2020, and Paris 2024 Olympics have enabled more effective coordination of elements such as crowd management, environmental conditions, transportation infrastructure, and resource allocation through real-time data flows. This study employs qualitative document analysis and case comparison methods to explore how sensor data can function not only as a passive monitoring tool but also as an active decision support mechanism. Based on the findings, a four-layered conceptual model is proposed to guide the integration of sensor data into digital logistics processes: data collection, data processing, decision support, and intervention planning. This structure enhances predictability in large-scale sports events while offering sustainable and strategic solutions for resource management. The study aims to contribute to the existing gap in the sports logistics literature and to provide practitioners with a strategic framework for planning and operational efficiency in complex event settings. Ultimately, the integration of sensor technologies into logistics planning is positioned as a key enabler of agility, responsiveness, and sustainability in contemporary mega-event management.

Keywords

• sports logistics
• digitalization
• sensor data
• decision support systems
• mega-events

Olimpik Ölçekli Spor Etkinliklerde Dijital Lojistik Yönetimi: Sensör Verilerinin Rolü ve Entegrasyon Potansiyeli

Abstract

Olimpik ölçekli spor etkinlikleri, günümüzde yalnızca atletik performansların sergilendiği alanlar olmaktan çıkmış; çok paydaşlı, dijitalleşmiş ve entegre lojistik sistemlerle yürütülen karmaşık organizasyonlara dönüşmüştür. Bu bağlamda, sensör tabanlı teknolojiler dijital lojistik planlama süreçlerinde kritik bir rol üstlenmektedir. Özellikle Rio 2016, Tokyo 2020 ve Paris 2024 Olimpiyatları’nda kullanılan sensör sistemleri; izleyici yoğunluğu, çevresel koşullar, ulaşım altyapısı ve kaynak yönetimi gibi unsurların daha etkin şekilde koordine edilmesini sağlamıştır. Bu çalışma, nitel belge incelemesi ve vaka karşılaştırması yöntemleriyle, sensör verilerinin yalnızca pasif bir izleme aracı olarak değil, aynı zamanda aktif bir karar destek mekanizması olarak nasıl kullanılabileceğini analiz etmektedir. Elde edilen bulgular doğrultusunda, sensör verilerinin dijital lojistik süreçlerine entegrasyonunu sağlayacak dört katmanlı bir kavramsal model önerilmektedir: veri toplama, veri işleme, karar destek ve müdahale planlaması. Bu yapı, büyük ölçekli spor organizasyonlarında öngörülebilirliği artırmakta, kaynak kullanımında ise sürdürülebilir ve stratejik çözümler sunmaktadır. Çalışma, spor lojistiği alanındaki literatür boşluklarına katkı sağlamayı ve uygulayıcılara planlama süreçlerinde yol göstermeyi amaçlamaktadır. Sonuç olarak, sensör teknolojilerinin lojistik planlamaya entegrasyonu, mega etkinlik yönetiminde çeviklik, hızlı tepki verebilirlik ve sürdürülebilirlik için kritik bir kolaylaştırıcı olarak konumlanmaktadır.

Keywords

• spor lojistiği
• dijitalleşme
• sensör verisi
• karar destek sistemleri
• mega etkinlikler

Ethical Statement

Etik kurul kararı gerektirmemektedir.

References

1. Aslan, B. G., Yazıcı, K., Ünal Ankaya, F., & Balık, G. (2019). Olimpiyat köyleri, ülkeye katkıları, Dünya’dan ve Türkiye’den örnekler. Ulusal Çevre Bilimleri Araştırma Dergisi, 2(1), 1–10.
2. Baca, A., Dabnichki, P., Hu, C. W., Kornfeind, P., & Exel, J. (2022). Ubiquitous computing in sports and physical activity—Recent trends and developments. Sensors, 22(21), 8370. https://doi.org/10.3390/s22218370
3. Bai, Z., & Bai, X. (2021). Sports big data: Management, analysis, applications, and challenges. Complexity, 2021, Article ID 6629872. https://doi.org/10.1155/2021/6629872
4. Berelson, B. (1952). Content analysis in communication research. Hafner.
5. Berg, B. L., & Lune, H. (2012). Qualitative research methods for the social sciences (8th ed.). Pearson Education.
6. Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
7. Cao, L. (2022). Design and optimization of a decision support system for sports training based on data mining technology. Scientific Programming, 2022, Article 1846345. https://doi.org/10.1155/2022/1846345
8. Charmaz, K. (2016). Constructing grounded theory: A practical guide through qualitative analysis (2nd ed.). SAGE.

9. Corbin, J., & Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory (3rd ed.). SAGE.
10. Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE.
11. Çavuş, M. F. (2024). Mega spor etkinliklerinin spor turizmi üzerindeki etkileri. Spor Bilimleri Dergisi, 35(2), 45–60. https://doi.org/10.33689/spormetre.1404163
12. Çetin, A. (2019). Mega spor etkinliklerinde spor mirası konseptinin gerekliliği. Sağlık ve Spor Bilimleri Dergisi, 2(2), 66–73.
13. Downe-Wamboldt, B. (1992). Content analysis: Method, applications, and issues. Health Care for Women International, 13(3), 313–321. https://doi.org/10.1080/07399339209516006
14. Elbanna, S., Elsharnouby, T., Al-Fayoumi, N., & Abuzayed, B. (2025). Beyond the pitch: Logistics and sustainability at the FIFA World Cup. In S. Elbanna, T. Elsharnouby, A. Aljafari, & T. Fatima (Eds.), The FIFA World Cup Qatar 2022: Unveiling insights beyond the pitch (pp. 301–315). Springer.
15. Er, B., & Güzel, P. (2019). Mega spor etkinlikleri ve sürdürülebilirlik. CBÜ Beden Eğitimi ve Spor Bilimleri Dergisi, 14(2), 199–221. https://doi.org/10.33459/cbubesbd.556623
16. Esentaş, M., Güzel, P., Özbey, S., & Çelik, E. (2018). Mega spor organizasyonları sporcularının gözüyle olimpik hareket ve olimpizm algıları. Gaziantep Üniversitesi Spor Bilimleri Dergisi, 3(4), 32–47. https://doi.org/10.31680/gaunjss.477512
17. Hussein, M., Karam, A., Eltoukhy, A. E., Darko, A., & Zayed, T. (2023). Optimized multimodal logistics planning of modular integrated construction using hybrid multi-agent and metamodeling. Automation in Construction, 145, 104637. https://doi.org/10.1016/j.autcon.2022.104637
18. International Olympic Committee. (2018). NEC unveils its facial recognition system for Tokyo 2020. https://www.olympics.com/ioc/news/la-technologie-d-intel-apportera-plusieurs-innovations-durant-les-jeux-de-tokyo-2020
19. International Olympic Committee. (2022). IOC annual report 2021: Faster, higher, stronger—Together (p. 137). https://stillmed.olympics.com/media/Documents/International-Olympic-Committee/Annual-report/IOC-Annual-Report-2021.pdf
20. International Organization for Standardization. (2024a). ISO 20121:2024—Event sustainability management systems: Requirements with guidance for use (2nd ed.). https://www.iso.org/obp/ui/en/#iso:std:iso:20121:ed-2:v1:en
21. International Olympic Committee. (2024b). AI and tech innovations at Paris 2024: A game changer in sport. https://www.olympics.com/ioc/news/ai-and-tech-innovations-at-paris-2024-a-game-changer-in-sport
22. International Olympic Committee. (2024c). Paris 2024: Sustainable Games. https://www.olympics.com/ioc/paris-2024-sustainable-games
23. International Olympic Committee. (2025). IOC annual reports. https://www.olympics.com/ioc/documents/international-olympic-committee/ioc-annual-report
24. Kahriman, C., & Yıldırım, H. M. (2019). Etkinliklerin öteki yüzü: Olimpiyat oyunları örneği. Türk Turizm Araştırmaları Dergisi, 3(4), 1304–1319. https://doi.org/10.26677/TR1010.2019.243
25. Karlaftis, M. G., Kepaptsoglou, K., Stathopoulos, A., & Starra, A. (2004). Planning public transport networks for the 2004 Summer Olympics with decision support systems. Transportation Research Record, 1887(1), 71–82. https://doi.org/10.3141/1887-10
26. Le Monde. (2024). Paris 2024: Controversial AI-led video surveillance put to the test during Olympics. https://www.lemonde.fr/en/pixels/article/2024/07/24/paris-2024-controversial-ai-led-video-surveillance-put-to-the-test-during-olympics_6697267_13.html
27. Minis, I., Paraschi, M., & Tzimourtas, A. (2006). The design of logistics operations for the Olympic Games. International Journal of Physical Distribution & Logistics Management, 36(8), 621–642. https://doi.org/10.1108/09600030610694241
28. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE.
29. Özdemir, H., & Sevim, G. (2022). Etkinlik lojistiği: Lojistik firmaları üzerine nitel bir araştırma. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 21(42), 621–642. https://dergipark.org.tr/tr/download/article-file/1438681
30. Özsoy, D., Özsoy, Y., & Karakuş, O. (2023). Endüstri 5.0’da spor. Fenerbahçe Üniversitesi Spor Bilimleri Dergisi, 3(2), 83–94. https://dergipark.org.tr/tr/download/article-file/2915688
31. Polo, A., & Rocca, P. (2022). Decision support system for mobility and transportation management in large sport events. In 2022 IEEE International Workshop on Sport, Technology and Research (STAR) (pp. 84–88). IEEE. https://doi.org/10.1109/STAR55997.2022.9851509
32. Pott, C., Breuer, C., & ten Hompel, M. (2023). Sport logistics: Considerations on the nexus of logistics and sport management and its unique features. Logistics, 7(3), 57. https://doi.org/10.3390/logistics7030057
33. Reuters. (2018). Tokyo 2020 Olympics to up security with facial recognition system. https://www.reuters.com/article/sports/corrected-tokyo-2020-olympics-to-up-security-with-facial-recognition-system-idUSKBN1KS0C5/
34. Reuters. (2024). How France plans to use AI to keep Paris 2024 safe. https://www.reuters.com/sports/olympics-how-france-plans-use-ai-keep-paris-2024-safe-2024-03-08/
35. Senkal, T., & Demir, A. (2024). 2024 Paris Olimpiyat Oyunlarına inovatif (yenilikçi) bakış. International Journal of Holistic Health, Sports and Recreation, 3(2), 63–83.
36. Şimşek, A., & Devecioğlu, S. (2024). Spor teknolojileri tutum ölçeği: Bir ölçek geliştirme çalışması. Beden Eğitimi ve Spor Bilimleri Dergisi, 18(2), 161–176.
37. Terekli, M. S., & Çobanoğlu, H. O. (2018). Mega spor organizasyonlarının ekonomik etkilerinin Türkiye açısından avantaj ve dezavantajları. The Journal of Social Science, 2(3), 95–107. https://doi.org/10.30520/tjsosci.429220
38. Yang, L., Amin, O., & Shihada, B. (2024). Intelligent wearable systems: Opportunities and challenges in health and sports. ACM Computing Surveys, 56(7), 1–42. https://doi.org/10.1145/3634150
39. Yu, L., Ling, P., & Zhang, H. (2010). Study on the decision support system of techniques and tactics in net sports and the application in Beijing Olympic Games. In Proceedings of the 2010 Second WRI Global Congress on Intelligent Systems (pp. 170–174). IEEE. https://doi.org/10.1109/GCIS.2010.139
40. Weber, R. P. (1990). Basic content analysis (2nd ed.). SAGE.
41. Wang, Z. (2025). Research on dynamic evaluation and decision support system optimization of Olympic Games based on AHP-based multi-criteria decision-making oriented towards globalization and sustainable development. Advances in Engineering Technology Research, 13, 1420–1426.