Research on the digital transaction model of the sports industry chain based on blockchain technology

被引:0
作者
Wei, Heng [1 ]
Zhang, Yuze [2 ]
机构
[1] Shanxi Univ, Sch Econ & Management, Taiyuan 030006, Peoples R China
[2] Shanxi Univ, Coll Phys Educ, Taiyuan 030006, Peoples R China
关键词
Blockchain; Digital transactions; Sports industry chain; Smart contracts; Decentralization;
D O I
10.1038/s41598-025-10045-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The rapid digital transformation of the sports industry has opened up unprecedented opportunities for efficiency, transparency, and innovation. Traditional transaction models still suffer from significant challenges, including centralized control, lack of trust, and inefficiencies in revenue distribution. These issues often stem from reliance on intermediaries that introduce risks such as data manipulation, high operational costs, and delays in processing financial transactions. Blockchain technology presents a promising solution by enabling decentralized, secure, and transparent transactions, fostering greater trust among all stakeholders within the sports ecosystem. Existing approaches to digital transactions in the sports industry primarily depend on centralized financial institutions and third-party service providers, which not only limit transparency but also create barriers to financial inclusivity for athletes, clubs, sponsors, and fans. To address these critical limitations, we propose a blockchain-based digital transaction model that leverages smart contracts and distributed ledger technology (DLT) to enhance the efficiency, security, and fairness of transactions across the entire sports industry value chain. Our model integrates key economic principles with advanced network analysis to optimize revenue distribution, mitigate fraudulent activities, and enable real-time transaction verification. Through extensive simulations and empirical analysis, our results demonstrate a significant improvement in transaction speed, cost reduction, and overall transparency compared to conventional models. By decentralizing financial transactions, the proposed approach not only enhances financial inclusivity for all participants but also aligns with the broader vision of sustainable and equitable growth in the digital sports economy.
引用
收藏
页数:20
相关论文
共 48 条
[1]  
Ahmed S., 2022, Circuits, systems, and signal processing
[2]   The healing power of Camellia japonica L.: how flower types influence urban residents' physiological and psychological wellbeing [J].
Ai, Lijiao ;
Wang, Huan ;
Feng, Yilong ;
Li, Ting ;
Li, Zezhou ;
Zou, Min ;
Zhang, Qiaoyong .
FRONTIERS IN PSYCHOLOGY, 2025, 16
[3]   RNN-LSTM: From applications to modeling techniques and review [J].
Al-Selwi, Safwan Mahmood ;
Hassan, Mohd Fadzil ;
Abdulkadir, Said Jadid ;
Muneer, Amgad ;
Sumiea, Ebrahim Hamid ;
Alqushaibi, Alawi ;
Ragab, Mohammed Gamal .
JOURNAL OF KING SAUD UNIVERSITY COMPUTER AND INFORMATION SCIENCES, 2024, 36 (05)
[4]   The financial impact of financial fair play regulation: Evidence from the English premier league [J].
Alabi, Mobolaji ;
Urquhart, Andrew .
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 2024, 92
[5]   Coronavirus Disease 2019 Pandemic: Impact Caused by School Closure and National Lockdown on Pediatric Visits and Admissions for Viral and Nonviral Infections-a Time Series Analysis [J].
Angoulvant, Francois ;
Ouldali, Naim ;
Yang, David Dawei ;
Filser, Mathilde ;
Gajdos, Vincent ;
Rybak, Alexis ;
Guedj, Romain ;
Soussan-Banini, Valerie ;
Basmaci, Romain ;
Lefevre-Utile, Alain ;
Brun-Ney, Dominique ;
Beaujouan, Laure ;
Skurnik, David .
CLINICAL INFECTIOUS DISEASES, 2021, 72 (02) :319-322
[6]   Optimized communication during risk disclosure to reduce nocebo headache after lumbar puncture-a study protocol for a randomized controlled clinical trial [J].
Asan, Livia ;
Gronen, Johanna Sophie ;
Peters, Lorenz ;
Kleinschnitz, Christoph ;
Holle-Lee, Dagny ;
Benson, Sven ;
Bingel, Ulrike .
FRONTIERS IN PSYCHOLOGY, 2025, 16
[7]   Detecting and date-stamping bubbles in fan tokens [J].
Assaf, Ata ;
Demir, Ender ;
Ersan, Oguz .
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE, 2024, 92 :98-113
[8]  
Choi K., 2021, Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines
[9]   Stress-Related Hormonal and Psychological Changes to Simulated and Official Judo Black Belt Examination in Older Tori and Adult Uke: An Exploratory Observational Study [J].
Ciaccioni, Simone ;
Martusciello, Francesca ;
Di Credico, Andrea ;
Guidotti, Flavia ;
Conte, Daniele ;
Palumbo, Federico ;
Capranica, Laura ;
Di Baldassarre, Angela .
SPORTS, 2024, 12 (11)
[10]   Intergenerational Judo: Synthesising Evidence- and Eminence-Based Knowledge on Judo across Ages [J].
Ciaccioni, Simone ;
Perazzetti, Andrea ;
Magnanini, Angela ;
Kozsla, Tibor ;
Capranica, Laura ;
Doupona, Mojca .
SPORTS, 2024, 12 (07)