Author(s)

Yadong Zhang ¹

Affiliation(s)

¹ Sports Department, Beijing Second Foreign Studies University, Beijing, China

Corresponding Author

Yadong Zhang

ABSTRACT

Sports tourism has promoted the development of a series of related industries including catering, accommodation, entertainment, transportation, communications, clothing manufacturing, food processing, construction and even finance and insurance, forming a huge industrial chain system. It effectively meets the needs of sports enthusiasts and travel enthusiasts in sports experience, leisure and entertainment, rehabilitation and health care, and has a broad market space. This article aims to study the construction of sports tourism information data model based on smart big data and the development of sports economy. This paper constructs a simulation system model of sports tourism industry operation. Through the various elements in the causal feedback loop in the operation of the sports tourism industry system, the main variables involved in the sports tourism industry operation system model are analyzed and a mathematical model is constructed. It also constructed a dynamic evolution model for the integration and development of the sports tourism industry, theoretically discussed the existence and stability of the industry integration cycle, and provided indicators for judging the operation stability of the sports tourism industry integration development system, the existence of the integration cycle, and the existence of the integration cycle. The experimental data shows that the highest correlation coefficient obtained by the simulation experiment is 0.992, and the lowest is 0.9026, indicating that the result data of the system simulation simulation is not much different from the actual data, and the data is valid. The dynamic evolution model constructed in this article predicts that not only the number of domestic and international tourists, but also tourism income will increase significantly in the next ten years. It is predicted that sports tourism income will increase by about 320% over the current ten years in the next ten years.

KEYWORDS

Big Data, Mobile Internet, Sports Tourism, Sports Econoour

CITE THIS PAPER

Yadong Zhang, Data Model of Sports Tourism and Economic Information Based on Intelligent Video Imaging Technology. Tourism Management and Technology Economy (2024) Vol. 7: 39-49. DOI: http://dx.doi.org/10.23977/tmte.2024.070305.

REFERENCES

[1] Xu W, Zhou H, Cheng N, et al. Internet of Vehicles in Big Data Era. IEEE/CAA Journal of Automatica Sinica, 2018, 5 (1): 19-35.
[2] Mann L. Left to Other Peoples' Devices? A Political Econoour Perspective on the Big Data Revolution in Development. Development and Change, 2018, 49 (1): 3-36.
[3] Wang X, Zhang Y, Leung V, et al. D2D Big Data: Content Deliveries over Wireless Device-to-Device Sharing in Large Scale Mobile Networks. IEEE Wireless Communications, 2018, 25 (1): 32-38.
[4] Al-Ali A R, Zualkernan I A, Rashid M, et al. A smart home energy management system using IoT and big data analytics approach. IEEE Transactions on Consumer Electronics, 2018, 63 (4): 426-434.
[5] Chen Y, Chi Y. Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation. IEEE Signal Processing Magazine, 2018, 35 (4): 14-31.
[6] Zhang N, Yang P, Ren J, et al. Synergy of Big Data and 5G Wireless Networks: Opportunities, Approaches, and Challenges. IEEE Wireless Communications, 2018, 25 (1): 12-18.
[7] Wu C, Zapevalova E, Chen Y, et al. Time Optimization of Multiple Knowledge Transfers in the Big Data Environment. Computers Materials & Continua, 2018, 54 (3): 269-285.
[8] Meng X L. Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election. The Annals of Applied Statistics, 2018, 12 (2): 685-726.
[9] Al-Salim A M, El-Gorashi T, Lawey A Q, et al. Greening Big Data Networks: The Impact of Veracity. Iet Optoelectronics, 2018, 12 (3): 126-135.
[10] Vayena E, Blasimme A. Health Research with Big Data: Time for Systemic Oversight. The Journal of Law Medicine & Ethics, 2018, 46 (1): 119-129.
[11] Chang Z, Lei L, Zhou Z, et al. Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era. IEEE Wireless Communications, 2018, 25 (3): 28-35.
[12] Phinyomark A, Petri G, E Ibáñez-Marcelo, et al. Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions. Journal of Medical & Biological Engineering, 2018, 38 (2): 244-260.
[13] Chu J F, Wu J, Song M L. An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application. Annals of Operations Research, 2018, 270 (1): 105-124.
[14] Yu L, Zhao Y, Ling T, et al. Online big data-driven oil consumption forecasting with Google trends. International Journal of Forecasting, 2018, 35 (1): 213-223. 
[15] Lamba K, Singh S P. Modeling Big Data Enablers for Operations and Supply Chain Management. The International Journal of Logistics Management, 2018, 29 (2): 629-658.
[16] Muhammad S S, Dey B L, Weerakkody V. Analysis of Factors that Influence Customers' Willingness to Leave Big Data Digital Footprints on Social Media: A Systematic Review of Literature. Information Systems Frontiers, 2018, 20 (3): 559-576.
[17] Lei G, Ning Z, Hou W, et al. Quick Answer for Big Data in Sharing Econoour: Innovative Computer Architecture Design Facilitating Optimal Service-Demand Matching. Automation Science and Engineering, IEEE Transactions on, 2018, 15 (4): 1494-1506.

Sponsors, Associates, and Links

---

• Information Systems and Economics
  
  
• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Journal of Computational and Financial Econometrics
  
  
• Financial Engineering and Risk Management
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics