Statistical Analysis-Based Chinese Sports Industry Listed Companies Competition Factor and Strategic Performance

Guang, Lu; Zhou, Xianjiang; Li, Shali

doi:10.1166/jctn.2016.6243

Cited by 4 publications

(2 citation statements)

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“…According to the advantages and characteristics of the coast, they used the SWOT method to study the impact of sports economic development on the development trend of coastal tourism. Huo [25] believed that listed companies in the sports economic industry are an industry that has only recently emerged, and China's listed companies in the sports industry are relatively weak. He analyzed the development trend of China's sports economy and the necessity of the sports industry for China's comprehensive economic development from the perspective of the economic strategy of listed companies.…”

Section: Related Workmentioning

confidence: 99%

Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis

2022

Mathematical Problems in Engineering

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The sports economy also occupies a main part of the national economy, which requires professionals to be able to evaluate the development of the sports economy. The sports industry will generate cumbersome data, which are important for the future development trend of the sports economy. This research will collect a large amount of data from the sports industry, data mining technology, and neural network method that will be used to fully mine and predict the relationship between sports economic data, and it will provide corresponding management references for sports industry companies. Some important statistical parameters will be used to evaluate the feasibility of data mining techniques and neural network methods in sports economic management. The research results show that the error of data mining technology in the classification of sports economy is within 2.54%, and the prediction error of the neural network method is also within 3.2%. This shows that the data mining technology proposed in this study is feasible for classification and prediction application in sports economic management. Once the forecast data of the sports economy are output through the output layer, the sports economy managers can rely on these data to manage and adjust the relevant factors of the sports economy.

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Section: Related Workmentioning

confidence: 99%

Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis

2022

Mathematical Problems in Engineering

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“…Proof of Equity Algorithm. The POW algorithm needs to consume a lot of computing power for "mining," and this part of the computing power has not received actual benefits [11,12]. Therefore, a consensus algorithm based on Proof of Stake (POS) is proposed, which competes for the right to bookkeeping through the number of coins held and the holding time.…”

Section: Bt-related Algorithmsmentioning

confidence: 99%

Research on Optimization of Blockchain Network and Data Communication in the Ecological Structure of Sports Industry

Kim

Ding

2021

Wireless Communications and Mobile Computing

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Problems such as excessive centralization of sports industry operations, unclear value, and lack of IP protection hinder the benign interaction between various formats of the sports industry and the healthy operation of the industrial ecosystem. This article is aimed at studying the use of the decentralization, openness and transparency, smart contracts, copyright traceability, and other characteristics of the BT to construct a PCMR model, which can solve the pain points faced by the sports industry ecosystem in a targeted manner, and forming a way to reconstruct trust, the specific implementation path of the integration of BT and sports industry with mechanism as the core. This paper proposes blockchain network and data communication algorithms such as consensus algorithm, signature core algorithm, and practical Byzantine fault-tolerant algorithm to provide technical support for the application of blockchain technology in the sports industry ecosystem and, at the same time, provide technical support for blockchain network and data communication. The feasibility analysis of the application of the sports industry ecosystem is proposed, and the implementation path of the blockchain network and data communication to reconstruct the sports industry ecosystem is analyzed. Finally, the empirical test of the support of blockchain sports to the sports industry is carried out. By analyzing the panel data of 240 observations of 48 listed companies in 5 years as a sample of the sports industry, the experimental results show that the dominant modulus of the sample does not have other differences, and the leftovers all pass significance test at the 10% level at least, denoting that the fundamental sample is more rational.

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Sports Game Management Method Based on Intelligent Computer Computing

Shen

2020

Advances in Intelligent Systems and Computing

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Statistical Analysis-Based Chinese Sports Industry Listed Companies Competition Factor and Strategic Performance

Cited by 4 publications

References 0 publications

Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis

Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis

Research on Optimization of Blockchain Network and Data Communication in the Ecological Structure of Sports Industry

Sports Game Management Method Based on Intelligent Computer Computing

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