Data Science and Big Data Technologies Role in the Digital Economy

Новиков, С. В.

doi:10.18421/tem92-44

Cited by 36 publications

(19 citation statements)

References 8 publications

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“…Such co-development with stakeholders can also enable the integration of green elements and technical knowledge into the supply chain (Parmigiani et al, 2011). The Internet will help enterprises search for and analyze information about cutting-edge green technologies (Novikov, 2020) and reduce the transactional costs of searching, matching and negotiating. Enterprises can also collect data about consumers' green preferences from the market, which will offer more possibilities for green innovation development (Xie et al, 2015).…”

Section: Internet Development and Gtimentioning

confidence: 99%

How does the digital economy promote green technology innovation by manufacturing enterprises? Evidence from China

Ning

Yin

2022

Front. Environ. Sci.

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With the rapid development of the digital economy and the increasingly severe environmental issues, the role of the digital economy in green innovation has been attracting more attention; however, only a limited amount of research has been done in this area. Therefore, based on matching data at the city and manufacturing enterprise level in China during 2011–2018, this paper attempted to integrate the digital economy (more specifically, the Internet and digital finance) with resource allocation and green technology innovation together in a unified scheme. Our study confirmed that the digital economy could significantly promote green technology innovation by manufacturing enterprises, but that digital finance was the dominant feature. Resource allocation efficiency played a partial mediating role between digital economy and green technology innovation. Furthermore, considering the heterogeneity in enterprise ownership and industrial pollution, the digital economy had a more positive effect on green technology innovation in state-owned enterprises (SOEs) and high pollution industries. As for the heterogeneity of region, the Internet significantly contributed to green technology innovation in regions with different levels of development. In the eastern region of China, especially, the influence of digital finance on green technology innovation was more significant. In view of these findings, this study provides important insights for strengthening the integration of the digital economy with green transformation, emphasizing the rationality of resource allocation, and formulating policies for different enterprises.

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Section: Internet Development and Gtimentioning

confidence: 99%

How does the digital economy promote green technology innovation by manufacturing enterprises? Evidence from China

Ning

Yin

2022

Front. Environ. Sci.

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“…Ultimately, such systems have advantages and disadvantages. However, unless such digital tools are employed, both business and the state will simply be globally uncompetitive, and the quality of life will suffer [7,12,13].…”

Section: Resultsmentioning

confidence: 99%

Pandemic Economics: Problems and Prospects

Fedotova

2022

Russ. Engin. Res.

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The COVID-19 coronavirus poses a considerable and unexpected challenge to the global economy and the economy of each nation, even though specialists have repeatedly warned of a possible virus pandemic and the need for preparations. In the present work, the economic situation in pandemic conditions is analyzed in historical perspective. The associated problems and barriers are identified, and the potential impact on business processes is sketched. Possible approaches to improving the post-virus economy and the world as a whole are proposed.

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“…The results of the experiment show that this randomized decision tree algorithm classifies companies with large risk, large risk, small risk, and small risk with improved classification accuracy, which has been determined by bank staff to be a practical reference for predicting bank risk. However, because of the small number of large risk data in the training dataset, this branch is not sufficiently trained, making the stochastic decision tree algorithm less accurate than the other branches for large risk classification [ 25 ].…”

Section: Experimental Validationmentioning

confidence: 99%

Financial Data Analysis and Application Based on Big Data Mining Technology

Cheng

2022

Computational Intelligence and Neuroscience

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We provide a brief overview of the connotation and characteristics of data mining technology in the era of big data, analyze the feasibility of data mining technology in business management from the economic and technical perspectives, and propose specific application suggestions according to the content and requirements of business management. This paper describes in detail the principles and steps of using the weighted plain Bayesian algorithm and the decision tree algorithm to analyze students’ performance; firstly, we need to obtain the plain Bayesian analysis model of college students’ learning literacy in physical education and the C4.5 graduation literacy analysis model, and then use certain rules to combine the weighted plain Bayesian algorithm and the decision tree algorithm to obtain the WNB-C4.5 college students’ learning literacy analysis model. In addition, in the prediction of financial risks, the classification scheme can be used in the judgment of violation of regulations, but the most used classification scheme is the decision tree. Experiments show that the effectiveness of this scheme in data mining for financial companies is increased by 2% compared to the benchmark method.

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Data Science and Big Data Technologies Role in the Digital Economy

Cited by 36 publications

References 8 publications

How does the digital economy promote green technology innovation by manufacturing enterprises? Evidence from China

How does the digital economy promote green technology innovation by manufacturing enterprises? Evidence from China

Pandemic Economics: Problems and Prospects

Financial Data Analysis and Application Based on Big Data Mining Technology

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