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<p>This paper is based on big data analysis technology to process the data related to rural construction and analyze the rural financial service development measurement after constructing the rural financial service indicator system combined with the principal component analysis method. The entropy value method is utilized to measure the constructed rural development index system and assess the development level of rural financial services for rural revitalization. On this basis, the benchmark regression model of rural financial services and rural revitalization is constructed, descriptive statistics are carried out, and the development effect of rural financial services on rural revitalization is analyzed after passing the smoothness test to explore its development path. The results show that the development measure of rural financial services from 1978 to 2021 rises from less than 0.5 to more than 0.7, and the development index of rural revitalization also rises by about 0.1, and the levels of both rural financial services and rural revitalization are rising. The mean value of the rural revitalization index is 0.282, the minimum value of the rural revitalization index is 0.143, and the maximum value is 0.494, and all the variables of rural financial services on rural revitalization are significant at the 1% level, with a significant impact. Based on this study, rural financial reform is synergistically promoted in three major aspects, namely, coordinating all kinds of financial organizations, innovating financial support for agricultural products and strengthening financial supervision and prevention.</p>
</abstract>

This paper is based on big data analysis technology to process the data related to rural construction and analyze the rural financial service development measurement after constructing the rural financial service indicator system combined with the principal component analysis method. The entropy value method is utilized to measure the constructed rural development index system and assess the development level of rural financial services for rural revitalization. On this basis, the benchmark regression model of rural financial services and rural revitalization is constructed, descriptive statistics are carried out, and the development effect of rural financial services on rural revitalization is analyzed after passing the smoothness test to explore its development path. The results show that the development measure of rural financial services from 1978 to 2021 rises from less than 0.5 to more than 0.7, and the development index of rural revitalization also rises by about 0.1, and the levels of both rural financial services and rural revitalization are rising. The mean value of the rural revitalization index is 0.282, the minimum value of the rural revitalization index is 0.143, and the maximum value is 0.494, and all the variables of rural financial services on rural revitalization are significant at the 1% level, with a significant impact. Based on this study, rural financial reform is synergistically promoted in three major aspects, namely, coordinating all kinds of financial organizations, innovating financial support for agricultural products and strengthening financial supervision and prevention.

Development path of rural financial services for rural revitalization based on big data analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper is based on big data analysis technology to process the data related to rural construction and analyze the rural financial service development...

Development path of rural financial services for rural revitalization based on big data analysis

Data publikacji: 18 gru 2023

Zakres stron: -

Otrzymano: 13 sty 2023

Przyjęty: 28 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01541

Słowa kluczowe
Big data analysis, Principal component analysis, Entropy value method, Regression model, Rural financial services

© 2023 Kangkang Cheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Development path of rural financial services for rural revitalization based on big data analysis

Data publikacji: 18 gru 2023

Zakres stron: -

Otrzymano: 13 sty 2023

Przyjęty: 28 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01541

Słowa kluczoweBig data analysis, Principal component analysis, Entropy value method, Regression model, Rural financial services

© 2023 Kangkang Cheng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Big data analysis, Principal component analysis, Entropy value method, Regression model, Rural financial services