Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization

Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization

Rui Luan, Ping Xu
Copyright: © 2024 |Pages: 21
DOI: 10.4018/IRMJ.343095
Article PDF Download
Open access articles are freely available for download

Abstract

In today's society, rural areas face challenges such as complex terrain and uneven population distribution, and infrastructure construction is exceptionally difficult. At the same time, poor information transmission and low communication efficiency have also become a major obstacle to the promotion of the digital economy in rural areas. This study aims to use gradient advancement models to identify potential risks in the growth of the digital economy sector related to rural revitalization. In this study, we used an enhanced hierarchical gradient boosting algorithm. The research results indicate that the introduction of this technology can provide us with a more comprehensive and reliable risk prediction model, thereby more scientifically assisting the development and decision-making of the digital economy in rural areas. This article provides a new perspective and solutions for development issues in rural areas, promoting sustainable development and economic growth in rural areas.
Article Preview
Top

Literature Review

The percentage of digitalized agriculture will reach 22.5% by 2020, while the percentage of digitalized quality safety traceability will reach 22.1%. Livestock and poultry output, as well as the cultivation of their facilities, will rise to levels that outpace those of the whole country (Zhang, 2022). For rural economies to thrive, it is crucial to increase the degree of digitization in agricultural output (Zhao et al., 2022). Establishing a new pattern of coordinated development of e-commerce services, packaging and transportation, and other related industries through the digital sales model, centered on the sale of local characteristics, is essential if rural e-commerce is to realize its full potential in large-scale industrial development (Henrique et al., 2019). One of the most visible indicators of the growth of the digital economy in rural regions is the rise of online shopping (Petropoulos et al., 2020). As a result of the spread of digital technology into China's rural areas, analysts anticipate that e-commerce sales from rural areas will increase by a factor of roughly six by 2021 (Huateng et al., 2021). As a result of rising consumer interest in buying food and other farm goods online, the number of marketplaces that cater to this niche has grown (Obthong et al., 2020). Agricultural commodity trade has increased during the last five years. E-commerce in rural areas has helped boost sales on a massive scale, made it easier for information to flow more smoothly, and leveled the playing field between farmers in different parts of the country and a sizable market (Wei et al., 2020).

The agriculture sector is a prime example of how scientific and technological innovation may positively impact economic growth due to the many ways in which it has been used there (Vadlamudi et at., 2020). As part of a broader drive to revitalize rural areas, today's farmers have embraced the digital age, therefore advancing agricultural research and technology. Science and technology in agriculture are directly responsible for 60.7% of the development made thus far (Schwartz, 2022). Insistence on using cutting-edge innovation has fueled the demonstration effect, leading to a number of game-changing discoveries (Lee et al., 2011).

The development of new technologies has had a significant effect on farming in rural areas (Zhang et al., 2021). As an example, we discuss rural digital finance, investigating how big data and other technologies may be utilized to address the funding gaps that exist, overcome the unique challenges of rural financing, and ultimately contribute to the growth of the rural digital economy. New enterprises are the best evidence of industrialization in rural regions. New growth is being sparked in rural economies and the new economy as a result of the use of information technology and electronic commerce to address the supply-side imbalance. In 2020, several new rural companies mimicking rural tourism sprung up in response to the New Coronary Pneumonia pandemic. The rural tourist sector is expected to begin its revival in 2021. Economic growth in China stands to benefit from ecotourism, which is expected to attract over 2.1 billion visitors to the nation by 2020. In 2020, there will be an estimated 10.1 million city dwellers who have moved to the country in search of better economic and creative opportunities (Tao, 2018). There is a new type of rural business that is contributing to the digital transformation of rural areas by maintaining their own distinctive products and services and gaining product appreciation based on local peculiarities (Johnson & Noguera,2012).

Complete Article List

Search this Journal:
Reset
Volume 37: 1 Issue (2024)
Volume 36: 1 Issue (2023)
Volume 35: 4 Issues (2022): 3 Released, 1 Forthcoming
Volume 34: 4 Issues (2021)
Volume 33: 4 Issues (2020)
Volume 32: 4 Issues (2019)
Volume 31: 4 Issues (2018)
Volume 30: 4 Issues (2017)
Volume 29: 4 Issues (2016)
Volume 28: 4 Issues (2015)
Volume 27: 4 Issues (2014)
Volume 26: 4 Issues (2013)
Volume 25: 4 Issues (2012)
Volume 24: 4 Issues (2011)
Volume 23: 4 Issues (2010)
Volume 22: 4 Issues (2009)
Volume 21: 4 Issues (2008)
Volume 20: 4 Issues (2007)
Volume 19: 4 Issues (2006)
Volume 18: 4 Issues (2005)
Volume 17: 4 Issues (2004)
Volume 16: 4 Issues (2003)
Volume 15: 4 Issues (2002)
Volume 14: 4 Issues (2001)
Volume 13: 4 Issues (2000)
Volume 12: 4 Issues (1999)
Volume 11: 4 Issues (1998)
Volume 10: 4 Issues (1997)
Volume 9: 4 Issues (1996)
Volume 8: 4 Issues (1995)
Volume 7: 4 Issues (1994)
Volume 6: 4 Issues (1993)
Volume 5: 4 Issues (1992)
Volume 4: 4 Issues (1991)
Volume 3: 4 Issues (1990)
Volume 2: 4 Issues (1989)
Volume 1: 1 Issue (1988)
View Complete Journal Contents Listing