Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)

Research and Analysis of New Urbanized Rural Development Based on the Context of Big Data Development

Authors
Bingchuan Wang1, Xu Yifan2, *
1School of Architecture, Planning and Landscape, Newcastle University, Newcastle Tyne Upon, NE1 7RU, UK
2Sichuan Agricultural University, Chengdu, Sichuan, China
*Corresponding author. Email: 704082285@qq.com
Corresponding Author
Xu Yifan
Available Online 30 December 2023.
DOI
10.2991/978-94-6463-326-9_7How to use a DOI?
Keywords
Big data; rural development; agricultural optimization; Rural revitalization
Abstract

The two strategies of rural revitalisation and new urbanisation have a symbiotic relationship of mutual promotion and mutual penetration. In view of this, this paper, on the basis of the evaluation index system of the relevant literature of scholars such as Yu Yunfeng and Lei Na, takes into full consideration the connotation and ultimate goal of the two strategies of rural revitalisation and new urbanisation and constructs the evaluation index system of rural revitalisation and new urbanisation in accordance with this. Principles for the construction of the indicator system: the principle of scientificity - the selection of indicators should be in accordance with the objective laws of economic development and the actual development situation of the region, and based on the principle of scientificity, to ensure that the selection of indicators can truly reflect the characteristics and situation of urban and rural development. Systematic principle - The selection of indicators should focus on the logic between indicators, closely link independent indicators, and accurately present the intrinsic connection between the two systems of rural revitalisation and new urbanisation. Typicality principle, availability - the accuracy of the original data is the key to constructing a comprehensive evaluation index system, at the same time, there are certain differences in the calibre of the data statistics of various regions, therefore, the selection of each indicator should take into account the availability of the original data as well as the operability.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

Volume Title
Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
30 December 2023
ISBN
10.2991/978-94-6463-326-9_7
ISSN
2589-4900
DOI
10.2991/978-94-6463-326-9_7How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Bingchuan Wang
AU  - Xu Yifan
PY  - 2023
DA  - 2023/12/30
TI  - Research and Analysis of New Urbanized Rural Development Based on the Context of Big Data Development
BT  - Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)
PB  - Atlantis Press
SP  - 61
EP  - 68
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-326-9_7
DO  - 10.2991/978-94-6463-326-9_7
ID  - Wang2023
ER  -