Evidence map›Paper›PMID 33419351›Full record

ArticleEntropy (Basel, Switzerland)2020

Analysis on the Development of Digital Economy in Guangdong Province Based on Improved Entropy Method and Multivariate Statistical Analysis.

Xue Deng, Yuying Liu, Ye Xiong

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?International journal of environmental research and public health · 2022
    Article
  4. Estimation and Potential Analysis of Land Population Carrying Capacity in Shanghai Metropolis.International journal of environmental research and public health · 2022
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xue DengSchool of Mathematics, South China University of Technology, Guangzhou 510640, China.
Yuying LiuSchool of Mathematics, South China University of Technology, Guangzhou 510640, China.
Ye XiongSchool of Mathematics, South China University of Technology, Guangzhou 510640, China.

Funding

Guangdong Graduate Education Innovation Program 2019SFKC07Humanities and Social Sciences Research and Planning Fund of the Ministry of Education of China 18YJAZH014-x2lxY9180090Natural Science Foundation of Guangdong Province 2019A1515011038Soft Science of Guangdong Province 2018A070712006, 2019A101002118
6 · The paper itself

Abstract

The lack of adequate indicators in the research of digital economy may lead to the shortage of data support on decision making for governments. To solve this problem, first we establish a digital economy indicator evaluation system by dividing the digital economy into four types: "basic type", "technology type", "integration type" and "service type" and select 5 indicators for each type. On this basis, the weight of each indicator is calculated to find the deficiencies in the development of some digital economic fields by the improved entropy method. By drawing on the empowerment idea of Analytic Hierarchy Process, the improved entropy method firstly compares the difference coefficient of indicators in pairs and maps the comparison results to the scales 1-9. Then, the judgment matrix is constructed based on the information entropy, which can solve as much as possible the problem that the difference among the weight of each indicator is too large in traditional entropy method. The results indicate that: the development of digital economy in Guangdong Province was relatively balanced from 2015 to 2018 and will be better in the future while the development of rural e-commerce in Guangdong Province is relatively backward, and there is an obvious digital gap between urban and rural areas. Next we extract two new variables respectively to replace the 20 indicators we select through principal component analysis and factor analysis methods in multivariate statistical analysis, which can retain the original information to the greatest extent and provide convenience for further research in the future. Finally, we and provide constructive comments of digital economy in Guangdong Province from 2015 to 2018.

Indexed as

digital economyfactor analysisimproved entropy methodindicator systemprincipal component analysis

Identifiers

PMID33419351
PMCPMC7766761

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