Evidence map›Paper›PMID 37036889›Full record

ArticlePloS one2023

A hybrid MCDM model combining Fuzzy-Delphi, AEW, BWM, and MARCOS for digital economy development comprehensive evaluation of 31 provincial level regions in China.

Haoran Zhao, Yuchen Wang, Sen Guo

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Haoran ZhaoSchool of Economics and Management, Beijing Information Science & Technology University, Beijing, China.ORCID 0000-0003-4480-2577
Yuchen WangSchool of Management, Dalian University of Finance and Economics, Dalian, China.
Sen GuoSchool of Economics and Management, North China Electric Power University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the deepening of a new round of technological revolution and industrial reform, digital technology has been continuously innovated and widely penetrated into various economic fields. The digital economy (DE) is gradually becoming the focus of China's economic development planning and a new engine to enhance national strength. Evaluating the development level of DE in various regions is conducive to timely discover the shortcomings in China's DE development, as well as provide an important basis for putting forward corresponding policy suggestions. This investigation established a hybrid multi-criteria decision making (MCDM) model for evaluating DE development of 31 provincial level regions in China ranging from 2015 to 2020. Firstly, the evaluation indicator system is established from digital infrastructure, integrated development, social benefits, innovation ability, and electronic-commerce dimensions containing 17 quantitative sub-criteria based on Fuzzy-Delphi method. Secondly, integrated weights of 17 sub-criteria from 2015 to 2020 are computed in terms of objective weights calculated by the anti-entropy weight (AEW) approach from 2015 to 2020 and subjective weights obtained via the best-worst method (BWM). Thirdly, MARCOS model is applied to evaluate the DE development degree of various regions in China ranging from 2015 to 2020. Case analysis illustrates that the DE development of Guangdong, Jiangsu, Zhejiang, and Beijing always maintain in the top four from 2015 to 2020, while the southwest and northwest regions in China are obviously fall behind others. And the DE development degree of various regions is primarily affected under the integrated development performance, innovation ability performance, and social benefits performance. Therefore, the backward regions should emphasize the development of software industry and information technology industry. The robustness of the proposed MCDM model combining Fuzzy-Delphi, AEW, BWM and MARCOS is discussed employing three similarity coefficients of rankings. And it is verified that the proposed MCDM model has superior robustness and validity in evaluating DE development.

Indexed as

IndustryTechnologyBeijingChinaCommerceEconomic Development

Identifiers

PMID37036889
PMCPMC10085058

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