Evidence map›Paper›PMID 36105642›Full record

ArticleComputational intelligence and neuroscience2022

Study on the Drivers of Inclusive Green Growth in China Based on the Digital Economy Represented by the Internet of Things (IoT).

Xiaoxue Liu, Shuangshuang Fan, Fuzhen Cao, Shengnan Peng, Hongyun Huang

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Xiaoxue LiuSchool of Economics, Beijing Technology and Business University, Beijing 100048, China.
Shuangshuang FanSchool of Management, China University of Mining and Technology-Beijing, Beijing 100083, China.ORCID https://orcid.org/0000-0003-1317-2509
Fuzhen CaoSchool of Economics, Beijing Technology and Business University, Beijing 100048, China.
Shengnan PengSchool of Management, China University of Mining and Technology-Beijing, Beijing 100083, China.
Hongyun HuangCenter for Economic Research, Shandong University, Jinan 250100, China.ORCID https://orcid.org/0000-0001-7310-3930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the vigorous development of digital economy based on digital technologies such as Internet of things (IoT), big data, and artificial intelligence, new vitality has been injected into China's economic model. Inclusive green growth (IGG) supports the transformation of society towards a better quality of life and well-being, as well as environmental protection. Therefore, it is crucial to identify the main drivers of IGG. However, IGG is subject to a variety of interpretations and lacks definitional clarity. To brigade this gap, this study primarily evaluates the performance of IGG and explores the key drivers on IGG in China. Specifically, the data envelopment analysis (DEA) model is employed to calculate IGG for 281 cities in China during 2005-2020. Subsequently, we take advantage of a nest of machine learning (ML) algorithm to demonstrate the vital drivers of urban IGG, which avoids the defects of endogenous linear hypothesis of traditional econometric methods. The results indicate that digitization represented by the IoT and other digital technology is the core drivers of the urban IGG in the overall sample, accounting for about 50% among all of drivers. This finding provides new evidence supporting the "high-quality development" strategy in China, as well as shedding light on grasping the principal fulcrum to achieve the transformation towards IGG in developing economies similar to China.

Indexed as

Internet of ThingsArtificial IntelligenceChinaImmunoglobulin GQuality of LifeImmunoglobulin G

Identifiers

PMID36105642
PMCPMC9467763

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.