Evidence map›Paper›PMID 38434095›Full record

ArticleHeliyon2024

Empirical analysis of factors influencing industrial eco-efficiency in the Yellow River Basin from a social embeddedness perspective.

Junjie Wang, Zhun Chen, Taizheng Chen, Wei Wang, Bailu Liu

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

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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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Junjie WangThe College of Geography and Environmental Science, Henan University, Kaifeng, 475000, China.
Zhun ChenSchool of Philosophy and Public Management, Henan University, Kaifeng, 475000, China.
Taizheng ChenThe College of Geography and Environmental Science, Henan University, Kaifeng, 475000, China.
Wei WangSchool of Culture and Tourism, Henan University, Kaifeng, 475000, China.
Bailu LiuThe College of Geography and Environmental Science, Henan University, Kaifeng, 475000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measuring industrial eco-efficiency (IEE) is essential to improve environmental quality and industrial restructuring. However, most studies ignore the influence of embeddedness on industrial eco-efficiency and lack analysis of the pathways of influence factors. Therefore, this study assesses industrial eco-efficiency in the Yellow River Basin (YRB) using a super-efficiency model slacks-based measure (Super-SBM) that considers non-desired outputs, outlines the social embeddedness of IEE, and empirically analyzes the driving mechanism of IEE from the perspective of embeddedness by constructing hierarchical linear modeling (HLM) to address the pathways of action of the influencing factors of industrial eco-efficiency. The results showed that 50.79% of the overall differences in IEE in the YRB were caused by social embeddedness. Economic development level, industrial agglomeration, and environmental regulation (ER) are significant direct influencing factors. Increasing cognitive and cultural embeddedness will enhance the positive relationship between economic development level and IEE. Political and relational embeddedness significantly moderates the positive relationship between industrial agglomeration and eco-efficiency. Cultural embeddedness can significantly and directly affect industrial eco-efficiency and weaken the positive relationship between ERs and industrial eco-efficiency. Therefore, improving IEE should consider both fundamental and embedded factors. Our findings are conducive to promoting high-quality development in the YRB and support the government in formulating differentiated policies. In addition, this paper tries to establish an empirical analysis method suitable for social embeddedness theory, and the empirical results help to improve the situation due to the lack of empirical analysis of social embeddedness theory.

Indexed as

Hierarchical linear modelingIndustrial eco-efficiencySocial embeddednessYellow River Basin

Identifiers

PMID38434095
PMCPMC10906184

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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.