Evidence map›Paper›PMID 33920439›Full record

ArticleInternational journal of environmental research and public health2021

Are Clean Technologies More Effective Than End-of-Pipe Technologies? Evidence from Chinese Manufacturing.

Jiawei Li, Jianghong Zeng, Zhengke Ye, Xiangrong Huang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jiawei LiDepartment of Management Science and Engineering, Business School, Central South University, Changsha 410083, China.ORCID 0000-0002-4772-1775
Jianghong ZengDepartment of Management Science and Engineering, Business School, Central South University, Changsha 410083, China.
Zhengke YeDepartment of Management Science and Engineering, Business School, Central South University, Changsha 410083, China.
Xiangrong HuangDepartment of Marketing, School of Business Administration, Hunan University of Finance and Economics, Changsha 410083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing number of manufacturing enterprises are adopting environmental technologies to cope with the increasingly severe environmental regulatory pressure, but the existing studies about the impact of environmental technologies on economic performance come up with mixed results. This paper contributes to the literature by using the financial constraints and market advantages as a dual mediating process in this relationship. An empirical test using a sample of Chinese manufacturing enterprises listed in the Shanghai and Shenzhen exchange from 2011 to 2018 is established. The results of regression analyses show that end-of-pipe technologies and clean technologies have a positive effect on firms' economic performance. Moreover, we find that clean technologies not only directly affect economic performance but also indirectly affect economic performance through mitigating financial constraints. With the negative influence of end-of-pipe technologies on market advantages, the positive economic effect caused by end-of-pipe technologies is weakened. This research provides useful insights into the selection of environmental technologies for manufacturing firms and the establishment of new policies to promote green finance and green consumption.

Indexed as

CommerceTechnologyAsian PeopleChinaHumansPolicyeconomic performanceenvironmental technologiesfinancial constraintsmarket advantages

Identifiers

PMID33920439
PMCPMC8069999

What OpenQuestion holds

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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.