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Data · dataset · 2026

Panel Dataset of Environmental Regulation, Financing Constraints and Green Innovation Efficiency of Listed NEV Enterprises (2015–2023)

Listed in Teesside University Research Data Repository

This dataset includes 2340 firm-year observations from 260 listed new energy vehicle firms during 2015–2023.

Description

Green innovation efficiency is evaluated using a super-efficiency network SBM model with undesired outputs. Based on two-way fixed effect, moderation and threshold models, the data verifies that market-incentive environmental regulation hinders green innovation, while financing constraints play a mitigating moderating role with double thresholds at 4.0188 and 4.0273.

The dataset provides micro evidence for Porter’s hypothesis in the NEV industry and supports differentiated green policy design.

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Where it is published

Catalogue records · 1

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Provenance · 1 source records, 6 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/vc67rz253n.112 h agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title