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Maogang Tang

Biographic Data

ID3704839
NAMEMaogang Tang
GIVEN NAMESMaogang
FAMILY NAMETang
SIGNATURETANG M
AFFILIATIONSEast China University of Science and Technology
VERIFIEDNo
TOTAL WORKS7
TOTAL CITATIONS7
AUTHOR COUNT7
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Unlocking productivity growth through digital transformation’s dual matching-learning mechanism

    Open Access•Maogang Tang, Jiayi Zhu et al.•ARTICLE•Sustainable Futures•2026

    This study systematically investigates how digital transformation (DT) enhances enterprises’ total factor productivity (TFP) through a novel “matching-learning dual-mechanism” framework, bridging gaps in the existing literature. Unlike prior research focusing on singular mechanisms like transaction cost reductions or knowledge spillovers, this study integrates static resource allocation efficiency (matching) and dynamic technology spillovers (lea…

  • Relationship between land urbanization and the ecosystem service value of land

    Open Access•Hongyuan Du, Maogang Tang et al.•ARTICLE•Environment Development and…•2024

  • Government-led regional integration and economic growth

    Open Access•Lin Guo, Maogang Tang et al.•ARTICLE•Cities•2024•Cited by: 7•References: 4

  • Relationship between carbon emission trading schemes and companies’ total factor productivity

    Open Access•Maogang Tang, Silu Cheng et al.•ARTICLE•Environment Development and…•2023

  • The Impact of the Covid-19 Pandemic on Ambient Air Quality in China

    Open Access•Tuo Zhang, Maogang Tang•ARTICLE•International Journal of…•2021

    The novel coronavirus (COVID-19) pandemic has provided a distinct opportunity to explore the mechanisms by which human activities affect air quality and pollution emissions. We conduct a quasi-difference-in-differences (DID) analysis of the impacts of lockdown measures on air pollution during the first wave of the COVID-19 pandemic in China. Our study covers 367 cities from the beginning of the lockdown on 23 January 2020 until April 22, two week…

  • Assessing the impact of tradable discharge permit on pollution reduction and innovation

    Open Access•Maogang Tang, Ruihan Zhang et al.•ARTICLE•Environment Development and…•2021

  • Market failure, tradable discharge permit, and pollution reduction

    Open Access•Maogang Tang, Zhen Li et al.•ARTICLE•Ecological Economics•2021

  • Government-led regional integration and economic growth

    Open Access•Lin Guo, Maogang Tang et al.•ARTICLE•Cities•2024•Cited by: 7•References: 4

  • The Impact of the Covid-19 Pandemic on Ambient Air Quality in China

    Open Access•Tuo Zhang, Maogang Tang•ARTICLE•International Journal of…•2021

    The novel coronavirus (COVID-19) pandemic has provided a distinct opportunity to explore the mechanisms by which human activities affect air quality and pollution emissions. We conduct a quasi-difference-in-differences (DID) analysis of the impacts of lockdown measures on air pollution during the first wave of the COVID-19 pandemic in China. Our study covers 367 cities from the beginning of the lockdown on 23 January 2020 until April 22, two week…

  • Assessing the impact of tradable discharge permit on pollution reduction and innovation

    Open Access•Maogang Tang, Ruihan Zhang et al.•ARTICLE•Environment Development and…•2021

  • Market failure, tradable discharge permit, and pollution reduction

    Open Access•Maogang Tang, Zhen Li et al.•ARTICLE•Ecological Economics•2021

  • Relationship between carbon emission trading schemes and companies’ total factor productivity

    Open Access•Maogang Tang, Silu Cheng et al.•ARTICLE•Environment Development and…•2023

  • Relationship between land urbanization and the ecosystem service value of land

    Open Access•Hongyuan Du, Maogang Tang et al.•ARTICLE•Environment Development and…•2024

  • Government-led regional integration and economic growth

    Open Access•Lin Guo, Maogang Tang et al.•ARTICLE•Cities•2024•Cited by: 7•References: 4

  • Unlocking productivity growth through digital transformation’s dual matching-learning mechanism

    Open Access•Maogang Tang, Jiayi Zhu et al.•ARTICLE•Sustainable Futures•2026

    This study systematically investigates how digital transformation (DT) enhances enterprises’ total factor productivity (TFP) through a novel “matching-learning dual-mechanism” framework, bridging gaps in the existing literature. Unlike prior research focusing on singular mechanisms like transaction cost reductions or knowledge spillovers, this study integrates static resource allocation efficiency (matching) and dynamic technology spillovers (lea…

Economics (5 works) · Business (4 works) · China (4 works) · Climate Change Policy and Economics (3 works) · Economic growth (3 works) · Energy, Environment, Economic Growth (3 works) · Geography (3 works) · Industrial organization (3 works) · Ecology (2 works) · Energy, Environment, and Transportation Policies (2 works)

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