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Impact of pollution prevention practices and green environmental practices on sustainable performance: Empirical evidence from Chinese SMEs

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F24%3A50021651" target="_blank" >RIV/62690094:18470/24:50021651 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1016/j.envres.2024.118991" target="_blank" >https://doi.org/10.1016/j.envres.2024.118991</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.envres.2024.118991" target="_blank" >10.1016/j.envres.2024.118991</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Impact of pollution prevention practices and green environmental practices on sustainable performance: Empirical evidence from Chinese SMEs

  • Popis výsledku v původním jazyce

    Adequate protection of the environment is one of the hot spots of concern for all sectors of society due to severe environmental pollution. The solution to this issue is friendly management of the environment. With the rapid growth of Chinese Manufacturing SMEs for economic development, environmental pollution and abuse of resources are arising. To resolve these issues, Chinese manufacturing SMEs are accelerating the implementation of green innovation in their industries. However, it is a complex task that involves enterprise, government, and social considerations. Therefore, it is essential to identify the green drivers for this implementation. With a focus on China&apos;s current situation from previous research and views from experts, this study aims to investigate how Chinese Manufacturing Small and Medium-sized Enterprises (SMEs) are responding to resource misuse and environmental pollution by implementing green innovation, emphasising the role of artificial intelligence (AI) in improving environmental performance. This study primarily looks into the factors that influence the adoption of green innovations by analysing the growth paths of Chinese SMEs operating in highly polluting industries over a longer time frame than five years. Artificial Intelligence is a valuable tool for solving the issues of ecological degradation. A quantitative method has been implemented for the Chinese companies&apos; samples from the deeply polluting industries for more than five years. The findings of this paper advise that the average board size, the governing board meetings, and organizational performance are positively connected with the Chinese firms&apos; environmental process. Board independence and diversity of gender have irrelevant associations with ecological performance. A convenient threshold regression model has been used to accumulate the respondents&apos; data. It also reveals that larger board sizes and more frequent governing board meetings are positively associated with improved environmental performance among these firms. The findings state the critical implications for the firm executives, policymakers, environmental activists, and regulators. This result supports the insight drained from the resource dependence, stakeholder, firm agency, and legitimacy theories.

  • Název v anglickém jazyce

    Impact of pollution prevention practices and green environmental practices on sustainable performance: Empirical evidence from Chinese SMEs

  • Popis výsledku anglicky

    Adequate protection of the environment is one of the hot spots of concern for all sectors of society due to severe environmental pollution. The solution to this issue is friendly management of the environment. With the rapid growth of Chinese Manufacturing SMEs for economic development, environmental pollution and abuse of resources are arising. To resolve these issues, Chinese manufacturing SMEs are accelerating the implementation of green innovation in their industries. However, it is a complex task that involves enterprise, government, and social considerations. Therefore, it is essential to identify the green drivers for this implementation. With a focus on China&apos;s current situation from previous research and views from experts, this study aims to investigate how Chinese Manufacturing Small and Medium-sized Enterprises (SMEs) are responding to resource misuse and environmental pollution by implementing green innovation, emphasising the role of artificial intelligence (AI) in improving environmental performance. This study primarily looks into the factors that influence the adoption of green innovations by analysing the growth paths of Chinese SMEs operating in highly polluting industries over a longer time frame than five years. Artificial Intelligence is a valuable tool for solving the issues of ecological degradation. A quantitative method has been implemented for the Chinese companies&apos; samples from the deeply polluting industries for more than five years. The findings of this paper advise that the average board size, the governing board meetings, and organizational performance are positively connected with the Chinese firms&apos; environmental process. Board independence and diversity of gender have irrelevant associations with ecological performance. A convenient threshold regression model has been used to accumulate the respondents&apos; data. It also reveals that larger board sizes and more frequent governing board meetings are positively associated with improved environmental performance among these firms. The findings state the critical implications for the firm executives, policymakers, environmental activists, and regulators. This result supports the insight drained from the resource dependence, stakeholder, firm agency, and legitimacy theories.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Environmental Research

  • ISSN

    0013-9351

  • e-ISSN

    1096-0953

  • Svazek periodika

    255

  • Číslo periodika v rámci svazku

    August

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    11

  • Strana od-do

    "Article number: 118991"

  • Kód UT WoS článku

    001265014600001

  • EID výsledku v databázi Scopus

    2-s2.0-85193807093