School of Economics and Management, Changchun University Of Technology, 130000, China.
School of Economics and Management, Tongren University, Tongren, 554300, China.
Environ Res. 2024 Aug 15;255:118991. doi: 10.1016/j.envres.2024.118991. Epub 2024 Apr 25.
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'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' 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' 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' 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.
由于环境污染严重，环境保护得到充分保护是社会各界关注的热点之一。解决这个问题的办法是友好地管理环境。随着中国制造业中小企业经济的快速发展，环境污染和资源滥用问题日益突出。为了解决这些问题，中国制造业中小企业正在加快在其行业实施绿色创新。然而，这是一项复杂的任务，涉及企业、政府和社会的考虑。因此，必须确定实施绿色创新的绿色驱动因素。本研究从以往的研究和专家的观点出发，重点关注中国的现状，旨在探讨中国制造业中小企业（SMEs）如何通过实施绿色创新来应对资源滥用和环境污染问题，强调人工智能（AI）在提高环境绩效方面的作用。本研究主要研究了影响绿色创新采用的因素，分析了在五年以上的时间内，在污染严重的行业中运营的中国中小企业的增长路径。人工智能是解决生态退化问题的宝贵工具。本研究对来自深度污染行业的中国公司样本进行了定量分析，这些公司的样本已经存在五年以上。本文的研究结果表明，平均董事会规模、董事会会议次数和组织绩效与中国企业的环境流程呈正相关。董事会独立性和性别多样性与生态绩效无关。使用方便的门槛回归模型来积累受访者的数据。它还表明，较大的董事会规模和更频繁的董事会会议与这些公司改善环境绩效呈正相关。研究结果为企业高管、政策制定者、环保活动家和监管机构提供了重要启示。这一结果支持了从资源依赖、利益相关者、企业代理和合法性理论中得出的见解。
