工商管理学院知识库

在全球气候变化和资源短缺的背景下，中国提出了碳达峰和碳中和的“双碳”目标，强调了绿色化、低碳化发展的重要性。制造业作为中国经济的重要组成部分和碳排放的主要来源，其绿色转型尤为关键。在此背景下，企业绿色创新不仅是政策驱动下的必然趋势，更是企业履行社会责任、顺应市场变化、谋求可持续发展的关键路径。同时，数字经济蓬勃发展，数据价值凸显，但制造企业却面临着 “数据孤岛” 的难题，严重阻碍了绿色创新进程。鉴于此，本研究基于人-数交互理论，深入探究制造业企业绿色创新的内在机理与多元组态，旨在为制造业的绿色发展提供理论支撑与实践指导。

本研究选取2015-2022年间475家制造业上市公司构成的平衡面板数据为样本，采用回归和动态QCA方法，基于人-数交互理论视角，构建企业绿色创新研究框架，首先运用多元线性回归方法检验主效应、中介效应和调节效应，并采用 Bootstrap 法进行稳健性检验，确保研究结果的可靠性。其次，运用动态 QCA 方法，深入挖掘企业绿色创新的组态路径，揭示多因素协同作用的复杂机制。

研究表明，数字人才资源和环境信息披露对企业绿色创新具有显著的正向推动作用；数据要素利用水平在数字人才资源、环境信息披露与企业绿色创新之间发挥着关键的中介作用；数字经济发展水平对数据要素利用水平与企业绿色创新之间的关系具有显著的调节作用。制造业绿色创新是一个多因素协同作用的复杂过程，不存在单一的决定性因素。企业绿色创新存在特定的组态路径，包括高绿色创新路径和非高绿色创新路径，各路径受不同因素组合的影响。基于上述结论，企业应积极发挥人-数交互作用，优化内部创新要素配置；各地区应根据自身数字经济和环境信息披露状况，制定差异化的绿色创新政策，共同推动制造业绿色创新发展迈向新高度。

Against the backdrop of global climate change and resource scarcity, China has proposed a ‘dual carbon’ goal of carbon peaking and carbon neutrality, stressing the importance of green and low-carbon development. As an important part of China's economy and a major source of carbon emissions, the green transformation of the manufacturing sector is particularly critical. In this context, green innovation is not only an inevitable trend driven by policy, but also a key path for enterprises to fulfil their social responsibility, adapt to market changes and seek sustainable development. At the same time, the digital economy is booming, and the value of data is highlighted, but manufacturing enterprises are facing the problem of ‘data silos’, which seriously impedes the process of green innovation. In view of this, this study is based on the theory of human-digital interaction, in-depth investigation of the intrinsic mechanism and multiple grouping of green innovation in manufacturing enterprises, aiming to provide theoretical support and practical guidance for the green development of the manufacturing industry.

This study takes the balanced panel data of 475 listed companies of manufacturing enterprises from 2015 to 2022 as samples, adopts regression and dynamic QCA methods, constructs the research framework of corporate green innovation based on the perspective of human-digital interaction theory, firstly, applies multiple linear regression methods to test the main effect, the mediating effect and the moderating effect, and adopts the Bootstrap method to carry out the robustness test, to ensure that the results of the study are Secondly, the dynamic QCA method is used to test the main effect, mediating effect and moderating effect. Secondly, the dynamic QCA method is used to explore the group path of enterprise green innovation and reveal the complex mechanism of multifactor synergy.

The study shows that digital talent resources and environmental information disclosure have a significant positive driving effect on enterprise green innovation; the level of data factor utilization plays a key intermediary role between digital talent resources, environmental information disclosure and enterprise green innovation; and the level of digital economic development has a significant moderating effect on the relationship between the level of data factor utilization and enterprise green innovation. Manufacturing green innovation is a complex process of multi-factor synergy, and there is no single determining factor. There are specific group paths of enterprise green innovation, including high green innovation paths and non-high green innovation paths, and each path is influenced by different combinations of factors. Based on the above conclusions, enterprises should actively play the role of human-digital interaction to optimize the internal allocation of innovation factors; regions should formulate differentiated green innovation policies according to their own digital economy and environmental information disclosure status, so as to jointly promote the development of green innovation in manufacturing industry to a new height.