PDF(1206 KB)
PDF(1206 KB)
PDF(1206 KB)
数据要素对企业绿色创新的影响研究
Research on the impact of data elements on corporate green innovation
数据要素作为具有核心竞争力的关键生产要素和战略资源,为企业提升绿色创新绩效,实现可持续发展提供了新的途径。本文基于2012—2023年A股上市公司数据,实证探究了数据要素对企业绿色技术创新和管理创新的影响效应与机制。结果表明,数据要素显著提升了企业绿色技术创新和绿色管理创新绩效,战略引导和绿色文化强化了数据要素与绿色创新之间的关系。机制分析表明,数据要素通过“资源集聚效应”和“协同效应”提升企业绿色创新绩效。异质性分析发现,在技术密集领域、环境规制强度高的企业中,数据要素对绿色创新绩效的推动作用更加显著。本文拓展了数据要素影响企业行为领域的研究,为探究数字经济时代企业绿色创新路径提供了经验证据,对企业有效挖掘和利用数据要素的潜在价值具有启示意义。
As key production factors and strategic resources with core competitiveness, data elements provide new ways for enterprises to enhance green innovation performance and realize sustainable development. Based on the data of A-share listed companies from 2012 to 2023, this paper empirically explored the effect and mechanism of data elements on corporate green technology innovation and management innovation. The results showed that data elements significantly improve the performance of corporate green technology innovation and green management innovation, and the relationship between data elements and green innovation is strengthened by strategic guidance and green culture. The mechanism analysis showed that data elements promote the green innovation performance of enterprises through "resource agglomeration effect" and "synergistic effect". The heterogeneity analysis found that in technology-intensive fields and enterprises with high intensity of environmental regulation, data elements play a more significant role in promoting green innovation performance. This research has expanded the research in the field of data elements influencing corporate behaviour, and it will provide empirical evidence for exploring the path of corporate green innovation in the digital economy era, thus having implications for enterprises to effectively explore and utilize the potential value of data elements.
数据要素 / 绿色创新 / 资源集聚 / 协同效应 / 机器学习
data element / green innovation / resource agglomeration / synergistic effect / machine learning
| [1] |
李泽宇, 王雪方, 陈新芳. 政府数据开放对企业创新的影响效应及机制研究[J]. 科研管理, 2024, 45(7): 11-20.
|
| [2] |
李海舰, 赵丽. 数据成为生产要素:特征、机制与价值形态演进[J]. 上海经济研究, 2021(8): 48-59.
|
| [3] |
白永秀, 李嘉雯, 王泽润. 数据要素:特征、作用机理与高质量发展[J]. 电子政务, 2022(6): 23-36.
|
| [4] |
郑国强, 张馨元, 赵新宇. 数据要素市场化能否促进企业绿色创新?:基于城市数据交易平台设立的准自然实验[J]. 上海财经大学学报, 2024, 26(3): 33-48.
|
| [5] |
刘力源, 杨英法. 数据要素市场建设与企业绿色技术创新:基于“绿色金融-绿色信息”双螺旋政策的协同证据[J]. 商业研究, 2025(2): 107-117.
|
| [6] |
梁孝成, 吕康银, 陈思. 数据要素市场化对企业新质生产力水平的影响研究[J]. 科研管理, 2025, 46(2): 12-21.
|
| [7] |
王建冬, 童楠楠. 数字经济背景下数据与其他生产要素的协同联动机制研究[J]. 电子政务, 2020(3): 22-31.
|
| [8] |
陈晓佳, 徐玮. 数据要素、交通基础设施与产业结构升级:基于量化空间一般均衡模型分析[J]. 管理世界, 2024, 40(4): 78-98.
|
| [9] |
郭凯明, 王钰冰, 杭静. 数据要素规模效应、产业结构转型与生产率提升[J]. 中国工业经济, 2024(8): 5-23.
|
| [10] |
杨俊, 李小明, 黄守军. 大数据、技术进步与经济增长:大数据作为生产要素的一个内生增长理论[J]. 经济研究, 2022, 57(4): 103-119.
|
| [11] |
王柯丹, 刘颖, 汪寿阳. 数据要素与绿色创新:基于新质生产力视角[J]. 财经问题研究, 2024(9): 18-33.
|
| [12] |
高明, 魏浩, 王晓祺. 数据要素流动赋能企业绿色创新[J]. 中国人口·资源与环境, 2024, 34(11): 120-129.
|
| [13] |
Innovation is typically a trial-and-error process. While some research paths lead to the innovation sought, others result in dead ends. Because firms benefit from their competitors working in the wrong direction, they do not reveal their dead-end findings. Time and resources are wasted on projects that other firms have already found to be fruitless. We offer a simple model with two firms and two research lines to study this prevalent problem. We characterize the equilibrium in a decentralized environment that necessarily entails significant efficiency losses due to wasteful dead-end replication and an information externality that leads to an early abandonment of the risky project. We show that different types of firms follow different innovation strategies and create different kinds of welfare losses. In an extension of the core model, we also study a centralized mechanism whereby firms are incentivized to disclose their actions and share their private information in a timely manner.
|
| [14] |
|
| [15] |
席龙胜, 赵辉. 高管双元环保认知、绿色创新与企业可持续发展绩效[J]. 经济管理, 2022, 44(3): 139-158.
|
| [16] |
|
| [17] |
任英华, 刘宇钊, 胡宗义, 等. 大数据发展、知识产权保护对企业绿色技术创新的影响[J]. 中国人口·资源与环境, 2023, 33(7): 157-167.
|
| [18] |
|
| [19] |
|
| [20] |
刘剑民, 夏琴, 徐玉德, 等. 产业技术复杂性、政府补助与企业绿色技术创新激励[J]. 南开管理评论, 2024, 27(2): 94-103+149+104-105.
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
谢康, 夏正豪, 肖静华. 大数据成为现实生产要素的企业实现机制:产品创新视角[J]. 中国工业经济, 2020(5): 42-60.
|
| [25] |
冯檬莹, 陈海波, 郭晓雪. 大数据能力、供应链协同创新与制造企业运营绩效的关系研究[J]. 管理工程学报, 2023, 37(3): 51-59.
|
| [26] |
|
| [27] |
赵丽, 胡植尧. 数据要素、动态能力与企业全要素生产率:破解“数据生产率悖论”之谜[J]. 经济管理, 2024, 46(7): 55-72.
|
| [28] |
王永贵, 李霞. 促进还是抑制:政府研发补助对企业绿色创新绩效的影响[J]. 中国工业经济, 2023(2): 131-149.
|
| [29] |
白福萍, 黄宇杰, 王京, 等. 入芝兰之室:企业绿色文化与绿色创新[J]. 外国经济与管理, 2025, 47(1): 137-152.
|
| [30] |
|
| [31] |
袁淳, 肖土盛, 耿春晓, 等. 数字化转型与企业分工:专业化还是纵向一体化[J]. 中国工业经济, 2021(9): 137-155.
|
| [32] |
张叶青, 陆瑶, 李乐芸. 大数据应用对中国企业市场价值的影响:来自中国上市公司年报文本分析的证据[J]. 经济研究, 2021, 56(12): 42-59.
|
| [33] |
|
| [34] |
|
| [35] |
李鑫, 徐琼, 王核成. 企业数字化转型与绿色技术创新[J]. 统计研究, 2023, 40(9): 107-119.
|
| [36] |
何玉梅, 罗巧. 环境规制、技术创新与工业全要素生产率:对“强波特假说”的再检验[J]. 软科学, 2018, 32(4): 20-25.
|
/
| 〈 |
|
〉 |