Dynamic control of low-carbon efforts and process innovation considering knowledge accumulation under dual-carbon policies

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2024-08-30 DOI:10.1016/j.cie.2024.110526
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Abstract

Governments frequently implement carbon trading (CT) and carbon subsidy (CS) policies for encouraging enterprises to engage in low-carbon efforts (LCE) and reduce emissions, ultimately aiming for sustainable development in environmental and economic realms. In response, enterprises increase their investments in process innovation (PI) to balance revenue generation and cost reduction while simultaneously accumulating knowledge. Exploring the relation between LCE and PI is crucial to guide enterprises in effectively balancing these inputs, as well as to examine the role of government regulations on carbon emissions in motivating enterprises to enhance their efforts. This study proposes a dynamic optimal control model integrating PI and LCE within the dual-carbon policy framework, considering the effect of knowledge accumulation (KA). Moreover, it evaluates changes in inputs and benefits under profit-optimal and social welfare-optimal conditions. Finally, a comparative analysis is conducted using numerical simulation and emulation. The findings indicate complementary and substitution effects between the two inputs: the KA effect enhances input stability, and the impact of social incentives consistently outweighs that of monopoly incentives. Furthermore, CT and CS policies exhibit cross-impacts on enterprise returns and the two inputs.

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考虑到双碳政策下的知识积累,对低碳工作和流程创新进行动态控制
各国政府经常实施碳交易(CT)和碳补贴(CS)政策,鼓励企业开展低碳行动(LCE),减少排放,最终实现环境和经济领域的可持续发展。为此,企业增加了对工艺创新(PI)的投资,以在创收和降低成本之间取得平衡,同时积累知识。探索 LCE 与 PI 之间的关系对于指导企业有效平衡这些投入以及研究政府碳排放法规在激励企业加强努力方面的作用至关重要。考虑到知识积累(KA)的影响,本研究在双碳政策框架内提出了一个整合 PI 和 LCE 的动态优化控制模型。此外,它还评估了利润最优和社会福利最优条件下的投入和收益变化。最后,利用数值模拟和仿真进行了比较分析。研究结果表明,两种投入之间存在互补和替代效应:KA效应增强了投入的稳定性,社会激励的影响始终大于垄断激励的影响。此外,CT 和 CS 政策对企业回报和两种投入产生了交叉影响。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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