三方交易平台下考虑质量差异和政府补贴的低碳创新决策

Xu Wang, Longzhen Zhou, Zusheng Zhang, Yingbo Wu, Longxi Li
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引用次数: 0

摘要

在低碳创新背景下,合理的补贴、创新和定价策略是实现资源脱碳和供需匹配的重要手段,而资源的质量差异化对策略的制定有重要影响。本文整合资源质量差异和需求侧低碳偏好两个变量,研究了在资源交易平台上,两家供应商提供差异化制造资源的不同创新场景下,低碳创新与政府补贴的关系。运用效用理论和Stackelberg博弈理论,构建了低碳创新与政府补贴的决策模型,并运用逆归纳法得到了均衡解。然后,比较了不同创新情景下的低碳创新和补贴策略,并分析了质量相对系数和创新成本系数对策略的影响。研究结果表明,在资源质量差异较小的情况下,拥有优质资源的低碳创新情景的绿色创新水平高于拥有低质量资源的低碳创新情景,政府对创新投资的补贴率也更高。在资源质量差异较大的情况下,不同情景下绿色创新水平和政府创新投入补贴率的相对大小与创新成本系数相关。
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Low-Carbon Innovation Decision Considering Quality Differences and Government Subsidies under the Three-Party Trading Platform
In the context of low-carbon innovation, reasonable subsidy, innovation, and pricing strategies are important to achieve resource decarbonization and supply-demand matching, while the quality differentiation of resources has a significant impact on the strategy formulation. In this paper, we study low-carbon innovation and government subsidy in different innovation scenarios with two providers offering differentiated manufacturing resources on a resource trading platform, integrating two variables of resource quality difference and demand-side lowcarbon preference. Using utility theory and the Stackelberg game, a decision model of low carbon innovation and government subsidy is constructed, and the equilibrium solution is obtained with inverse induction. Then, the low-carbon innovation and subsidy strategies under different innovation scenarios are compared and the effects of relative coefficients of quality and innovation cost coefficients on the strategies are analyzed. The findings show that when the difference in resource quality is small, the level of green innovation is higher in the low carbon innovation scenario with high-quality resources compared to the low carbon innovation scenario with low-quality resources, and the rate of government subsidy for innovation investment is also higher. In case of the large difference in resource quality, the relative magnitudes of green innovation level and government subsidy rate for innovation inputs in different scenarios are related to innovation cost coefficients.
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