Chang Haodong, Zhao Yipeng
College of Mathematics and Physics, Chengdu University of Technology, Chengdu, China.
College of Management Science, Chengdu University of Technology, Chengdu, China.
Heliyon. 2024 Feb 1;10(3):e25668. doi: 10.1016/j.heliyon.2024.e25668. eCollection 2024 Feb 15.
To study the multi-factor linkage effect of carbon trading on green technology innovation, this paper employs the dynamic QCA analysis method and uses panel data from China's carbon trading pilot areas. The aim is to explore the causal path considering the time effect. Additionally, the Kruskal-Wallis rank sum test is applied to investigate the provincial coverage difference of the configuration and reveal the variation in configuration preferences between regions from a spatial dimension. The results indicate that a single factor alone does not constitute the necessary conditions for the "quantity" and "quality" of high-green technology innovation. However, the necessity of carbon trading price exhibits a declining trend over the years, demonstrating the presence of a time effect. Regarding the sufficiency analysis of conditional configuration, it mainly includes a "price-market scale" dual effect model and a single market scale effect model, with three configuration paths for each model. Among them, the "price-market scale" dual effect model can drive the increase in the quantity of green technology innovation through carbon trading price, market scale, government intervention degree, and other factors. The single market scale effect model can promote the high-quality development of green technology innovation, but the impact of carbon trading price on the quality of green technology innovation is relatively insignificant. In terms of the time dimension, the three configurations still maintain good applicability to green technology innovation under normal conditions. However, when considering the spatial dimension, the coverage distribution of the three configurations exhibits evident regional differences. This study introduces the dynamic panel QCA method into the research field for the first time. It addresses the limitations of the traditional QCA method, which is constrained by cross-section data and lacks the ability to explore the linkage effect between factors over time. Additionally, the study analyzes the effects of carbon trading price and market size on the "quantity" and "quality" of green technology innovation, considering both time and space dimensions, from a configuration perspective.
为研究碳交易对绿色技术创新的多因素联动效应，本文采用动态定性比较分析（QCA）方法，并运用中国碳交易试点地区的面板数据。目的是探索考虑时间效应的因果路径。此外，应用克鲁斯卡尔 - 沃利斯秩和检验来考察配置的省级覆盖差异，并从空间维度揭示地区间配置偏好的变化。结果表明，单一因素本身并不构成高绿色技术创新“量”与“质”的必要条件。然而，碳交易价格的必要性呈现出逐年下降的趋势，表明存在时间效应。关于条件配置的充分性分析，主要包括“价格 - 市场规模”双重效应模型和单一市场规模效应模型，每个模型有三条配置路径。其中，“价格 - 市场规模”双重效应模型可通过碳交易价格、市场规模、政府干预程度等因素推动绿色技术创新数量的增加。单一市场规模效应模型可促进绿色技术创新的高质量发展，但碳交易价格对绿色技术创新质量的影响相对较小。在时间维度上，这三种配置在正常情况下对绿色技术创新仍保持良好的适用性。然而，在考虑空间维度时，这三种配置的覆盖分布呈现出明显的区域差异。本研究首次将动态面板QCA方法引入该研究领域。它克服了传统QCA方法受横截面数据限制且缺乏探索因素间随时间联动效应能力的局限性。此外，该研究从配置角度，在时间和空间维度上分析了碳交易价格和市场规模对绿色技术创新“量”与“质”的影响。
