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学者姓名：陈毅辉
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Abstract ：
As a major greenhouse gas, carbon dioxide emissions (CO2E) are the main cause of global warming and environmental pollution. Thus, the reduction in carbon emissions has become a global concern. The widespread use of renewable energy and the improvement of energy efficiency seem to provide a feasible path for countries to achieve carbon emissions reduction, and have received the attention of governments and academics. However, very little literature has focused on the spatial and temporal heterogeneity of the effects of renewable energy use and energy efficiency on carbon emission intensity. This study applies the geographically and temporally weighted regression (GTWR) model and complies with a balanced panel of data from member countries of the Regional Comprehensive Economic Partnership (RCEP) between 2000 and 2019 to investigate the spatiotemporal heterogeneity of the effects of renewable energy and energy efficiency on CO2E. The results show that CO2E per capita (CO2EP) increases over time, but its distribution across RCEP member countries remains largely stable. Overall, the usage of renewable energy tends to decrease CO2EP, while energy efficiency tends to increase it. However, with the passage of time and changes in geographical location, renewable energy consumption and energy efficiency show significant temporal and spatial heterogeneity in their effects on CO2EP of RCEP member countries. Additionally, the effects of industrial structure, merchandise trade, urbanization rate, and energy poverty on CO2EP of RCEP member countries are also characterized by spatial and temporal heterogeneity.
Keyword ：
carbon dioxide emissions carbon dioxide emissions energy efficiency energy efficiency geographically and temporally weighted regression geographically and temporally weighted regression RCEP RCEP Renewable energy Renewable energy
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| GB/T 7714 | Li, Minjie , Chen, Yihui . Spatiotemporal heterogeneity of the impact of renewable energy and energy efficiency on carbon dioxide emissions in Regional Comprehensive Economic Partnership member countries [J]. | ENERGY & ENVIRONMENT , 2025 , 36 (6) : 2856-2879 . |
| MLA | Li, Minjie 等. "Spatiotemporal heterogeneity of the impact of renewable energy and energy efficiency on carbon dioxide emissions in Regional Comprehensive Economic Partnership member countries" . | ENERGY & ENVIRONMENT 36 . 6 (2025) : 2856-2879 . |
| APA | Li, Minjie , Chen, Yihui . Spatiotemporal heterogeneity of the impact of renewable energy and energy efficiency on carbon dioxide emissions in Regional Comprehensive Economic Partnership member countries . | ENERGY & ENVIRONMENT , 2025 , 36 (6) , 2856-2879 . |
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数字经济与绿色物流耦合协调发展对于推动数字中国和美丽中国融合共进、落实“双碳”目标具有重要意义.在厘清数字经济与绿色物流耦合协调发展机制的基础上，运用纵横向拉开档次法、修正的耦合协调度模型、冷热点分析及动态的汇总型模糊集定性比较分析（fsQCA）等方法揭示2013～2021年我国数字经济与绿色物流耦合协调发展的时空特征及组态路径.结果表明：(1)时序变化上，我国数字经济与绿色物流发展水平均呈波动中上升趋势，两者的耦合协调度也具有增长态势，经历了由濒临失调向勉强协调的阶段式跨越，但整体耦合协调度不高.(2)空间格局上，数字经济与绿色物流耦合协调度呈“东部高、中西部低”的分布格局，东部地区已处于初级协调状态，中西部多数省份仍处于以数字经济滞后型为特征的失调状态.(3)空间关联上，数字经济与绿色物流耦合协调度空间正相关特征显著，江苏、上海、浙江和福建形成热点区且变化相对稳定，冷点区由内蒙古自治区向东北往黑龙江和吉林扩张，向南逐步覆盖山西.(4)驱动数字经济与绿色物流高耦合协调的组态模式有3种，分别为技术主导型、技术-人才协同型和技术-结构优化型；分时段对比分析发现，技术条件随时间推移愈发重要，而在产业结构高级化程度较高的地区，人力资本可与技术条件形成替代关系.
Keyword ：
动态QCA 动态QCA 数字经济 数字经济 组态路径 组态路径 绿色物流 绿色物流 耦合协调 耦合协调
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| GB/T 7714 | 李敏杰 , 陈毅辉 , 吴桐雨 . “双碳”背景下数字经济与绿色物流耦合协调发展的时空特征及组态路径 [J]. | 环境科学 , 2025 , 46 (07) : 4159-4174 . |
| MLA | 李敏杰 等. "“双碳”背景下数字经济与绿色物流耦合协调发展的时空特征及组态路径" . | 环境科学 46 . 07 (2025) : 4159-4174 . |
| APA | 李敏杰 , 陈毅辉 , 吴桐雨 . “双碳”背景下数字经济与绿色物流耦合协调发展的时空特征及组态路径 . | 环境科学 , 2025 , 46 (07) , 4159-4174 . |
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采用改进熵权法、耦合协调度模型和GML指数测度2011—2022年福建省数实融合水平和绿色创新效率，采用计量经济模型分析数实融合对绿色创新效率的影响。结果表明，考察期内福建省数实融合水平和绿色创新效率在波动中呈上升趋势，且数实融合水平对绿色创新效率具有显著正向影响。据此提出政府应优化数字经济政策，构建产业协作平台；加大科技研发投入，强化创新主体合作；加强基础设施建设，缩减城乡收入差距的政策建议，以期为推动福建省数实融合赋能绿色创新提供参考。
Keyword ：
实体经济 实体经济 数字经济 数字经济 数实融合 数实融合 绿色创新效率 绿色创新效率
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| GB/T 7714 | 陈毅辉 , 李敏杰 . 福建省数实融合赋能绿色创新的实证研究 [J]. | 海峡科学 , 2025 , 10 (05) : 145-154 . |
| MLA | 陈毅辉 等. "福建省数实融合赋能绿色创新的实证研究" . | 海峡科学 10 . 05 (2025) : 145-154 . |
| APA | 陈毅辉 , 李敏杰 . 福建省数实融合赋能绿色创新的实证研究 . | 海峡科学 , 2025 , 10 (05) , 145-154 . |
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数字化和绿色化已成为新时期经济高质量发展的核心驱动力。然而，数字技术应用引致的能源回弹效应对绿色化形成显著制约。揭示数字化与绿色生产力协同转型的时空特征及其作用机制，对实现经济生态协同增效具有重要价值。利用2011-2022年我国30个省(自治区、直辖市)数据(不包括西藏自治区和港澳台地区数据)，结合熵权法、SBM-GML模型、耦合协调度模型、时空地理加权回归模型、核密度函数等对数字化和绿色全要素生产率耦合协调进行分析。结果表明：(1)2011-2022年我国30个省份的数字化转型和绿色全要素生产率耦合系统实现了从不协调到良好协调的三级跨越式提升，高水平耦合协调仅出现在若干东部发达省份。(2)耦合协调系统的影响因子表现出非线性、异质性和阶段性的作用特征。技术进步是持续稳定的驱动因子，但效能呈现“东强西弱”梯度衰减的变化，后发区域具有突破初级协调的潜力，城镇化建设释能范围最广泛，动力性效能出现在大部分省份。(3)环境治理因子、收入水平在均等状况下释放推动力，但和产业结构的作用相似，其影响在东西部均呈两极变异，且正向影响存在效能门槛。研究显示，数字化和绿色全要素生产率耦合系统表现出显著的非均衡特征，其影响因子作用不仅存在空间异质性，同时随着时间维度演变产生动态分异。因此，分区制定差异化政策是实现数字化和绿色全要素生产率均衡、良好耦合协调的关键。
Keyword ：
分异机理 分异机理 数字化转型 数字化转型 时空特征 时空特征 绿色发展 绿色发展 耦合协调 耦合协调
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| GB/T 7714 | 曾岚婷 , 陈毅辉 , 周小亮 . 数字化转型与绿色全要素生产率耦合协调的时空格局及分异机理研究 [J]. | 环境科学研究 , 2025 , 38 (06) : 1383-1396 . |
| MLA | 曾岚婷 等. "数字化转型与绿色全要素生产率耦合协调的时空格局及分异机理研究" . | 环境科学研究 38 . 06 (2025) : 1383-1396 . |
| APA | 曾岚婷 , 陈毅辉 , 周小亮 . 数字化转型与绿色全要素生产率耦合协调的时空格局及分异机理研究 . | 环境科学研究 , 2025 , 38 (06) , 1383-1396 . |
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Green innovation efficiency (GIE), which reflects the relationship between inputs and outputs that consider environmental impacts, is critical to China's realization of green and sustainable development. In view of the differences in economic development and resource endowment across provinces, it is necessary to measure and evaluate the GIE in a rational manner. In this paper, we study the evaluation, dynamic evolutionary characteristics, and influencing factors of GIE for 30 provinces in China over the period 2011-2022, using the super-SBM undesirable model, the spatial Markov chain model, and the geographically and temporally weighted regression model, respectively. Results show that the eastern region has a significantly higher GIE than the other regions, followed by the central region. Also, the state of provincial GIE in China is affected by the level of neighboring regions. GDP per capita, the marketization index, and industrial structure promoted GIE, while R&D expenditure, import and export trade, and the digital financial inclusion index showed negative results. There is also spatiotemporal heterogeneity in the effects of individual factors on GIE. Thus, a one-size-fits-all policy for GIE is highly unsuitable for the realities of individual provinces in China. We propose a number of targeted and differentiated policy recommendations that can be implemented.
Keyword ：
China China dynamic evolution dynamic evolution green innovation efficiency green innovation efficiency GTWR GTWR super-SBM undesirable model super-SBM undesirable model
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| GB/T 7714 | Li, Minjie , Lin, Shuangjiao , Chen, Yihui . The Evaluation, Dynamic Evolutionary Characteristics and Influencing Factors of Green Innovation Efficiency in China [J]. | POLISH JOURNAL OF ENVIRONMENTAL STUDIES , 2025 , 34 (2) : 1607-1619 . |
| MLA | Li, Minjie 等. "The Evaluation, Dynamic Evolutionary Characteristics and Influencing Factors of Green Innovation Efficiency in China" . | POLISH JOURNAL OF ENVIRONMENTAL STUDIES 34 . 2 (2025) : 1607-1619 . |
| APA | Li, Minjie , Lin, Shuangjiao , Chen, Yihui . The Evaluation, Dynamic Evolutionary Characteristics and Influencing Factors of Green Innovation Efficiency in China . | POLISH JOURNAL OF ENVIRONMENTAL STUDIES , 2025 , 34 (2) , 1607-1619 . |
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The digital economy represents a new economic form that exhibits a heavy reliance on data resources, and it has the potential to extensively affect green innovation. In this paper, the theoretical mechanism through which the digital economy affects green innovation is dissected and panel data from 278 Chinese cities covering the period of 2011 to 2019 are collected to empirically test both the quantitative and qualitative dimensions of the impact of the digital economy on green innovation. The results show the following: (1) The digital economy exerts a dual impact by both increasing quantity and improving quality in green innovation. (2) By eliminating financial restrictions, encouraging industrial collaborative agglomeration, and raising governmental environmental concerns, the digital economy exerts an influence on green innovation. (3) The relationship between the digital economy and green innovation is significantly negatively mediated by fiscal decentralization. (4) The digital economy hinders the growth of green innovation by exerting a negative spatial spillover effect on surrounding areas. (5) The digital economy has a more positive impact on green innovation in eastern cities, large cities, cities with high administrative hierarchy, and cities with strong intellectual property rights protection. Based on the conclusions of this study, we propose that the government should continue to promote the development of the digital economy in the future to fully release the innovation dividend of the digital economy, accelerate the construction of a scientific performance appraisal system to overcome government failure in the process of green innovation, and consider the differences in the development of regions to form a new pattern of synergistic green innovation between regions. In this paper, to understand how the digital economy promotes green innovation, we not only provide theoretical and empirical evidence at the city level but also provide references and insights with which governments can improve their green innovation incentive policies and optimize the design of fiscal decentralization systems for the promotion of green innovation.
Keyword ：
C33 C33 Digital economy Digital economy Fiscal decentralization Fiscal decentralization Green innovation Green innovation O32 O32 R11 R11 Spatial spillover Spatial spillover
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| GB/T 7714 | Li, Minjie , Meng, Mengjun , Chen, Yihui . The impact of the digital economy on green innovation: the moderating role of fiscal decentralization [J]. | ECONOMIC CHANGE AND RESTRUCTURING , 2024 , 57 (2) . |
| MLA | Li, Minjie 等. "The impact of the digital economy on green innovation: the moderating role of fiscal decentralization" . | ECONOMIC CHANGE AND RESTRUCTURING 57 . 2 (2024) . |
| APA | Li, Minjie , Meng, Mengjun , Chen, Yihui . The impact of the digital economy on green innovation: the moderating role of fiscal decentralization . | ECONOMIC CHANGE AND RESTRUCTURING , 2024 , 57 (2) . |
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Agriculture is becoming a substantial contributor to carbon emissions in China, and the efficient reduction of agricultural carbon emissions (ACEs) has become a universal concern. Currently, the digital transformation of agriculture (DTA) provides a new way to reduce carbon emissions. However, questions regarding whether and how DTA suppresses ACEs remain the focus of both academic and practical attention; thus, they serve as the objectives of this study. Based on theoretical analyzes, the carbon emission reduction effect of DTA is empirically analyzed using panel data from 30 Chinese provinces between 2015 and 2021 with a benchmark regression model, mediating effect model and threshold effect model. The results show the following: (1) DTA significantly reduces ACEs. (2) DTA reduces ACEs through three paths: expanding the agricultural production scale, optimizing the agricultural industrial structure, and promoting agricultural technological progress. The agricultural industrial structure has the most considerable mediating effect, while the agricultural production scale expansion has the smallest effect. (3) The inhibitory effect of DTA on ACEs shows very distinct heterogeneity. DTA primarily reduces ACEs in eastern and nongrain production areas yet has an insignificant impact on other areas. In addition, the DTA has a significant inhibitory effect on ACEs from both fertilizers and diesel oil. (4) The inhibitory effect of DTA on ACEs is nonlinear rather than linear. There is a single threshold effect for the effect of DTA on ACEs, which is insignificant below the threshold and significantly negative above the threshold. Therefore, China's central and local governments need to increase the level of DTA, encourage farmers to moderately expand the scale of their operations, emphasize the agricultural service industry, and enhance agricultural technological innovation to ultimately reduce ACEs.
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| GB/T 7714 | Chen, Yihui , Li, Minjie . How does the digital transformation of agriculture affect carbon emissions? Evidence from China's provincial panel data [J]. | HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS , 2024 , 11 (1) . |
| MLA | Chen, Yihui 等. "How does the digital transformation of agriculture affect carbon emissions? Evidence from China's provincial panel data" . | HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS 11 . 1 (2024) . |
| APA | Chen, Yihui , Li, Minjie . How does the digital transformation of agriculture affect carbon emissions? Evidence from China's provincial panel data . | HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS , 2024 , 11 (1) . |
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基于DPSIR模型构建物流业绿色韧性评价指标体系，采用熵权法测度2004—2021年中国30个省域的物流业绿色韧性水平并分析其时空演变特征，借助修正的引力模型和社会网络分析方法考察物流业绿色韧性空间关联结构特征。结果表明：(1)研究期内中国物流业绿色韧性水平整体呈微弱上升态势，空间上呈现东部>中部>东北>西部的分布格局；(2)物流业绿色韧性空间关联整体网络的连通度和可达性较好，但紧密程度和稳定性有待加强，且网络存在较强的层级特征，网络结构有待优化；(3)京津和东南沿海发达省域在物流业绿色韧性空间关联网络中既扮演“中心行动者”的角色，又发挥“中介”和“桥梁”作用，东北和中西部省域则处于边缘位置；(4)2021年北京、天津、上海和江苏构成净受益板块，浙江、广东和福建作为经纪人板块，是连接东部和中部、西南地区的纽带，以东北、中部和西部省域为主的板块是物流业绿色韧性溢出的主体。
Keyword ：
DPSIR模型 DPSIR模型 物流业绿色韧性 物流业绿色韧性 社会网络分析 社会网络分析 空间关联网络 空间关联网络
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| GB/T 7714 | 李敏杰 , 陈毅辉 . 中国物流业绿色韧性的时空演变及空间关联网络结构 [J]. | 地理与地理信息科学 , 2024 , 40 (04) : 48-56 . |
| MLA | 李敏杰 等. "中国物流业绿色韧性的时空演变及空间关联网络结构" . | 地理与地理信息科学 40 . 04 (2024) : 48-56 . |
| APA | 李敏杰 , 陈毅辉 . 中国物流业绿色韧性的时空演变及空间关联网络结构 . | 地理与地理信息科学 , 2024 , 40 (04) , 48-56 . |
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乡村振兴是我国实现农业农村现代化、建设农业强国的重要保障。全面推进乡村振兴的核心和关键在于高素质复合型创新人才培养，这需要高等院校不断加强大学生农村创新创业教育。在实践中，大学生农村创新创业仍存在诸多困境，逐渐成为高等院校创新创业教育的掣肘。因此，高等院校不仅要传授大学生农村创新创业理论知识，更要培养他们的实践能力、团队协作精神和社会责任感。高等院校要树立农村创新创业教育理念，完善创新人才培养体系，推进思政课程和课程思政融合。高等院校还要采取多种措施对大学生农村创新创业教育的过程、效果和环境进行管理和评价。
Keyword ：
乡村振兴 乡村振兴 农村 农村 创新创业 创新创业 大学生 大学生
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| GB/T 7714 | 陈毅辉 , 李敏杰 . 乡村振兴视阈下大学生农村创新创业教育探索与实践 [J]. | 牡丹江教育学院学报 , 2024 , 6 (03) : 56-60,86 . |
| MLA | 陈毅辉 等. "乡村振兴视阈下大学生农村创新创业教育探索与实践" . | 牡丹江教育学院学报 6 . 03 (2024) : 56-60,86 . |
| APA | 陈毅辉 , 李敏杰 . 乡村振兴视阈下大学生农村创新创业教育探索与实践 . | 牡丹江教育学院学报 , 2024 , 6 (03) , 56-60,86 . |
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构建包括抵御力、恢复力、适应力、创新力和重构力5个维度的农业绿色韧性评价指标体系，运用熵值法测度2007～2021年中国30个省份的农业绿色韧性水平，借助空间马尔科夫链、地理探测器揭示其动态演变规律和影响因素。研究表明：2007～2021年中国农业绿色韧性水平呈小幅度上升趋势，但总体水平较低；空间上呈现“东部>中部>东北>西部”的分布格局。农业绿色韧性在转移过程中具有维持初始状态的“路径依赖”特征，同时存在“涓滴效应”，即与农业绿色韧性水平越高的省份邻接，其等级向上转移的概率也越大，但这种转移发生在相邻水平，不存在跨越式转移。农业绿色韧性水平的空间分异主要受科技创新能力和市场成熟程度驱动，各因素交互作用表现为双因素增强和非线性增强。据此，应强化对欠发达地区的扶持力度，加大农业领域研发投入，完善农产品市场体系，增强农业绿色韧性。
Keyword ：
农业 农业 地理探测器 地理探测器 时空格局 时空格局 空间马尔科夫链 空间马尔科夫链 绿色韧性 绿色韧性
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| GB/T 7714 | 陈毅辉 , 李敏杰 . 中国农业绿色韧性的时空格局演化及影响因素研究 [J]. | 经济体制改革 , 2024 , 9 (05) : 70-78 . |
| MLA | 陈毅辉 等. "中国农业绿色韧性的时空格局演化及影响因素研究" . | 经济体制改革 9 . 05 (2024) : 70-78 . |
| APA | 陈毅辉 , 李敏杰 . 中国农业绿色韧性的时空格局演化及影响因素研究 . | 经济体制改革 , 2024 , 9 (05) , 70-78 . |
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