专利密集型制造业绿色转型路径研究——基于EBM-GML模型与fsQCA的双重分析

专利密集型制造业是实现绿色转型升级与经济高质量发展的新引擎。如何协同技术、组织和环境三个层面,提升绿色转型效率是亟待解决的现实问题。论文以专利密集型制造业为研究对象,运用EBM-GML模型与模糊集定性比较分析方法,基于TOE框架探讨专利密集型制造业绿色转型路径。研究发现:(1)我国专利密集型制造业还未真正实现技术创新与绿色发展有效融合;(2)单个因素均无法作为推动绿色转型的必要条件;(3)存在环境主导型、自主创新型、全维度协同型三条驱动专利密集型制造业高绿色转型的路径,与非高绿色转型驱动路径存在非对称关系;(4)知识产权保护是专利密集型制造业绿色转型的关键因素。研究为专利密集型制造业绿色转型实践提供了经验借鉴。

长三角地区绿色经济效率的时空特征及影响因素分析

将非期望产出纳入EBM-GML模型,测算2010—2021年长三角地区41个地级市绿色经济效率,利用莫兰指数探讨其空间相关性,借助GWR模型分析多因素对长三角地区绿色经济效率的空间异质性影响。结果表明:(1)长三角地区绿色经济效率整体呈上升走势,时间上呈“波峰”形分布,空间上表现为非均衡发展;(2)全局空间正相关性由强减弱,局部形成以南通市为中心的“高高”集聚区和以合肥市为中心的“低低”集聚区;(3)影响因素上,绿色经济效率受经济发展、科技创新和环境规制的促进作用显著,而产业结构、金融发展、外商投资则表现为波动性关系。长三角地区应加强区域合作,推动一体化发展;发挥绿色经济高效率城市的辐射和溢出效应,缩小相邻城市的绿色发展差距;优化产业结构和投资环境,培育新发展动能。

Evaluation of the sustainable development level of countries along the Belt and Road and its impact factors:Empirical analysis based on the Super-efficiency slacks-based measure and Tobit measure models

Sustainable development is an important component of the Belt and Road Initiative(BRI)and is of great significance for evaluating the levels of sustainable development of countries along this route(henceforth,BRI countries).Therefore,this study aims to identify the factors that influence the levels of sustainable development of BRI countries in a reasonable and objective manner.Eventually,this study employs the super efficiency slacks-based measure(Super-SBM)model,which considers unexpected outputs to measure the level of sustainable development of BRI countries.The dynamic change and composition of the sustainable development level of these countries are calculated using the global Malmquist-Luenberger index.Furthermore,the Tobit model is used to identify the factors influencing the level of sustainable development of BRI countries in general and in various categories.The empirical results suggest the following points.(a)The overall level of sustainable development of BRI countries is low,whereas those of high-income and middle-and high-income countries are relatively high.(b)The overall sustainable development levels of BRI countries declined to a certain extent in 2008 owing to the effect of the financial crisis,.However,the sustainable development level of other countries,barring low-income countries,has gradually increased since 2011.(c)Since 2008,technological progress has replaced technical efficiency as the main driving force behind the improvement of the sustainable development level of BRI countries.(d)A U-shaped relationship is observed between the economic and sustainable development levels of these countries.(e)The level of science and technology and the proportion of renewable energy consumption can promote the sustainable development of these countries.Moreover,a negative correlation exists between the level of opening to the outside world and that of sustainable development of countries that mainly export resource-based products and are dominated by labor-intensive export industries.Barring low-income countries,the energy structure plays an effective role in improving the level of sustainable development.Finally,the study presents suggestions for China in the process of coping with the sustainable development of relevant countries during its promotion of the BRI.

Research on Smart Growth of Sustainable Cities Based on Information Entropy and Super-Efficiency DEA Model

Since the “smart growth” was put forward in the late 90s, it has become an accepted design idea and concept in the field of urban design in the world, and has been deeply studied and applied. In order to better promote “smart grown”, we set up an evaluation system, which consists of eleven indicators. In this paper, Oxford City and Fengzhen City are used as the objects of the study. Then smart growth evaluation model is established. The weight of the index is calculated by the entropy method. We use the model to evaluate the development plans of the two cities, from which to calculate the contribution of the indicators on the level of smart growth. Finally, we use the super-efficient data envelopment analysis model (DEA) to rank the importance of the indicators to the smart growth. The results show that the level of smart growth in Oxford is higher than that in Fengzhen. And “Multifunctional Building Density in Central City”, “The Density of Public Area in Central City” two indicators account for more than 36% weight. The contribution of the two indicators is also located in the top two indicators. Two cities focus on the direction of smart growth is also different. In summary, the differences between China and Western countries in urban planning are mainly focused on housing and public resources.

绿色生态效率时空分异特征及其影响因素研究——基于长三角城市群的实证分析

论文运用超效率EBM-GML模型测算了长三角城市群2008—2020年的生态效率,识别其时空分异特征及影响因素。研究发现:(1)长三角城市群生态效率在时间上呈波动上升趋势,在空间上呈“东高西低”的分布特征。(2)仅少数城市投入产出均有效率,其余城市效率不高,主要是源于能源利用率低、能源结构不合理和污染防治体系不健全。(3)Tobit模型结果表明经济发展、产业结构高级化、外商投资规模可以显著提高生态效率。(4)都市圈与城市规模差异对生态效率的影响效应存在异质性,经济发展对非上海大都市圈和小型城市生态效率正向作用更强烈。因此,要加快推动长三角一体化,促进各城市绿色协同发展。

中国全要素碳生产率及时空分异研究——基于中国30个省份的数据

运用EBM模型和全局Malmqusit-Luenberger指数对2011—2020年中国30个省份的全要素碳生产率(TFCP)进行测算,采用核密度函数和Dagum基尼系数及其分解法考察中国全要素碳生产率的时空分异特征。研究表明:(1)中国全要素碳生产率总体呈上升趋势,其中西部地区全要素碳生产率增长速度最快,整个样本时期内西部地区TFCP增长水平最高,之后依次是东部地区和中部地区,东北地区最低且自2015年起TFCP出现负增长并且趋势不断扩大。(2)通过核密度函数分析发现:全要素碳生产率水平存在区域差异,全国和四大区域内全要素碳生产率水平的绝对差异均呈一定的上升趋势,但随着时间的推移,全要素碳生产率水平高的省份与其他省份之间的差距有所缩小;近年来东中西地区极化现象减少,东北地区部分年份极化现象明显,变化规律性较小。(3)通过Dagum基尼系数及分解分析发现:从时序发展过程来看,西部地区和东北部地区的全要素碳生产率在十年间呈上升趋势,东部和中部地区的地区内则呈现下降趋势;从空间分异来看,西部和东北部地区之间的空间分异程度最大,东—中部地区、东—东北地区、东—西部地区之间的整体走势相近,中—西部地区、中—东北地区、西—东北地区之间的整体走势相近,区域间分异程度都呈现明显的扩大趋势。

数字贸易对碳排放效率影响的理论机制与溢出效应研究

提高碳排放效率是推动经济高质量发展的内在要求,因此,迫切需要寻找经济绿色发展的驱动引擎。本文采用EBM-GML测算2012-2020年中国30个省份(不包含西藏及港澳台地区)的碳排放效率,理论分析和实证检验了数字贸易对碳排放效率的作用机制及空间溢出效应。研究发现,数字贸易对碳排放效率具有显著促进作用,且相较于内陆区域,数字贸易对碳排放效率的促进作用在沿海区域更为明显。技术效率和技术进步为数字贸易影响碳排放效率的两大作用渠道,其中,促进作用主要来源于技术效率。空间计量发现,数字贸易对邻近区域碳排放效率存在正向的空间溢出效应。据此,地方政府在推进数字贸易发展过程中,需统筹数字贸易与前沿技术协调发展,为全球贸易数字化发展浪潮下我国如期实现“双碳”目标创造条件。

数字经济对我国制造业绿色全要素生产率的影响

数字经济作为一种新型经济形态,正不断融入经济社会各领域的全过程,为传统产业高端化、智能化、绿色化转型升级提供了有效途径。为了探究数字经济与制造业高质量发展之间的关联性,本文基于2013~2021年中国30个省份的面板数据,分别利用熵值法和EBM-GML模型测算数字经济发展水平与制造业绿色全要素生产率,探究数字经济对制造业绿色全要素生产率的影响。研究结果表明:数字经济对制造业绿色全要素生产率有显著的促进作用,数字经济发展水平越高,其对绿色全要素生产率的促进作用越大,且这一结论具有稳健性;数字经济对制造业绿色全要素生产率的影响具有区域异质性,数字经济能够显著提升东部地区制造业绿色全要素生产率,对中、西部地区的影响不显著。建议从加快两化融合发展、实施区域差异化发展策略、培养数字化人才等方面推动制造业高质量发展。As a new economic paradigm, the digital economy is continuously integrating into all areas of economic and social processes, providing effective pathways for the upgrade and transformation of traditional industries towards a more advanced, intelligent, and environmentally friendly model. In order to explore the correlation between the digital economy and the high-quality development of the manufacturing industry, based on the panel data of 30 provinces in China from 2013 to 2021, this paper uses the entropy method and EBM-GML model respectively to estimate the development level of the digital economy and green total factor productivity of manufacturing industry, and explores the impact of the digital economy on green total factor productivity of manufacturing industry. The results show that the digital economy has a significant promoting effect on the green total factor productivity of the manufacturing industry, and the higher the development level of the digital economy, the greater the promoting effect on green total factor productivity. This conclusion is robust;The influence of digital economy on the green TFP of the manufacturing industry has regional heterogeneity. The digital economy can significantly improve the green TFP of the manufacturing industry in the eastern region, but has no significant impact on the central and western regions. It is suggested to promote the high-quality development of the manufacturing industry from the aspects of accelerating the integrated development of the two, implementing regional differentiated development strategies, and training digital talents.

基于SBM-GML与面板门槛效应的碳排放强度与绿色全要素生产率的关系研究

如何实现工业绿色高质量发展已成为经济社会发展的迫切要求,提升绿色全要素生产率与经济高质量发展高度相关。本文基于SBM-GML模型和面板门槛回归模型,测算2005-2020年中国省市的绿色全要素生产率,并从区域和企业层面分析工业绿色全要素生产率的发展动态及其影响因素,以期对省市和企业发展提供理论借鉴。

人口老龄化对农业绿色全要素生产率的影响机制与门槛效应

探讨农村人口老龄化对农业绿色全要素生产率的影响与机理,为实现农业绿色、高质量发展提供政策启示。本文样本选自中国30个省(直辖市、自治区)2013—2021年度的面板数据,借助EBM-GML模型测算农业绿色全要素生产率,并通过面板中介效应与门槛模型分析农村人口老龄化对农业绿色全要素生产率的影响机制及门槛效应。结果表明:(1)从影响效果看,农村人口老龄化能够助推农业绿色全要素生产率提升;(2)从中介效应看,在农村人口老龄化对农业绿色全要素生产率的影响中,土地规模经营机制和农产品结构优化机制起显著的正向中介作用;(3)从门槛效应看,以城镇化水平为门槛变量,农村人口老龄化与农业绿色全要素生产率之间存在单门槛效应,未达到门槛值时,农村人口老龄化对农业绿色全要素生产率具有负面作用,当其达到临界点后,则具有明显的积极作用。因此,本文提出通过提高老龄劳动力人力资本水平、发展土地适度规模经营、优化农产品结构、推进人口城镇化等途径促进农业绿色全要素生产率提升。

基于极效率DEA模型的港口绩效评价

对集装箱港口的绩效进行评价一直是港口当局关心的问题,现有文献尚未提出比较有效的方法,尝试利用极效率(super-efficiency)DEA模型对集装箱港口的绩效进行评价。极效率DEA模型能够有效地区别出有效(绩效值1)决策单元之间的绩效差异,可以对所评价的决策单元进行有效的排序。此方法已在城市和企业的评价中得到了应用,但尚未在港口得到应用。在案例中,汉堡港最有效率,新加坡港次之,然后是香港港、泽布勒赫港和基隆港,香港港由于船舶的无效逗留时间长、新加坡港集卡数配置不合理,导致两者的绩效低于吞吐量远小于它们的港口。

环境规制、绿色技术创新与制造业绿色全要素生产率

本文基于我国30个省(区、市)2011~2021年的面板数据,运用EBM-GML模型测算出制造业绿色全要素生产率,将环境规制、绿色技术创新和制造业绿色全要素生产率纳入同一个分析框架中,建立PVAR向量自回归模型,并在此基础上运用GMM系统方法、格兰杰因果检验、脉冲响应函数和方差分解方法,对三者之间的内在关系进行了深入的分析和实证研究。研究结果表明:环境规制对绿色技术创新具有促进作用,对制造业绿色全要素生产率在短期内具有抑制作用,在长期内具有促进作用;绿色技术创新对环境规制具有抑制作用,对制造业绿色全要素生产率具有促进作用;制造业绿色全要素生产率对环境规制在短期内具有促进作用,长期内具有抑制作用,而对绿色技术创新均具有促进作用。最后基于以上研究结果提出相应政策建议。

我国海水养殖业绿色技术进步测度及其影响因素研究

本文运用EBM-GML方法,以沿海10个省份2008-2015年数据为样本测算我国海水养殖业绿色技术进步,并运用可行广义最小二乘法分析绿色技术进步的影响因素。研究表明,我国海水养殖业的绿色技术进步水平总体呈现上升趋势。技术推广因素和规模因素是促进当前我国海水养殖业绿色技术进步的关键因素,而与技术形成相关的科教投入因素的影响不显著。最后,根据研究结果提出了相应政策建议。

数字化转型提升了绿色全要素能源效率吗?——来自中国A股工业上市企业的经验证据

本文以2010—2021年中国A股工业上市企业为样本,运用EBM-GML模型对企业绿色全要素能源效率进行测算,并实证考察企业数字化转型对其提升效果的影响及作用机制。研究发现:数字化转型能够稳健且显著地提升企业绿色全要素能源效率,企业技术创新效率、管理效率在其中均起到中介作用;异质性分析发现,数字化转型对国有企业、“两高”企业、高新技术企业、东部及南部地区企业的绿色全要素能源效率的提升作用更为明显。因此,应重视数字化转型的战略价值,促进数字化加速融入能源管理体系;发挥数字化转型优势,赋能企业技术创新和管理优化;强化对企业数字化转型的引导和监督,推进数字化健康发展。

农业碳排放效率测度及空间溢出效应

基于2000—2021年的原始数据,采用EBM-GML模型测算我国农业碳排放效率,引入空间莫兰指数,分析农业碳排放效率的动态空间演变过程和空间关联性,进一步采用空间杜宾模型探讨农业碳排放效率的影响因素和溢出效应。研究表明,我国农业碳排放效率整体上处于上升状态,具有较强碳减排能力;各省份农业碳排放效率存在较大差异,空间上具有较强的关联性;农业碳排放效率具有正向的空间溢出效应,对邻省的农业投资强度、有效灌溉率和农业经济发展水平具有正向的空间溢出效应,对作物种植结构具有负向的空间溢出效应。应制定差异化低碳农业发展政策,加强农业投资强度和提升农业经济发展水平,协调均衡推进低碳农业化进程。

中国农田水利投资全要素生产率增长的分布动态演进

中国农田水利投资力度不断加大,其投资效率问题不容忽视。采用EBM与GML相结合的方法,对基于非期望产出的中国农田水利投资全要素生产率(TFP)进行测度,运用Dagum基尼系数法探究地区差异的来源,应用核密度方法分析中国农田水利投资TFP的分布动态,最后通过Markov链方法描述中国农田水利投资TFP的分布格局。研究表明:中国农田水利投资TFP年均增长3.60%,呈现“双轮驱动”的特征;东北和东部地区增长速度相对较快,而中西部地区增长速度相对缓慢;区域差异呈波动状态,主要由超变密度贡献;时空转移受空间因素影响较大,难以形成“等级锁定”。研究成果有助于为政府优化水利投资结构提供正确方向。据此建议:注重中西部地区水利投资和水资源效率的提升,加强邻近省份农田水利投资的协同合作,推进农田水利投资市场化运行进程,激励各地因地制宜利用好自身水资源优势。

Performance Evaluation of Public Bus Transportation by Using DEA Models and Shannon’s Entropy:An Example From a Company in a Large City of China

The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.

Dynamic analysis of agricultural green development efficiency in China: Spatiotemporal evolution and influencing factors

Green development of agriculture is important for achieving coordinated and high-quality regional development for China. Using provincial data from 1990 to 2020, this work explored the dynamics of agricultural green development efficiency of 31 provinces in China, its spatiotemporal characteristics, and its driving factors using a super-efficiency slacks-based measure(Super-SBM), the Malmquist productivity index(MPI), spatial autocorrelation, and a geographic detector. Results showed that the overall agricultural green development efficiency showed a U-shaped trend, suggesting a low level of efficiency. Although a gradient difference was visible among eastern, central, and western regions, the efficiency gap narrowed each year. Technological progress and efficiency both promoted agricultural green development efficiency, especially technological progress. Agricultural green development efficiency had significant spatial aggregation characteristics, but Moran’s Ⅰ result showed a downward trend from 2015 to 2020, indicating a risk of spatial dispersion in the later stage. The provinces with high agricultural green development efficiency were mainly concentrated in the eastern region, while those with low efficiency were concentrated in the central and western regions. Agricultural green development efficiency was influenced by various factors, which showed differences according to time and region. The impact of the labor force’s education level and technological progress increased during the study period, and significantly facilitated agricultural green development efficiency in the eastern region, while the central and western regions were still affected by the scale level and environmental regulation, reflecting the advantages of the eastern region in terms of economy and technology. In the future, strengthening agricultural scientific and technological innovation and deepening interprovincial cooperation can help further improve the level of green agricultural development. In addition, local governments should formulate more precise local agricultural support policies based on macro-level policies and local conditions.

The spatial-temporal differentiation of green land use in Beijing-Tianjin-Hebei urban agglomeration

As the space carrier of the construction of ecological civilization, land's green and efficient utilization is an important guarantee for realizing national sustainable development. Based on traditional land evaluation, this paper scientifically defines the green land use, puts land as one of the production factors, and brings energy consumption, environmental pollution, etc. into the input-output system to measure the green land utilization efficiency of the urban construction land of Beijing-TianjinHebei Urban Agglomeration from 2006 to 2016. The study shows that the overall efficiency variation of the urban agglomeration is related with the land and environment policies. Efficiency of 2016 is higher than that of 2006, and energy and environment are the principal factors affecting the green land use. The efficiency of each city is positively correlated with its economic development, negatively correlated with the construction land expansion. Efficiency gaps in different cities are expanding.There is positive correlation with overall weak space between cities, and the partial spatial agglomeration phenomenon appears. Therefore, the green land use efficiency could be improved by improving land utilization efficiency, coordinating economic growth of construction land utilization with environmental protection and taking feasible ways to transregional renovation of the stock ecological land utilization, etc.

SE-DEA-SVM evaluation method of ECM operational disposition scheme

Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a super-efficient data envelopment analysis support vector machine(SE-DEA-SVM)method for evaluating the operational configuration scheme of ECM is proposed.Firstly,considering the subjective and objective factors affecting the operational disposition of ECM,the index system of operational disposition scheme is established,and we explain the solution method of terminal indexs.Secondly,the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced.In this method,the super-efficient data envelopment analysis(SE-DEA)model is used to calculate the weight of index system,and the support vector machine(SVM)method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configuration.Finally,by an example(obtaining five schemes),we verify the SE-DEA-SVM evaluation method and analyze the results.The efficiency analysis,comparison analysis,and error analysis of this method are carried out.The results show that this method is more suitable for military evaluation with small samples,and it has high efficiency,applicability,and popularization value.