Against the backdrop of global economic development and coexisting risks, digital technology has become the core driving force for enhancing the resilience of innovative industrial clusters. This article is based on panel data of China's innovative industrial clusters, and constructs a digital technology indicator system from the three-dimensional framework of "technology foundation application innovation". Combining the system GMM model, mediation effect model, and panel threshold model, it reveals the impact of digital technology on cluster resilience. Research has found that: (1) Digital technology significantly enhances the resilience level of innovative industrial clusters through the triple role of the foundation layer, application layer, and innovation layer, with the foundation of digital technology having the most significant impact on the resilience of innovative industrial clusters; (2) The spillover effects of technology and regional scale effects play a partial mediating role in the process of enhancing the resilience of innovative industrial clusters through digital technology; (3) The impact of digital technology on resilience exhibits a significant non-linear threshold effect. When the level of digital technology development crosses the critical value of 1.9612, the marginal effect jumps from 0.7902 to 1.1116 (p<0.01), showing a non-linear increase in marginal benefits. Based on this, this article provides more possible path choices for policy makers in solving the dual dilemma of "large but not strong" industrial clusters and "low innovation level lock-in".

As global climate change and environmental challenges intensify, low-carbon transformation has become a common goal worldwide. Intelligent manufacturing (IM) is a crucial driver of total factor productivity enhancement and carbon reduction, necessitating an in-depth exploration of its impact on enterprises' low-carbon transformation. This study utilizes data from Chinese A-share listed manufacturing enterprises from 2011 to 2022, taking the intelligent manufacturing demonstration projects (IMDP) policy. A staggered difference-in-differences (DID) model is adopted to analyze the impact and mechanism of IM on the total carbon emissions and carbon emission intensity. The study finds that IM reduces the total carbon emissions and carbon emission intensity of manufacturing enterprises. This effect is more pronounced in non-state-owned enterprises, high-pollution industries, and inland firms. Mechanism analysis indicates that enterprises achieve low-carbon transformation mainly through three pathways: promoting green technological innovation, improving total factor productivity, and alleviating financing constraints. Additionally, the transformation of the energy structure in the region where the enterprise is located contributes to enhancing the carbon reduction effect of IM. Research confirms that IM empowers enterprises in low-carbon transformation and provides insights for achieving green development and optimizing energy structures.

Digital trade assumes a vital role in tackling critical challenges such as the mitigation of carbon emissions and the pursuit of sustainable development. This study draws upon panel data encompassing 30 provinces and municipalities in China spanning the years 2013 to 2021. By establishing an index system to gauge regional digital trade development levels, the article examines the impact mechanism and spillover effects of digital trade on carbon reduction from both the supply and demand perspectives. The research results show that: (1) Digital trade can effectively promote regional carbon reduction, with a more pronounced effect in China's central and western regions and lower carbon emissions regions. (2) Digital trade further suppresses regional carbon emissions through green technological innovation and upgrades in residential consumption structure. (3) Digital trade has spillover effect on carbon emissions, and this “neighborhood effect” is greater than the “local effect”. Digital trade provides strong support for carbon reduction and sustainable development and also provides a strategic direction for government policy formulation.

In the era of the digital economy, digital trade has demonstrated strong vitality, becoming a crucial driving force for the high-quality development of national and regional economies. However, understanding the resilience of digital trade in the face of external crises is an important topic. Taking the backdrop of Sino-US trade friction, this paper constructs a resilience index system for digital trade. It utilizes entropy method, kernel density estimation, and ArcGIS mapping to calculate and visually analyze the resilience of China’s digital trade from 2017 to 2021. Additionally, a Tobit model is constructed to explore the main influencing factors of digital trade resilience patterns. The research findings indicate: 1) temporally, during the period of Sino-US trade friction, China’s digital trade resilience shows an overall upward trend, but there are regional differences in resilience levels across the country, with a severe polarization phenomenon. 2) Spatially, high resilience is observed in the eastern and central regions of China, while the western and northeastern regions exhibit low resilience. 3) From a dimensional perspective, the resistance of digital trade resilience displays a spatial distribution of high values in the east and low values in the west. The recovery force is aggregated along coastal areas, and the renewal force tends to aggregate along the eastern coastline. 4) Factors such as economic scale, industrial structure, urbanization rate, government fiscal expenditure, and technological talents significantly promote the enhancement of digital trade resilience. This study reveals the dynamic characteristics and influencing factors of digital trade resilience in responding to external shocks, providing theoretical basis and policy suggestions for enhancing digital trade resilience, and promoting high-quality economic development in China.

Amidst the escalating challenge of global climate change, it is imperative to further explore whether digital trade, as an emerging element in the global development landscape, can reduce carbon emissions and achieve sustainable development. This study draws upon panel data encompassing 30 provinces and municipalities in China spanning the years 2013 to 2021. By establishing an index system to gauge regional digital trade development levels, the article examines the impact mechanism and spillover effects of digital trade on carbon reduction from both the supply (enterprises) and demand (residents) perspectives. The research results show that: (1) Digital trade can effectively promote regional carbon reduction, with a more pronounced effect in China's central and western regions and lower carbon emissions regions. (2) Digital trade can incentivize green innovation by enterprises and improve residents' consumption behavior, thereby reducing carbon emissions. (3) Digital trade has spillover effect on carbon emissions, and this "neighborhood effect" is greater than the "local effect". Digital trade provides strong support for carbon reduction and sustainable development and also provides a strategic direction for government policy formulation.

数字经济和实体经济的融合是当前我国经济发展中的重要话题,关系到产业升级和结构优化,也深刻影响着要素资源的有效配置.基于2013—2020年我国30个省(直辖市、自治区)的面板数据,测度数字经济与实体经济的融合水平,并考察其时空演变特征及省际差异,实证分析各类地区数实融合对要素配置效率的影响.研究发现:(1)我国大部分省份的数实融合度仍处于较低水平,年均融合水平东部>中部>东北>西部地区,但省际差异在不断缩小.(2)相对于数字经济基础设施和数字产业化,产业数字化与实体经济的融合程度最高.(3)数实融合水平的提高能显著促进要素配置效率的提高,其中,数字基础设施与实体经济融合的促进作用最明显.此外,数实融合对劳动要素配置的优化作用大于对资本要素配置的优化作用.(4)数实融合水平的提升能显著改善Ⅲ类和Ⅳ类地区的要素配置效率,即能显著改善融合度较低省份要素配置效率,但对融合度较高省份的要素配置效率的影响不显著.

The current regional development crisis and opportunities coexist. On the one hand, the economic environment is complex and volatile, with more and more crisis shocks testing the resilience of urban development, while on the other hand, the rapid development of science and technology such as the digital economy has affected all areas of the economy, life, and governance of cities, bringing opportunities for urban development. The use of digital transformation to enhance urban resilience is therefore an obvious and important topic. Based on panel data of 27 cities in the Yangtze River Delta from 2011 to 2020, this study empirically analyses the impact of digital transformation on urban resilience by constructing a fixed effects model, a mediated effects model and a spatial Du bin model. The study finds that: (1) In terms of time, the urban resilience and digital transformation capacity of the Yangtze River Delta region are both on the rise; From a spatial point of view, the urban resilience of the Yangtze River Delta region basically shows a spatial distribution pattern of "high in the central cities, and low in the peripheral cities", while the digital transformation capacity basically shows a pattern of "high in the east-central region, and low in the west". (2) Digital transformation has a significant positive impact on improving urban resilience; (3) Digital transformation enhances urban resilience through three main paths: technological innovation capacity, new economic sector development momentum, and innovation and entrepreneurship development vitality; (4) Digital transformation has a spatial spillover effect on the urban resilience of neighboring regions.

推动山区 26 县跨越式高质量发展,是浙江省高质量发展建设共同富裕示范区的重点、难点与关键点,事关浙江现代化先行和共同富裕示范区建设全局.2021 年 7 月,《浙江省山区 26 县跨越式高质量发展实施方案(2021—2025 年)》印发,正式将山区县探索共同富裕新路径纳入快车道.

随着乡村振兴战略的推进,浙江省农村产业形成了新业态和新模式.浙江省松阳县石仓村是这方面的典型样本.在同一区位,石仓村形成了三种不同的新业态和新模式,促进了乡村产业振兴,提升了经济效益、生态效益和社会效益.

企业直接投资区位选择是经济地理学的经典议题.目前直接将区位条件与关系网络衔接起来分析企业直接投资区位选择过程的研究较为少见.本文基于关系视角和中国情境,构建了关系连通、区位耦合、博弈谈判三位一体的模型,提出了 一种对企业直接投资区位选择过程化的理解方法.文章以案例研究方法,对企业家赴甘肃省和浙江省开发区投资考察过程进行了参与式观察与访谈.研究发现,企业直接投资区位选择遵循关系连通—区位耦合—博弈谈判的过程.第一,企业与投资地关系连通是企业到当地投资的前提,而结构洞有利于企业与投资地关系形成.第二,企业与投资地区位耦合是企业投资区位选择的必经过程.第三,企业与投资地政府博弈谈判是企业投资的重要过程,且必须达成两厢情愿企业才可能在当地投资.在中国情境中,本文的理论模型具有现实代表性.本文的创新之处是结合中国情境,运用关系视角,对企业投资区位选择过程进行了理论重构.

Under the new development pattern of "dual circulation" in China, it is of great theoretical and practical significance to study the spatial pattern and evolution law of port systems. This study takes the port system in the Yangtze River Delta Region (YRDR) as an example, based on the panel data from 2000 to 2019, analyses the spatial pattern and evolution characteristics of port domestic trade throughput (PDTT) and port foreign trade throughput (PFTT) from the perspective of dual circulation. The key influencing factors in the evolutionary process are explained, and the spatio-temporal evolution characteristics of the two types of port throughput are compared. The results show that (1) in spatial evolution, the PDTT and PFTT of the port system in the YRDR fluctuate and increase significantly, showing a typical three-level echelon structure in space. (2) From the perspective of spatial equilibrium, the two types of port throughput are markedly discrete; however, the degree of agglomeration of PFTT is greater than that of PDTT. (3) In spatial patterns, the centers of gravity of PDTT and PFTT are distributed in Suzhou and Jiaxing, respectively. Both are distributed from northwest to southeast. However, the rotation angle of PFTT was larger, and the north-south differentiation was more evident than that of PDTT. (4) In influencing factors, the throughput pattern of the port system in the YRDR is driven by multiple factors, and some differences exist in the driving mechanism between PDTT and PFTT.

运用指标体系法对浙江省县域资本进行了测度,使用多因素方差分析不同地域资本类型地区的经济韧性,在上述基础上,运用巴罗线性区域增长模型分析了地域资本与经济韧性之间的关系.研究结果表明:地域资本最丰富的地区(类型Ⅰ)为杭州市区和宁波市区,地域资本较为丰富地区(类型Ⅱ)包括淳安县、临安市、安吉县等16个地区,中间区(类型Ⅲ)包括富阳市、桐庐县等13个地区;地域资本较稀缺地区(类型Ⅳ)包括建德市、磐安县等20个地区,低地域资本地区(类型Ⅴ)包括庆元县、遂昌县等15个地区;地域资本最丰富的地区(类型Ⅰ)比其他类型地区更有韧性,而低地域资本地区(类型Ⅴ)韧性最低.国际金融危机期间,人均GDP与对最初冲击的抵抗力呈现正相关关系,与对缺口的阻力呈现负相关关系;外商直接投资越高的地区抵御冲击的能力越强;外部资本与人力资本对不同地区韧性均有显著影响,而集聚经济与韧性无直接关系;私营资本对韧性的作用较小.

在"乡村振兴"背景下,农村既面临着发展机遇,又面临着来自各种不确定事件的挑战.为分析外部冲击对农村韧性的影响,文章以浙江省农村地区为例,建构了农村韧性指标体系,融合农村地区的异质性与多样性,研究了浙江省农村地区应对冲击的韧性问题及地区差异,分析了影响浙江省农村韧性的主要因素.研究发现:①浙江省北部农村地区发展整体比南部农村地区好,不同地区之间韧性水平差距不仅表现在较为明显的经济发展水平上,更体现在不易被察觉的社会福利水平、人口素质、自然环境等方面.②浙江省农村韧性可分为5种类型,发展较好的类型V与类型Ⅳ地区偏向于全面发展,拥有较强的可持续发展能力,类型Ⅲ地区处于一种较低的均衡当中,拥有可持续发展的潜力,而类型Ⅱ与类型I地区的要素禀赋良莠不齐,可持续发展能力较弱.③经济、社会、人力和生态资本的不同方面共同促进浙江省农村地区的韧性变化,其中经济发展水平、经济多元化、通讯技术可获得性、连通性、人口规模等因素成为影响农村韧性的重要因素.

当前经济环境复杂多变,产业集群面临的冲击越来越多,一些集群有可能实现路径突破,而一些集群可能会落入发展的低端陷阱而难以自拔.因此,研究产业集群在危机冲击下的韧性特征、影响因素以及如何走上复苏道路是摆在研究者面前的重要问题.利用中国工企数据库对长三角地区电子信息产业集群进行识别,判断其所遭受的主要冲击,从抵抗力和恢复力两个维度测度集群韧性,构建数学模型分析韧性影响因素.结果表明:①集群面临两次冲击的抵抗力均较弱;②集群在遭遇两次冲击后的恢复力较好,均强于抵抗力,但各个集群的恢复力差异明显,出口比例高的集群更容易受到经济危机的冲击;③外生型集群韧性主要体现为"低抵抗力-高恢复力"型和"高抵抗力-低恢复力"型,内生型集群韧性主要体现为"低抵抗力-高恢复力"型;④区域产业非相关多样性仅对两次冲击中的集群恢复力具有促进作用,对抵抗力的影响不明显.区域产业相关多样化对两次冲击的抵抗力和恢复力均无显著影响.企业知识异质性对集群抵抗力和恢复力发挥正向促进作用,而集群的对外开放程度在总体上发挥了抑制作用.龙头企业对在两次冲击下集群抵抗力的作用方向不同.所有制异质性和年轻企业占比对集群韧性的影响作用不明显.

采用"理论演绎-案例实证-机理阐释"的研究逻辑,从空间视角提出理论假设,分析港口体系在运量、航线与后勤3个维度的集散及转型规律,并以长三角集装箱港口体系为例进行假设验证.结果 表明,运量和航线总体上表现为空间分散化态势,低端后勤要素亦由中心枢纽港城市向外围边缘港城市扩散,但高端后勤要素在空间上呈现出进一步向中心枢纽港城市集聚的趋势.通过数理模型研究发现,全球化、市场化、信息化等外部因素以及城市工业发展水平促使运量和航线趋子集聚分布,腹地经济实力、传统交通因素以及金融发展水平、服务化水平等推动运量和航线趋于离散分布;同时,腹地经济和交通等传统因素对港口后勤要素区位选择的影响程度有所下降,而全球化、市场化、服务化等外部因素以及信息化、金融发展水平等新兴因素的影响程度明显上升,尤其对高端后勤要素的区位决策影响更显著.

区域韧性是指区域受冲击后生成新路径的能力.2008年金融危机爆发后,受到学术界的广泛关注,特别是在城市和区域经济学以及经济地理学中.本文基于韧性理论,对三个欧美典型地区在发展中遭遇的危机冲击、路径创造及韧性因素进行分析,认为影响区域韧性的关键因素有区域创新、产业结构和政府效能等.鉴于当前国内外复杂的形势,我国地区发展存在危机冲击的风险,欧美地区的典型案例可为我国东北老工业基地转型、东部沿海地区转型升级和西部地区的振兴提供了有益的借鉴.最后,论文对区域韧性的相关问题进行了进一步思考.

利用全局主成分分析法对全国体育用品制造业创新能力进行比较,并应用收敛模型进行检验.研究发现:(1)我国各省市体育用品制造业创新能力的差距较大,我国体育用品制造业创新能力可分为3类,第1类创新能力最强,包括北京、天津、上海和浙江.第2类次之,包括安徽、湖南、广东、重庆和江苏.其它为第3类,创新能力弱.(2)只有第1类地区表现出较明显的σ发散,说明其内部各省市间体育用品制造业创新能力差异在逐步扩大.(3)在全国范围内以及第3类地区内存在绝对β收敛,说明其内部各省市的体育用品制造业创新能力增长速度呈现收敛趋势.(4)全国总体、第2类地区和第3类地区都存在条件β收敛,表明在吸收先进技术和获得管理经验后,其体育用品制造业的创新能力增长速度得到提升,最终各地区达到一个稳态水平.研究旨在通过分析我国地区体育用品制造业创新能力差异及收敛的可能性,为缩小地区差距、从整体上提升我国体育用品制造业创新能力提供借鉴.

在区域一体化背景下,基于资金流通、产业发展、劳动力供给和交通信息4个维度构建指标体系,运用势能联系模型测度2007-2017年长三角潜在经济关系,并从空间格局和网络特征双重视角对测度结果进行深度分析.主要得出如下结论:①长三角潜在经济关系上升态势明显,空间上表现为典型的"三圈层"结构特征;②潜在经济关系总体上呈现极化趋势,上海与其他3省域潜在经济关系的基尼系数下降明显,但苏浙皖之间的基尼系数仍在上升;③潜在经济关系的点度中心性和中介中心性均呈上升态势,潜在经济关系网络表现为明显的4类凝聚子群结构;④长三角经济合作潜力格局呈现空间马太效应,少数城市表现出异质性特征.根据研究结论提出政策建议:优化长三角空间一体化格局,权衡区内与区外经济联系,强化合作潜力大的城市之间的经济联系,完善一体化运行的体制机制.

结合我国体育用品规上制造业的区位熵及产值份额变化量来识别体育用品制造业的转移,通过标准差椭圆结果分析其转移的方向、路径与距离,同时运用逻辑模型对短面板数据进行回归,分析2000—2015年影响我国体育用品制造业产业转移的因素,研究得出以下结论:(1)我国体育用品制造业在东部地区具有绝对集聚优势,但通过产业转移,一些中西部省份如江西、湖南等开始跻身优势区域;(2)在转移数量上,上海、福建转出量最大,中部地区江西、湖南和安徽转入量最大,西部地区四川、广西转入最大,东部地区如山东也存在产业转入;(3)我国体育用品制造业在空间上呈"北(偏东)—南(偏西)"的分布格局,并呈现"北偏西-西偏南-南偏西"垂直翻转的"√"型转移的趋势;(4)产业固定资产投资、人力资源、技术水平、基础设施、经济支撑是促进我国体育用品制造业转入的主要因素;人力成本越高、地方政府税收越高则会降低产业转入的概率,其中人力资源与地方政府政策影响程度最大.

构建我国体育用品制造业升级能力综合评价指标体系,采用熵值法对全国22个省(直辖市、自治区)2007-2015年的体育用品制造业升级能力进行评价,并运用Dagum基尼系数分解法和Kernel密度估计方法对我国四个主要经济区体育用品制造业升级能力的空间非均衡及分布动态演化进行了实证.研究结果表明:(1)我国体育用品制造业升级能力分布呈现东强西弱、南强北弱的格局,长三角经济区的体育用品制造业升级能力始终高于全国平均水平,而京津冀和东北经济区的产业升级能力均低于全国平均水平;(2)四大经济区的总体差距呈现小幅波动上升的趋势,地区间差距是总体差距的第一来源,地区内差距贡献次之,超变密度贡献率最小;(3)Kernel密度函数估计显示,虽然我国体育用品制造业升级能力在样本考察期内略有提升,但各经济区内出现了两极分化和多极化趋势.