市场转向与产业升级路径分析——以珠江三角洲出口导向型家具产业为例

近年来,特别是2008年全球金融危机爆发以后,中国出口导向型制造业出现了由以出口为主转向出口和内销并进的发展趋势。然而现有文献较少关注市场转向对制造业企业产业升级的影响。基于全球生产网络的视角,以珠江三角洲出口导向型家具产业为例,通过以深度访谈为主的定性研究方法,探讨出口导向型制造业企业在出口转内销过程中的产业升级路径。结果显示：在与中国国内市场进行战略耦合（strategic coupling）的过程中,家具制造业企业分别通过网络式、企业内部协调式及市场型方式嵌入国内市场导向型的生产网络,并呈现出产业升级（upgrading）和降级（downgrading）等多元化路径。中国市场为家具制造业企业提供了产业升级特别是功能升级的机会,但小部分制造业企业也经历着产品降级的过程。研究市场转向中的产业升级对理解后危机时代新兴市场的崛起具有一定的理论意义;同时对理解在全球经济背景下中国出口导向型加工制造业转型具有实践意义。     

Structural attributes of individual trees for identifying homogeneous patches in a tropical rainforest

Mapping and monitoring tropical rainforests and quantifying their carbon stocks are important, both for devising strategies for their conservation and mitigating the effects of climate change. Airborne Laser Scanning (ALS) has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. This study identifies forest patches using ALS-based structural attributes in a tropical rainforest in Sumatra, Indonesia. A method to group trees with similar attributes into forest patches based on Thiessen polygons and k-medoids clustering is developed, combining the advantages of both raster and individual tree–based methods. The structural composition of the patches could be an indicator of habitat type and quality. The patches could also be a basis for developing allometric models for more accurate estimation of carbon stock than is currently possible with generalised models.     

Class imbalance in unsupervised change detection – A diagnostic analysis from urban remote sensing

Automatic monitoring of changes on the Earth’s surface is an intrinsic capability and simultaneously a persistent methodological challenge in remote sensing, especially regarding imagery with very-high spatial resolution (VHR) and complex urban environments. In order to enable a high level of automatization, the change detection problem is solved in an unsupervised way to alleviate efforts associated with collection of properly encoded prior knowledge. In this context, this paper systematically investigates the nature and effects of class distribution and class imbalance in an unsupervised binary change detection application based on VHR imagery over urban areas. For this purpose, a diagnostic framework for sensitivity analysis of a large range of possible degrees of class imbalance is presented, which is of particular importance with respect to unsupervised approaches where the content of images and thus the occurrence and the distribution of classes are generally unknown a priori. Furthermore, this framework can serve as a general technique to evaluate model transferability in any two-class classification problem. The applied change detection approach is based on object-based difference features calculated from VHR imagery and subsequent unsupervised two-class clustering using k‐means, genetic k-means and self-organizing map (SOM) clustering. The results from two test sites with different structural characteristics of the built environment demonstrated that classification performance is generally worse in imbalanced class distribution settings while best results were reached in balanced or close to balanced situations. Regarding suitable accuracy measures for evaluating model performance in imbalanced settings, this study revealed that the Kappa statistics show significant response to class distribution while the true skill statistic was widely insensitive to imbalanced classes. In general, the genetic k-means clustering algorithm achieved the most robust results with respect to class imbalance while the SOM clustering exhibited a distinct optimization towards a balanced distribution of classes.     

NET‐DBSCAN: clustering the nodes of a dynamic linear network

NET‐DBSCAN, a method for clustering the nodes of a linear network, whose edges may be temporarily inaccessible, is introduced. The new method extends the idea of a well‐known spatial clustering method, named density‐based spatial clustering of applications with noise (DBSCAN). The new algorithm is described in detail and through a series of examples. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic networks, is also presented. Finally, the application of NET‐DBSCAN method to support real‐world situations is briefly discussed.     

Evolution of clusters in dynamic point patterns: with a case study of Ants' simulation

Recent developments in sensing and tracking technologies have enabled large geographical databases to be established that represent spatial dynamics of ‘behavioral entities’. Within this type of dynamics there are several levels and modes of organization that need to be revealed. Clusters are high‐level groupings of entities, where change in their location and form, including split and merge events, represents self‐organization and functioning patterns. Such information may contribute for better understanding spatially complex dynamic patterns. The main objective of this article is to develop an adaptable methodology that facilitates exploration of spatial order and processes in point pattern dynamics. The approach presented here utilizes data‐clustering at each snapshot of the moving pattern, and then involves pairwise linking between the clusters identified at each snapshot and those identified in the following snapshot. Such linking is based on a new methodology that defines well globally optimized solutions for numerous possible linking combinations based on Linear Programming. A preliminary assessment of the approach was conducted with an existing Ants' simulation tool, capable of creating data sets covering in detail a substantial portion of the nest's life cycle.     

Fast-growing firms as elements of change in Canada’s headquarters city system

This research explores the factors that shape the evolving geographic distribution of business headquarters (HQ) activity. We address an understudied influence on HQ geographies: metropolitan HQ changes driven by the process of small, rapidly expanding businesses growing into mature companies. This investigation focuses on the developmental paths followed by fast-growing firms (FGFs) and the geographic distinctions that can be observed in a FGF tracking study of Canada’s metropolitan regions from 1987 to 2005. Our research findings indicate that geography plays an important role in this development, as FGF tracking records throughout Canada’s metropolitan areas diverge sharply. We find that most FGFs that emerged in Vancouver and Toronto continued as ongoing businesses following their rapid growth phase, while a high proportion of FGFs based in Montréal and Calgary did not. These results contribute to a greater understanding of metropolitan economies, business development, and HQ location in Canada     

企业所有制结构与中国区域产业演化路径

以技术关联性与技术复杂性为标准划分出四类区域产业演化路径,利用2000-2016年中国海关进出口贸易数据库,集成新产业识别方法,考察了中国不同地区产业演化路径的差异性并分析了企业所有制对区域产业演化路径的影响.研究发现:①中国区域产业演化具有路径依赖性.2000-2016年,路径依赖型新产业占新产业总数的70％左右,路...     

投影寻踪聚类在新疆地震预报中的应用

投影寻踪聚类(PPC)是投影寻踪和非分层聚类方法的综合,它同时尝试分类数据和寻找聚类结构的低维有代表性的特征。对于本项研究,Richard J．Bolton Richard J．B提出一个基于正交标准变量(考虑样本的大小)的投影寻踪指教和判断投影寻踪聚类的最优类别数的方法对新疆地区地震活动作聚类分析,模拟聚类结构。我出不同区域的有效的参量组合结构,判断后续聚类结构,对未来地震大小做出预测。通过对由不同的时间窗长和滑动步长的地震活动性自变量的PP聚类分析,发现短期预测效果不好,而时间窗长分别为12个月和18个月,相应的步长为6个月和12个月的PP聚类效果较好：柯坪地区、乌恰地区的投影寻踪聚类分析的内符检验对应率达60％以上。通过对比分析,认为取时间窗长为18个月的结果更好些。这与自变量的选取有关——地震活动性参量主要是反映中期震兆信息。     

滨海电厂周边海域潜在赤潮生物多样性特征

笔者于2015年7月(夏季)、11月(秋季)、2016年1月(冬季)和4月(春季)于湛江湾滨海电厂海域开展潜在赤潮生物生态调查,对该海域潜在赤潮生物的种类组成、优势种、丰度以及生物多样性的时空变化特征进行研究,文章分析了各季节的群落结构相似性及季节间的差异程度。调查海域共鉴定出潜在赤潮生物31属78种,其中硅藻门最多(60种),其次为甲藻门(16种),蓝藻门以及着色鞭毛藻门各1种。优势种组成具有明显的季节演替现象,其中冬季、夏季、秋季以硅藻门为主要优势种,而春季则以硅藻门-甲藻门为主要优势种。浮游植物丰度由大到小依次排序为夏季(47.69×104 cells/L)、秋季(10.87×104 cells/L)、冬季(9.07×104 cells/L)、春季(4.40×104 cells/L)。聚类分析结果显示,各季节的潜在赤潮生物群落结构相似程度较低,差异程度显著。Shannon多样性指数和均匀度指数季节变化明显,均为冬季最高值,夏季最低值,但季节间的差异不明显。SIMPER分析得出,各组组间差异性几乎均达90%以上,而各组组内相似程度由大到小依次为秋季组群、夏-2组群、冬季组群、春季组群、夏-1组群。     

全球-地方出口溢出效应对新企业进入出口市场的影响

出口增长是驱动中国经济发展的关键力量,新出口企业进入是出口增长的微观体现。新贸易理论认为集聚外部性带来的知识溢出是影响企业出口决策的关键因素。出口地、目的国维度的知识溢出均有利于企业获取必要的出口知识,降低进入出口市场的难度。演化经济地理理论强调认知邻近是出口溢出发挥作用的前提,出口地、目的国维度的出口经验、产品关联是出口溢出的主要内容。论文利用2002—2011年中国海关贸易数据库,分析出口地、目的国溢出对新企业进入出口市场的作用。结果发现：① 出口溢出可以显著提升新出口企业进入概率,私营企业更倾向于进入出口溢出更强的出口地、目的国市场;② 出口溢出对跟随型企业,特别是本土跟随型企业进入的促进作用更强,国有集体企业更强调整体出口经验溢出,私营企业更强调产品知识溢出;③ 出口地溢出有利于新出口企业拓展到新目的国,目的国溢出有利于新出口企业拓展到新产品。论文完善了出口企业空间动态研究,拓展了出口溢出对出口决策作用的空间维度,也有助于深化对中国贸易空间的理解。