, 曹有挥, 王佳韡Organization network of Chinese container transportation from the perspective of enterprises
YEShilin, CAOYouhui, WANGJiawei通讯作者:
收稿日期:2016-09-12
修回日期:2017-03-21
网络出版日期:2017-08-20
版权声明:2017《地理学报》编辑部本文是开放获取期刊文献，在以下情况下可以自由使用：学术研究、学术交流、科研教学等，但不允许用于商业目的.
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1 引言
20世纪50年代中期以后,集装箱运输从陆上推至海上,成为世界货运体系的一场重要技术革新,极大地提高了长距离货物运输的灵活性和安全性,使全球物流成本持续降低[1]。进入21世纪,伴随着全球生产网络和新国际劳动分工的深入发展,生产要素和商品在全球范围内广泛流动,推动了以集装箱运输为代表的现代物流的快速发展,使其成为资源要素全球配置的重要载体,对全球贸易、区域发展、货运空间组织等产生深远影响。以此为依托,集装箱运输组织网络受到了国内外****的持续关注,已成为交通地理学研究的重要课题。目前,国内外相关研究主要集中于以下几个方面：首先,****们对集装箱运输网络建设与优化展开了广泛探讨,力图实现集装箱运输资源的优化配置,提高集装箱运输系统运行效率,相关议题主要涉及多式联运系统协调、运输线路优化、内陆场站布局、优化模型构建等内容[2-3]。韩增林等[1]在分析世界集装箱运输发展与网络构成的基础上,基于GIS系统提出了中国集装箱港口、内陆中转站和主要运输通道的优化布局方案。Shintani等[4]认为集装箱航运网络设计应综合考虑船舶和集装箱部署,并将其作为一个双阶段问题,提出一种启发式遗传算法用以优化集装箱航运网络。其次,集装箱运输组织网络及其空间效应分析也是****们长期关注的焦点,侧重于组织网络发展机制、航线网络组织模式与等级结构、及其对港口体系演化的空间效应等方面[5-8]。Wilmsmeier等[9]提出集装箱航运网络格局是市场规模与市场覆盖率之间战略权衡的结果,受港口设施、腹地可达性、市场参与者策略和政府政策等多种因素的影响。Notteboom[10]指出航运公司转向采用轴辐系统组织全球集装箱运输,将改变全球枢纽港空间分布格局,促进东西向航线上新枢纽港的发展。值得一提的是,近年兴起的图论、复杂网络理论等分析方法为揭示集装箱运输网络拓扑结构特征提供了一种新的途径,被越来越多的****所接受和应用[11-12]。如Ducruet等[13]基于1996年和2006年全球集装箱船队航行路径及其挂靠港口数据,运用复杂网络理论探讨了全球集装箱航运网络结构与演化特征。再次,随着供应链管理理念发展和运输管制的放松,市场主体对集装箱运输的影响愈发突出,有关集装箱运输链上的企业行为研究不断增多,尤其关注航运企业、码头企业、物流企业等在港口供应链整合过程中的行为及其对集装箱运输组织的影响[14-16]。Cullinane等[17]****指出航运企业所实施的联盟、并购等横向整合战略及其对航线和挂靠港的决策将对全球集装箱运输网络、港口竞争力等产生深远影响。
综合来看,已有研究从不同视角和尺度揭示了集装箱运输网络特征,为本文的研究奠定了良好基础。但值得注意的是,虽然****们已注意到企业行为在集装箱运输组织网络发展与演化中的重要作用[14, 18-19],但更多的是关注海向集装箱航运组织,相关研究也多采用航运企业的集装箱班轮数据,使研究对象局限于港口城市,客观上忽视了非港口城市在集装箱运输组织网络中的重要作用。鉴于此,本文尝试以企业空间网络为切入点,借鉴世界城市网络研究方法和复杂网络理论,力求更加全面和客观地揭示中国集装箱运输组织网络的等级结构、空间格局、网络联系及复杂性特征,以期为中国集装箱运输组织网络布局与优化决策提供参考依据。
2 研究方法与数据来源
2.1 研究方法
2.1.1 网络联系测度方法 航运公司、货代、船代等物流企业是市场经济条件下集装箱货物全球跨区域流动的主要组织者。作为典型的多区位网络型组织,出于快速响应市场需求、提高空间网络服务效率、增强企业竞争力等考虑,物流企业大多倾向于在目标市场所能覆盖的城市设立不同等级的分支机构,负责承接和组织集装箱物流业务,形成遍布全国乃至全球众多大中小城市的企业空间网络[16]。同时,通过企业间紧密的垂直性和水平性功能联系将众多节点城市紧密联系在一起,共同推动物质、资本、信息、技术等要素的融合与快速流动,从而实现在区域、国家、全球不同空间尺度上集装箱流的组织与协调。因此,从微观企业视角出发,集装箱运输组织网络可理解为众多物流企业空间网络及其内部功能联系的集合。有关集装箱运输组织网络空间联系的量化,本文借鉴P.Taylor[20]等提出,并在城市联系网络研究中广泛应用的方法,将企业a在城市i的得分值定义为企业a布局于该城市的分支机构在其集装箱运输组织网络中的重要程度,并具体用via表示。则城市i和城市j间的组织联系度（rij）可以表示为：
式中：rij为城市i、j间的组织联系度;rija为以企业a表示的城市i、j间的基本组织联系量;m为企业总数,则每个城市最多有n-1个这样的联系。
基于此,得到城市i在集装箱运输组织网络中的组织联系强度（
组织联系强度是一个城市与网络中其他城市相互联系的总和,直观反映了该城市在整个网络中的对外联系状况。为更加综合的反映集装箱运输组织网络中各节点城市的组织枢纽功能,本文引入集装箱运输组织系数（COI）进行测度[5],计算公式为：
式中：COIi是指集装箱运输组织网络城市i的组织联系强度（Ri）与网络内所有城市组织联系强度平均值的比值。
2.1.2 网络复杂性测度方法 复杂网络（Complex Network）是以复杂系统的实体及实体间的相互作用或联系构建网络,并利用物理学方法分析网络结构及其动力学特征,为网络结构复杂性研究提供了新的途径,近年来被广泛应用于交通运输网络和城市经济网络研究,取得了丰富成果[21-22]。对于集装箱运输组织网络而言,最为重要也最为直接地反映网络结构复杂性特征的指标有度中心性、平均路径长度和聚类系数。本文将借助网络分析工具UCINET计算相关指标。
（1）度（Degree, D),用以测度网络中与城市i直接相连的其他城市的个数,反映该城市处于网络中心位置的程度。度值越大,城市中心性越高,拥有的网络资源也越多。
（2）平均路径长度（Average Path Length, L）,用以测度网络中任意两城市间最短路径边数（拓扑最短距离）的平均值,反映网络的整体性质。计算公式为：
式中：L是平均路径长度;n为节点数;dij为城市i和城市j间最短路径边数;L越小,说明网络的连通性越好,网络空间组织性能和效率越高。
（3）聚类系数（Clustering Coefficient, C）,用以测度网络的集团化程度,反映了网络中一个城市的邻接城市之间相互联系的紧密程度,是一种关于网络连接局部属性的指标。城市i的聚类系数
式中：Ci为城市i的聚类系数;Ei为城市i的邻接城市间实际存在的边数;ki为城市i的度数;显然Ci是一个介于0和1之间的数值,Ci的值越大,城市i的邻接城市间联系越紧密。
若对网络中所有城市的聚类系数取平均值,即为整体网络的聚类系数C,计算公式为：
式中：C为网络平均聚类系数;Ci为城市i的聚类系数;n为网络的城市总数;C值越大,表示整个网络的局部连接越明显。
2.2 数据来源
集装箱运输的组织与参与者主要包括航运企业、货代企业、船代企业、集装箱租赁公司、集装箱堆场和货运站等,基于企业运营特征和数据完整性考虑,本文选取集装箱运输主要组织者航运企业和货代物流企业作为分析样本。参照2015年全球集装箱班轮公司100强排名（前50名）（航运界网：http://www.ship.sh/news_detail.php?nid=17100。）和2015年度中国货代物流企业百强排名（中国国际货运代理协会：http://118.26.162.39:801/hdtz/hybtz/2016-07-01-2815.html。）,逐一对企业官网进行访问查询（数据收集时间为2016年6月）,结合全国企业信息查询平台（www.tianyancha.com）,将在中国大陆两个以上（含两个）城市设有分支机构的企业纳入研究名单中,进行机构分布数据采集。剔除信息不完整和未涉及集装箱业务的企业,最终获得33家航运企业和79家货代物流企业（本文将二者合称为物流企业）,共计112家物流企业在全国176个城市的分布数据,包括马士基航运、地中海航运、达飞轮船、长荣海运、赫伯罗特、中远集运等航运企业和中国外运长航集团、中国物资储运、敦豪全球货运、厦门象屿速传、锦程国际物流集团等货代物流企业。样本企业在全国集装箱运输市场具有较大规模和影响力,代表性强,数据可有效反映中国集装箱运输组织网络情况。企业数据具体说明为：① 采集的企业数据不包括香港、澳门和台湾;② 如物流企业在同一个城市拥有两个及以上分支机构,以高等级机构为准对城市进行赋值;③ 将外企在中国的最高统筹协调机构定义为在中国总部;④ 本文所指城市均为地级以上城市,县、市、区企业数据归并到地级市;⑤ 由于大型物流企业通常都开展综合物流服务,企业数据实际上涉及集装箱运输组织中航运、货代、船代、集装箱租赁等诸多方面情况。
然后,按照物流企业在各城市分支机构（总部、区域分公司、地方分公司和办事处）的等级规模分别赋值4、3、2、1和0分,如企业总部所在城市赋值为4分,未布局的城市则赋值为0分,以此类推。从而得到112家企业在全国176个城市分布的112×176初始矩阵,实现企业资料向矩阵数据转化。考虑到部分城市总得分较低,本研究选取总得分高于3的城市做进一步分析,共获得119个城市数据（图1）。
显示原图|下载原图ZIP|生成PPT图1中国集装箱运输组织网络节点城市分布
-->Fig. 1Distribution of node-cities in Chinese container transportation organization network
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3 中国集装箱运输组织网络分析
3.1 网络的等级结构特征
根据公式（1）~（3）,计算得出119个节点城市的集装箱运输组织系数（COI）,以此综合考察中国集装箱运输组织网络中各节点城市的组织枢纽功能。从计算结果可以直观的看出（图2）,各城市的组织系数差距较大,呈现出明显的位序—规模递减趋势,组织系数超过1的城市仅有39个,占总数的32.78%,数量较少。基于组织系数,采用层次聚类分析法（组间连接）可将各节点城市划分为全国性枢纽城市、区域性枢纽城市、次区域性枢纽城市和地方性枢纽城市四种类型（表1）。全国性枢纽城市仅有上海,其组织系数高达5.08,远高于网络中的其他城市,处于组织网络的核心地位,国际化程度较高,深刻影响甚至主导着全国集装箱运输组织网络的运行。这可能要归因于上海凭借其国际大都市和全国重要经济、金融、贸易和航运中心地位,以及全球吞吐量最大的上海港所形成的庞大集装箱运输市场,吸引了大量物流企业（特别是总部）集聚,成为众多物流企业空间网络的重要节点,进而使上海成为中国集装箱运输组织网络的组织核心。区域性枢纽城市包括天津（3.54）、青岛（3.45）和深圳（3.44）等8个城市,数量较少,主要承担各运营区或跨省级大区域的集装箱运输组织与协调职能,除北京外均为中国东部沿海重要枢纽港口城市。这些港口城市均为全球集装箱航运网络的主要挂靠港,是集装箱运输服务要素的天然聚集点,使其成为航运公司、货代等物流企业开展全球业务的理想区位。而北京作为中国政治、经济和文化中心,除了自身所拥有的广阔物流市场,还能够凭借“信息不对称”为企业提供大量政策信息与市场信息,对物流企业布局也具有极大的吸引力。次区域性枢纽城市包括南京（2.64）、武汉（2.54）和重庆（2.16）等24个城市,主要承担次区域或省内集装箱运输组织与协调职能,一般为省区级经济中心或重要交通枢纽。地方性枢纽城市包括石家庄（1.09）、济南（1.09）和南昌（1.03）等86个城市,物流企业分支机构布局数量和对外联系相对较少,集装箱运输组织与协调能力最弱,处于整个组织网络的底层与边缘,服务于地方集装箱运输市场。4种类型枢纽城市的数量比例为0.84∶6.72∶20.17∶72.27,且各类型的组织系数均值依次降低,即整体上呈现明显的金字塔型结构特征。Tab. 1
表1
表1中国集装箱运输组织网络等级体系
Tab. 1Hierarchy system of Chinese container transportation organization network
| 类型 | 城市 | 组织系数(COI) | 均值 | 数量(个) | 比重(%) |
|---|---|---|---|---|---|
| 全国性枢纽城市 | 上海 | 5.08 | 5.08 | 1 | 0.84 |
| 区域性枢纽城市 | 天津、青岛、深圳、北京、厦门、大连、广州、宁波 | 3.02~3.54 | 3.26 | 8 | 6.72 |
| 次区域性枢纽城市 | 南京、武汉、重庆、福州、苏州、杭州、成都、连云港、郑州、西安、中山、烟台、东莞、合肥、南通、汕头、佛山、沈阳、昆明、长沙、嘉兴、无锡、南宁、珠海 | 1.19~2.64 | 1.63 | 24 | 20.17 |
| 地方性枢纽城市 | 石家庄、济南、南昌、哈尔滨、常州、温州、江门、淄博、湛江、海口、营口、秦皇岛、济宁、临沂、泉州、丹东、潍坊、惠州、唐山、威海、芜湖、太原、扬州、日照、吉林、呼和浩特、锦州、金华、贵阳、九江、镇江、长春、襄樊、洛阳、东营、保定、乌鲁木齐、防城港、廊坊、宜昌、徐州、绍兴、泰州、沧州、肇庆、兰州、包头、湖州、钦州、漳州、西宁、北海、莆田、银川、菏泽、南阳、延边、株洲、盐城、台州、安庆、荆州、邢台、聊城、岳阳、龙岩、黄石、柳州、梧州、衡阳、绵阳、泰安、邯郸、衡水、三明、宿迁、淮安、潮州、滨州、遵义、呼伦贝尔、泸州、晋中、平顶山、自贡、盘锦 | 0.05~1.09 | 0.57 | 86 | 72.27 |
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显示原图|下载原图ZIP|生成PPT图2中国集装箱运输组织网络组织系数分布
-->Fig. 2Distribution of COI in Chinese container transportation organization network
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总体来看,众多物流企业市场组织行为及其空间集散过程的集合推动了中国集装箱运输组织网络中各节点城市集装箱运输组织能力的差异化发展,并已形成较为明晰的规模等级结构。处于等级体系上层的少数枢纽城市集聚了大量企业分支机构,承担着全国主要的集装箱运输组织与协调职能,并具有影响和控制整个组织网络运行的能力。此外,虽然港口城市在高等级枢纽城市中占据较大比重,但随着等级降低,非港口城市（如北京、昆明、郑州等）所占比重表现出不断增长趋势。这也在一定程度上验证了非港口城市在中国集装箱运输组织网络中的重要地位与作用,是组织网络的不可或缺的组成部分。
3.2 网络组织能力的空间分异特征
在前文基础上,利用ArcGIS中的核密度估计方法验证中国集装箱运输组织网络的空间分异特征（图3）。中国集装箱运输组织能力空间分布非均衡性突出,区位倾向性特征明显,高密度区和较高密度区主要集中于东部沿海地区,而中西部地区除小面积较高密度区和中等密度区外皆为大面积低密度区,整体呈现出明显的东西地带性差异及向环渤海、长三角、东南沿海和珠三角地区集聚分布的特征。具体来看,围绕全国性枢纽城市和区域性枢纽城市,在区域层面上形成了6个连片的集装箱运输组织系数高值核心区：① 辽东半岛核心区：以大连为组织核心,包括沈阳、锦州和营口等城市组成;② 京津冀核心区：以天津和北京为组织核心,包括石家庄、秦皇岛和唐山等城市组成;③ 山东半岛核心区：以青岛为组织核心,包括连云港、烟台和潍坊等城市组成;④ 长三角核心区：以上海为组织核心,宁波为副核心,包括南京、苏州和杭州等城市组成,枢纽城市集聚程度最高,覆盖范围也最广;⑤ 东南沿海核心区：以厦门为组织核心,包括福州、泉州和漳州等城市组成;⑥ 珠三角核心区：以深圳和广州为组织核心,包括中山、东莞和汕头等城市组成。与此同时,围绕武汉、重庆、成都、郑州、西安、昆明、长沙和南宁次区域性枢纽城市,在中国中西部地区集聚形成7个相互“孤立”且覆盖范围不一的集聚区（重庆和成都联系紧密,共同构成一个集聚区）。虽然集聚区在集装箱运输组织能力方面远弱于核心区,但对促进广大中西部地区的集装箱运输和区域经济发展具有重要的辐射带动作用。
显示原图|下载原图ZIP|生成PPT图3中国集装箱运输组织能力空间分异
-->Fig. 3Spatial differentiation of the organizational ability of container transportation in China
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由此可见,中国集装箱运输组织能力空间分异特征同全国区域经济发展格局和综合交通网络布局表现出较高的空间耦合性。改革开放以来中国外向型经济实现快速发展,东部沿海地区（尤其是环渤海、长三角和珠三角地区）和长江沿岸地区作为中国对外贸易的主要发生地,进出口货物贸易繁荣,逐步发展成为全球最重要的集装箱货源地和目的地,集装箱运输市场广阔,吸引大量物流企业在此布局,促进了沿海沿江集装箱运输组织网络的发育。同时,由于物流企业对大型交通设施和交通区位强烈的依附性[23],使重大交通干线节点城市和多式联运枢纽城市成为物流企业集聚的重要区位,特别是作为海陆多种运输方式交汇地的沿海沿江港口城市,正发展成为集装卸、运输、仓储、包装、加工、信息处理等多种物流功能为一体的综合物流中心和物流产业集群发展的重要载体,吸引众多航运公司、货代等企业集聚,从而影响全国集装箱运输组织能力的空间分异。
3.3 网络联系的空间结构特征
为进一步揭示中国集装箱运输组织网络联系的空间结构特征,按网络中各节点城市间的组织联系度从高到低排序,分别提取前0.1%、0.1%~0.5%、0.5%~2.5%和2.5%~10%4种网络联系城市对,从而简化密集的联系网络以便于分析。然后,借助ArcGIS软件分别绘制成图（图4）。
显示原图|下载原图ZIP|生成PPT图4中国集装箱运输组织网络空间联系结构(前10%)
-->Fig. 4Linkages of Chinese container transportation organization network (Top 10%)
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图4中,前0.1%联系网络共有7组城市对（图4a）,组织联系度处于360~486之间,涉及上海、天津、青岛和深圳等8个城市,均为网络中的全国性枢纽城市和区域性枢纽城市。网络联系主要发生在上海—天津（486）、上海—青岛（458）、上海-深圳（457）等城市间,表现出明显的以上海为空间联系指向核心的特征。前0.1%~0.5%联系网络共有27组城市对（图4b）,组织联系度处于213~350之间,在已有节点城市的基础上加入了大连、南京、武汉和重庆,使城市数量增加到12个。联系网络除分别增加了南京、武汉、重庆3个次区域性枢纽城市同上海间的联系外,其余均为包括新增加的大连在内的全国性枢纽城市和区域性枢纽城市间相互联系的进一步加密,特别是宁波、广州和深圳等对外联系数量增加明显。前0.5%~2.5%联系网络共有135组城市对（图4c）,组织联系度处于79~210之间,城市对主要包括上海—苏州（210）、上海—福州（204）、重庆—天津（161）、福州—深圳（159）等,在原有网络基础上进一步接入了成都、福州、杭州、连云港、苏州和中山等次区域性枢纽城市。同前两类联系网络相比,前0.5%~2.5%联系网络主要是次区域性枢纽城市同全国性枢纽城市和区域性枢纽城市之间联系的建立,具有强烈的东部沿海地区空间指向性,网络联系向沿海6大核心区集聚的趋势开始显现。前2.5%~10%联系网络共有506组城市对（图4d）,涉及全国性、区域性、次区域性和地方性枢纽城市四类共69个城市,组织联系度处于30~78之间,整体联系度水平相对较低。这部分网络联系空间分布情况表现出与前0.5%~2.5%联系网络相类似特征,在继续加密东部节点城市间联系网络的基础上,覆盖范围进一步向中西部地区地方性枢纽城市（如南宁、乌鲁木齐、哈尔滨等城市）拓展,使网络联系空间结构更加复杂和稠密。
综合来看,上海、天津、青岛、深圳等全国性枢纽城市和区域性枢纽城市间拥有相对较高的组织联系度,彼此联系十分紧密,构成了中国集装箱运输组织网络联系的核心与基本框架。而数量众多的次区域性枢纽城市和地方性枢纽城市则倾向于通过与高等级枢纽城市建立联系,进而融入全国集装箱运输组织网络,但其组织联系度要明显弱于高等级枢纽城市之间的组织联系度。同时,由于具有强烈的空间指向性,网络联系更容易建立在东部沿海城市之间,中西部地区城市间联系较弱且在联系网络中所占比重相对较低,从而形成中国集装箱运输组织网络联系东部地区稠密、中西部地区相对稀疏的基本空间格局。
3.4 网络结构的复杂性特征
利用UCINET软件分别测算网络的度中心性、平均路径长度和聚类系数,以便更为直观地揭示中国集装箱运输组织网络的空间联系特征、网络发育程度及其服务水平。从度中心性计算结果可以发现,中国集装箱运输组织网络节点城市的度值普遍较高,整体网络平均度值达113.41,即每个城市平均与其他113个城市有直接联系。其中,有27个城市的度值达118,占城市总数的22.69%。说明组织网络节点城市间连接紧密,对外直接联系便捷,对邻近城市的依赖性较低。从网络连通性来看,平均路径长度达1.04,即组织网络中任意城市对之间最少通过1.04条边就可以建立组织联系,略高于同等规模的随机网络最短路径理论值（LER ∝lnN/ln<k > ≈ 1.01）,其中有96%的城市之间存在直接联系。可见中国集装箱运输组织网络节点城市间具有相对较高的连通性和空间组织效率,信息传递十分便捷。从网络的集团化程度考察,组织网络的聚类系数达0.98,略高于随机网络聚类系数理论值（CER = k/n ≈ 0.95）,表现出较强的集聚性,反映出中国集装箱运输组织网络节点城市之间形成紧密组织联系的可能性较大。在此基础上,基于节点城市的组织系数、度和聚类系数3个指标数据,分析网络结构复杂性特征与节点城市集装箱运输组织枢纽功能的内部关联性。相关性分析结果显示,节点城市的组织系数与度值呈显著正相关,相关系数为0.343（显著性水平达0.01）,即度值越高的城市,其组织系数也越高。随着对外直接联系数量的增加,节点城市越发靠近网络的中心位置,其所能掌握的物流资源、信息和在网络中的话语权不断增加,对集装箱运输的组织和协调能力得到持续增强。同时,节点城市的组织系数与聚类系数的相关系数为-0.676（显著性水平达0.01）,呈显著负相关。这主要是因为一般来说聚类系数低的城市对外开放程度较高,对外直接联系的城市数目普遍较多[24],所集聚的企业分支机构数量和等级规模也优于聚类系数较高的城市,使其在集装箱运输网络中拥有相对较大的组织能力,即更高的组织系数。可见,集装箱运输组织网络拓扑结构特征对网络节点城市的组织能力具有重要影响。
4 结论与讨论
4.1 结论
本文尝试利用企业空间网络数据刻画中国集装箱运输组织网络拓扑结构,使网络不仅仅局限于班轮航线所联系的港口城市,而是覆盖到经济中心、政治中心、交通枢纽等多种具备集装箱运输组织与协调功能的城市,为了解市场经济条件下中国集装箱流空间组织特征提供了有益信息。主要研究结论为：① 中国集装箱运输组织网络中各节点城市的集装箱运输组织能力存在显著差异,基于组织系数可将节点城市划分为全国性枢纽城市、区域性枢纽城市、次区域性枢纽城市和地方性枢纽城市四种类型,总体上呈现出明显的金字塔型等级结构特征,等级越高,节点城市数量越少。② 以节点城市为空间载体的中国集装箱运输组织能力在空间分布上表现出十分显著的非均衡性特征,具有明显的东西地带性差异及向环渤海、长三角、东南沿海和珠三角地区集聚的特点,大体形成由东部沿海6个核心区和中西部7个集聚区所构成的“6+7”空间分布格局,这可能与全国区域经济发展格局和综合交通网络布局以及集装箱运输业自身特点等具有密切关系。③ 中国集装箱运输组织网络中的全国性枢纽城市和区域性枢纽城市间具有紧密而广泛的网络联系,成为众多节点城市空间联系指向的核心。同时,东部地区网络联系密度要显著高于中西部地区,联系网络整体呈现从东部沿海向中西部地区、从全国性枢纽城市向地方性枢纽城市逐渐拓展的趋势。④ 基于企业功能联系的中国集装箱运输组织网络中的节点城市间联系紧密,集聚性特征明显,网络结构具有相对较高的连通性和空间组织效率,网络结构复杂性特征与节点城市集装箱运输组织协调能力具有显著相关性。4.2 讨论
综合来看,集装箱运输组织网络是区域经济发展格局与众多物流企业市场组织行为长期耦合作用的结果,节点城市在网络中的地位与对外连通性不仅与自身发展条件密切相关,众多物流企业空间网络设置所引起的城市间分支机构等级与集聚数量差异更是塑造节点城市集装箱运输组织能力和集装箱运输运输组织网络结构特征的关键力量。因此,物流企业空间网络布局与选址为优化中国集装箱运输组织网络结构、扩大覆盖范围和提高节点城市集装箱运输组织能力提供了一条重要途径。整体而言,不仅要进一步加强节点城市交通基础设施、物流园区、集装箱物流中心等硬件设施的规划与建设,增强基础设施支撑保障能力,还应在财政、金融、税收和土地供应等方面制定相应的优惠扶持政策,营造良好的市场环境,从而有效促进物流企业集聚与发展。就不同区域而言,要积极引导和鼓励大型物流企业（特别是骨干物流企业）向组织网络相对稀疏的中西部地区布局,提高网络覆盖范围和密度;而东部沿海沿江港口城市要特别重视对大型航运公司的吸引,以提高港口城市对外连通性和在全球航运网络中的枢纽地位。须注意的是,拓扑网络并非真实网络的简单投影,两者仍存在一定差距[22]。本文基于112家航运企业和货代物流企业的数据也难以完全反映中国集装箱运输组织网络的全貌,且对样本城市的筛选也可能影响网络复杂性特征的精确性。今后将进一步补充企业数据,从组织网络形成与演化机制、枢纽城市竞合关系、城市内部企业组织网络特征等方面对中国集装箱运输组织网络进行更加深入的研究。
The authors have declared that no competing interests exist.
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
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| [2] | This study focuses on one of the intermodal operational issues: how to select best routes for shipments through the international intermodal network. International intermodal routing is complicated by three important characteristics: (1) multiple objectives; (2) scheduled transportation modes and demanded delivery times; and (3) transportation economies of scale. In this paper, the international intermodal routing problem is formulated as a multiobjective multimodal multicommodity flow problem (MMMFP) with time windows and concave costs. The objectives of this paper are to develop a mathematical model encompassing all three essential characteristics, and to propose an algorithm that can effectively provide answers to the model. The problem is NP-hard. It follows that the proposed algorithm is a heuristic. Based on relaxation and decomposition techniques, the original problem is broken into a set of smaller and easier subproblems. The case studies show that it is important to incorporate the three characteristics into the international intermodal routing problem, and our proposed algorithm can effectively and efficiently solve the MMMFP with time windows and concave costs. |
| [3] | A key issue affecting the viability and efficacy of intermodal transportation via truck and rail is the operational selection of intermodal ramps. In this paper, two alternatives for ramp selection are examined. Both methods seek to reduce total empty and circuitous miles incurred during intermodal drayage movements. The sensitivity to the ramp group configuration and to freight compatibility is tested to determine the robustness of the findings. The analysis is industrially motivated, using data supplied by J.B. Hunt Transport, Inc. The primary contribution of the paper is in quantifying the performance of the ramp selection methods in various operational settings. |
| [4] | This paper addresses the design of container liner shipping service networks by explicitly taking into account empty container repositioning. Two key and interrelated issues, those of deploying ships and containers are usually treated separately by most existing studies on shipping network design. In this paper, both issues are considered simultaneously. The problem is formulated as a two-stage problem. A genetic algorithm-based heuristic is developed for the problem. Through a number of numerical experiments that were conducted it was shown that the problem with the consideration of empty container repositioning provides a more insightful solution than the one without. |
| [5] | . |
| [6] | This paper applies a specific research methodology designed to evaluate and compare competing seaport locations within a given region as the optimal site for international container transhipment activity. The main focus is on container transhipment hub locations in northern Europe. Transhipment is the fastest growing segment of the containerport market, resulting in significant scope to develop new transhipment terminal capacity to cater for future expected traffic flows. Transport distances and associated shipping costs are calculated for existing hub locations and these are then compared with a new proposed transhipment location in the region, in this instance the vast natural deep-water harbour at Scapa Flow in the Orkney Islands. Findings from the research demonstrate that current container hub ports are not necessarily optimal (for serving transhipment markets), and that alternative port sites such as Scapa Flow could provide a superior and more competitive location from which to support the fast expanding transhipment markets of northern Europe. |
| [7] | The study of ports in supply chain systems is an emerging area of importance which has drawn more attention from researchers in recent years. This paper presents a new perspective in this research area by examining the calling patterns of container shipping services in order to understand the dynamics of port connectivity and inter-port relationships in the supply chains. Empirical evidence is drawn from four major ports in East Asia, namely Shanghai, Busan, Kaohsiung and Ningbo. The study identifies the shipping capacity, trade routes and geographical regions connected to the ports, shipping lines involved, and the extensity and intensity of inter-port relationships among the four container ports from liner shipping network鈥檚 perspective. The findings show that most of the shipping capacity employed on the major east鈥搘est trade routes became non-exclusive and involved calls at two or more of the four ports. Port planners, terminal operators and carriers could capitalise on opportunities through exploitation of complementary relationships that exist among the selected ports, such as offering a package for shipping lines to call at a portfolio of terminals owned by the same terminal operator. Policy and research implications as well as recommendations are discussed for various stakeholders concerned with port planning and regional development. |
| [8] | |
| [9] | The worldwide network of container transport services is becoming increasingly diffuse. The different strategies of shipping lines, the balance of power between shipping lines and shippers and constra |
| [10] | |
| [11] | The reaction to the financial and economic crisis has shown a new redesign of scenarios taking into account the changes made by maritime companies choosing different ports. In this research, containerized traffic evolution in 2008 and 2010 is described, both in big ports and geographic regions as from the emergent port activity areas. Database used is a sample of the world containership fleet movements that have called in some Chinese port in the years analysed. Calculus methodologies based on Graph Theory are applied to this set of data, able to give information about the global and local importance of a port given. Containerized goods transportation network have been contracted between 2008 and 2010 respect the port throughput, but there鈥檚 no contraction in the distribution capacity of the main hub ports, which seem to have adopted commercial diversification strategies and foreland expansion. On the other hand, port emergent regions placed in the entrance and exit of Panama Canal will have important business opportunities. |
| [12] | 自1997年以来,两岸集装箱港口体系在"间接通航"、"试点直航"以及"全面直航"特殊政策的影响下,先后经历了直航萌芽期、直航发展期及直航成熟期三个阶段。以国家交通部发布的台湾海峡两岸集装箱海上运输航线为主干数据,基于复杂网络的分析视角,利用网络分析软件GEPHI和GIS技术,对直航背景下海峡两岸集装箱港口体系空间联系格局、中心性空间分异和区域集散效应的演化特征进行定量测度,并进一步探究两岸集装箱港口体系空间结构演化的动力机制。结果表明:1两岸集装箱港口体系空间结构总体呈现"特定转运港集中—枢纽港集中—区域网络化发展"的三阶段演变过程,主要表现为航线联系范围的扩大和干线权重的减弱,中心性功能在枢纽港弱化、在次级港口增强,以及新兴小型港口呈现"小世界"区域集聚的现象,体现了重要的复杂网络特性。2两岸直航前,港口区域集聚性主要分布于珠三角及环渤海地区,两岸直航后,区域集聚现象主要分布于珠三角地区与海峡西岸经济区。3两岸航运网络的空间演化机制受制度、市场及技术三方面因素共同驱动,特殊的通航政策是港口体系形成、演化的重要社会制度环境,两岸经贸联系和ECFA的全面推进在很大程度上重塑了中国沿海四大经济区主要港口与台湾港口间的航运联系,而基于技术革新的港口竞争机制影响了两岸航运企业的航线配置。 . 自1997年以来,两岸集装箱港口体系在"间接通航"、"试点直航"以及"全面直航"特殊政策的影响下,先后经历了直航萌芽期、直航发展期及直航成熟期三个阶段。以国家交通部发布的台湾海峡两岸集装箱海上运输航线为主干数据,基于复杂网络的分析视角,利用网络分析软件GEPHI和GIS技术,对直航背景下海峡两岸集装箱港口体系空间联系格局、中心性空间分异和区域集散效应的演化特征进行定量测度,并进一步探究两岸集装箱港口体系空间结构演化的动力机制。结果表明:1两岸集装箱港口体系空间结构总体呈现"特定转运港集中—枢纽港集中—区域网络化发展"的三阶段演变过程,主要表现为航线联系范围的扩大和干线权重的减弱,中心性功能在枢纽港弱化、在次级港口增强,以及新兴小型港口呈现"小世界"区域集聚的现象,体现了重要的复杂网络特性。2两岸直航前,港口区域集聚性主要分布于珠三角及环渤海地区,两岸直航后,区域集聚现象主要分布于珠三角地区与海峡西岸经济区。3两岸航运网络的空间演化机制受制度、市场及技术三方面因素共同驱动,特殊的通航政策是港口体系形成、演化的重要社会制度环境,两岸经贸联系和ECFA的全面推进在很大程度上重塑了中国沿海四大经济区主要港口与台湾港口间的航运联系,而基于技术革新的港口竞争机制影响了两岸航运企业的航线配置。 |
| [13] | Port and maritime studies dealing with containerization have observed traffic concentration and dispersion throughout the world. Globalization, intermodal transportation, and technological revolutions in the shipping industry have resulted in both network extension and rationalization. However, lack of precise data on inter-port relations prevent the application of wider network theories to global maritime container networks, which are often examined through case studies of specific firms or regions. In this article, we present an analysis of the global liner shipping network in 1996 and 2006, a period of rapid change in port hierarchies and liner service configurations. While we refer to literature on port system development, shipping networks, and port selection, the article is one of the only analyses of the properties of the global container shipping network. We analyse the relative position of ports in the global network through indicators of centrality. The results reveal a certain level of robustness in the global shipping network. While transhipment hub flows and gateway flows might slightly shift among nodes in the network, the network properties remain rather stable in terms of the main nodes polarizing the network and the overall structure of the system. In addition, mapping the changing centrality of ports confirms the impacts of global trade and logistics shifts on the port hierarchy and indicates that changes are predominantly geographic. |
| [14] | The basin of the Mediterranean Sea has become an important focus of container traffic. Two functions are represented by this activity: one, the transhipment of containers involved in global networks; and, second, the intra-regional distribution of containers. This trade is revitalising port activity in many parts of the basin. Most striking has been the emergence of new hub ports, many of which now eclipse old-established port cities. The revitalisation offers prospects for a third function: the possibility of becoming the southern gateway of Europe. This paper examines the patterns, problems and prospects of the ‘new’ Mediterranean in the era of containerisation. |
| [15] | As the entrep么t to the Chinese mainland, the economy of Hong Kong has enjoyed a high growth rate of economic development. When Hong Kong developed its container ports in order to accommodate the regional economic boom, its counterparts in China were left far behind; there was no serious port competition from China. However, as China develops its economy, the port of Hong Kong faces real challenges from Chinese ports, particularly from southern ones. Interestingly, the handover of its sovereignty to China in 1997 caused an issue of competition and co-operation between these ports. This paper aims to examine the possible competition and co-operation of the adjacent container ports in Hong Kong and South China from a strategic perspective. |
| [16] | 物流企业是承担物流活动的专业化组织，是具有空间网络的企业形式。基于相关研究的评述，分析了物流企业网络的基础理论，重点解析其空间体系、职能联系与运营机制。通过研究，认为物流企业由企业属性要素和物流属性要素组成，其共同作用形成企业部门的职能分化和区位分离，由此形成物流企业网络，包括企业组分网络和物流运营网络。物流企业在城市和区域尺度构筑企业组分网络，城市网络包括总公司、配送中心和营业点，总公司布局于市中心区，配送中心倾向于近郊区，营业点集中在物流密集区；区域网络包括总部、区域分公司、地方分公司、办事处和受理点，总部布局于国内大城市，区域分公司倾向于各区政治经济中心，地方分公司集中在省会、经济中心和交通枢纽，办事处与受理点在企业网络外部或内部空白处布局。物流运营网络由运输专线、配送体系和物流网络组成，运输专线形成支线和干线两类，是物流运营的基本途径；配送体系形成区域、城市区域和城市三层，是物流企业提升竞争力的保障：运输专线和配送体系的交错、融合和优化，最终形成轴辐物流网络。 . 物流企业是承担物流活动的专业化组织，是具有空间网络的企业形式。基于相关研究的评述，分析了物流企业网络的基础理论，重点解析其空间体系、职能联系与运营机制。通过研究，认为物流企业由企业属性要素和物流属性要素组成，其共同作用形成企业部门的职能分化和区位分离，由此形成物流企业网络，包括企业组分网络和物流运营网络。物流企业在城市和区域尺度构筑企业组分网络，城市网络包括总公司、配送中心和营业点，总公司布局于市中心区，配送中心倾向于近郊区，营业点集中在物流密集区；区域网络包括总部、区域分公司、地方分公司、办事处和受理点，总部布局于国内大城市，区域分公司倾向于各区政治经济中心，地方分公司集中在省会、经济中心和交通枢纽，办事处与受理点在企业网络外部或内部空白处布局。物流运营网络由运输专线、配送体系和物流网络组成，运输专线形成支线和干线两类，是物流运营的基本途径；配送体系形成区域、城市区域和城市三层，是物流企业提升竞争力的保障：运输专线和配送体系的交错、融合和优化，最终形成轴辐物流网络。 |
| [17] | In recent years, China's container ports have experienced a significant expansion in throughput and capacity. This paper provides a review of the sector and analyses the recent development of container ports and terminals within Mainland China. It then focuses in more depth on the competition between the ports of Shenzhen and Hong Kong. In particular, the port of Shenzhen is analysed in the context of Robinson's criteria for hub port development to try to discern whether it will become the dominant regional hub. The discussion concludes that despite Shenzhen's current competitive advantages, Hong Kong will, in all probability, retain its dominant role. |
| [18] | This paper brings forward the concept of change and its impact on the geography of maritime transportation. Maritime systems are investigated from perspectives of constant contradiction between transport supply and demand, containerization and its spatial diffusion, and the adaptation capacity of transport networks in response to changes. Central to these perspectives are cycles which provide a conceptual background for the analysis of the world economy and of the role of transportation. |
| [19] | This paper describes the development of containerisation in one of the most important theatres of maritime trade, the North Atlantic. As the original hearth of containerisation, it has been an area of experimentation and evolution for a technology that has burst around the world. Although over the last decade the Atlantic has been superceded by the Pacific Ocean as the major market focus for containers, it still is an important market arena. The emergence of global shipping networks is tending to favour the Atlantic once again. The paper provides an analysis of these recent developments. |
| [20] | Abstract World cities are generally deemed to form an urban system or city network but these are never explicitly specified in the literature. In this paper the world city network is identified as an unusual form of network with three levels of structure: cities as the nodes, the world economy as the supranodal network level, and advanced producer service firms forming a critical subnodal level. The latter create an interlocking network through their global location strategies for placing offices. Hence, it is the advanced producer service firms operating through cities who are the prime actors in world city network formation. This process is formally specified in terms of four intercity relational matrices鈥攅lemental, proportional, distance, and asymmetric. Through this specification it becomes possible to apply standard techniques of network analysis to world cities for the first time. In a short conclusion the relevance of this world city network specification for both theory and policy-practice is briefly discussed. |
| [21] | |
| [22] | <p>通过分析复杂网络理论在航空、轨道交通(地铁和铁路)、城市交通(公交和道路)等中的应用，指出系统复 杂性是交通运输网络复杂性的根源，以及复杂网络分析方法中忽视地理空间性所引起的问题，即一般性地认为交 通运输网络为小世界网络或无标度网络。目前基于统计物理学的交通运输网络的复杂性研究多为拓扑化的理论分 析或数据建模，与实际网络结构特征及动力学机理仍存在较大差距。研究进一步指出，交通运输网络由需求网络、 组织网络、径路网络和设施网络四种网络结构组成，是一类具有“开放性”复杂系统的网络化复合结构。交通运输作 为一门实践应用性较强的学科，应围绕“理论→模型与方法→实践”模式前向性循环推进。综合分析复杂网络的理 论与实践情况，提出未来交通运输网络的复杂性研究的主要内容：①对交通运输系统的网络结构复杂性的基础认 识；②以地理空间特性为基础的网络复杂性分析；③基于组织与效率的网络结构复杂性分析及应用；④相互作用产 生的各种流与网络结构的互动关系；⑤网络局域结构特征及对广域结构的影响；⑥系统开放性对网络演化的影响。</p> . <p>通过分析复杂网络理论在航空、轨道交通(地铁和铁路)、城市交通(公交和道路)等中的应用，指出系统复 杂性是交通运输网络复杂性的根源，以及复杂网络分析方法中忽视地理空间性所引起的问题，即一般性地认为交 通运输网络为小世界网络或无标度网络。目前基于统计物理学的交通运输网络的复杂性研究多为拓扑化的理论分 析或数据建模，与实际网络结构特征及动力学机理仍存在较大差距。研究进一步指出，交通运输网络由需求网络、 组织网络、径路网络和设施网络四种网络结构组成，是一类具有“开放性”复杂系统的网络化复合结构。交通运输作 为一门实践应用性较强的学科，应围绕“理论→模型与方法→实践”模式前向性循环推进。综合分析复杂网络的理 论与实践情况，提出未来交通运输网络的复杂性研究的主要内容：①对交通运输系统的网络结构复杂性的基础认 识；②以地理空间特性为基础的网络复杂性分析；③基于组织与效率的网络结构复杂性分析及应用；④相互作用产 生的各种流与网络结构的互动关系；⑤网络局域结构特征及对广域结构的影响；⑥系统开放性对网络演化的影响。</p> |
| [23] | Logistics company is an economic entity to specialize in organization and operation of logistics activities and has a strategic significance in supporting various economic activities of circulation field and effective operation of the whole social-economic system, even impacting the reorganization of regional spatial structures. However, review articles in the literature show that for a long time most scholars only pay attention to the distribution features or spatial modes of logistics companies at the city scale and organization mode of logistics operational network at the regional or national scale, due to the limit of data collection and methodology, but the distribution patterns of logistics companies and the dynamic mechanisms at the national scale are seldom investigated. Particularly, the number of logistics companies has been increasing explosively since the end of 1990s in Mainland China. For this purpose, in this paper, we choose 1855 A-level logistics companies, rated by the government authority by various criterions over the past seven years, as the study samples, from the spatial scales of region, province and city, to describe and analyze the spatial features of the logistics companies in China, including the overall pattern, spatial centralization, coverage and spatial differentiation. And we explore the dynamic mechanisms of spatial disparities of logistics companies' distribution from the multi aspects. The results show that there are obvious spatial distribution disparities among the logistics companies in China. The coastal region has more logistics companies than inland region and their numbers show a "2:1" ratio. Interestingly, the eastern region also has obvious larger number than central and western regions, with "4:2:1" ratios. Generally, the southern provinces have more logistics companies, and the northern, northeastern, northwestern and southwestern provinces have fewer. Furthermore, the southeast coastal provinces especially Jiangsu and Zhejiang have the most companies. The spatial disparity of logistics companies' distribution among the cities seems to be more significant, showing clear separation of aggregation regions and sparse regions. The logistics companies not only are concentrated in the provincial capitals and economic centers, but also cover a large number of prefectural-level cities, even extending into many counties. More interestingly, South Jiangsu, Shanghai, South Anhui and Zhejiang have a large number of logistics companies and large coverage of various cities. But in each province, logistics companies are mainly located at the capital city and important economic centers and port cities. Logically, this spatial pattern is determined by the various factors combined. The results also show that the economic scale and industrial structure (among eastern, central and western regions, or between northern and southern regions), opening up and international trade, location and transport condition become the important factors to influence the spatial differentiation of logistics companies' distribution. It`s noteworthy that the development of a large number of local and specialized industrial clusters and private economies promotes the emergence and centralized distribution of logistics companies in Zhejiang and Jiangsu. More strikingly, the logistics planning and support policies made and provided by local governments also profoundly influence the development and flourish of logistics market and companies, especially in the coastal region and large cities of central and western regions. Theoretically, this distribution disparity among logistics companies generates different supporting capabilities for each region to operate the socio-economic system effectively. This research can provide a guidance to optimize the distribution of logistics companies and organize the logistics activities. . Logistics company is an economic entity to specialize in organization and operation of logistics activities and has a strategic significance in supporting various economic activities of circulation field and effective operation of the whole social-economic system, even impacting the reorganization of regional spatial structures. However, review articles in the literature show that for a long time most scholars only pay attention to the distribution features or spatial modes of logistics companies at the city scale and organization mode of logistics operational network at the regional or national scale, due to the limit of data collection and methodology, but the distribution patterns of logistics companies and the dynamic mechanisms at the national scale are seldom investigated. Particularly, the number of logistics companies has been increasing explosively since the end of 1990s in Mainland China. For this purpose, in this paper, we choose 1855 A-level logistics companies, rated by the government authority by various criterions over the past seven years, as the study samples, from the spatial scales of region, province and city, to describe and analyze the spatial features of the logistics companies in China, including the overall pattern, spatial centralization, coverage and spatial differentiation. And we explore the dynamic mechanisms of spatial disparities of logistics companies' distribution from the multi aspects. The results show that there are obvious spatial distribution disparities among the logistics companies in China. The coastal region has more logistics companies than inland region and their numbers show a "2:1" ratio. Interestingly, the eastern region also has obvious larger number than central and western regions, with "4:2:1" ratios. Generally, the southern provinces have more logistics companies, and the northern, northeastern, northwestern and southwestern provinces have fewer. Furthermore, the southeast coastal provinces especially Jiangsu and Zhejiang have the most companies. The spatial disparity of logistics companies' distribution among the cities seems to be more significant, showing clear separation of aggregation regions and sparse regions. The logistics companies not only are concentrated in the provincial capitals and economic centers, but also cover a large number of prefectural-level cities, even extending into many counties. More interestingly, South Jiangsu, Shanghai, South Anhui and Zhejiang have a large number of logistics companies and large coverage of various cities. But in each province, logistics companies are mainly located at the capital city and important economic centers and port cities. Logically, this spatial pattern is determined by the various factors combined. The results also show that the economic scale and industrial structure (among eastern, central and western regions, or between northern and southern regions), opening up and international trade, location and transport condition become the important factors to influence the spatial differentiation of logistics companies' distribution. It`s noteworthy that the development of a large number of local and specialized industrial clusters and private economies promotes the emergence and centralized distribution of logistics companies in Zhejiang and Jiangsu. More strikingly, the logistics planning and support policies made and provided by local governments also profoundly influence the development and flourish of logistics market and companies, especially in the coastal region and large cities of central and western regions. Theoretically, this distribution disparity among logistics companies generates different supporting capabilities for each region to operate the socio-economic system effectively. This research can provide a guidance to optimize the distribution of logistics companies and organize the logistics activities. |
| [24] | 航空运输是现代交通运输的重要组成部分,以机场和航线构建的网络是其提供运输服务的空间载体.基于复杂网络理论,借助度分布、平均路径长度、簇系数、度度相关性、簇度相关性等指标对以城市为节点的中国航空网络空间结构进行分析,发现其度累计概率分布表现为具有置信度较高的指数分布,且具有较小的平均路径长度(2.23)和较大的簇系数(0.69),整体结构呈现"小世界网络"的特点.由于中国航空网络规模较小,且新建机场倾向于直接与最高级枢纽机场建立航线联系,不利于区域枢纽机场的形成.因而除顶层结构(北京-上海-广州)外,中国航空网络的其它层级结构并不十分明显.从节点的度、簇系数、可达性等指标及其相关性分析,中国航空网络空间结构特征差异明显,表现出较强的集聚性,且可达性与城市体系上层结构在空间分布上较为吻合.随着中国航空运输需求的快速增加,未来航空网络在市场经济的推动下,将进一步表现出向具有"无标度"特征的"小世界网络"演变的趋势,航空网络的空间结构将日趋复杂化. . 航空运输是现代交通运输的重要组成部分,以机场和航线构建的网络是其提供运输服务的空间载体.基于复杂网络理论,借助度分布、平均路径长度、簇系数、度度相关性、簇度相关性等指标对以城市为节点的中国航空网络空间结构进行分析,发现其度累计概率分布表现为具有置信度较高的指数分布,且具有较小的平均路径长度(2.23)和较大的簇系数(0.69),整体结构呈现"小世界网络"的特点.由于中国航空网络规模较小,且新建机场倾向于直接与最高级枢纽机场建立航线联系,不利于区域枢纽机场的形成.因而除顶层结构(北京-上海-广州)外,中国航空网络的其它层级结构并不十分明显.从节点的度、簇系数、可达性等指标及其相关性分析,中国航空网络空间结构特征差异明显,表现出较强的集聚性,且可达性与城市体系上层结构在空间分布上较为吻合.随着中国航空运输需求的快速增加,未来航空网络在市场经济的推动下,将进一步表现出向具有"无标度"特征的"小世界网络"演变的趋势,航空网络的空间结构将日趋复杂化. |
