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SCIENTIA GEOGRAPHICA SINICA >

2012 , Vol. 32 >Issue 12: 1439 - 1443

DOI: https://doi.org/10.13249/j.cnki.sgs.2012.012.1439

Orginal Article

Location Determinants of Foreign Clustering Investment：An Empirical Research Based on Confirmatory Factor Analysis

  • WANG Qing-xi ,
  • XU Wei-xiang ,
  • ZHU Heng-fu
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  • School of Economics and Management, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China

Received date: 2012-03-14

  Request revised date: 2012-07-16

  Online published: 2012-12-20

Copyright

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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Abstract

FDI (foreign direct investment) location selection is an important subject in international economics and transnational business field. Following the seminal work of Dunning (1973), many researchers have been persisting in contributing to it. Such type of study is advanced along with related theoretical progress and changing circumstances of international economy, and has been far from ended yet. Today, FDI has evolved differently from its original form. One of its development trends is growing into foreign clustering investment (FCI) introduced in this article, which is agglomeration of foreign direct investment through industrial linkages. In comparison with traditional FDI, FCI has two distinctive characteristics, i.e., firm agglomeration and industrial linkages. This means that they may be different in location selection. With respect to FCI location determinants, extant literature has some shortcomings. For instance, little literature has listed location-specific attributes completely and identified their dimensions explicitly; most of literature has depended on second and aggregate data collecting at regional or industrial level. The aim of this study is to investigate latent dimensions of location-specific attributes and factors influencing location decision of foreign clustering investment, so it can be expected to make up for the defects of previous research to a certain extent. Under a review of extant literature, this study proposes that there are four dimensions constituting FCI determinants system, i.e., location conditions, inputs cost, firm agglomeration, and industrial linkages. Then this study put forward a 13-item measurement scale to capture the four dimensions. Through a survey of 106 foreign firms coming from three counties of Kunshan, Wujiang and Pinghu in Yangtze River delta, the confirmatory factor analysis confirms FCI determinant dimensions proposed above. The empirical results indicate that, in addition to traditionally location-specific and cost-driven factors, firm agglomeration and industry linkage should also be taken into consideration of location determinants of FCI. The implication of this study is that future studies should incorporate such dimensions as firm agglomeration and industry linkage into location determinants of FCI-type foreign direct investment, and then they can get relatively correct and complete results.

Key words： foreign clustering investment; location determinants; confirmatory factor analysis

Cite this article

WANG Qing-xi , XU Wei-xiang , ZHU Heng-fu . Location Determinants of Foreign Clustering Investment：An Empirical Research Based on Confirmatory Factor Analysis[J]. SCIENTIA GEOGRAPHICA SINICA, 2012 , 32(12) : 1439 -1443 . DOI: 10.13249/j.cnki.sgs.2012.012.1439

外商直接投资（FDI）区位选择是跨国经营领域重点关注的问题。随着经济全球化和地域化的推进,FDI的发展出现了新的动向,这直接导致了其在选择区位的时候,所考虑的因素与以前有所不同。本文利用企业层面的调查数据研究了FDI发展的一种特殊形式——外商群集投资（Foreign Clustering Investment,FCI）的区位决定因素。
FCI意指存在产业协作关系的FDI集聚[1,2]。与传统的FDI相比,FCI明显地表现出企业集聚和产业联系特征。这些网络化的可能性常常诱使跨国公司将业务设在靠近（合适的）相关公司群集的地点”[3]。因此,除了一些传统的FDI区位决定因素（如市场潜力、基础设施、税收优惠、劳动力成本等）外,企业集聚和产业关联也是外商群集投资在选择区位时应予考虑的因素。
前人在研究FDI区位决定因素时,存在两点不足：一是除了少数研究外[4,5],限于数据的可获得性,前人研究多采用产业或区域层面的汇集数据,并不能准确地反映外资企业的个体选择与决策情况;二是在区位决定因素的选择上,角度不一,缺乏系统性,不能完整展现各种因素的逻辑架构。本文在前人文献基础上,提炼出影响外商群集投资区位选择的4个维度变量,以此为基础构造出测量FCI企业区位决定因素的Likert量表,通过问卷调查来收集第一手数据,利用验证性因子分析方法来确证FCI企业区位决定因素体系的内在结构。

1 FCI区位决定因素体系

1.1 FCI区位决定因素

外商群集投资是FDI的一种特殊形式,邓宁把区位因素概括为4种：市场因素、交易障碍、成本因素和投资环境[6]。并进一步将区位特定因素细分为9个方面：资源禀赋和市场差异、投入要素、国际运输和通讯成本、投资促进和遏制、产品贸易壁垒、基础设施条件、文化距离、集聚经济、政府的经济体制和政策[7]。随着国际和区域经济活动的集中,以及新经济地理学对经济活动空间聚集的关注,邓宁后来意识到,在解释跨国公司区位选择行为时,产业集聚和关联也是其中的重要因素[8]。
Fetscherin等人总结出以下几个因素对于FDI在中国的区位选择相当重要：制度变迁和改革、集聚效应、经济发展程度、教育水平、工资成本和制度环境等[9]。魏后凯等人将影响外商投资区位选择的主要因素总结为：成本最小化、市场潜力、风险因素和集聚经济、其他因素[10]。刘作丽和贺灿飞将影响在华FDI 区位选择的主要因子归纳为：传统区位因子、制度文化因子和集聚经济因子[11]。
相比传统的FDI,外商群集投资最重要的两大特点是集聚性和产业关联性。Head等人通过日本企业在美国的投资研究发现,在控制影响FDI区位选择的区域和产业特征后,那些日本投资存量相对更高的美国地区更有可能吸引后续投资[12]。随后,Head和Ries又研究了外资在中国的区位选择情况,同样发现了集聚效应的存在[13]。在产业关联方面,Amiti和Javorcik基于新经济地理理论,利用1998~2001年中国省级层面的515组行业数据,发现接近市场和供应厂商是影响外企进入的最为重要的因素[14]。
总结以上文献,可以发现,除了一些传统和公认的FDI区位选择因素,如地理区位、市场潜力、要素成本、投资优惠、政策制度、基础设施等外,影响外商群集投资区位选择的因素还应包括外资集聚状况和产业关联程度（即上游厂商和下游客户的接近性以及水平）。

1.2 FCI区位决定因素的结构体系及其测量量表

本文将外商群集投资的区位选择因素大致归为4个维度：区位条件、成本考虑、企业集聚和产业关联状况。其中区位条件涉及的具体因素较多,因此本文又对其做了硬条件和软条件的区分。区位硬条件指地理位置、交通、基础设施等与区位有关的硬性因素,区位软条件则指有关市场、政府、中介机构、人力资源等方面的软性因素。围绕这些维度,笔者开发了测量FCI区位决定因素的具体问卷项目。在咨询了有关行业专家和企业高管人员后,最终形成了如下包含13个测量项目的7级Likert量表。为避免系统性的误差,问卷打乱了这些测量项目的归类顺序。具体的区位决定因素的结构体系及相应的测量量表如图1和表1所示。
Fig. 1 Structure of FCI location determinants

图1 外商群集投资区位决定因素的结构体系

Table 1 Measurement scale of FCI location determinants

表1 外商群集投资区位选择因素测量量表

序号 测量项目 测量内容 文献来源
1 此地聚集有众多与本企业来源国相同的企业 同来源国企业集聚 [8,12,16,17,19]
2 有重要客户在此地设厂或经营 产业链下游联系 [18,19]
3 此地有本企业的主要原材料或零部件供应商 产业链上游联系 [18,19]
4 政策是否优惠 政策优惠 [7,9]
5 劳动力成本是否低廉 劳动力成本 [5,9,10]
6 土地价格是否便宜 土地成本 [10,11]
7 产品是否有好的市场 市场潜力 [6,7]
8 政府行为是否规范 政府服务水平 [9,11]
9 是否有较强的研发资源和人才优势 人力资本 [7,9]
10 是否有显著的地理区位优势 地理区位 [7,10]
11 交通与货物运输是否便利 交通与物流状况 [5,7]
12 市政基础设施是否完善 基础设施建设 [7,10]
13 中介服务体系（如金融、会计、培训、法律、贸易、物流等）是否完善 中介服务体系 [5,9]

注: 序号含义同图1。

需要说明的是,基于Likert量表的问卷调查,是通过被调查企业信息提供者（informant）的主观判断打分来获得分析数据,主观性较强,这是利用这一方法进行研究需要注意的地方。不过,其好处也是明显的,可以更为细致、深入地考察企业个体的区位决策情况,这是前人研究中利用区域或产业层面的汇集数据所不能的。已经有研究人员将Likert量表或类似方法引入研究。如张文忠等人利用调查问卷,通过企业自我评判的方式来分析韩资企业在山东省的投资区位决策因子[4]。Ulgado构建了一个包含58个区位属性的7级Likert量表,调查了300多家美国内资和外资制造业企业,对他们的区位选择因素进行了比较分析[5]。这些研究,为本研究提供了方法上的借鉴。
根据以上量表,笔者设计了调查问卷,选择外商群集投资特征明显的3个地区（产业）作为采样地点,分别是江苏省昆山市和吴江市的电子信息产业、以及浙江省平湖市的光机电产业。这3个地区(产业)素以外商群集投资闻名。如昆山台资企业以IT产品链条为中心形成了高度集聚,拥有3 100多家台资企业,投资总额370多亿美元。台湾6大笔记本电脑厂商均在昆山投资设厂,笔记本电脑年产量占世界的1/2,数码相机产量占全球的1/8。吴江自1993年开始着手构筑电子信息产业基地,经过十几年的发展,一个以台资为重点的电子信息产业基地已经形成。大到集成电路、线路板,小到各种电阻、绝缘塑片,已形成一个完整的电脑资讯产品工业体系。再如浙江平湖,形成了以日资为中心的光机电产业集群。平湖经济开发区现有外资企业近200家,其中,日本投资企业已达56家,包括日本JFE、日本电产等国际知名企业,台湾企业已经超过40家。
调查一共获得了106份有效样本,样本构成情况如表2所示：从样本分布情况来看,生产最终产品的企业数远比生产中间产品的企业数要少,昆山和吴江来自台湾地区的企业明显居多,而平湖则多为来自日本的企业。这些情况,基本与调查地区的实际情况一致,说明样本具有一定的有效性。
Table 2 sample description

表2 样本企业构成

投资地点 企业来源国(地区) 总计
台湾地区 日本 韩国 中国香港地区 新加坡 泰国 马来西亚 文莱
平湖 中间产品 2 9 1 0 12
最终产品 2 3 0 1 6
昆山 中间产品 34 2 2 2 2 1 43
最终产品 1 0 0 0 0 0 1
吴江 中间产品 18 2 5 4 2 0 31
最终产品 11 0 0 0 0 2 13

2 调查样本及验证性因子分析结果

根据调查数据,以图1为基础进行结构方程建模（SEM）,利用AMOS17.0做验证性因子分析,结果如表3所示：
Table 3 Results of confirmatory factor analysis on FCI location determinants

表3 FCI区位选择因素结构的验证性因子分析结果

因子项目 测量项目 标准化因子负载 C.R.值
区位条件因子 硬条件： 0.910 /
地理区位 0.933 /
交通运输 0.757 10.034***
市政设施 0.831 11.979***
软条件： 0.980 9.538***
产品市场 0.770 8.670***
政府行为 0.763 8.565***
中介服务 0.839 9.704***
研发人才 0.801 /
成本驱动因子 政策优惠 0.776 6.916***
劳力成本 0.831 7.266***
土地价格 0.688 /
企业集聚因子 同源集聚 1.0 /
产业关联因子 供应商 0.586 /
重要客户 0.703 3.955***
拟合指标 CMIN/DF=1.902, GFI=0.879, CFI=0.933, RMSEA=0.093

注：①企业集聚因子为单指标测量,其负载系数默认为1。②根据AMOS建模要求,“/”处对应的测量指标其负载系数预设为1,故没有C.R.值。

从以上验证性分析结果来看,各测量项目对应其潜在因子的负载系数均在0.01水平上显著,负载系数大多在0.7以上,只有少数如“供应商→产业关联” 、“土地价格→成本驱动”等负载系数稍低于0.7。因此,从因子负载的角度来看,各测量指标大多能有效地负载于其对应因子之上。同时,产业关联指标的负载情况不太理想,这表明,产业关联因子的测量项目需要改进,比如说指标设计得更为细致一点,以便得到更为聚合的测量效果。总体来看,模型的拟合性基本上成立,CFI在一般标准0.9以上,GFI也接近0.9,RMSEA尽管超出一般标准0.08但超出不多。考虑到本研究的样本量仅为106,这一状况尚可接受。如果能够增大样本量,相信结果将更为理想,这是后续研究需要注意的。

3 结 论

FDI区位选择问题一直是国际经济和跨国经营领域重点关注的问题。从邓宁的开创性研究到现在[6],众多学者不断在丰富和推进这一研究。梳理邓宁本人对这一问题的研究脉络也可发现,对FDI区位选择的研究事实上是随相关理论进展和国际经济形势演变而不断补充和完善的,远谈不上完结。时至今日,FDI的发展已经与原本形态有了很大的不同。其中一大变化是向本文所提出的外商群集投资方向发展,而且有越来越强的趋势。相比传统的FDI,外商群集投资具有集聚性和产业关联性两大特征,因此在区位选择上较之传统的FDI有所区别。在有关研究上,前人文献存在因素体系不够全面、体系结构不够清晰,所用数据多为二手数据、汇集数据的缺陷。本文在前人文献基础上,构建了一个测量外商群集投资区位选择因素的指标体系,利用一手企业调查数据,采用验证性因子方法确证了这一指标体系的内在结构。实证研究清楚地表明,除了传统的区位特定因素（包括硬条件和软条件）、成本驱动因素外,外商群集投资的区位选择因素还包括企业集聚和产业关联两个方面。这意味着,后续研究在考察具有外商群集投资这样特征的FDI的区位决定因素及其效应时,必须综合考虑企业集聚和产业关联这两个要素,才能得到比较准确和全面的结果。

The authors have declared that no competing interests exist.

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魏后凯, 贺灿飞, 王新. 外商投资区位研究的理论前沿及最新进展[J]. 上海行政学院学报, 2001, (4): 42~52.本文系统考察了近几十年来外商直接投资区位研究的理论前沿及重要进展,并在此基础上对近年来我国外商投资区位研究进行了简要的述评,指出了未来我国外商投资区位研究的发展方向.

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刘作丽, 贺灿飞. 在华外商直接投资区位研究述评[J]. 地理科学进展, 2009, 28(6): 952~961.<p>尽管学术界至今未能形成一般性的外商直接投资(FDI)区位理论，但已有的大量研究却对加深理解FDI的区位选择规律做出了重要贡献。中国作为一个成功转型国家，在华FDI区位研究早已成为各界关注的热点问题之一。本文从区位理论和FDI理论两方面梳理FDI区位研究的理论基础后，回顾并评述了在华FDI区位研究进展，并提出了其未来发展中需要完善的相关命题。早期的研究以定性描述为主，从20世纪90年代中期开始转入利用计量经济模型对影响在华FDI区位选择的因素进行识别；研究主要集中在省区尺度，识别出的区位因子主要包括成本、市场、集聚和制度等。FDI在东道国的区位选择行为是&ldquo;区域&mdash;产业&mdash;企业&rdquo;共同作用的结果，在识别东道国区位要素的基础上，已有文献同时也关注了来源国效应、产业特征与企业属性和时间演化对FDI区位决策的影响。未来研究中需要加强对新兴经济体FDI区位模型的一般性讨论，强化&ldquo;区域&mdash;产业&mdash;企业&rdquo;系统研究，并关注基于功能视角的在华FDI(跨国公司)区位研究。</p>

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[12]
Head K, Ries J, Swenson D.Agglomeration benefits and location choice: Evidence from Japanese manufacturing investments in the United States[J]. Journal of international economics, 1995, 38(3-4): 223-247.Recent theories of economic geography suggest that firms in the same industry may be drawn to the same locations because proximity generates positive externalities or ‘agglomeration effects’. Under this view, chance events and government inducements can have a lasting influence on the geographical pattern of manufacturing. However, most evidence on the causes and magnitude of industry localization has been based on stories, rather than statistics. This paper examines the location choices of 751 Japanese manufacturing plants built in the United States since 1980. Conditional logit estimates support the hypothesis that industry-level agglomeration benefits play an important role in location decisions.

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[13]
Head K, Ries J.Inter-City Competition for Foreign Investment: Static and Dynamic Effects of China's Incentive Areas[J]. Journal of Urban Economics, 1996, 40(1): 38-60.ABSTRACT China's &ldquo;Open Door&rdquo; policy has created a natural experiment for studying agglomeration externalities and the role of incentives designed to attract foreign direct investment. We build a model which predicts that foreign firms will prefer cities where other foreign firms are located. We estimate the model using data on 931 foreign ventures. We then use simulations to explore the effect policies favoring particular cities had on the distribution of investment. We find that &ldquo;attractive&rdquo; cities&mdash;those with good infrastructure and an established industrial base&mdash;gained most and that agglomeration effects greatly magnified the direct impact of policy.

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[14]
Amiti M, Javorcik B S.Trade costs and location of foreign firms in China[J]. Journal of Development Economics, 2008, 85(1-2): 129-149.This study examines the determinants of entry by foreign firms, using information on 515 Chinese industries at the provincial level during 1998-2001. The analysis, rooted in the new economic geography, focuses on market and supplier access within and outside the province of entry, as well as production and trade costs. The results indicate that market and supplier access are the most important factors affecting foreign entry. Access to markets and suppliers in the province of entry matters more than access to the rest of China, which is consistent with market fragmentation due to underdeveloped transport infrastructure and informal trade barriers.

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