Analyzing China's Inland Transport Development Title URL

Meiji University

　

Title

Analyzing China's Inland Transport Development

for Belt and Road Initiative -focusing on the

Railway and the road cargo transport along

Eurasia-

Author(s) Baixun,Wang, 町田,一兵

Citation 明大商學論叢, 102(2): 1-28

URL http://hdl.handle.net/10291/21443

Rights

Issue Date 2020-03

Text version publisher

Type Departmental Bulletin Paper

DOI

　　　　　　　　　　　　　　　　　　　　　　　　　　　https://m-repo.lib.meiji.ac.jp/

Analyzing China’s Inland Transport Development for Belt and Road Initiative

―focusing on the Railway and the road cargo transport along Eurasia―

Baixun Wang＊, Ippei Machida＊

AbstractUnder China’s basic policy, “The belt and road initiative （BRI）” has triggered the comprehensive develop-ment of China’s international and inland transportation infrastructure since 2013. The soaring operation of Sino-Europe Block Train （SEBT） over the past six years indicates BRI has been the crucial and solid foundation for China’s international railway development. However, from the view of transport efficiency, though SEBT’s operations increasing operation sets up remarkable records every year and attracts the attention of the logistics market, the rationality of SEBT’s subsidy from governments is always discussed frequently. Under this background, whether SEBT accords with the needs of BRI’s logistics market, and the better solutions for Eurasian inland transport need discussion. China has become a member of TIR Convention since 2016, which provides new chances for Eurasian inland transport. Therefore, the logistics market condition of SEBT has changed, and the logistics enterprises could provide new services. Under the changes in those elements. This study will examine the current situation of SEBT in terms of trans-port volume and trade amount firstly; then, we will analyze China’s cross-border road transport （CBR） over the past years. Finally, we will compare the advantages of both the patterns in transport characters. Besides, trade and business conditions are the foundation of transport and logistics services. Therefore, this study will also analyze the trade facilitation and operational risk of significant regions in Eurasia. Moreover, this study proposes suggestions for the future development of China’s inland transport in Eur-asia based on the results.

Keywords: inland transport, Sino-Europe Block Train, cross-border highway transport, trade facilitation and operational risk, logistics market

1. Introduction

　　BRI’s implementation brought more opportunities for international trade between China

＊ Xi’an Eurasia University, [email protected]＊ Meiji University, [email protected]

1

and other Eurasian countries. The lasting and evolutionary construction of transport over the

past two decades makes China’s railway and highway connect to the major trade partners

along Eurasia and provide more efficient service for international trade, summarized by Enom-

oto ［1］.

　　Consequently, China’s international inland logistics has enjoyed a booming era since 2013.

Benefiting from the situation, SEBT is developing rapidly since then. It increased steeply from

2015 and reached to the number of 21,225 at the end of 2019. The main cargoes include indus-

trial materials, machinery, building materials, industrial accessories, food, light industrial prod-

ucts, and automobile.

　　On the other hand, the charge of railway freight is much higher than maritime; besides,

SEBT is commonly becoming the image projects of their local government. Thus, the cargo

sourcing by providing freight subsidies to the consignor or forwarder becomes the crucial

point. Bi ［2］, Wang, et al., ［3］, Feng et al., ［4］ pointed out SEBTs’ subsidies contravene the

transport principle and cause the malignant competition of logistics market. Meanwhile, the

low value-added cargoes, and overlapping routes are SEBTs’ common issues.

　　For CBR, by joining TIR Convention in 2016, China improved international highway trans-

port, especially the door-to-door service. Some China’s logistics enterprises tested the feasibili-

ty from China to Europe from 2016 to 2018 and succeeded in security, cost and time-effective.

　　SEBT is the primary mode for Eurasian inland transport, and the business keeps increas-

Source: Annual Operation of SEBT by Landbridge Logistics Alliance Public Information Platform

Figure 1.1　　　Operations of SEBT （2011-2019.10）

『明大商学論叢』第 102 巻第 2 号2 （ 70 ）

ing during recent years, yet some issues and suggestions about SEBT’s future development

still need to be discussed and proposed. Meanwhile, the conditions of China’s CBR turned to

be positive, and evolutionary by TIR, which could provide more choices and efficient solutions

to trade and logistics services. The studies of Feng, et al. ［5］ Rogers ［6］, and Rodrigue, Com-

tois and Slack ［7］ indicate that cross-border road transport is more cost-time effective in

terms of for speed, autonomy and flexibility for inland transport. Therefore, it is necessary to

consider the current situation of SETB and the progress of CBR along Eurasia. This study ex-

plores the answers to the following questions:

　　According to the SEBT’s current situation, does the SEBT is the most suitable inland

transport for BRI?

　　How did China’s CBR transport develop since 2016, and what will CBR function for BRI?

　　By answering these questions, the study contributes to the literature in the following

three aspects:

　　Firstly, this research reviews on informative aspects by estimating SEBTs’ operations and

the performance in China’s international trade.

　　Secondly, the research analyzes the impact of TIR Convention on China’s CBR based on

the case studies to identify the effect of road transport to BRI.

　　Thirdly, the research compares the advantages of SEBT and CBR, respectively, in order

to provide reasonable suggestions for realizing the effective logistics service.

　　The remainder of this paper organizes as follows: Section 2 introduces the datasets and

methodologies. Section 3 presents the empirical analyses. Section 4 provides the discussions of

the findings and proposes suggestions for BRI’s inland transport. Finally, Section 5 concludes

this study.

2. Data and Methodology

2.1　Data

　　The dataset utilized for this study is public and comprises Global Competitiveness Report

（GCR）, Corruption Perceptions Index （CPI）, China’s statistical yearbooks, and statistical com-

munique cover the related industrials, national, provincial, and capital level. The data on offi-

cial websites related to BRI and transport are also adopted. For this study, SEBT denotes for

Europe bound, while the block train for Central and Southeast Asia bounds is SABT （Si-

no-Asia Block Train）, which does not discuss in this paper due to the constraint of data. Be-

sides, the information and data from the interviews with logistics enterprises are for empirical

studies.

Analyzing China’s Inland Transport Development for Belt and Road Initiative 3（ 71 ）

　　The period for China’s trade amount by transport is from 2003 to 2015 due to the con-

straints of data. The general data updated to 2017 or 2018. The data structure of GCR changed

from 2017. Thus GCR’s data utilized for this paper is from 2010 to 2016.

2.2　Methodology

　　This study applies both qualitative and quantitative analysis. Both methodologies lay the

foundation for the suggestion of this study.

2.2.1　Qualitative Analysis-Case Study

　　The qualitative analysis based on case studies applies to the research of SEBT’s current

situation and the development of China’s CBR to demonstrate the current situation of China’s

inland cross-border transport.

　1） Hub Selection

　　Affected by BRI, 56 China’s cities operate SEBT in succession until 2018, yet the number

of operations in 8 hub cities accounts for over 80% of the amount and increases steadily since

2013 . Thus, this study adopts these hubs as the research targets. Considering China’s trade

amount and transport volume are geographically unbalance, the comparison of the hubs focus-

es on the growth rate. Besides, the data of 2019 has not published yet; hence, the duration for

this study ends in 2018.

　　Chongqing’s decreasing share is because more hubs operated SEBT from 2013, Chengdu

and Zhengzhou are Chongqing’s significant competitors. Thus, SEBT’s gross operation in-

creased, then Chongqing’s share decreased. Chengdu replaced Chongqing for the first rank

since 2016 . Xi’an’s SEBT operations reached to the number of 640 in 2018 and listed as the

fourth position.

Table 2.1 SEBT’s Operations Ratio of Major Hubs against Gross Amount （2013-2018）

Hub/Ratio ‘13 ‘14 ‘15 ‘16 ‘17 ‘18Chongqing 43.8% 33.1% 31.5% 24.7% 18.1% 22.7%Chengdu 38.8% 14.6% 12.6% 26.6% 27.6% 24.9%Zhengzhou 16.3% 25.3% 11.9% 8.0% 13.6% 11.8%Suzhou 1.3% 11.4% 9.8% 6.7% 3.2% 2.1%Wuhan 8.4% 20.1% 7.2% 10.3% 6.6%Yiwu 0.3% 4.3% 5.9% 4.6% 5.0%Xi’an 1.0% 3.3% 10.1%Hefei 1.5% 1.3% 2.9%Ratio against Gross 100.0% 93.2% 90.3% 81.6% 81.9% 86.1%

Source: processed by Annual Operation of SEBT by Landbridge Logistics Alliance Public Information Platform

『明大商学論叢』第 102 巻第 2 号4 （ 72 ）

　2） CBR Case Study

　　The development of China’s CBR focuses on the increase of cross-border transport agree-

ment between China and other nations and China’s TIR pilot transport. The former demon-

strates China’s cross-border transport agreements based on online official documents. The lat-

ter concludes the cases of the TIR pilot transport between China and other Eurasian countries

according to the online reports and news.

2.2.2　Quantitative Analysis-Principal Component Analysis

　　The quantitative analysis focuses on the principal component analysis （PCA） that set up

the trade facilitation index （TFI） and operational risk index （ORI）. The application of TFI

and ORI to this study is to examine the business condition of Eurasian CBR.

　　PCA, probably the most popular multivariate statistical technique applied to nearly all sci-

entific disciplines, involves analyzing the data representing observations of several dependent

variables. Abdi and Williams ［7］ opined PCA’s goal is to extract meaningful information from

the data table and express this information as a set of new orthogonal variables. It is an ex-

ploratory statistical method for the graphical description of the information present in large

datasets. Saporta and Niang ［8］ indicated in most applications, PCA involves studying p vari-

ables measured against n individuals. When n and p are large, the aim is to synthesize the

considerable quantity of information into an easy and understandable form.

　　Based on the theories, if X is （n, p）, xij is the value of the individual i for variable j （ex-

pressed as xj）, which is identified as a vector of n components （x1j, x2

j,…xnj）. Similarly, an indi-

vidual i is identified to a vector xi of p components as xi=（xi1, xi

2, … xip）, where i=1, 2,…,n，and

n ＞ p, and sets z as a matrix x of observations, then the normalized matrix can be calculated

as follows:

　The correlation coefficient matrix can be calculated as follows:

zij＝ , i＝1, 2,…,n, j＝1, 2,…,psj

zij－xj

xj＝ , s2j＝n

Σni＝1 xij

n－1Σn

i＝1（xij－xj）2

R＝[rij]pxp＝ n－1ZTZ

rij＝ n－1Σn

i＝1 zkj zkj , i＝1, 2,…,n


　　|R－Λ Ip|=0 can calculate the eigen roots of the correlation coefficient matrix.

　　Next, calculate m, if Σm

j＝1 Λj

Σpj＝1 Λj

≥ 0.85 is applicable, which means that 85% of the dataset is

applied.

　　For each, Λ j j=1, 2,…,m, the value of bj0 can be calculated by solving the function Rb =Λ

　　Transform the variables by calculating Fij=ziibj

0, where j=1, 2,…,m.

　　F1 F2…Fp are the principal components.

　　The result can be calculated by obtaining the sum of the weighed components. The vari-

ance contribution rate of each component is the weight number. For the study, PCA is pro-

cessed by SPSS 22.

　　TFI has become a hot topic in research regarding international trade. Wilson et al. ［9］

measured TFI by using several different indicators, including port efficiency, customs environ-

ment, regulatory environment, and e-business usage. This study revises a new evaluation sys-

tem for TFI, comprising six primary indicators: government regulatory, logistics condition,

customs situation, business environment, marketing condition, and financial level with 37 sec-

ondary indicators detailed in Appendix 1. E-business is excluded because of the rapid develop-

ment of the internet of Eurasian countries in recent years. Assuming trade tariff and total tax

rates are negative indicators, while other indicators are positive, the higher the positive indica-

tor, the better the TFI, and vice versa.

　　International transport also needs to face any possible risks. This paper applies PCA to

set up ORI to estimate the operation risk of China’s major partner of Eurasia. Similarly, ORI

consists of seven primary indicators: government management, enterprise condition, sanitation

situation, education level, labor force condition, technology level and innovative level with 45

secondary indicators detailed in Appendix 2 , judicial independence and intellectual property

protection are for both TFI and ORI for the importance to trade condition and risk aversion.

3. Empirical Research

3.1　SEBT’s Current Situation

3.1.1　International Cooperation

　　SEBT attracted large-scaled logistics enterprises after the first arriving in Germany. The

routes expanding made more challengers joined in SEBT’s business by providing express, dis-

tribution, or other related services to/from Europe and cargo sourcing in China and aboard

（Ex: Europe and Japan）, which made more business chances for SEBT. With the cooperation

of the companies, SEBT expanded rapidly, and the trunk lanes of SEBT and SABT include

『明大商学論叢』第 102 巻第 2 号6 （ 74 ）

Europe, Russia, Southeast Asia, and Central Asia. A new railway operation style originating

from China to West Europe and Southeast Asia has set up.

Table 3.1 Global Logistics Enterprises and SEBT’s Operation （2013-2018）

Logistics Enterprise Cooperation HubsDB Schenker1 Chongqing, Shenyang, ZhengzhouDHL2 Chengdu, Zhengzhou, Suzhou

UPS3 Chengdu, Zhengzhou, ChongqingSuzhou, Wuhan, Changsha

Maersk4 ChongqingNippon Express5 Xi’an

Russian Railway6 Shenyang, Dalian, Suzhou, ChangchunWuhan, Guangzhou, Tianjin, Qingdao

National Company Kazakhstan Temir Zholy7 Lianyungang

Source: collected from the websites shown as follows1） https://www.dbschenker.com/cn-zh/about/about-db-schenker-in-china/history2） https://www.prnasia.com/story/124282-1.shtml3） https://www.pressroom.ups.com/pressroom/ContentDetailsViewer.page?ConceptType=PressReleases&id=

1490878051851-2574） http://www.sofreight.com/news_28849.html l5） https://news.sina.com.cn/o/2018-12-21/doc-ihqhqcir8820768.shtml6） https://www.rzdlog.ru/upload/medialibrary/f0d/f0d0499023b5b665408a62b14943d6b3.pdf7） http://www.xinhuanet.com/world/2015-03/26/c_127624923.htm

3.1.2　Impact on International Trade

　　This part examines SEBT’s whether SEBT promoted the international trade of both the

local and national aspects and changed China’s traditional cross-border transport structure.

Some other hubs of SEBT or SABT are introduced to enhance the objectiveness of the com-

parison analysis. These hubs are Lianyungang, Qingdao, and Urumqi. Lianyungang operated

SABT along China Land Bridge （CLB） from the 1990s, Qingdao is a crucial node connecting

China’s ocean shipping and CLB, and initiated the maritime-railway transport for BRI from

early 2010s, and Urumqi is the pivotal node for both SEBT and SABT.

　　The figures and tables indicate that though over 80% of gross operations amount proceed

by the significant eight hubs and the operations kept steadily increasing over the past five

years, both the trade amount and shares of the hubs against national data did not increase ob-

viously during the same period, even though Suzhou and Qingdao benefited from the devel-

oped coastal industrial parks. The amount is much higher than the other selected hubs. The

increase of Xi’an and Zhengzhou was originated from the semiconductor and iPhone, respec-

tively, while Yiwu is the world’s most significant export base of small commodities. A notable

case is Xi’an; the SEBT operations increased from 121 to 640 in 2018 （excluding SABT）; mean-


while, the trade amount decreased by 4.67 billion USD.

　　The total amount of trade at these hubs did not obviously affect by SEBT over the past

five years; in other words, SEBT’s increasing operations did not promote local international

trade. However, the transport of westbound cargoes started to assemble to some domestic

hubs, such as Chengdu and Chongqing.

　　China’s trade amount transported by railway is about 1% （Terms of monetary amount）

during the long term, and the ratio of both gross and import amount have decreased since

Figure 3.1　　　Operations of SEBT （2013-2018）

Source: Annual Operation of SEBT by Landbridge Logistics Alliance Public Information Platform

Source: Statistical Communiques of the Cities （2013-2018）

Figure 3.2　　　International Trade Amount of the Hubs （2013-2018）

『明大商学論叢』第 102 巻第 2 号8 （ 76 ）

2009. Though the export amount increased slightly from 2011 to 2014, the increasing opera-

tions do not bring increasing value simultaneously. The situation shows that the primary car-

goes transported by SEBT are commonly low value-added goods, which will negatively affect

the operation for the long term because of its high operation cost.

Table 3.2 Trade Ratio of the Hubs against National Gross Amount （2013-2018）

‘13 ‘14 ‘15 ‘16 ‘17 ‘18Chongqing 1.65% 2.22% 1.88% 1.70% 1.62% 1.71%Chengdu 1.22% 1.30% 0.99% 1.11% 1.42% 1.63%Zhengzhou 1.03% 1.08% 1.44% 1.49% 1.45% 1.34%Suzhou 7.44% 7.24% 7.72% 7.43% 7.68% 7.66%Xi’an 0.43% 0.58% 0.72% 0.75% 0.92% 0.70%Wuhan 0.52% 0.61% 0.71% 0.65% 0.70% 0.84%Yiwu 0.45% 0.56% 0.87% 0.91% 0.83% 0.71%Hefei 0.44% 0.48% 0.51% 0.51% 0.61% 0.67%Urumqi 0.19% 0.19% 0.15% 0.13% 0.31% 0.17%Qingdao 1.87% 1.86% 1.78% 1.78% 1.81% 1.74%Lianyungang 0.16% 0.19% 0.20% 0.19% 0.20% 0.21%Shares of China 15.39% 16.31% 16.98% 16.65% 17.54% 17.38%

Source: processed by the data of Statistical Communiques of the Cities （2014-2018）

3.1.3　Loading Cargo and Freight Subsidy Issues

　　The transport patterns of cargoes are different in lead time. The ocean commonly ships

the low value-added bulk cargo with long-term lead time, and the air delivers the high val-

Source: 1） Annual Operation of SEBT by Landbridge Logistics Alliance Public Information Platform; 2） China Customs Statistical Yearbook （2003-2015）

Figure 3.3　　　Ratio of Trade Amount by Railway compared with Operations of SEBT （2003-2015）


ue-added cargo with short-term lead time.

　　Onishi ［10］ pointed out that SEBT should transport the cargo with reasonable lead time

and tonnage, and higher value-added than that of ocean shipping. Nonetheless, local govern-

ments just focus on increasing the number of operations by ignoring the selection of cargo

and long-term development. The SEBT’s main cargo in 2018 includes machinery, electronic

products, garment, automobile spares, small commodity, textile, pulp, lumber, agriculture prod-

ucts, hardware, electric equipment, and Baby products. Most of the cargo is low value-added,

and compared with SEBT, ocean transport is more suitable for these cargoes in terms of logis-

tics cost-efficiency.

Table 3.3 Advantages of Different Transport

Lead timeRailway Air Ocean

Railway Low HighAir High HighOcean Low Low

FreightRailway Air Ocean

Railway Low HighAir High HighOcean Low Low

Transport TonnageRailway Air Ocean

Railway High HighAir Low LowOcean High High

　　Besides, due to SEBT has been the image project for the local government; hence, cargo

tonnage is the keyword for SEBT operation companies. Local governments provide the freight

subsidy in attracting the shippers or forwarders to source more cargoes. Thus, SEBT’s opera-

tions depended on the subsidy since the first operation in 2011, which is the heaven burden of

the local governments. Under this background, it is necessary to examine whether there is a

more suitable pattern for BRI’s transport.

『明大商学論叢』第 102 巻第 2 号10 （ 78 ）

Table 3.4 Freight Subsidy of Major Hubs

City Freight Subsidy （USD） for each containerChongqing 7,5001

Chengdu 171 million for each year2

Zhengzhou 7,5001

Xi,an 3,000-5,000 （123 thousand for each operation）Wuhan 2,500-3,0002

Hefei 3,0002

Harbin 3,000 （123 thousand for each operation）2

Changchun 1.43 million for each year2

Guangzhou 7,3001

Changsha 3,500-4,0002

Lianyungang 2,5002

Source: 1） https://k.sina.com.cn/article_2359441912_8ca239f802000hp17.html 2） https://k.sina.com.cn/article_5813707658_15a86238a01900rq7n.html

3.2　Development of Cross-border Road Cargo Transport

　　The development of China’s CBR along Eurasia mainly focuses on two aspects: the in-

crease of cross-border transport agreement between other nations and the improvement of

business conditions in terms of trade facilitation and operational risk of the region. The former

one enhances the road connectivity between China and other Eurasian countries, while the

latter provides better business conditions for the logistics companies. This part analyzes both

the aspects respectively to demonstrate the current situation of China’s CBR.

3.2.1　Increase of Cross-Border Transport Agreement between other Nations

　　The analysis above on China’s trade amount by transport indicates the cargoes delivered

by road account about 18% of the gross amount, and this ratio keeps rising tendency in recent

years. The statistics show that CBR will have another proper pattern for BRI’s road transport.

　　China has realized the importance of CBR and impelled the negotiation of transport agree-

ment with neighboring countries since the early 1990s and joined in TIR Convention in 2016.

By July 2019, China’s General Administration of Customs approved all the road ports of entry

to implement TIR Convention, which offers road transport companies more opportunities for

BRI’s road transport.

　　TIR’s information-sharing system enhances the efficiency of China logistics companies by

allowing the sealed cargoes to the destination directly with the same truck without examining

when passing through the other host countries, as well as rescinding the route restrictions of

previous cross-border transport agreements.


　　China’s government signed new cross-border transport agreements with the neighboring

countries and improved the logistics efficiency via the third part country, especially the new

agreement with Russia provides the reference for the negotiating agreements.

Table 3.5 China’s Cross-border Transport Agreements

Country/Region Year SummarizeBilateral Agreements

Mongolia 1991 Transport on the designated roadRussia 1992 IdemKazakhstan 1992 IdemLaos 1993 IdemPakistan 1993 IdemKyrgyzstan 1993 IdemUzbekistan 1993 IdemVietnam 1994 IdemNepal 1994 IdemTajikistan 2008 Idem

Multilateral AgreementsThe Quadrilateral Traffic in Transit Agreement （QTTA）China, Pakistan, Kyrgyzstan and Kazakhstan

1995

From 2004 , the quota limit for permits for each country per year is 200.One permit is valid for one round trip only, allowing vehi-cles to carry return load.

Kyrgyzstan and Uzbekistan 1998 Transport on the designated road

The Greater Mekong Subregion Cross-Border Transport Agreement （CBTA）.

1999

Each contracting party shall be entitled to issue up to 500 permits.A border crossing transport operation shall be completed within no more than 30 days.

Shanghai Cooperation Organization＊ 2014 Transport on the designated roadMongolia, Russia ＊＊ 2018 Not public

Source: 1） https://tadb.unescap.org/CHN/chn.html 2）＊http://www.mot.gov.cn/jiaotongyaowen/201510/t20151014_1899396.html 3）＊＊http://tradeinservices.mofcom.gov.cn/article/lingyu/gjhdai/201907/86196.html

3.2.2　China’s TIR Pilot Transport

　　China’s logistics companies started to test the condition of CBR for BRI from 2016, and the

successful pilots brought more companies to take part in this business.

　　The first pilot was from Tianjin （China） via Ulan Bator （Mongolia） and arrived at Ulan-

Ude （Russia） in August 2016 and succeeded, which promoted the transport agreement of Chi-

na, Mongolia, and Russia. The second pilot started from Tashkent （Uzbekistan） via Kyrgyz-

stan and delivered to Kashgar （China） also succeeded in November 2016. Nevertheless, CBR

operated by both domestic and foreign companies developed fast in 2018, and the routes also

『明大商学論叢』第 102 巻第 2 号12 （ 80 ）

spread from neighboring countries to further destinations, including West and Southeast Eu-

rope, and Southeast Asia. Besides, the pilot results indicate the infrastructures, service areas,

and gas stations between Central Asia to Europe are generally in good condition except for

specific ranges in Kazakhstan.

Table 3.6 TIR Pilot Transport Cases （2016-2018）

Route Month Days ReferenceDalian-New Siberia May 10 5,500km1

Khorgas-Georgia May N/A 4,500km2

Erkeshtam-Kyrgyzstan/Uzbekistan July N/A 950km3

Tianjin-Ulan Bator August 3 10 days by railway4

Kunming-Haiphong September 1 780km5

Vladivostok-Dalian N/A 4 3 weeks by ocean6

Shenzhen-Pingxiang-Hanoi N/A N/A 1,309km7

Khorgas-Poland November 13 7,000km8

Urumchi-Poland/Gernany November 10 7,000km, 2 drivers9

Foshan （China）-Alicante （Spain） November 16 13,600km, first long distance transport10

Manzhouli （China）-Istanbul November 14 13,000km11

Paris-Urumchi November 13 8,200km, 1 driver, winter12

Source: collected from the websites or interview shown as follows 1） http://news.sina.com.cn/c/2018-06-04/doc-ihcmurvh2732899.shtml 2） https://finance.jrj.com.cn/2018/05/27115924595134.shtml 3） http://www.chinacar.com.cn/newsview283376.html 4） http://tj.sinotrans.com/art/2016/8/18/art_4454_24647.html 5） http://www.xinhuanet.com/politics/2018-09/19/c_1123454646.htm 6） http://sputniknews.cn/russia_china_relations/201811111026802584/ 7） http://jtys.sz.gov.cn/zwgk/jtzx/gzdt/ghdt/201809/t20180920_14106028.htm 8） https://www.yicai.com/news/100067838.html 9） interview with CEO of Alblas China Company 10） http://www.xinhuanet.com/finance/2019-05/03/c_1210125088.htm 11） http://inews.nmgnews.com.cn/system/2019/06/17/012727966.shtml 12） http://xj.sina.com.cn/news/b/2019-02-21/detail-ihqfskcp7214724.shtml

　　In addition to the higher lead time than the railway, the other advantages of CBR for dif-

ferent kinds of goods can be summarized based on the pilots as follows:

　1） General goods: Eurasia has developed road network, the cargo sourcing, consolidation

and door-to-door service of CBR are more accessible to execute than that of the railway;

　2） Cold chain goods: the cargoes from the factory to consignee need not be reconsolidated

or opened during the transport, which means the process is a closed-loop;

　3） Oversized goods: for road transport, this kind of cargo is not limited by size or weight.

At present, CBR is the only choice for oversized goods with the required lead-time.


3.2.3 Improvement of Trade Facilitation and Operational Risk

　　Trade facilitation and operational risk should be considered for logistics and transport in

case of unpredictable matters when conducting business.

　　Based on PCA, the weight of the indicators for TFI and ORI are shown as follows, the

more the absolute value if the indicators close to zero, the weaker the indicator influence in

the index.

　　For the weight of TFI indicators, Total tax rate （M3） seldom impact on the index, Quali-

ty of roads （L2）, Intensity of local competition （B4）, No. of procedures to start a business （B5）

and Legal rights （F8） are less important than the other indicators. Trade tariffs （C2） has a

noticeable influence on the index.

　　For the weight of ORI indicators, the Flexibility of wage determination （L2） seldom im-

pact on the index, Hiring and firing practices （L3） and Redundancy costs （L4） are less im-

portant than the other indicators. Tuberculosis incidence （H1） has an evident negative influ-

ence on the index.

　　According to the formula in Appendix, the TFI of 73 countries related to BRI is calculat-

ed, and this study selects 59 countries of 9 Eurasian subregions. Mongolia is attribute to Cen-

tral Asia for the similar political and historical conditions. The result shows that TFI from

west to east generally spread like a “W” shape. The index decreased in 2016 due to the global

depression, and the rising trade protectionism decreased the trade facilitation since then.

　　Likewise, ORI also generally spread like a “W” shape. However, the value of 2016 went up

Source: calculated based on PCA

Figure 3.4　　　Indicator’s Weight of TFI （2010-2016）

『明大商学論叢』第 102 巻第 2 号14 （ 82 ）

because the selected countries enhance the related aspects to develop a better environment

for comprehensive cooperation. The analysis shows though trade protectionism is rising while

the countries also make efforts to attract more investment and business to promote the pros-

perity of the domestic economy. The situation will impact Eurasian CBR in the future.

　　Combining both TFI and ORI, this study could conclude that inland transport, especially

the CBR, may develop the business with West, North, and Central Europe as well as Southeast

Asia. Though the conditions still need to be upgraded, Central Asia is the pivotal node con-


Figure 3.5　　　Indicator’s Weight of ORI （2012-2016）


Figure 3.6　　　TFI of Eurasian Subregion （2012-2016）


necting China, Europe, and Russia. China exports heavy industrial equipment to this region;

besides, the principal trade items from China to Central Asia and Mongolia are more suitable

for CBR. The pilot transport brought more solutions to Eurasian inland logistics, trade, and

governments. Thus, China should improve Eurasian road transport by promoting multilateral

cooperation.

4. Discussion

　　This study demonstrates the current situation of BRI’s inland transport in terms of rail-

way and road cargo to find out the proper pattern for Eurasian long-distance inland transport.

This part proposes discussions about empirical analysis.

4.1 Current Situation of SEBT

　　As the critical factor to support BRI, SEBT has been operation for seven years with rapid

growth; however, the analysis above showed the increasing operations are irrelative to the

trade amount of most hub bases.

　　The impact of SEBT on regional international trade is insignificant because the spatial

structure of China’s export still bases on the coastal region, focusing on Eastern and South-

eastern China. At the same time, the SEBT hubs locate in Middle and West China where lacks

export-oriented industrial clusters. For example, only 30% of the cargoes originated from Xi’an

and Chengdu made in local areas, and the ratio decreased of both hubs from 2017 due to the


Figure 3.7　　　ORI of Eurasian Subregion （2012-2016）

『明大商学論叢』第 102 巻第 2 号16 （ 84 ）

massive amount freight subsidy provided by the hubs attracted more cargoes from outside

since then.

　　Most of the inland hubs need to provide high freight subsidy to collect the export cargoes

to increase the number of operations by fierce competition, such as Chengdu and Zhengzhou

provide 2 billion and 1.6 billion RMB annual subsidy respectively in 2018. However, the subsi-

dy cannot last for long, and China’s central government has made the policies to enhance the

cooperation between the domestic hubs and foreign railway enterprises of Kazakhstan, Russia,

and Western Europe to reduce the operation cost. Meanwhile, China’s Ministry of Finance re-

quired the hubs decreased the freight to USD 0.8/Km per FEU, besides, the subsidy in 2018

requires to no more than 50% of the freight, and the ratio should decrease to 40% and 30% of

the freight in 2019 and 2020 respectively.

　　Under the background, some hubs realized the significant competitors for cross-boundary

transport are the ports locating in eastern coastal areas, and the better solution should focus

on developing inland industrial clusters or change the operation methods. Therefore, the hubs

have found new ways of collecting trade cargoes.

　　Xi’an developed the relation between domestic food corporation “Aiju” （a famous local

food productive enterprise） and the Kazakhstan agriculture department, then the import agri-

culture cargoes by SEBT was increasing over the past two years. Meanwhile, Xi’an developed

a cooperative relationship with the trade companies in West Europe Counties, focusing on Ger-

many and Italy from 2016 to gain more eastbound cargoes.

　　With the experience of delivering HP Laptop to Europe, Chongqing develops and expends

the export processing zone to introduce more export-oriented enterprises focusing on Fortune

Global 500 List by providing more preferential policies.

　　However, most cargoes transported by SEBT are low value-added goods, which is the

core problem. The dilemma of SEBT is the numerical tonnage is the foundation for increasing

the number of operations while the high value-added products are commonly light cargoes.

Based on lead time and transport efficiency, the major SEBT’s cargoes can ship by the ocean.

The bulk and low added value goods transported by SEBT with subsidies is the heavy burden

of each local government. Though SEBT is the symbol for Eurasian inland transport, its oper-

ation and business strategies should follow the objective law of transport and logistics so that

the cost of STBT could be reduced and transferred to marketization rather than under image

projects.

4.2 Current Situation of Cross-border Road cargo Transport

　　TIR Convention provides a new choice and strategic solution for Eurasian inland trans-


port since 2016. Road transport shared a higher ratio than air transport in terms of monetary

amount during the past 12 years and kept increasing in recent years with no support like

SEBT. With the successful pilot TIR transport, most cargoes with average lead time, and the

goods delivered by SEBT, could be transported to CBR.

　　Before joining TIR Convention, China’s CBR developed slowly, and the cargoes could only

deliver to boundary due to the domestic logistics companies were restricted by the limitation

of cross-border qualification and assigned routes. However, road transport has advantages and

flexibility in door-to-door service of general, cold chain, and oversized goods than the railway.

TIR provides more chances for China’s companies. These companies had excellent perfor-

mance in the successful pilot transport and promoted the negotiation of the new cross-border

agreement between China and other countries, which demonstrates the prosperous future of

the field.

　　CBR has the potential of development in terms of flexible service and connectivity of in-

frastructure （no restriction of railway gauge）; besides, the analysis on trade facilitation and

operational risk indicates the condition of Central Asian partners will not impact CBR. It is

necessary to point out that CBR’s development will not impact on SETB and SATB negative-

ly. CBR will focus on the cargoes with the requirement of flexible service such as door-to-door

or cold chain goods, yet the railway could aim at the bulk cargoes with extended lead time.

Therefore, CBR will not only reduce BRI’s logistics cost but also helps the development of

“The Silk Road Economic Belt.”

5. Conclusion

　　This study examines SEBT’s current situation and CBR’s development and discusses the

suitable international inland transport pattern for China. According to the results, this study

answers the research questions as follows:

　　1） SEBT has been enjoying a booming increase over the past three years, and the ten-

dency lasts in 2019 as well. Nevertheless, SEBT’s operation still relays on high freight subsidy,

and delivering low added value cargoes is the long-term discussing issue. The international

trade was not promoted by SEBT’s operating; besides, the cargoes accounted by price via rail-

way did not increase as well. Considering the view of cost-efficiency and lead time of logistics,

SEBT is not the most suitable pattern for BRI’s inland transport obviously, yet SEBT has

been the symbol for the local image project already. The situation will increase China’s social

logistics cost and negatively impact on the further development of BRI’s inland transport.

Thus, it is necessary to find more solutions to realize the cost-efficiency law of BRI’s inland

『明大商学論叢』第 102 巻第 2 号18 （ 86 ）

transport. TIR Convention now provides a new way of reducing the gross cost for the govern-

ment and enterprise;

　　2） China’s CBR develops rapidly since joining in TIR Convention, and the domestic and

foreign logistics companies operated pilot transport in different seasons and circumstances

from 2016 to 2018 . The pilots promoted international road cooperation between the nations.

Compared with railway transport, road cargo transport could avoid the negative factors or

risks of trade and operation. Though the trade facilitation and operational condition in Central

Asia and East Europe are not as good as other regions, road transport could operate the busi-

ness in the region with the least risk. For the foreseeable future, CBR will become a crucial lo-

gistics pattern for BRI’s inland trade for the advantages in flexible door-to-door service, cold

chain goods, and oversized cargoes. Railway and road transport could complement for differ-

ent needs each other then.

　　This study is the first to conclude Eurasian railway, road cargo transports, trade facilita-

tion, and operational risk together. The results could provide both researchers and policymak-

ers with a better understanding of BRI’s inland transport reference. However, this research

could not cover the possible issues of the field due to the constraints in the authors’ knowl-

edge and materials. Further research could be extended this content to the economical trans-

port distance for SEBT to find the proper range.

Reference

［ 1 ］　榎本俊一．2017．中国の一帯一路構想は「相互繁栄」をもたらす新世界秩序か？ポリシー・ディスカッション・ペーパー，pp. 17-P-021

［ 2 ］　畢国通．2017．「一帯一路」戦略下中欧班列発展的現状与対策（中国語）．中国市場．（22）：pp. 121-122.

［ 3 ］　王姣娥，景悦，王成金．2017．「中欧班列」運輸組織策略研究（中国語）．中国科学院院刊，32（04）：pp. 370-376．

［ 4 ］　馮其云，常海青，刘斌．2018．「一帯一路」視域下中欧班列発展模式探索（中国語）．中国国情国力，（05）：pp. 34-37．

［ 5 ］　Feng, H., Prozzi, J.P., & Prozzi, J.A. 2007. Characterizing Truck Traffic in the U.S.-Mexico Highway Trade Corridor and the Load Associated Pavement Damage. Research Report , No. SWUTC/07/167555-1, Southwest Region University Transportation Center, Center for Transportation Research, University of Texas at Austin

［ 6 ］　Rogers, L. （2011）. The Cascade Gateway―cross-border flows and systems. （A Study for Transport Canada, Translink, & BC Ministry of Transportation & Infrastructure）.

［ 7 ］　Rodrigue, J., Comtois, C., Slack, B. （2016）. The Geography of Transport Systems 4th Edition. Oxford, UK: Routledge.

［ 8 ］　Abdi, H., Williams, L.J., 2010 . Principal component analysis. Wiley Interdisciplinary Reviews:


Computational Statistics 2（4）, pp. 387-515.［ 9 ］　Saporta, G., Niang, N., 2009. Principal component analysis: application to statistical process control.

Data Analysis, ISTE, London, UK, pp. 1-23.［10］　Wilson, J.S., Mann, C.L., Otsuki, T., 2003 . Trade facilitation and economic development. World

Bank Economic Review 17（3）, pp. 367-389.［11］　大西康雄．2018．「一帯一路」構想の展開と日本への示唆，経営センサー，7，pp. 21-25

『明大商学論叢』第 102 巻第 2 号20 （ 88 ）

Appendix 1Indicators of Trade Facilitation Index

Primary Indicator Secondary Indicator MarkForecasted

Impact

Government Regulatory （R）

Intellectual property protection R1 ＋Judicial independence R2 ＋Efficiency of legal framework in settling disputes R3 ＋Efficiency of legal framework in challenging regs R4 ＋Transparency of government policymaking R5 ＋CPI R6 ＋

Logistics Condition （L）

Quality of overall infrastructure L1 ＋Quality of roads L2 ＋Quality of railroad infrastructure L3 ＋Quality of port infrastructure L4 ＋Quality of air transport infrastructure L5 ＋

Customs Situation （C）Prevalence of non-tariff barriers C1 ＋Trade tariffs % C2 －Burden of customs procedures C3 －

Business Environment （B）

Irregular payments and bribes B1 －Business costs of terrorism B2 －Business costs of crime and violence B3 －Intensity of local competition B4 －No. of procedures to start a business B5 －Time to start a business B6 －Prevalence of foreign ownership B7 ＋Business impact of rules on FDI B8 ＋

Marketing Condition （M）

Extent of market dominance M1 ＋Effect of taxation on incentives to invest M2 ＋Total tax rate M3 ＋Degree of customer orientation M4 ＋Buyer sophistication M5 ＋Domestic market size index M6 ＋Foreign market size index M7 ＋

Financial Level （F）

Financial services meeting business needs F1 ＋Affordability of financial services F2 ＋Financing through local equity market F3 ＋Ease of access to loans F4 ＋Venture capital availability F5 ＋Soundness of banks F6 ＋Regulation of securities exchanges F7 ＋Legal rights index F8 ＋


Total Variance Explained （TFI）

ComponentInitial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 16.363 44.224 44.224 16.363 44.224 44.2242 4.348 11.750 55.974 4.348 11.750 55.9743 3.202 8.655 64.629 3.202 8.655 64.6294 2.703 7.306 71.934 2.703 7.306 71.9345 1.592 4.304 76.238 1.592 4.304 76.2386 1.109 2.998 79.236 1.109 2.998 79.2367 .934 2.523 81.7598 .788 2.131 83.8909 .747 2.019 85.90910 .637 1.722 87.63211 .500 1.352 88.98412 .491 1.328 90.31213 .412 1.112 91.42414 .389 1.053 92.47715 .340 .920 93.39716 .316 .854 94.25117 .272 .736 94.98718 .231 .624 95.61119 .210 .567 96.17820 .200 .540 96.71821 .185 .501 97.21922 .155 .420 97.63823 .142 .384 98.02324 .128 .345 98.36825 .124 .335 98.70226 .096 .259 98.96227 .076 .206 99.16828 .069 .187 99.35529 .067 .180 99.53630 .048 .129 99.66531 .041 .110 99.77632 .026 .071 99.84633 .021 .058 99.90434 .014 .037 99.94135 .011 .029 99.97036 .007 .018 99.98837 .004 .012 100.000

Extraction Method: Principal Component Analysis.

『明大商学論叢』第 102 巻第 2 号22 （ 90 ）

Component Matrix （TFI）

Component

1 2 3 4 5 6

IPP .476 －.767 .221 .327 －.030 .051JI .537 －.715 .287 .289 －.046 .001ELS .492 －.748 .366 .217 －.019 －.030ELC .637 －.638 .357 .161 －.013 －.021TGP .389 －.846 .222 .222 .006 .009CPI .657 －.222 －.139 .135 .068 －.015QOI .866 .164 －.245 .129 －.176 .032QR .814 .190 －.119 .064 －.295 .045QRI .434 .188 －.170 .634 .329 －.139QPI .827 .257 －.142 .040 －.183 －.027QAI .861 .200 －.075 .040 －.113 －.098PNB .754 －.095 －.333 －.237 －.018 .067TT －.468 .126 .567 －.060 －.176 －.325BCP .675 －.065 －.345 －.152 －.099 .078IPB .909 －.046 －.226 －.035 －.111 －.058BCT .477 －.333 －.540 －.021 －.066 .240BCV .644 －.207 －.435 －.119 －.269 .167ILC .751 .268 .058 .213 .010 .181PSB －.216 .261 .616 .047 －.065 .518TSB －.254 .206 .505 －.057 .227 .610PFO .820 －.016 －.115 －.003 .400 .125BIR .769 －.006 －.055 －.221 .283 .017EMD .800 .293 －.002 .198 －.022 .062ETI .554 －.144 .292 －.622 －.152 .042TTR －.122 .319 －.063 .642 .251 －.155DCO .836 .231 －.023 .105 .001 .011BS .796 .171 .210 .081 －.084 －.046DMS .256 .530 .329 .568 －.077 －.003FMS .299 .346 －.067 .457 －.334 .213FSB .916 .193 .115 －.066 .173 .013AFS .933 .160 .148 －.118 .081 .011FLM .766 .219 .455 －.003 .044 －.158EAL .768 .130 .229 －.378 .099 －.098VCA .781 .169 .309 －.304 .059 －.024SB .670 .145 .276 －.299 .192 －.148RSE .734 .239 .275 －.117 .044 －.191LR .091 －.133 －.295 －.046 .764 .080

Extraction Method: Principal Component Analysis.7 components extracted.


The function of TFI:

TFI＝ 0.0194R1＋0.0226R2＋0.0204R3＋0.0277R4＋0.0144R5＋0.0293R6＋0.0409L1＋0.0388L2＋

0.0233L3＋0.0398L4＋0.0413L5＋0.0327C1－0.0195C2＋0.0293C3＋0.0411B1＋0.0180B2＋

0.0264B3＋0.0381B4－0.0054B5－0.0079B6＋0.0386B7＋0.0355B8＋0.0401M1＋0.0241M2－

0.0016M3＋0.0410M4＋0.0394M5＋0.0185M6＋0.0171M7＋0.0448F1＋0.0452F2＋0.0391F3＋

0.0367F4＋0.0381F5＋0.0327F6＋0.0366F7＋0.0032F8

『明大商学論叢』第 102 巻第 2 号24 （ 92 ）

Appendix 2Indicators of Operational Risk Index

Primary Indicator Secondary Indicator MarkForecasted

Impact

Government Management （G）

Property rights G1 ＋Public trust in politicians G2 ＋Judicial independence G3 ＋Favoritism in decisions of government officials G4 ＋Burden of government regulation G5 －Organized crime G6 －Reliability of police services G7 ＋

Enterprise Condition （E）

Ethical behavior of firms E1 ＋Strength of auditing and reporting standards E2 ＋Efficacy of corporate boards E3 ＋Protection of minority shareholders’ interests E4 ＋Strength of investor protection E5 ＋

Sanitation Situation （H）Tuberculosis incidence H1 －Business impact of tuberculosis H2 －Business impact of HIV/AIDS H3 －

Education Level （Et）

Quality of primary education ET1 ＋Primary education enrollment rate ET2 ＋Secondary education enrollment rate ET3 ＋Tertiary education enrollment rate ET4 ＋Quality of the education system ET5 ＋Quality of math and science education ET6 ＋Quality of management schools ET7 ＋Internet access in schools ET8 ＋Local availability of specialized training services ET9 ＋Extent of staff training ET10 ＋

Labor Force Condition （L）

Cooperation in labor-employer relations L1 ＋Flexibility of wage determination L2 ＋Hiring and firing practices L3 ＋Redundancy costs L4 ＋Effect of taxation on incentives to work L5 ＋Pay and productivity L6 ＋Reliance on professional management L7 ＋Country capacity to retain talent L8 ＋Country capacity to attract talent L9 ＋

Technology Level （T）

Availability of latest technologies T1 ＋Firm-level technology absorption T2 ＋FDI and technology transfer T3 ＋Internet users T4 ＋Internet bandwidth T5 ＋

Innovative Level （I）

Capacity for innovation I1 ＋Quality of scientific research institutions I2 ＋Company spending on R & D I3 ＋University-industry collaboration in R & D I4 ＋Gov’t procurement of advanced tech. products I5 ＋Availability of scientists and engineers I6 ＋


Total Variance Explained （ORI）

ComponentInitial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %1 24.328 55.291 55.291 24.328 55.291 55.2912 4.681 10.638 65.929 4.681 10.638 65.9293 2.805 6.375 72.305 2.805 6.375 72.3054 1.685 3.830 76.134 1.685 3.830 76.1345 1.431 3.252 79.386 1.431 3.252 79.3866 1.169 2.658 82.044 1.169 2.658 82.0447 1.069 2.430 84.474 1.069 2.430 84.4748 .844 1.918 86.3929 .763 1.735 88.12610 .670 1.524 89.65011 .572 1.300 90.95012 .526 1.195 92.14513 .484 1.100 93.24414 .386 .877 94.12115 .325 .739 94.86016 .301 .684 95.54417 .275 .624 96.16818 .258 .586 96.75519 .195 .444 97.19920 .158 .358 97.55721 .134 .305 97.86222 .120 .273 98.13423 .114 .259 98.39324 .104 .236 98.62925 .088 .201 98.83026 .074 .168 98.99827 .065 .147 99.14528 .060 .137 99.28229 .052 .119 99.40030 .042 .096 99.49631 .037 .085 99.58132 .032 .072 99.65333 .029 .065 99.71834 .021 .047 99.76535 .019 .043 99.80836 .017 .038 99.84637 .014 .032 99.87838 .013 .029 99.90739 .010 .023 99.93140 .008 .019 99.95041 .008 .018 99.96742 .007 .015 99.98343 .004 .009 99.99244 .004 .008 100.000

Extraction Method: Principal Component Analysis.

『明大商学論叢』第 102 巻第 2 号26 （ 94 ）

Component Matrix （ORI）

Component1 2 3 4 5 6 7

PR .939 .043 －.102 －.193 .053 .019 －.048PTP .824 .339 .161 －.239 －.014 .044 －.171JI .906 .065 －.157 －.190 .035 .075 －.055FDG .884 .249 .109 －.173 －.040 .072 －.180BGR .572 .648 .315 －.060 .043 .087 －.159OC .781 －.047 .314 －.288 .086 －.018 －.006RPS .901 －.108 .127 －.221 .002 .056 －.100EBF .953 .086 .009 －.174 .074 .010 －.116SAR .898 .023 －.179 －.124 .178 －.080 .052ECB .892 .112 －.187 －.040 .204 －.102 .063PMS .868 .229 －.208 －.196 .106 .037 －.058SIP .278 .033 －.021 .339 .563 .301 .056TI －.324 .461 －.644 .081 .363 －.076 .016BIT .599 －.627 .278 －.229 －.142 .060 .032BIH .481 －.625 .423 －.219 －.088 .082 .065QPE .402 －.241 .155 .245 －.039 －.532 －.178PEE .517 －.352 .011 －.026 .017 .491 .127SEE .639 －.532 .105 －.051 .256 .117 .118TEE .387 －.757 .133 .248 .175 .132 －.050QES .856 .115 .071 .185 －.217 －.097 －.240QMS .697 －.237 .220 .326 －.223 －.170 －.203QM .819 －.107 －.256 .153 －.088 －.054 －.116IAS .827 －.190 .186 .181 .115 －.109 .151LAS .914 －.149 －.186 .144 －.064 －.124 －.041EST .931 .161 －.138 .054 .057 －.123 .035CLR .808 .217 .269 －.069 －.025 .009 －.068FWD －.088 .311 .700 .247 .123 －.101 .302HFP .095 .485 .498 .253 .031 .238 －.003RC －.257 .251 －.228 .071 －.570 .228 .399ETI .422 .729 .256 －.157 .044 .028 －.001PAP .574 .397 .411 .412 .041 －.131 .171RPM .941 .073 －.173 .028 .132 －.023 .038CRT .874 .357 －.108 －.039 －.102 .052 －.060ALT .927 －.173 －.139 －.004 .021 .024 .141FTA .929 .016 －.148 .029 －.001 .060 .159FTT .763 .161 .006 .127 .050 －.021 .345IU .787 －.414 .187 －.094 .103 －.123 .114IB .265 .067 －.004 －.450 －.118 －.384 .480CI .895 －.051 －.258 .174 －.105 －.005 .060QSR .868 －.200 －.237 .197 －.057 .003 .089CSR .889 .019 －.259 .160 －.149 .015 .054UCR .914 .002 －.242 .183 －.051 －.016 .041GPA .724 .489 .086 .025 －.214 .124 .081ASE .724 －.110 －.081 .216 －.374 .239 －.113

Extraction Method: Principal Component Analysis.7 components extracted.


The function of ORI:

ORI＝ 0.0330G1＋0.0226G2＋0.0204G3＋0.0277G4＋0.0144G5＋0.0293G6＋0.0293G7＋0.0409E1＋

0.0388E2＋0.0233E3＋0.0398E4＋0.0413E5＋0.0327H1－0.0195H2＋0.0293H3＋0.0411ET1＋

0.0180ET2＋0.0264ET3＋0.0381ET4－0.0054ET5－0.0079ET6＋0.0386ET7＋0.0355ET8＋

0.0355ET9＋0.0355ET10＋0.0401L1＋0.0241L2－0.0016L3＋0.0410L4＋0.0394L5＋0.0185L6＋

0.0171L7＋0.0171L8＋0.0171L9＋0.0448T1＋0.0452T2＋0.0391T3＋0.0367T4＋0.0381T5＋

0.0327I1＋0.0366I2＋0.0032I3＋0.0032I4＋0.0032I5＋0.0032I6

『明大商学論叢』第 102 巻第 2 号28 （ 96 ）

Analyzing China's Inland Transport Development Title URL

Documents