Competition Model with Development
Policies for Emerging Ports：Case
Study of the Mainland of China
Bao-Hua MAO ([email protected])
Prof. Ph.D, Beijing Jiaotong University, Beijing, China
Peng DU ([email protected])
Ph.D, Beijing Jiaotong University, Beijing, China
Yu-Ting ZHU ([email protected])
Ph.D Candidate, Beijing Jiaotong University, Beijing, China
Qi XU ([email protected])
Ph.D Candidate, Beijing Jiaotong University, Beijing, China
Presented at The 3rd Annual International Workshop on Port Economics and Policy, Singapore, December 9, 2013
Outline
‡
Introduction
‡
Analysis of Factors
‡
Competition Model
‡
Case Study
‡
Conclusions
1 Introduction
Current status of ports in mainland China
‡
112 primary ports
‡
Five port clusters
The Bohai Bay port cluster
The Yangtze River Delta port cluster
The southeastern coastal port cluster
The Pearl River Delta port cluster
The southwestern coastal port cluster
1 Introduction
Cargo throughput of coastal ports in China (billion tons)
8
6.88
7
6.36
5.64
6
5
4.49
4.87
4
3
2
1
0
2008
2009
2010
2011
2012
Source: Statistical communique of the People's Republic of China on the 2012 national road and
waterway transportation development
1 Introduction
Top 10 container terminals in world (million TEUs)
No.
PORT
COUNTRY
2012
2011
2010
1
Shanghai
China
32.53
31.74
29.07
2
Singapore
Singapore
31.65
29.94
28.43
3
Hong Kong
China
23.11
24.22
23.70
4
Shenzhen
China
22.94
22.57
22.51
5
Pusan
Korea
17.04
16.19
14.19
6
Zhoushan
China
16.83
14.69
13.14
7
Guangzhou
China
14.74
14.40
12.55
8
Qingdao
China
14.50
13.02
12.01
9
Dubai
UAE
13.28
13.00
11.60
10
Tianjin
China
12.30
11.50
10.08
Source: UNCTAD, review of maritime transport, report 2012
1 Introduction
In order to stimulate regional economy, a series of preferential
policies have been launched by local governments in coastal area to
support port construction.
528.5
370.0
201.1
140.8
0.8
3.2
5.6
11.7
26.2
41.6
1949-1972 1973-1980 1981-1985 1986-1990 1991-1995 1996-2000 2001-2005 2006-2010 2011-2012
The infrastructure investment in coastal ports, 1949-2012 (billion RMB)
1 Introduction
Are there any problems hidden by the prosperous picture ?
1 Introduction
‡
In 2006, in order to regulate the development of ports, Chinese
central government issued Allocation Plan of China’s Coastal
Ports
‡
However, the plan seems not to be strictly followed.
‡
A great number of the small and medium-sized ports have
overestimated their competitiveness, and are planning to become
internationally large-scale ports in spite of their congenital
deficiencies.
1 Introduction
How the problem come into being?
Confusion in Development Strategy
Overlapping Functions
Low-level Repeated Construction
Imbalanced utilization among ports
1 Introduction
Ports in the Bohai Bay Area
‡
Main port
Regional port
12 ports.
‡
A
di
t
k
Average
distance:
127 km.
‡
Shortest distance: 20 km.
‡
Most of them transport the same
kind of goods -- large bulk cargo
and container.
1 Introduction
Capacity Utilization in 2011
300%
Capacity
nn
Capacityutilization
utilization
250%
200%
150%
100%
50%
0%
0
5
10
15
20
25
Container throughput(million TEUs)
30
35
1 Introduction
Capacity Utilization in 2011 (ports below 1 million)
300%
Capacity
tion
Capacityutilizat
utilizaation
250%
200%
150%
100%
50%
0%
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
Container throughput(million TEUs)
0.80
0.90
1.00
1 Introduction
Capacity Utilization in different port groups
‡
‡
More than 50% of small and medium-sized ports have low
rates.
Most of the large-sized ports (with more than 500 million
TEUs of throughout) have high rates.
‡
Small-sized ports:
beyond the requirements
‡
Large-sized ports:
behind the requirement
1 Introduction
9 Why shippers would rather choose large ports, which are overused, than small or medium-sized ports, which have abundant
capacity?
9 What are the main factors in determining port competitiveness?
9 How much competitiveness can an emerging port get?
9 What strategies it can take to increase its competitiveness?
9 And what kind of port it is expected to be in the future?
Can an emerging port realize
its dream of mega
g int’l p
port?
2 Analysis of Factors
Port hinterland (also known as port market area) is a performance
indicator to gauge the competitiveness of a port.
Factors for port hinterland selection
‡
Service frequency
‡
Inspection & Quarantine, Customs
‡
Land-side transportation
‡
Port efficiency
2 Analysis of Factors
Service frequency
‡
Ship service frequency
‡
Waitingg time
2 Analysis of Factors
Inspection & Quarantine, Customs
‡
Customs regulations and procedure
‡
Procedure of commodityy inspection
p
and q
quarantine
‡
Time
‡
Cost and tariff
2 Analysis of Factors
Land-side transportation
‡
Location and natural conditions
‡
Inland transportation
p
network availabilityy and accessibilityy
‡
Distance or time
‡
Cost between ports and hinterland
2 Analysis of Factors
Port efficiency
‡
Handling efficiency
‡
Transshipment
p
efficiencyy
‡
Port cost
2 Analysis of Factors
3 Competition Model
Problem description
P1
Hinterland
H1
P2
Hinterland
H2
Overlapping area
3 Competition Model
Typical Land-side Operational Procedures in mainland China
Simple procedure
Booking ship
space
Transit in
land-side
Inspection and
Quarantine
（IQ）
Port
customs
Handling
process
Local IQ
Booking ship
space
IQ
Transit in
land-side
Port
customs
Handling
process
Port
customs
Handling
process
Local customs
Booking ship
space
IQ
Local
customs
Transit in
land-side
IQ
Local
customs
Transit in
land-side
Dry port
Booking ship
space
Handling
process
Note: IQ stands for Inspection and Quarantine
3 Competition Model
We assume that:
9 All shippers will choose the procedure of Local customs;
9 The procedure of Dry port is a special case of the Local customs.
Local customs
Booking ship
space
IQ
Local
customs
Transit in
land-side
Booking shipp
space
IQ
Local
customs
Transit in
land-side
Port
customs
Handling
process
Dry port
difference
Handling
process
Note: IQ stands for Inspection and Quarantine
3 Competition Model
Generalized cost of land-side part in Wang(2010, 2011)
‡ terminal
• transshipment cost
• transfer time
‡ transportation
• time
• cost
Ending time
Terminal
Handling process
transportation
Starting time
transportation
Destination area
Origin area
(Port)
(Freight yard)
• XINCHANG W. Port Hinterland Estimation and Optimization for Intermodal Freight Transportation Networks[D]. 2010.
• Wang X, Meng Q. The impact of land bridge on the market shares of Asian ports[J]. Transportation Research Part E, 2011, 47(2): 190-203.
3 Competition Model
More considerations on land-side procedure
Ending time
Ending time
Handling process
Handling process
customs transferring
Starting time
Applying to the customs
Applying to IQ
Waiting at freight yard
Booking ship space
(Starting time)
transportation
Origin area
Destination area
(Freight yard)
(Port)
transportation
Destination area
Origin area
(Port)
(Freight yard)
3 Competition Model
Time and cost analyses of Land-side Procedure
Generalized Cost for waiting a ship ( cw )
Ending time
‡ Cost: booking shipping space (Fw )
Handling process
‡ Time: waiting for a ship (Tw )
customs transferring
cw = α ⋅ Tw + Fw
Applying to the customs
where, α is the VOT perceived by the intermodal operator.
Applying to CIQ
Waiting at freight yard
Booking shipping space
(Starting time)
Tw , Fw
transportation
Origin area
(Freight yard)
Destination area
(Port)
3 Competition Model
Time and cost analyses of Land-side Procedure
Generalized Cost for customs clearance ( ccu )
Ending time
Handling process
T'cu , F'cu
‡ Commodity inspection and customs
d l i (T
declaration
( cu andd Fcu )
‡ Customs transferring (T'cu and F'cu )
customs transferring
ccu = α ⋅ (Tcu + Tcu′ ) + ( Fcu + Fcu′ )
Applying to the customs
Tcu , Fcu
Applying to IQ
Waiting at freight yard
Booking shipping space
(Starting time)
transportation
Origin area
(Freight yard)
Destination area
(Port)
where, α is the VOT perceived by the intermodal operator.
3 Competition Model
Time and cost analyses of Land-side Procedure
Generalized cost for land-side transportation ( ctr )
‡
transit cost (Ftr )
9
Ending time
Handling process
‡
customs transferring
Land-side transportation
Ftr ,Ttr
Applying to the customs
Applying to CIQ
transit cost of different mode (fm)
transit time (Ttr)
9
in-vehicle travel time ttrm
9
transfer time
ttrs
ctr = α ⋅ Ttr + Ftr = α ⋅ (∑ ttrm + ∑ ttrs )+∑ f m
m
s
m
Waiting at freight yard
where, m is the transportation mode, s is transfer node.
Booking shipping space
(Starting time)
transportation
Origin area
(Freight yard)
Destination area
(Port)
3 Competition Model
Time and cost analyses of Land-side Procedure
Generalized cost for handling( ch )
Ending time
Handling process
Fh ,,Th
‡ handling time(Th )
‡ transshipment cost (Fh )
customs transferring
ch = α ⋅ Th + Fh
Apply to the customs
where, α is the VOT perceived by the intermodal operator
Applying to CIQ
Waiting at freight yard
Booking shipping space
(Starting time)
transportation
Origin area
(Freight yard)
Destination area
(Port)
3 Competition Model
Time and cost analyses of Land-side Procedure
• the generalized cost of the
Ending time
Handling process
whole land-side pprocedure
ch
customs transferring
ci = cwi + chi + ccui + ctri
ccu
Apply to the customs
Applying to IQ
Waiting at freight yard
Booking shipping space
(Starting time)
cw
transportation
Origin area
(Freight yard)
Destination area
(Port)
3 Competition Model
• The market share of port i in hinterland H can be
approximated by the probability of the port being
selected by shippers in this area from available port
set S.
se
• Thus, the market share can be formed as follow:
MS Hi =PSi = Pr ( ci ≤ c j , ∀j ∈ S and i ≠ j )
3 Competition Model
Utility (Ui): Deterministic and Random Utility Components
U i = Vi + ε i
= − ci + ε i
Random Component
Independently and
Identically Distributed (IID)
Gumbel
Deterministic Component
Actual generalized cost
ci = cwi + chi + ccui + ctri
P =
i
S
exp ( −ci )
∑ exp ( −c )
i
S
4 Case Study
Putian Port -- an emerging port
‡ Location:
southeastern coast of China
‡ Current
C
t hi
hinterland:
t l d
Fujian Province
‡ Throughput:
1.6 million TEU
‡ Land-side transportation mode:
highway
4 Case Study
A high speed railway -Xiangpu Railway -- will
connect Nanchang, capital of
Jiangxi Province,
Province and Putian
Port, shortening the travel time
in half.
4 Case Study
31.7
14.7
Export ports for Jiangxi
Province
• The existing ports
1.7
1.6
6.5
9 Shanghai Port
9 Ningbo Port
9 Xiamen Port
9 Shenzhen Port
9 Fuzhou Port
• The emerging port
22.6
9 Putian Port
Container Throughput
(million TEUs)
4 Case Study
‡ How much market share can Putian Port get now?
‡ Can the railwayy helpp Putian Port realize
z its dream off mega
g pport?
‡ Which strategies can benefit the increase of its market share?
4 Case Study
Port competitive model:
ci = cwi + chi + ccui + ctri
MS Hi =PSi = Pr ( ci ≤ c j , ∀j ∈ S and i ≠ j )
MS =P =
i
H
i
S
exp ( −ci )
∑ exp ( −c )
i
S
4 Case Study
Performance of ports -- Service frequency
Service Frequency
7
Without loss of generosity, we take
ships to Rotterdam as an example to
identify the difference of service
frequency among these ports.
The number of ship Ns is counted
from 10/24/2013 to 12/25/2013 (63
days).
Ships / week
5.89
6
5
4.00
4
3
2.89
2.89
2.00
2
Weekly service frequency:
f = Ns / 63*7
1
0.44
0
Xiamen
Ningbo
Shanghai
Shenzheng
Fuzhou
Putian
4 Case Study
Performance of ports -- Port efficiency
Port Efficiency
3000
The annual container handing
capacity CAPh (TEU/year) of ports
comes from CHINA PORTS YEAR
BOOK(2012).
Port efficiency (TEU/hour):
e= CAPh /365/24
TEU/hour
2,705
2500
2,285
2000
1500
1,100
1,161
1000
500
276
141
0
Xiamen
Ningbo
Shanghai Shenzheng
Fuzhou
Putian
4 Case Study
Performance of ports -- Transshipment cost in Ports
Transshipment cost in Ports
Miscellaneous fees will be charged at
port along with transshipment. Here,
we take a lump sum cost per unit
based on data available.
USD/TEU
250
237
206
231
192
200
201
201
150
Source: Regulations on Collection of Port Charges of
the People's Republic of China (Domestic Trade Part)
http://www.gdcd.gov.cn/gfzj/20080826181024477_1.s
html
100
50
0
Xiamen
Ningbo
Shanghai Shenzheng Fuzhou
Putian
4 Case Study
Commodity inspection and customs declaration
Ports
Dry port in
Jiangxi
Commodity inspection and customs
declaration in Jiangxi Province
Customs transferring
Time / days
cost/ USD
Time / day
cost / USD
-
-
2
3
114
117
Xiamen
O
3
41
Ningbo
O
3
41
Shanghai
O
3
41
Shenzhen
O
Fuzhou
Putian
X
X
3
3
3
41
41
41
Note: O indicates a dry port; X indicates not having dry port;
Source: PENAVICO FUZHOU E-COM MERCE PORTAL http://www.penavicofz.com/e_commerceui/index.aspx
EAI http://www.eaifreight.com/list.asp?class=683&oneid=11
4 Case Study
Transportation
-- time and cost for railway
The cost for Chinese railway are calculated by data from the former Ministry of
Railways’ website (http://www.12306.cn/mormhweb/hyfw/).
Railway
y transportation
p
time t1 ((day)
y)
t1 = l / (33.2 × 24)
Where l demotes travel distance.
4 Case Study
Transportation
-- time and cost for highway
The cost c2 (USD) and time t2 (day) of transporting one TEU by Chinese highways:
c2 = 5.5 × 0.146l = 0.803l
t2 = 0.0015l
Where l demotes travel distance.
Relevant Sources: Wang X, Meng Q. (2011)
4 Case Study
Transportation
Ports
main transit mode
Distance/km
Time/days
cost/USD
Time/days
cost/USD
Xiamen
946
1.19
527.98
-
-
Ningbo
813
1.02
466.83
-
-
880
1 10
1.10
538 17
538.17
0 04
0.04
41 01
41.01
Shenzhen
946
1.19
645.37
0.04
53.32
Fuzhou
642
0.81
426.66
0.04
41.01
681
1.02
820.35
-
-
Sh h i
Shanghai
Putian
mode
Auxiliary transportation*
R il
Railway
Highway
9 In Xiamen port, Ningbo port and Fuzhou port, railway can reach ports directly or
just outside the port.
9 While, in Shanghai port and Shenzhen port, cargos cannot reach ports only by
railway, thus an auxiliary transportation (Port Transportation Services by trailers are
available.
4 Case Study
Summary of parameters
Port
Ports
Waiting time Handling time
days
days
cost
USD
Commodity inspection and
customs declaration
Time
cost
days
USD
Transportation
Time
days
cost
USD
Xiamen
1.21
0.31
205
3
41
1.19
527.98
Ningbo
1.21
0.29
236
3
41
1.02
466.83
Shanghai
0.88
0.15
231
3
41
1.14
538.17
Shenzhen
0.59
0.13
192
3
41
1.23
645.37
Fuzhou
1.75
1.42
200
5
155
0.85
426.66
Putian
7.88
2.42
200
6
158
1.02
820.35
Note: VOT=3USD/ TEU
4 Case Study
Benchmark -- market share of Putian Port
25%
20%
19.3%
9 Xiamen Port and Ningbo Port have a
strong competitiveness, the market
share
h off th
them are higher
hi h than
th 19%.
19%
19.9%
18.8%
18.0%
market share
15 9%
15.9%
15%
10%
8.2%
5%
0%
Xiamen
Port
Ningbo
Port
Shanghai Shenzheng Fuzhou
Port
Port
Port
Putian
Port
9 Putian Port have the weakest
competitiveness, the market share of
it is only 8.2%.
4 Case Study
• Scenario I – Improving land-side transportation system
• Scenario II – Improving the customs efficiency
• Scenario III – Improving the port operations
4 Case Study
Scenario I -- Improving land-side transportation system
with / without Xiangpu Railway
Ports influenced by Xiangpu Railway
‡
Fuzhou Port
‡
Putian Port
Ports
without Xiangpu Railway
time/days
cost/USD
Xiamen
1.19
Ningbo
1.02
Shanghai
1.14
Shenzhen
1.23
Fuzhou
0.85
Putian
1.02
527.98
466.83
538.17
645.37
426.66
820.35
with Xiangpu Railway
time/days
cost/USD
1.19
1.02
1.14
1.23
0.42
0.41
527.98
466.83
538.17
645.37
419.49
418.42
4 Case Study
Scenario I -- Improving land-side transportation system
100%
8.2%
MS Hi =PSi =
exp ( −ci )
15.9%
80%
∑ exp ( −c )
i
70%
ctr = α ⋅ Ttr + Ftr
Have a reduce on Ftr and Ttr
Market share
S
ci = cwi + chi + cci u + ctir
10.3%
90%
15.9%
17.4%
18.8%
Ningbo Port
Xiamen Port
19.9%
19.4%
19.3%
18.8%
without Xiangpu
Railway
with Xiangpu
Railway
20%
10%
Shanghai Port
18.2%
40%
30%
Fuzhou Port
Shenzheng Port
18.0%
60%
50%
Putian Port
0%
4 Case Study
Scenario I -- Improving land-side transportation system
100%
8.2%
The market share of Putian Port
increases from 8.2% to 10.3%.
15.9%
80%
70%
Market share
Railway, with the advantage of
ow ttransit
a s t cost, ca
can improve
p ove tthee
low
competiveness of the connected
ports.
10.3%
90%
15.9%
18.0%
17.4%
18.2%
Xiamen Port
19.9%
19.4%
19.3%
18.8%
without Xiangpu
Railway
with Xiangpu
Railway
20%
10%
Shanghai Port
Ningbo Port
18.8%
40%
30%
Fuzhou Port
Shenzheng Port
60%
50%
Putian Port
0%
4 Case Study
Scenario II -- Improving the customs efficiency
Ports
whether have dry
port in Jiangxi
Xiamen
Ningbo
Shanghai
Shenzhen
Fuzhou
Putian
O
O
O
O
X
X
MS Hi =PSi =
exp ( −ci )
∑ exp ( −c )
i
S
ci = cwi + chi + cci u + ctir
ccu = α ⋅ (Tcu + Tcu′ ) + ( Fcu + Fcu′ )
Note: O indicates have a dry port;
X indicates do not have a dry port;
Have a reduce on Tcu′ and Fcu′
•
Case I -- without dry port for Fuzhou Port and Putian Port
•
Case II -- dry port for Fuzhou Port
•
Case III -- dry port for Putian Port
•
Case IV -- dry port for Fuzhou Port and Putian Port
4 Case Study
Scenario II -- Improving the customs efficiency
Ports
Fuzhou
Putian
Case I
X
X
Case II
O
X
Case III
X
O
Case IV
O
O
Note: O indicates have a dry port;
X indicates do not have a dry port;
Xiamen Port
Ningbo Port
Shanghai Port
Shenzheng Port
Fuzhou Port
Putian Port
100%
90%
80%
10.0%
12.6%
12.3%
15.9%
18.7%
15.4%
18.4%
17.4%
16.9%
16.9%
16.0%
18.2%
17.8%
17.8%
18.0%
19.4%
18.8%
18.9%
17.9%
18.8%
17.8%
18.3%
17.4%
Case I
Case II
Case III
Case IV
70%
Market share
Dry port operation can help
Putian Port to increase the
market share in Jiangxi
Province.
10.3%
60%
50%
40%
30%
20%
10%
0%
4 Case Study
Scenario III -- Improving operations of Putian port
Case 1: change of the port efficiency
MS Hi =PSi =
Xiamen Port
Shanghai Port
Fuzhou Port
exp ( −ci )
Ningbo Port
Shenzheng Port
Putian Port
20%
∑ exp ( −c )
i
S
ci = cwi + chi + ccui + ctri
Have a change on Th
Market share
ch = α ⋅ Th + Fh
18%
16%
14%
12%
10.29%
10.91% 10.99% 11.05% 11.10% 11.13%
10.62% 10.80%
10%
140
200
260 320 380 440 500
Port efficiency (TEU/hour)
560
4 Case Study
Scenario III -- Improving operations of Putian port
Case 1: change of the port efficiency
Ningbo Port
Shenzheng Port
Putian Port
20%
18%
Market share
‡ The increase of port
efficiency can gain a higher
share of market for the Putian
port.
Xiamen Port
Shanghai Port
Fuzhou Port
16%
14%
12%
10.29%
10.91% 10.99% 11.05% 11.10% 11.13%
10.62% 10.80%
10%
140
200
260 320 380 440 500
Port efficiency (TEU/hour)
560
4 Case Study
Scenario III -- Improving operations of Putian port
Case 2: change of the service frequency
MS Hi =PSi =
Xiamen Port
Shanghai Port
Fuzhou Port
exp ( −ci )
Ningbo Port
Shenzheng Port
Putian Port
20%
∑ exp ( −c )
i
S
ci = cwi + chi + ccui + ctri
Have a change on Tw
Market share
cw = α ⋅ Tw + Fw
18%
16%
14%
12.67%
12.97%
13.50%
13.19% 13.36%
12.23%
11.54%
12%
10.30%
10%
0.44 0.67 0.89 1.11 1.33 1.56 1.78 2.00
weekly service frequency (ships/week)
4 Case Study
Scenario III -- Improving operations of Putian port
Case 2: change of the service frequency
Xiamen Port
Shanghai Port
Fuzhou Port
Ningbo Port
Shenzheng Port
Putian Port
20%
‡ Service frequency is highly sensitive
Market share
to the market share of Putian Port.
18%
16%
14%
12.67%
12.97%
13.50%
13.19% 13.36%
12.23%
11.54%
12%
10.30%
10%
0.44 0.67 0.89 1.11 1.33 1.56 1.78 2.00
weekly service frequency (ships/week)
4 Case Study
Scenario
Description
Sensitivity
I
Transportation improvement
★☆☆☆
II
Customs improvement
★★☆☆
III case 1
High port efficiency
★★★☆
III case 2
High service frequency
★★★★
Results show that the market share of the Putian Port is
highly sensitive to factors as service frequency, customs
efficiency, and is less sensitive to factors as the landside
transportation time.
5 Conclusions
(1) Though several main ports have reached the top level of
world-wide ports, there are more ports which have been in
their difficult stage of development to their target of
international mega port due to confusions at planning level in
mainland China.
China
(2)It is difficult for many emerging ports in China to realize the
dream of becoming internationally mega port. Main
difficulties are as below.
• Low frequency of shipment schedule
• Low efficiency of customs operational procedure
5 Conclusions
(3)The most sensitive factor is also the most difficult factor.
• Service frequency is hard to increase in a short time
(4)It is urgent for most emerging ports to adjust its
development to reasonable and feasible scheme.
• Specialized port
• Feeding port
Thank you!
4 Case Study
Scenario I -- Improving land-side transportation system
Case II: change of the average speed of Xiangpu Railway
MS Hi =PSi =
Xiamen Port
Shanghai Port
Fuzhou Port
exp ( −ci )
20%
∑ exp ( −c )
i
18%
ctr = α ⋅ Ttr + Ftr
Have a change on Ttr
market share
S
ci = cwi + chi + cci u + ctir
Ningbo Port
Shenzheng Port
Putian Port
16%
14%
12%
10.36%
10.16%
10%
8%
30
43
56
69
81
94
average speed (km/h)
0.9
107
120
0.2
Travel time (days)
4 Case Study
Scenario I -- Improving land-side transportation system
Case II: change of the average speed of Xiangpu Railway
Xiamen Port
Shanghai Port
Fuzhou Port
20%
‡ time can reduced by Xiangpu
Railway is limited.
18%
market share
‡ With this limited reduce,
Xiangpu Railway can not
contribute too much to the
market share of Putian Port.
Ningbo Port
Shenzheng Port
Putian Port
16%
14%
12%
10.36%
10.16%
10%
8%
30
43
56
69
81
94
average speed (km/h)
0.9
107
120
0.2
Travel time (days)
4 Case Study
Scenario I -- Improving land-side transportation system
Case III: change of the tariff of Xiangpu Railway
MS Hi =PSi =
Xiamen Port
Shanghai Port
Fuzhou Port
exp ( −ci )
∑ exp ( −ci )
Ningbo Port
Shenzheng Port
Putian Port
25%
23%
S
ci = cwi + chi + cci u + ctir
21%
ctr = α ⋅ Ttr + Ftr
Have a change on Ftr
market share
19%
17%
15%
13%
11%
9%
10.67% 11.06%
10.30%
9.95%
9.32% 9.63%
8.75% 9.03%
7%
5%
1.53 1.37 1.22 1.07 0.92 0.76 0.61 0.46
traffic rate (USD/km)
4 Case Study
Scenario I -- Improving land-side transportation system
Case III: change of the tariff of Xiangpu Railway
Xiamen Port
Shanghai Port
Fuzhou Port
‡ The reduction of the tariff rate of
Xiangpu Railway will
significantly improve the market
share of Putian Port.
25%
23%
21%
19%
market share
‡ Unfortunately, the traffic rate
have a price floor, it can not
reduce without consider the
benefits of the railway.
Ningbo Port
Shenzheng Port
Putian Port
17%
15%
13%
11%
9%
10.67% 11.06%
10.30%
9.95%
9.32% 9.63%
8.75% 9.03%
7%
5%
1.53 1.37 1.22 1.07 0.92 0.76 0.61 0.46
traffic rate (USD/km)