Competition Model with Development Policies for Emerging Ports:Case Study of the Mainland of China Bao-Hua MAO (bhmao@bjtu.edu.cn) Prof. Ph.D, Beijing Jiaotong University, Beijing, China Peng DU (pdu@bjtu.edu.cn) Ph.D, Beijing Jiaotong University, Beijing, China Yu-Ting ZHU (11114241@bjtu.edu.cn) Ph.D Candidate, Beijing Jiaotong University, Beijing, China Qi XU (10114216@bjtu.edu.cn) Ph.D Candidate, Beijing Jiaotong University, Beijing, China Presented at The 3 rd 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 7 6.88 6.36 6 5.64 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. 528.5 370.0 140.8 201.1 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 12 ports. Average distance: 127 km. Shortest distance: 20 km. Most of them transport the same kind of goods -- large bulk cargo and container. Main port Regional port
1 Introduction 300% Capacity Utilization in 2011 250% Capacity utilization n 200% 150% 100% 50% 0% 0 5 10 15 20 25 30 35 Container throughput(million TEUs)
1 Introduction 300% Capacity Utilization in 2011 (ports below 1 million) 250% Capacity utilizat ation 200% 150% 100% 50% 0% 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Container throughput(million TEUs)
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 Why shippers would rather choose large ports, which are overused, than small or medium-sized ports, which have abundant capacity? What are the main factors in determining port competitiveness? How much competitiveness can an emerging port get? What strategies it can take to increase its competitiveness? And what kind of port it is expected to be in the future?
Can an emerging port realize its dream of mega int l 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 Waiting time
2 Analysis of Factors Inspection & Quarantine, Customs Customs regulations and procedure Procedure of commodity inspection and quarantine Time Cost and tariff
2 Analysis of Factors Land-side transportation Location and natural conditions Inland transportation network availability and accessibility Distance or time Cost between ports and hinterland
2 Analysis of Factors Port efficiency Handling efficiency Transshipment efficiency Port cost
2 Analysis of Factors
3 Competition Model Problem description P 1 Hinterland H 1 P 2 Hinterland H 2 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 Local customs Booking ship space IQ Local customs Transit in land-side Port customs Handling process Dry port Booking ship space IQ Local customs Transit in land-side Handling process Note: IQ stands for Inspection and Quarantine
3 Competition Model We assume that: All shippers will choose the procedure of Local customs; 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 Port customs Handling process Dry port Booking shipp space IQ Local customs Transit in land-side 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 Terminal Ending time Handling process transportation time cost transportation Starting time Destination area (Port) transportation Origin area (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 Handling process Ending time Handling process customs transferring Applying to the customs Starting time Applying to IQ Waiting at freight yard Booking ship space (Starting time) Origin area (Freight yard) transportation Destination area (Port) Destination area (Port) transportation Origin area (Freight yard)
3 Competition Model Time and cost analyses of Land-side Procedure Generalized Cost for waiting a ship ( c w ) Ending time Handling process customs transferring Cost: booking shipping space (F w ) Time: waiting for a ship (T w ) Applying to the customs Applying to CIQ c = α T + F w w w where, α is the VOT perceived by the intermodal operator. Waiting at freight yard Booking shipping space (Starting time) T w, F w Origin area (Freight yard) transportation Destination area (Port)
3 Competition Model Time and cost analyses of Land-side Procedure Generalized Cost for customs clearance ( c cu ) Ending time Handling process customs transferring Applying to the customs Applying to IQ Waiting at freight yard Booking shipping space (Starting time) T' cu, F' cu T cu, F cu Commodity inspection and customs declaration (T cu and F cu ) Customs transferring (T' cu and F' cu ) c = α ( T + T ) + ( F + F ) cu cu cu cu cu where, α is the VOT perceived by the intermodal operator. Origin area (Freight yard) transportation Destination area (Port)
3 Competition Model Time and cost analyses of Land-side Procedure Generalized cost for land-side transportation ( c tr ) transit cost (F tr ) Ending time Handling process customs transferring Land-side transportation Applying to the customs Applying to CIQ Waiting at freight yard Booking shipping space (Starting time) F tr,t tr transit cost of different mode (f m ) transit time (T tr ) in-vehicle travel time transfer time s t tr m s c = α T + F = α ( t + t )+ f tr tr tr tr tr m m s m where, m is the transportation mode, s is transfer node. m t tr Origin area (Freight yard) transportation Destination area (Port)
3 Competition Model Time and cost analyses of Land-side Procedure Generalized cost for handling( c h ) Ending time Handling process customs transferring Apply to the customs Applying to CIQ Waiting at freight yard Booking shipping space (Starting time) F h,t h handling time(t h ) transshipment cost (F h ) α c = α T + F h h h where, is the VOT perceived by the intermodal operator Origin area (Freight yard) transportation Destination area (Port)
3 Competition Model Time and cost analyses of Land-side Procedure Ending time Handling process c h the generalized cost of the whole land-side procedure c cu customs transferring c = c + c + c + c i i i i i w h cu tr Apply to the customs Applying to IQ Waiting at freight yard Booking shipping space (Starting time) c w Origin area (Freight yard) transportation 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. Thus, the market share can be formed as follow: ( ) i i MS = P = Pr c c, j Sandi j H S i j
3 Competition Model Utility (U i ): Deterministic and Random Utility Components U Deterministic Component = V + ε i i i = c + ε i i Random Component Independently and Identically Distributed (IID) Gumbel Actual generalized cost c = c + c + c + c i i i i i w h cu tr P i S = S exp exp ( ci ) ( c ) i
4 Case Study Putian Port -- an emerging port Location: southeastern coast of China Current thinterland: 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, and Putian Port, shortening the travel time in half.
4 Case Study 31.7 14.7 Export ports for Jiangxi Province 6.5 1.6 1.7 The existing ports Shanghai Port Ningbo Port Xiamen Port Shenzhen Port Fuzhou Port 22.6 The emerging port Putian Port Container Throughput (million TEUs)
4 Case Study How much market share can Putian Port get now? Can the railway help Putian Port realize its dream of mega port? Which strategies can benefit the increase of its market share?
4 Case Study Port competitive model: c = c + c + c + c i i i i i w h cu tr ( ) i i MS = P = Pr c c, j S and i j H S i j MS i H = P i S = S exp exp ( ci ) ( c ) i
4 Case Study Performance of ports -- Service frequency Service Frequency 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 N s is counted from 10/24/2013 to 12/25/2013 (63 days). Weekly service frequency: 7 6 5 4 3 2 Ships / week 2.89 2.89 4.00 5.89 2.00 f = N s / 63*7 1 0 0.44 Xiamen Ningbo Shanghai Shenzheng Fuzhou Putian
4 Case Study Performance of ports -- Port efficiency Port Efficiency The annual container handing capacity CAP h (TEU/year) of ports comes from CHINA PORTS YEAR BOOK(2012). 3000 2500 2000 TEU/hour 2,285 2,705 Port efficiency (TEU/hour): 1500 e= CAP h /365/24 1000 1,100 1,161 500 276 141 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. 250 200 USD/TEU 206 237 231 192 201 201 150 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 Xiamen O 3 41 - - Ningbo O 3 41 - - Shanghai O 3 41 - - Shenzhen O 3 41 - - Fuzhou X 3 41 2 114 Putian X 3 41 3 117 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 transportation time t 1 (day) t1 = l/ (33.2 24) Where l demotes travel distance.
4 Case Study Transportation -- time and cost for highway The cost c 2 (USD) and time t 2 (day) of transporting one TEU by Chinese highways: Where l demotes travel distance. c2 = 5.5 0.146l = 0.803l t2 = 0.0015l Relevant Sources: Wang X, Meng Q. (2011)
4 Case Study Transportation Ports main transit mode Auxiliary transportation* mode Distance/km Time/days cost/usd Time/days cost/usd Xiamen 946 1.19 527.98 - - Ningbo 813 1.02 466.83 - - Shanghaih Ril Railway 880 110 1.10 538.17 004 0.04 41.01 Shenzhen 946 1.19 645.37 0.04 53.32 Fuzhou 642 0.81 426.66 0.04 41.01 Putian Highway 681 1.02 820.35 - - In Xiamen port, Ningbo port and Fuzhou port, railway can reach ports directly or just outside the port. 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 Commodity inspection and Port Transportation customs declaration Ports Waiting time Handling time cost Time cost Time cost days days USD days USD days 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 25% Benchmark -- market share of Putian Port 20% 19.3% 19.9% 18.8% 18.0% Xiamen Port and Ningbo Port have a strong competitiveness, the market 15.9% share of them are higher h than 19%. market share 15% 10% 8.2% Putian Port have the weakest competitiveness, the market share of it is only 8.2%. 5% 0% Xiamen Port Ningbo Port Shanghai Port Shenzheng Port Fuzhou Port Putian Port
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 with Xiangpu Railway time/days cost/usd time/days cost/usd Xiamen 1.19 527.98 1.19 527.98 Ningbo 1.02 466.83 1.02 466.83 Shanghai 1.14 538.17 1.14 538.17 Shenzhen 1.23 645.37 1.23 645.37 Fuzhou 0.85 426.66 0.42 419.49 Putian 1.02 820.35 0.41 418.42
4 Case Study Scenario I -- Improving land-side transportation system MS i H = P i S = exp exp ( ci ) ( c ) c = c + c + c + c i i i i i w h cu tr S c tr = α + i Tt r F tr Market share 100% 90% 80% 70% 60% 50% 40% 8.2% 10.3% 15.9% 18.0% 15.9% 17.4% 18.8% 18.2% Putian Port Fuzhou Port Shenzheng Port Shanghai Port Ningbo Port Xiamen Port Have a reduce on F tr and T tr 30% 20% 10% 19.9% 19.4% 19.3% 18.8% 0% without Xiangpu Railway with Xiangpu Railway
4 Case Study Scenario I -- Improving land-side transportation system Railway, with the advantage of low transit ta stcost, can improve the competiveness of the connected ports. The market share of Putian Port increases from 8.2% to 10.3%. Market share 100% 90% 80% 70% 60% 50% 40% 30% 20% 8.2% 10.3% 15.9% 18.0% 15.9% 17.4% 18.8% 18.2% 19.9% 19.4% Putian Port Fuzhou Port Shenzheng Port Shanghai Port Ningbo Port Xiamen Port 10% 19.3% 18.8% 0% without Xiangpu Railway with Xiangpu Railway
4 Case Study Scenario II -- Improving the customs efficiency Ports Xiamen Ningbo Shanghai Shenzhen Fuzhou Putian whether have dry port in Jiangxi O O O O X X Note: O indicates have a dry port; X indicates do not have a dry port; c MS i H = P i S = exp exp ( ci ) ( c ) = c + c + c + c i i i i i w h c u t r S c = α ( T + T ) + ( F + F ) cu cu cu cu Have a reduce on T cu and F cu i cu 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 Case I Case II Case III Case IV Fuzhou X O X O Putian X X O O Note: O indicates have a dry port; X indicates do not have a dry port; 100% 90% 80% Xiamen Port Ningbo Port Shanghai Port Shenzheng Port Fuzhou Port Putian Port 10.3% 10.0% 12.6% 12.3% 15.9% 18.7% 15.4% 18.4% Dry port operation can help Putian Port to increase the market share in Jiangxi Province. Market share 70% 60% 50% 40% 30% 20% 17.4% 16.9% 16.9% 16.0% 18.2% 17.8% 17.8% 18.0% 19.4% 18.8% 18.9% 17.9% 10% 18.8% 17.8% 18.3% 17.4% 0% Case I Case II Case III Case IV
4 Case Study Scenario III -- Improving operations of Putian port Case 1: change of the port efficiency c MS i H = P i S = exp exp ( ci ) ( c ) = c + c + c + c i i i i i w h cu tr S i 20% 18% Xiamen Port Shanghai Port Fuzhou Port Ningbo Port Shenzheng Port Putian Port c h = α T + F Have a change on T h h h Market share 16% 14% 12% 10% 10.29% 10.62% 10.80% 10.91% 10.99% 11.05% 11.10% 11.13% 140 200 260 320 380 440 500 560 Port efficiency (TEU/hour)
4 Case Study Scenario III -- Improving operations of Putian port Case 1: change of the port efficiency The increase of port efficiency can gain a higher share of market for the Putian port. Market share 20% 18% 16% 14% Xiamen Port Shanghai Port Fuzhou Port Ningbo Port Shenzheng Port Putian Port 12% 10% 10.29% 10.62% 10.80% 10.91% 10.99% 11.05% 11.10% 11.13% 140 200 260 320 380 440 500 560 Port efficiency (TEU/hour)
4 Case Study Scenario III -- Improving operations of Putian port Case 2: change of the service frequency MS i H = P i S = exp exp ( ci ) ( c ) c = c + c + c + c i i i i i w h cu tr S i 20% 18% Xiamen Port Shanghai Port Fuzhou Port Ningbo Port Shenzheng Port Putian Port c w = α T + F w w Have a change on T w Market share 16% 14% 12% 11.54% 12.23% 12.67% 12.97% 13.19% 13.36% 13.50% 10% 10.30% 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 20% Xiamen Port Shanghai Port Fuzhou Port Ningbo Port Shenzheng Port Putian Port Service frequency is highly sensitive 18% to the market share of Putian Port. Market share 16% 14% 12% 11.54% 12.23% 12.67% 12.97% 13.19% 13.36% 13.50% 10% 10.30% 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. (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 i H = P i S = exp exp ( ci ) ( c ) c = c + c + c + c i i i i i w h cu tr S c tr i = α + F Tt r tr Have a change on T tr market share Xiamen Port Shanghai Port Fuzhou Port 20% 18% 16% 14% 12% 10% 10.16% Ningbo Port Shenzheng Port Putian Port 10.36% 8% 30 43 56 69 81 94 107 120 average speed (km/h) 0.9 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 time can reduced by Xiangpu Railway is limited. With this limited reduce, Xiangpu Railway can not contribute too much to the market share of Putian Port. market share 20% 18% 16% 14% 12% 10% 8% Xiamen Port Shanghai Port Fuzhou Port 10.16% Ningbo Port Shenzheng Port Putian Port 10.36% 30 43 56 69 81 94 107 120 average speed (km/h) 0.9 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 i H = P i S = exp exp ( ci ) ( c ) c = c + c + c + c i i i i i w h cu tr S c = α T + F i tr tr tr Have a change on F tr market share Xiamen Port Shanghai Port Fuzhou Port 25% 23% 21% 19% 17% 15% 13% 11% 9% 7% 5% Ningbo Port Shenzheng Port Putian Port 8.75% 9.03% 9.32% 9.63% 9.95% 10.30% 10.67% 11.06% 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 The reduction of the tariff rate of Xiangpu Railway will significantly improve the market share of Putian Port. Unfortunately, the traffic rate have a price floor, it can not reduce without consider the benefits of the railway. market share 25% 23% 21% 19% 17% 15% 13% 11% 9% 7% 5% 8.75% Xiamen Port Shanghai Port Fuzhou Port 9.03% 9.32% 9.63% 9.95% 10.30% Ningbo Port Shenzheng Port Putian Port 10.67% 11.06% 1.53 1.37 1.22 1.07 0.92 0.76 0.61 0.46 traffic rate (USD/km)