集装箱货运仿真模型在珠三角港港口投资方案评估(英文)

In the Pearl River Delta (PRD), there is severe competition between container ports, particularly those in Hong Kong, Shenzhen, and Guangzhou, for collecting international maritime container cargo. In addition, the second phase of the Nansha terminal in Guangzhou’s port and the first phase of the Da Chang Bay container terminal in Shenzhen opened last year. Under these circumstances, there is an increasing need to quantitatively measure the impact these infrastructure investments have on regional cargo flows. The analysis should include the effects of container terminal construction, berth deepening, and access road construction. The authors have been developing a model for international cargo simulation (MICS) which can simulate the movement of cargo. The volume of origin-destination (OD) container cargo in the East Asian region was used as an input, in order to evaluate the effects of international freight transportation policies. This paper focuses on the PRD area and, by incorporating a more detailed network, evaluates the impact of several infrastructure investment projects on freight movement.     

A dynamic model for marginal cost pricing of port infrastructures

ABSTRACT

A dynamic model for marginal cost pricing of port infrastructures links costs to system performance by combining a power-law function with time-dependent queueing analysis. Additionally, the model incorporates the marginal cost of capacity, including the effects of economies of scale. This allows the calculation of the marginal cost price under a dynamic framework. The model accounts for nonlinear behaviour of port demand, which is sensitive to price and service levels. The effects over time of cost and service levels on the port’s operational performance are quantified. The proposed model allows determining the optimal timing for capacity investment. The model is a starting point for the application of marginal cost pricing to ports. However, for practical application of such pricing method it is necessary to apply a system’s approach, as productivity and costs must be assessed at the terminal’s component level. This should allow the derivation of a marginal cost function at the terminal’s component level.     

The foreign non-fuel cargo-traffic demand of the major British seaports in 1980 and 1985, a Markov Chain approach

Projections of the future traffic demand of British seaports are of great importance to port management bodies because of the huge capital investment required for installing modern port facilities. In this paper, the author uses a first order Markov Chain model to forecast the non-fuel cargo traffic demand of the major British seaports in 1980 and 1985.     

基于条件期望的港口货物吞吐量预测模型的建立与分析

为了有效预测港口货物总吞吐量的大小,利用条件数学期望提出了港口货物总吞吐量的预测模型.由于货物总吞吐量的变化与到达港口的货运船数目以及装卸设备的工作效率有密切关系,构造一个关于到达港口的货运船数目以及装卸设备的工作能力组合而成的复合变量,货物总吞吐量是这些复合变量所表示的货物装卸量的和.应用全概理论,得到货物总吞吐量的概率分布.在此基础上,将未来货物总吞吐量看作已完成吞吐量的条件期望.利用增长函数得出港口货物吞吐量的预测模型.以山东地区某港口的货物吞吐量变化规律进行了案例分析.理论分析和案例分析均表明该模型是预测港口货物总吞吐量的有效方法.     

Which terminals should expand investment: a perspective of internal non-cooperative competition in a port?

ABSTRACT

With the increasing container cargo throughput and the arising of port congestion, container ports start to choose the investment expansion strategy to increase the port efficiency and then to figure out the problem of port congestion. To analyze this strategy, we formulate a non-cooperative game model for a two-terminals-one-port system, and derive the optimal equilibrium outcomes of the investment expansion strategy and investment constant strategy. In the game, we find that when the investment parameter of expansion strategy and impact of handling efficiency on demand changes, both pure-strategy Nash equilibrium and mixed-strategy Nash equilibrium exist, and two terminals are more likely to choose the investment expansion strategy in most cases. Numerical simulation is applied to explore the equilibrium strategy under different circumstance.     

A game theory analysis of port specialization—implications to the Chinese port industry

The fast growth of the Chinese economy and its international seaborne trade has escalated the demand for high-quality and efficient port services. “Decentralization” of the port management regime has given local government greater freedom in port development and operational decision-making. However, major port capacity expansion in coastal areas, coupled with the slowing down of both the economy and trade growth over recent years, has led to overcapacity and excessive competition. Although both port specialization and government regulations are called for to address these issues, few studies have investigated the formation mechanism and economic implications of port specialization. This paper uses alternative duopoly games, namely a Stackelberg game and a simultaneous game, to model port competition, where ports provide differentiated services in the sectors of containerized cargo and dry-bulk cargo. Our analytical results reveal that inter-port competition can lead to port specialization in the following three ways. A port can specialize in a type of cargo (1) for which there is relatively high demand, (2) where it has established capacity first, or (3) for services which require prohibitively high capacity costs. Also, it is seen that overcapacity is likely if strategic port decisions are made simultaneously instead of sequentially. These results suggest that if there is a clear market leader, policy intervention may not be necessary. However, if no port has clear market power, then government coordination and intervention may be needed in order to prevent overcapacity and to encourage specialization.     

Norwegian port connectivity and its policy implications

The importance of a seaport depends on how well it is connected in a transportation network. A port’s connectivity is therefore one of the key issues in determining its competitiveness and developments in regions and countries. We construct a port connectivity index for major Norwegian ports based on a unique dataset derived from the automated identification system (AIS) for multiple vessel types over a 7-year period. Port connectivity is evaluated empirically by the number of unique vessel visits, vessel sizes, and cargo sizes. The research has implications for port authorities and policy makers in the areas of port planning, infrastructure investment, short sea shipping promotion, and environmental policies. The contributions of this research are twofold. First, the methodology linking the AIS vessel-tracking system with port connectivity is a pioneering empirical application of maritime big data. Second, the port connectivity index is constructed for multiple vessel types and regional port groups, which is an improvement from the current literature where conceptual measures are constructed based on hypothetical and usually too simple optimization rules. The methodology can be easily expanded to other regions in the world.     

Vertical integration and its implications to port expansion

ABSTRACT

Over the years many shipping lines have established terminal operation companies, with some set up as independent firms. However, port authorities and local governments have not always welcomed external investment and control with open arms. The economic implications and each stakeholder’s best strategies remain unclear. This study develops an analytical model in order to study the effects of vertical integration, with a focus on shipping lines’ investment in ports’ capacity. Modelling results suggest that vertical integration between terminal operator and a shipping line leads to higher port capacity, port charge, market output and consumer surplus. It also reduces delay costs. All these results suggest that vertical integration can be an important source of synergy for the maritime industry. Although vertical integration increases the participating carrier’s output at the expenses of non-integrating rival shipping firms, our numerical analysis suggests that the overall social welfare is likely to increase. Preliminary empirical tests confirm that vertically integrated ports handle more traffic volumes and are associated with better infrastructure and equipment. Therefore, port authorities and government regulators should carefully review the market competition status as well as port expansion plans.     

Optimal investment priority in container port development

The aim of this paper is to develop realistic and relevant investment planning models for inland container transportation systems. The models may be utilized to identify the most effective investment plan for inland transportation infrastructure development and to evaluate the inland container transportation system. The procedure enables determination of the optimal locations, sizes and time of container port developments as well as the optimal container cargo flows through transportation networks. A heuristic algorithm was developed for the purpose of evaluating alternative investment plans. Dynamic and linear programming methods are applied to each of the two planning problems: the former for the optimum container port capacity development problem and the latter for the optimal allocation of inland container traffic movements. The model has been applied to concrete inland container transportation system problems in Korea.     

Optimal investment priority in container port development

The aim of this paper is to develop realistic and relevant investment planning models for inland container transportation systems. The models may be utilized to identify the most effective investment plan for inland transportation infrastructure development and to evaluate the inland container transportation system. The procedure enables determination of the optimal locations, sizes and time of container port developments as well as the optimal container cargo flows through transportation networks. A heuristic algorithm was developed for the purpose of evaluating alternative investment plans. Dynamic and linear programming methods are applied to each of the two planning problems: the former for the optimum container port capacity development problem and the latter for the optimal allocation of inland container traffic movements. The model has been applied to concrete inland container transportation system problems in Korea.     

A game-theoretic analysis of competition among container port hubs: the case of Busan and Shanghai 1

Countries throughout the world, and especially within Asia, are investing heavily in container port infrastructure in the hopes of capturing a larger share of global shipping activity for their economies. Many existing ports are emphasizing developing the capacity to serve as a hub port, building deepwater berths with large terminals to facilitate transfer of containers from feeder ships to mother ships for intercontinental transport. We develop a game-theoretic best response framework for understanding how competitor ports will respond to development at a focus port, and whether the focus port will be able to capture or defend market share by building additional capacity. We apply this model to investment and competition currently occurring between the ports of Busan and Shanghai.     

Research on probability distribution of port cargo throughput

In order to more accurately examine developing trends in gross cargo throughput, we have modeled the probability distribution of cargo throughput. Gross cargo throughput is determined by the time spent by cargo ships in the port and the operating efficiency of handling equipment. Gross cargo throughput is the sum of all compound variables determining each aspect of cargo throughput for every cargo ship arriving at the port. Probability distribution was determined using the Wald equation. The results show that the variability of gross cargo throughput primarily depends on the different times required by different cargo ships arriving at the port. This model overcomes the shortcoming of previous models： inability to accurately determine the probability of a specific value of future gross cargo throughput. Our proposed model of cargo throughput depends on the relationship between time required by a cargo ship arriving at the port and the operational capacity of handling equipment at the port. At the same time, key factors affecting gross cargo throughput are analyzed. In order to test the efficiency of the model, the cargo volume of a port in Shandong Province was used as an example. In the case study the actual results matched our theoretical analysis.     

Factoring a real value of cargo in port investment and funding decisions

Ports are marine gateways to economic activities. Ports’ ability to perform services depends on their facilities, harbor conditions, and other factors. Generally, ports have control over their facilities but must compete for funding to improve them. As for waterways, in the U.S., a Harbor Maintenance Trust Fund was established to fund dredging, which levies a 0.125% cargo value tax on most shippers using U.S. coastal and Great Lakes harbors. Yet, commonly, a gross tonnage metric is used to allocate the fund’s resources, resulting in under-maintenance of some harbors. This, reportedly, deters additional port funding and hinders valuable commerce. Supplemental economic metrics, such as value of commerce or cargo, can improve port financing decisions, but such data is not readily available. Container ports collect cargo value data in nominal terms, but bulk ports do not. When making economic decisions, however, real values must be used. Further, when allocating resources, decision-makers must be able to assess ports over time and relative to each other. Conforming to these criteria, this paper develops three port financing indicators based on a real value of cargo and illustrates their calculations using the U.S. Port of Duluth-Superior as a case study.     

‘Tool port’ to ‘landlord port’: a game theory approach to analyse gains from governance model transformation

This study investigates potential port users’ surplus and terminal operators’ profits due to transforming port governance from the ‘tool port’ model to the ‘landlord port’ model. Although the landlord port model is one of the most adopted and successful port governance models, many ports still operate under other models. Chittagong Port, the largest port in Bangladesh, currently operates under the tool port model, while the country’s second-largest port, Mongla Port, operates under the service port model. Chittagong Port is currently facing many challenges, including capacity expansion and renovation of port facilities. Therefore, we form four hypothetical situations for port governance model transformation, assuming that Chittagong Port will transform to the landlord port model but that Mongla Port will run under the existing governance model. Estimating a Bertrand game model, we present a cost-benefit analysis for port users and terminal operators (or port authorities) in hypothetical game situations. The results reveal that privatising one of the container terminals under a landlord setting is the most profitable scenario for Chittagong Port Authority, but privatising all terminals of Chittagong Port yields the highest users’ surplus. However, privatising two of the terminals while they cooperate yields the lowest users’ surplus.     

Multicommodity network flow model for Asia's container ports

This paper seeks to develop a multi-commodity network model to analyse the flow of containers within the Asia Pacific context. The model is used to evaluate the impact of container throughput in Asia's port by varying terminal handling charges and turnaround time. The three main regions analysed are north-east Asia, east Asia (Chinese port region) and south east Asia. Using the model, it could be shown that Busan port, which is an important transhipment hub in north-east Asia, could boost the container activities in the north-eastern part of China by improving its service quality. It is also found that the efficiency of the land link between Hong Kong and mainland China plays a crucial role for the future of Hong Kong port. While Singapore port maintains its position as a transhipment hub in south-east Asia, there would be expected competition from neighbouring low costs ports.     

Evaluating seaport operation and capacity analysis—preliminary methodology

The marine terminal in general and the container terminal in particular is the physical link between ocean and land modes of transportation. Port capacity is commonly defined as the amount of cargo that can be handled by a port per time period, usually a year. For containers it is the number of processed containers per year, for bulk cargo-tons or pallets per year and for Ro-Ro cargoes-autos per year. As the number of ships and the amount of cargo passing through the port increase, a point is reached at which some elements of the port system are functioning near or beyond their maximum productivity rate. The concept that should direct the terminal capacity analysis is controlled by the terminal activity that determines the lowest capacity rate per unit of time, during one cycle of operation. Four performance measures are introduced in order to establish a recommended methodology that quantifies the port's quality of operation and also functions as a tool for decision makers to justify a required investment. The methodology should become a standard that might turn into a requirement for examining every port's level of service.     

Evaluating determinants of attractiveness and their cause-effect relationships for container ports in Taiwan: users’ perspectives

The attractiveness of ports is usually a pre-requisite and necessary condition for ports to achieve competitiveness, as well as the springboard to explore the competitive advantages of ports. To determine whether a port is competitive, it is necessary to explore whether it boasts certain factors that make the port attractive to users. The main purpose of this article is to apply the Analytic Hierarchy Process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to evaluate key determinants of attractiveness and their cause/effect relationships for container ports in Taiwan. The empirical results showed that: (1) Top six determinates of attractiveness for container ports are ‘ample cargo sources,’ ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ ‘efficient wharf operations,’ and ‘adequate wharfs and back-line land,’ respectively. (2) Among the above six determinants of attractiveness, ‘ample cargo sources’ is the cause determinant. Three determinants of port attractiveness, ‘favorable port charges,’ ‘dense ship network and routes,’ ‘low transshipment costs,’ which are the effect determinants. They are affected by the determinants of attractiveness of ‘ample cargo sources’. In addition, this study discusses the above findings and expects to provide the study results to Taiwan’s port authorities for reference.     

Optimal handling capacity at a berth

In a recent paper Wanhill [1] described a method for determining the number of berths that should be provided at a port so that the total usage cost would be minimized. However, in many situations a port will provide a single specialized berth to cater for a particular type of cargo; for example, the unloading of iron-ore at a steelworks or the discharge of oil at a general cargo port. The problem then is not one of deciding on the number of berths to be built but rather that of finding the optimal cargo handling capacity for the single berth available. A model is presented in this paper indicating how such a decision may be made, and two examples give approximate lower and upper bounds for the optimal capacity for many practical cases. A second paper will show how a theoretical model often has to be modified in the light of particular circumstances.     

Optimal handling capacity at a berth

In a recent paper Wanhill [1] described a method for determining the number of berths that should be provided at a port so that the total usage cost would be minimized. However, in many situations a port will provide a single specialized berth to cater for a particular type of cargo; for example, the unloading of iron-ore at a steelworks or the discharge of oil at a general cargo port. The problem then is not one of deciding on the number of berths to be built but rather that of finding the optimal cargo handling capacity for the single berth available. A model is presented in this paper indicating how such a decision may be made, and two examples give approximate lower and upper bounds for the optimal capacity for many practical cases. A second paper will show how a theoretical model often has to be modified in the light of particular circumstances.     

基于AIS大数据耦合分析的沿海港口泊位利用率研究*

针对我国沿海港口能力供给水平数据跟踪方面长期存在的时效性差、人为统计过程中易出现错漏等诸多问题,分析传统泊位通过能力统计失真的具体原因,提出将泊位利用率作为评价港口服务水平的表征指标,依托地理信息系统(GIS)平台和基于船舶自动识别系统(AIS)等数据耦合的空间拓扑分析,综合考虑空间关系、航速特征、经留时间等影响因素,研发基于AIS大数据的泊位利用率算法模型,并以上海港2019年集装箱泊位利用率为例进行算法验证。结果表明,所提出的泊位利用率算法模型是可信的;提供了一种能够反映客观实际、定量分析判断港口服务水平的技术手段,可为政府部门长期动态监测港口能力与运输需求互动平衡关系,支撑政府部门决策港口发展重点和建设时序,避免空间资源浪费、重复建设、能力过剩等问题提供技术支撑。