Time efficiency assessment of ship movements in maritime ports: A case study of two ports based on AIS data

Operational efficiency of a maritime port is an important issue for shipping lines and port authorities. It is desirable to move ships in and out of a maritime port as efficiently as possible. Automatic identification system (AIS) data recording the trajectory of ship movements allow us to assess the operational efficiency as ships move in and out of a port. This study proposes a time efficiency assessment framework that evaluates the amount of time each ship spends in the different areas within a port (i.e., berth, anchorage, and fairway) based on the space-time trajectories of ship movements derived from AIS data. According to the statistical distributions of time spent by different types of ship in each port area, the proposed framework can compare time efficiency across different zones within a port and between different ports. This study uses AIS data of four types of ships (i.e., container, cargo, tanker, and passenger ships) at two selected ports in China, Shanghai Yangshan Port and Xiamen Port, to demonstrate how the proposed approach can effectively assess and compare time efficiency levels of ship movements between the times entering and leaving the vessel traffic service (VTS) lines of a port. This study demonstrates the value of deriving space-time trajectories from AIS data based on the concepts of time geography to assess time efficiency levels of maritime ports and monitor their performance over time, which offer useful information to both shipping lines and port authorities for operations such as efficient scheduling and logistic support.     

Spatial patterns of landside trade impedance in containerized South American exports

The paper addresses claims implicating higher domestic transportation costs as a significant barrier to Latin America's trade and economic integration - and the region's inadequate transportation infrastructure as the primary cause. The relative “trade space” for U.S.-bound containerized shipments is delineated via reverse spatial interaction modeling. Reconfiguration and reverse calibration of the doubly constrained spatial interaction model is used to derive functional distances between origins and ports of export, as a means of estimating a Trade Impedance Quotient (TIQ) for trade flows at the scale of the continent. Global and local statistics of spatial autocorrelation are then used to analyze the spatial pattern of trade impedance. With this approach, the analysis of containerized flows establishes the existence, extent, location, and spatial distribution of discrepancies in South American landside trade impedance. A large share of trade flows have trade impedance that is disproportionate to distance. Trade impedance at origins is spatially clustered for the total dataset and randomly distributed for commodity segments, and randomly distributed at destinations. Potential focus areas for high trade impedance are identified.     

A maritime container repositioning yield-based optimization model with uncertain upsurge demand

The role of container repositioning has become more important under the severe cargo shipping environment, affected by world trade growth, trade imbalance, slow steaming strategy and high container manufacturing cost. Low cost, better routing, and supplying equipment to higher yield cargo become the top criteria. A yield-based container repositioning framework is developed, followed by a constrained linear programming optimizing the container repositioning from surplus to deficit locations. The model incorporated change of destinations of empty containers and adjustment factors handling upsurge demand. The model is applied to optimize daily container repositioning operations with a better route, costs and equipment supply.     

Analysing passenger network changes: The case of Hong Kong

Passenger throughput at Hong Kong International Airport (HKIA) has shown steady growth since its opening. Various aspects relating to HKIA have been studied in prior literature. This paper investigated changes in HKIA's passenger network for the period of 2001–2012 and used the gravity model to examine the key factors explaining its passenger traffic flows. The findings suggested that HKIA's passenger network has changed significantly and expanded to many new different destinations. Two regions (East Asia and Southeast Asia) were the most important markets for HKIA, and most key destinations connected by Hong Kong showed healthy growth. Nine factors could explain passenger traffic flows between Hong Kong and its key destinations: Hong Kong GDP per capita, GDP per capita of destinations connected by HKIA, distance, airport hub status of the destination airport, tourist destinations connected by HKIA, numbers of passenger airlines in service, bilateral trade flows, speaking a common language and having strong cultural/colonial links with Hong Kong, and the route presence of Cathay Pacific.     

Multivariate autoregressive models for forecasting seaborne trade flows

This paper contributes to the literature on forecasting seaborne trade flows by presenting multivariate autoregressive time series models that can be used to produce long-term forecasts. The models are applied to forecasting the trade flows of four commodity markets (crude oil, iron ore, grain and coal) on major trade routes. The empirical results indicate that the models can produce long-term seaborne trade flow estimates that have relatively small forecast errors.     

Vessel and voyage determinants of tanker freight rates and contract times

The behavior of shipping freight (charter) rates and the timing of shipping contracts affect the transportation costs of charterers and the operating cash flows of shipowners. Although the literature has established macroeconomic determinants of shipping freight rates, there has been no systematic investigation of microeconomic determinants of freight rates and the delivery time of chartered ships (the laycan period) in the tanker market. Therefore, the aim of this paper is to investigate the importance of vessel and contract specific factors in the determination of tanker freight rates and laycan periods in shipping contracts. Individual tanker shipping contracts from January 2006 to March 2009 are used to estimate freight rates and laycan periods using a system of simultaneous equations. The estimation results suggest that the duration of the laycan period is an important determinant of the shipping freight rate and vice versa. Other determinants of freight rates include the vessel's hull type, fixture deadweight utilization ratio, vessel age, and voyage routes. Determinants of the laycan period include the former determinants as well as the Baltic Dirty Tanker Index and its volatility.     

Shipping efficiency comparison between Northern Sea Route and the conventional Asia-Europe shipping route via Suez Canal

The continuous retreat of Arctic sea ice and seemingly appealing cost competitiveness of transarctic shipping routes are expected to boost shipping activities in the region. However, in reality, the number of Arctic transits remains meagre compared with major shipping routes. This study first develops a profit estimation model for containership sailing from an original port to a destination port with multiple port calls and a cost estimation model for oil tanker sailing from an origin port to a destination port. The authors then proceed to compare the shipping efficiency between the Northern Sea Route (NSR) and the Asia-Europe shipping route via Suez Canal by using the developed models and real shipping operational data. The results demonstrate that NSR shipping is not economically favored compared to traditional one in container shipping, but may be only appealing to small or medium-size tanker operators.     

Route choice of bike share users: Leveraging GPS data to derive choice sets

To identify the determinants of bike share users' route choices, this research collects 132,397 hub-to-hub global positioning system (GPS) trajectories over a 12-month period between April 1, 2015 and March 31, 2016 from 750 bicycles provided by Hamilton Bike Share (HBS). A GIS-based map-matching algorithm is used to derive users' routes along the cycling network within Hamilton, Ontario and generate multiple attributes for each route, such as route distance, route directness, average distance between intersections, and the number of turns, intersections, and unique road segments. Concerning route choice analysis, the origin and destination pair should be the same for all routes within a choice set, thus HBS users' trips are grouped by origin-destination hub pairs. Since trips taken by different users between a hub pair can follow the same route, unique routes are extracted using a link signature extraction tool. Following this, a normalized Gini (G_n) coefficient is calculated for each hub pair to evaluate users' preferences among all the unique hub-to-hub route choices. A G_n closer to 0 indicates that routes between a hub pair are more evenly used, while a value closer to 1 implies a higher preference toward one dominant route. Three route choice models, a global model, a medium G_n model, and a high G_n model, are estimated using Path-Size Logit to determine how route choice is affected by the presence of dominant routes. These models suggest that HBS users are willing to detour for some attributes, such as bicycle facilities, but tend to avoid circuitous routes, turns, steep slopes, and roads with high traffic volume.     

Connectivity to international markets: A multi-layered network approach

Improving connectivity for freight movements between countries is increasingly a topic at the centre of the international trade and transport policy agendas. In spite of this, a method to asses a country's degree of connectivity to its international markets for freight is still missing. To close this gap, this paper proposes a multi-layered network approach that enables the assessment of: (i) the different factors that influence connectivity to international markets; and (ii) the extent to which a country's connections matter for its international trade activities. The international trade network and its ‘support network’ are analysed using network theory. The approach proposed is applied to the Americas, a region the relevant literature has not specifically focused on yet. It is expected that a comprehensive understanding and assessment of the determinants of connectivity for freight will contribute to guide and design more effective policies to remove barriers to international trade flows.     

Interregional trade network analysis for road freight transport in Greece

This paper suggests a flexible decision support framework for the strategic planning of a freight transport hub network in Greece. The proposed methodology treats practical aspects related to the optimal number, location and geographical covering of hubs, through the network analysis of interregional trade, based on original survey data for road freight flows during 2004–2012. The results offer insights into the hierarchical structure of the network and related investment priorities, as the hub role of a prefecture is found to be strongly influenced by high population densities and manufacturing specialization, and its location along highway corridors.     

Evolution of regional inequality in the global shipping network

Global shipping is a backbone of the global economy, and as such, it evolves alongside the development of trade and the elaboration of commodity chains. This paper investigates the evolution of regional inequality in the global shipping network by analyzing the changing positions of world regions during the period from 2001 to 2012. This was a period of both prosperity and recession in maritime shipping. Using data on inter-regional flow connections, the positions of seventeen regions in the global shipping network are analyzed in terms of their traffic development, centrality, dominance and vulnerability. The East Asian, Northwest European and Europe Mediterranean regions have consistently held the highest positions, while East African and North African regions have held the lowest positions. By commanding the largest flows in the network, East Asia assumes a dominant position. The Australasian, North American West Coast, Northwest European and Southern African regions show an increasing dependency on East Asia. The analysis also identifies a few emerging regions that have had the highest growth rates in total traffic volume and connectivity for the studied period, namely South American North Coast, South American East Coast, West Africa, Southern Africa and West Asia. The empirical results of this paper supplement existing research on global shipping network evolution. One implication of the analysis is that the traffic growth of East Asia does not imply that, there is an equivalent improvement in its position in the global shipping network. The paper also shows that indicators from network analysis may be used to provide a more nuanced understanding of port-regional development than existing measures based solely on total traffic volume.     

The Nicaragua Canal: scenarios of its future roles

Connections between the Atlantic and Pacific oceans are vital for international trade. Since 1914, the Panama Canal has provided ships with a direct interoceanic canal for crossing the Atlantic and Pacific oceans. The geographical advantage of the Panama Canal allows it to enjoy an exclusive position in international seaborne trade. Passage demand through the canal has increased continuously since its opening, with about 12,000 vessels travelling through it in 2013. However, the Panama Canal’s monopoly in interoceanic canal operations may soon come to an end. In 2012, a memorandum of understanding was signed between the Nicaraguan Government and a Chinese investor to construct the Nicaragua Canal, which will be built about 400 nautical miles from the Panama Canal. It is expected that the Nicaragua Canal will be operational by 2020. The proposed canal will not only provide an alternative route for vessels to pass between the Atlantic and Pacific oceans, but will also trigger dynamic changes in seaborne trade patterns. To assess the long-term benefits of the proposed canal, we use a scenario planning method in this study to provide a framework for constructing several scenarios for 2030, 10 years after the anticipated construction of the canal. To develop the scenarios, we consider three macroscale drivers, namely politics, economics, and environment, and the causal relationships between them. Combinations of pairs of drivers are used to generate dominant scenarios to anticipate the role of the Nicaragua Canal with respect to future international trade. The analysis presented in this study will provide transport geographers and other major stakeholders with alternative mindsets into the future spatial changes in and development of maritime transport.     

The underlying drivers and future development of air cargo

Air cargo plays a crucial role in the air transport chain and in the globalized economy. As for other modes of transport, the demand for air cargo is a derived demand. Previous studies showed that the main determinants of air cargo demand are merchandise trade and the share of manufactures in merchandise trade. This paper aims to fill a gap in the existing literature by additionally taking the influence of air freight yields and oil prices into account when modelling the global air cargo development. Furthermore, it provides an insight into the future development of air cargo. Forecasts until 2023 are made based on a number of scenarios for the main determinants of air cargo demand. Moreover, an insight is provided into the current air cargo market, including traffic levels and different types of actors and traffic flows. The results are useful not only for academics but also for industry stakeholders for which air cargo is an important contributor to profit and/or cash levels.     

Urban gravity in the global container shipping network

While the spatial and functional relationships between ports and cities have been put in question in the last decades, the continued importance of urbanization and maritime transport in global socio-economic development motivates deeper research on their interaction. The global trade network is often studied at the country level and all transport modes included, concluding that distance remains a strong counterforce to exchange. This article wishes to detect whether the global container shipping network obeys similar properties at the city level. More than 2 million inter-port vessel movements between 1977 and 2016 are assigned to about 9000 ports and 4600 cities to run a gravity model on two different network topologies. Gravitational properties are found, as larger cities connect more with each other but less at distance. The degree of distance effects negatively expanded in 40 years, confirming the “puzzling” or reinforcing effect of distance, yet it varies greatly depending on node aggregation and network topology. We conclude that ports and cities continue to share important interdependencies, but these often rest on a detrimental physical transformation. A discussion is proposed about the underlying operational and theoretical mechanisms at stake. Keywords container shipping; gravity model; maritime trade; port cities; spatial interaction; world city networks.     

The benchmarking of airport performance

This paper examines how benchmarking is being used by airport managers as a means of internal performance comparison and improvement. Drawing on interviews with airport managers and a questionnaire survey of the world's top 200 busiest passenger airports, the paper discusses the nature, prevalence and consequences of current benchmarking practices in airports. The authors also include a review of the literature on airport benchmarking and a discussion of the characteristics and relevance of Best Practice Benchmarking.     

On the optimal environmental liability limit for marine oil transport

Recent changes in the US liability regime for oil pollution damage have intensified a policy debate about environmental liability limits. Economic theory suggests that some type of limit may be needed under certain conditions, and that such a limit should be set so that the marginal social benefit and cost are equal. However, it is unclear how a liability limit may be determined specifically for tanker shipping in US waters. We first examine conditions under which corner solutions (no liability or unlimited liability) are desirable. We then formulate a model to determine a socially optimal liability limit for oil pollution damage in US waters when a non-zero, finite liability limit is desirable. The model captures the tradeoff between less expensive energy supply and more stringent protection of the marine environment. Numerical simulations illustrate the properties of the model and major factors affecting the public policy decision regarding a liability limit.     

Celebrity livery featured aircraft,the Moneki Neko (fortune cat) of airlines

Aircraft livery is a painting scheme on the aircraft that allows an airline not only to differentiate its aircraft from those of others, but also to promote the perceived values of the airline. Besides being visually attractive, celebrity-themed aircraft liveries also become increasingly popular today because they can influence consumers' perceptions of airlines. This study uses the data collected from Taiwan international airport, ranked the world's top 15 heaviest passenger traffic, to investigate the influences of celebrity worship on the original Theory of Planned Behavior's constructs, and purchase intention. The results reveal significant positive relationships between celebrity and attitude, perceived behavioral control, and purchase intention. Finally, contributions and implications are discussed.     

Causal nexus between the transport and logistics sector and trade: The case of Australia

Although a number of studies have already been conducted on the economic impact of the development of the transport and logistics sector and international trade, these are regarded as two separated topics, and little has been done so far to study in depth the relationship between them. This paper seeks to shed light on this issue in the context of Australia. To this end, the vector autocorrelation (VAR) framework is employed to explore the causal relationship between Australia–China trade and the development of the Australian transport and logistics sector. This framework is then extended to allow for the effect of Australia's trade with the US, Japan, the rest of the world and other variables. Based on the analysis results, implications for the transport and logistics sector are discussed.     

Space-time dynamics: A modeling approach for commuting departure time on linked datasets

Commuters' departure time related decisions are important in time geography. Analytic tools have been proposed to capture the inherent choice determinants both in time and space. Although the dynamic aspects of the problem have been identified, most of the existing studies are based on static models. In this paper, a dynamic modeling framework is proposed to explore the relationship between commuters' departure time choices and the evolution of en route traffic. A data linkage method is developed to create an integrated dataset that enables the observation of commuters' reaction to changes in travel time and traffic conditions over time. A regional household travel survey is linked to travel information obtained from the Google Maps application program interface (API), creating a synthetic longitudinal dataset. Two decision rules are applied to model commuters' response to the evolution of traffic. The results indicate that travel time, distance to work location, flexibility in working schedule, expected arrival time, and commuters' sociodemographic influence departure time choices. It is also found that accounting for dynamics improves model fit and out-of-sample predictions. Both the dynamic model and the proposed data linkage method contribute to the understanding of human activities in space and time and can be used to enhance transportation demand analysis and urban policy studies.     

Estimating an origin–destination table for US imports of waterborne containerized freight

Containerized freight imports into the US are growing at an average of 10% per year. This traffic is concentrated at a small number of US seaports. It is therefore important to have an accurate understanding of the flow of containers from their origin country through these seaports to their final destination. This paper develops an optimization model to estimate route flows and a corresponding multi-modal origin–destination table for containers by synthesizing data on international trade and railcar movements with a gravity model for the demand of container traffic. This analysis provides insights into the balance of rail and truck inland transportation from each port.