Container Throughput Research Articles

Stochastic Frontier Analysis of Selected Nigerian Seaports Container Throughput’s Efficiency

This paper measures economic efficiency of container throughputs with the aid of input-output efficiency ratio of selected terminals across Nigerianseaports. Productivity of a terminal does not equal toits efficiency. Different efficiencies like allocative and technical characterized economic efficiency of a port system.Overall economic efficiency means there is no delay at the port in processing container as all ship, labour and machines are optimally utilized. This research determinedthe overall efficiencies of container throughputs Apapa, Warri, Onne, Calabal and Tin Can Island usingsecondary data (2012-2022) from Nigerian Bureau of Statistics oncontainer cargo throughputs in Nigeria. Total container outputsin (Tonnes) from different terminals with their corresponding inputs variables from number of ship per annum, cranes used and the dock workers net gang hour (ngh) were aggregated together in form of input-output ratio and arrived at each port’s level of overall economic efficiency. The analysis was executed with the aid of R using Stochastic Frontier Analysis(SFA)for each termina/seaport collected data. It was found from the results that;terminals at Onne are most efficient followed by Calabar. Tin can Island terminal efficiency was a slightly higher than that of Apapa as both had a little above average mean efficiency value. Warri terminals are the least while Rivers was not considered for unavailabilityof data. There may be other unexplained factors causing inefficiencies of mostly Apapa, Tin Can and Warri seaports not explained but can be investigated in future research.

Joint scheduling optimization model for yard cranes and AGVs considering running routes

The escalation in global consumer demand has prompted the continual expansion of container throughput, which drives container terminals to bolster their production capacities. Globally, ports worldwide have been adopting automated equipment and embracing digital operational environments to reinforce their logistics system efficiency and curtail transportation costs. Enhancement of the efficiency of container transportation at automated terminals depends on terminal loading and unloading operations. The efficiency of these operations directly hinges on the automated mechanical equipment deployed at terminals. Consequently, optimization of resource allocation and production scheduling of loading and unloading equipment at terminals has become an essential and effective approach. In this regard, automated yard cranes, which are responsible for rear-end handling, and automated guided vehicles (AGVs), which transport containers between the yard and the terminal quay, have been proven indispensable. This paper principally delves into the scheduling optimization of mechanical equipment in automated container terminal yards, with a unique focus on the coordinated scheduling optimization of yard cranes and AGVs while also accounting for AGV path planning. This research centers on the automated container terminal yard system and the challenge in yard crane scheduling. This work also establishes a grid-based terminal network model and validates the model and algorithm using practical examples. Optimal solutions are obtained for the joint scheduling of yard cranes and AGVs, accompanied by strategies on rational AGV path selection. The findings provide valuable references and theoretical underpinnings for operational scheduling and enhancement of the efficiency in container transport in automated container terminal yards. Furthermore, these results facilitate the overall improvement of production efficiency at automated terminals and the reduction of operational costs, thus carrying theoretical and practical significance.

Challenges and opportunities for Southeast Asia's container ports throughout the COVID-19 pandemic

The COVID-19 pandemic has had a profound impact on the Southeast Asian seaport system, with a decrease in container throughput and ship calls. However, the pandemic has also presented excellent opportunities for ports to increase competitiveness and market share, as some ports are weakened. This study will assess challenges and opportunities for container port development during the pandemic. The study analyses Southeast Asia's port system through three perspectives: market share gain/loss, changes in market concentration, and the relationship between market share gain/loss and efficiency. The study found that Vietnam and Malaysia's seaports have grown during the pandemic due to maintaining domestic production, increasing transportation demand, and changes in shipping routes. Moreover, small and medium-sized ports gain market share from larger ports, this leads to a decrease in the degree of concentration and shows their active participation in the regional transport network, providing more route options for shippers. The study also shows that while some seaports that gained market share were inefficient, some that lost market share were efficient due to the timely implementation of policies to cope with COVID-19. Finally, many ports are struggling to recover due to inadequate infrastructure, equipment, and low loading/unloading productivity, or facing unexpected risks.

Impact of Geopolitical Risk on International Trade: Evidence from Container Throughputs

It is of great importance for manufacturers and consumers that raw materials and products can be delivered on time without any disruption in the supply chain. The fact that production chains can be located in more than one country in the globalized world makes the smooth operation of the supply chain partially difficult. For this reason, especially suppliers may stop doing business with countries where geopolitical risk is high, and this may change the container traffic of countries. Therefore, this study empirically tests whether geopolitical risks change the container volumes of countries. Our sample includes 15 of the 19 countries in the world for which the geopolitical risk index is calculated because some values of the excluded countries are missing. The countries included are Argentina, Brazil, China, Colombia, India, Indonesia, Korea, Malaysia, Mexico, Philippines, Russia, Saudi Arabia, South Africa, Thailand, and Türkiye in alphabetical order. The period covered consists of 21 observations annually, covering the years between 2000 and 2020. The asymmetric causality test method was applied to consider the possible asymmetrical consequences of the geopolitical risk on the container trade in the countries. The panel causality test results obtained show that positive shocks in geopolitical risk cause negative shocks in container traffic. These results show that the security and stability of the countries around them are critical for the country's economy, as well as the security and stability of the countries themselves. Countries that want to grow commercially should develop their policies by considering regional security and stability.

Spillover effects from inland waterway transport development: Spatial assessment of the Rhine-Alpine Corridor

Inland waterways have the potential to enhance port-hinterland connectivity and foster sustainable freight transport. Their development as transport corridors is highly dependent on geography, yet spatial spillovers of port throughput are often overlooked. In Europe, the configuration of inland container terminals can lead to cross-border spillovers. This paper analyzes inland container throughput between 2007 and 2021 in the Rhine-Alpine Corridor to quantify its spatial dependence and economic spillover effects. The assessment involves 43 regions from Belgium, France, Germany, Netherlands, Luxemburg, and Switzerland. A Spatial Durbin Model is developed accounting for economic conditions, fixed effects, and time trends. The results suggest that throughput exhibited spatial concentration patterns, which intensified after water levels dropped in 2018. Second, the spatial dependence is heterogeneous between transport performance in tonne-km vs. TEU-km. Third, technological resources and population density were positively associated with throughput, while the opposite was found for employment and motorways. Notably, the spillovers of technological resources and employment were considerably higher than the local impact. Based on these findings, the paper advises on spatially oriented policies to address low water levels, workforce decline, and the need for new business models.

Measuring the causal effect of Panama Canal expansion on Latin America and the Caribbean's economic growth: a Bayesian structural time series approach

PurposeThis study provides empirical evidence on the impact of the Panama Canal expansion (PCE) on the economies of Latin American and Caribbean (LAC) countries, particularly in light of the emergence of larger container ships such as neo-Panamax and post-Panamax vessels.Design/methodology/approachThis study uses the Bayesian structural time Series (BSTS) model to evaluate the economic effects of the PCE on 21 countries within the LAC region. It utilized the World Bank's gross domestic product (GDP) figures between 2000 and 2019 as the primary variable, alongside the human development index (HDI) (X1), container throughput (TEU) (X2) and unemployment rates (UNEMPL) (X3) covariates. This allowed a precise and robust approach to analyzing time series data while accounting for uncertainties and allowing the inclusion of various components and external factors.FindingsThe findings revealed that the PCE has a positive and statistically significant impact on most countries within the Caribbean Transshipment Triangle, ranging from 9.2% in Belize to 46% in Cuba. This suggests that the causal effect of the PCE on regional economies was not confined to any specific type of economy or geographical location within the LAC region. Where the growth rates were statistically insignificant, primarily in some Latin American countries, it coincided with countries that are primarily driven by exports and service industries, where bulk and oil tanker vessels are likely to be the main carriers for exports rather than container vessels.Originality/valueThe practical implications of this research are crucial for various stakeholders in the maritime industry and economic planning. The factors influencing economic growth resulting from investing in maritime activities are vital for decision-makers to create policies that lead to positive outcomes and sustainable development in regions and countries with flourishing maritime industries. The methodology and findings have significant implications for governments, managers, professionals, policy-makers and investors.

A multi-variable hybrid system for port container throughput deterministic and uncertain forecasting

Container transport is the most environmentally friendly and sustainable way to transport bulk cargo currently. The accurate prediction of container throughput is of great significance to the operation of the port. It is directly related to the healthy development of the entire logistics system, and also serves as a reference for decision makers in the construction of port infrastructure. However, the container throughput sequence contains the influence and restriction of a variety of superimposed factors, and has the characteristics of nonlinear and non-stationary. Traditional technology cannot effectively capture the changes of external related factors. To make up for the deficiencies, a multi-variable hybrid deterministic and uncertain forecasting framework based on improved preprocessing technique and swarm intelligence optimizer is constructed. It not only considers the impact of port hinterland economic indicators, port transport system and transport capacity factors, but also calculates the upper and lower limits of container throughput under different probabilities. The results and tests show that mean absolute percentage errors obtained by the presented forecast system are 1.1551%, 2.0936% and 2.5546% respectively, and the prediction interval coverage probability values of 1 can be achieved. The hybrid system is effective, stable and has reasonable running time, which can be widely popularized. And it is conducive to the orderly operation of transportation industry and the development of container port cities.

Quantifying the impact of COVID-19 on Chinese ports

PurposeThe purpose of this study is to quantify port efficiency assessment indicators to analyze the impact of COVID-19 on Chinese One Belt One Road (OBOR) ports.Design/methodology/approachThis study utilized a grey prediction model GM(1,1) to forecast five relevant indicators for each of the 17 OBOR ports both with and without COVID-19 background conditions. Additionally, the data envelopment analysis (DEA) efficiency assessment approach was used to analyze the impact of COVID-19 on port efficiency.FindingsThe results indicate that cargo and container throughput growth rates during the COVID-19 pandemic are reduced by 1.7 and 2.1%, respectively. There was also a noticeable reduction in technological efficiency (TE) as well as pure technological efficiency (PTE), while scale efficiency (SE) remained largely unaffected. Furthermore, the dynamic efficiency MI was mainly negatively impacted by changes in overall efficiency change (EFFCH), where pure efficiency change (PECH) less than one contributed significantly towards overall regression of port efficiencies during this period.Originality/valueThis paper is unique in its use of a combination of the grey prediction model and DEA efficiency assessment to quantify changes in important indicators during pandemic periods. This approach not only provides a quantitative understanding of the impact on port-level efficiency through numerical quantification but also offers readers an intuitive understanding.

Chances and Challenges: Transformation from a Laser-Based to a Camera-Based Container Crane Automation System

In recent years, a steady increase in maritime business and annual container throughput has been recorded. To meet this growing demand, terminal operators worldwide are turning to automated container handling. For the automated operation of a crane, a reliable capture of the environment is required. In current state-of-the-art applications this is mostly achieved with light detection and ranging (LiDAR) sensors. These sensors enable precise three-dimensional sampling of the surroundings, even at great distances. However, the use of LiDAR sensors has a number of disadvantages, such as high acquisition costs and limited mounting positions. This raises the question of whether the LiDAR systems of automated container terminals (ACT) can be replaced with cameras. However, this transformation is not easy to accomplish and is explored in more depth in this paper. The field of camera-based container automation presented in this publication is largely unexplored. To the best of our knowledge, there is currently no automated container terminal in real-world operation that exclusively uses cameras. This publication aims to create a basis for further scientific research towards the goal of a fully camera-based container automation. Therefore, the authors present a narrative review providing a broad overview of the mentioned transformation, identifying research gaps, and suggesting areas for future research. In order to achieve this, this publication examines the fundamentals of an automated container terminal, the existing automation solutions and sensor technologies, as well as the opportunities and challenges of a transformation from LiDAR to camera.

An evaluation model of sustainable efficiency for container terminals

AbstractThe purpose of this paper is to evaluate the sustainable efficiency of container terminals (CTs). By the definition of United Nations Conference on Trade and Development (UNCTAD), business sustainable development includes three domains: Economics, Environment, and Society. Accordingly, based on the definition and the practical features of CT operations, this paper assesses sustainable efficiency for CTs from three perspectives: container throughput, CO2 emissions, and occupational safety. In this paper, a modality movement and a fuzzy grey relational analysis (GRA) approach are first proposed to estimate CO2 emissions and occupational safety index for CT operators, respectively. A hybrid slacks‐based measure (SBM)‐DEA model is then developed to assess the sustainable efficiency of CT operators. Finally, the CT operators in the Port of Kaohsiung are empirically investigated to validate the research model. Based on the results, theoretical and practical implications for the management of CT operators and port authorities are discussed.

Analysis of influencing factors and prediction of China’s Containerized Freight Index

China, as a major maritime nation, the China Containerized Freight Index (CCFI) serves as an objective reflection of the Chinese shipping market and an important indicator for understanding China’s shipping industry globally. The shipping market is a complex ecosystem influenced by various factors, including vessel supply and demand, cargo supply and demand relationships and prices, fuel prices, and competition from substitute and complementary markets. To analyze and study the state of the Chinese shipping market, we selected the CCFI as an indicator and collected data on six factors that may affect the overall shipping market. These factors include “ the China Coastal Bulk Freight Index(CCBFI)”, “the Baltic Dry Index(BDI)”, “the Yangtze River Container Freight Index”, “Global: Aluminum (minimum purity of 99.5%, London Metal Exchange (LME) spot price): UK landed price”, “Major Ports: Container Throughput”, and “Coal Price: US Central Appalachia: Coal Spot Price Index”. Then, we constructed an analyticaland predictive framework using Deep Neural Network (DNN), CatBoost regression model, and robust regression model to study the CCFI. Based on the R2 results of the three models, it is evident that DNN provides the best analytical and predictive performance for the CCFI, accurately forecasting its changes. Additionally, the robust regression model indicates that “Global: Aluminum (minimum purity of 99.5%, LME spot price): UK landed price” has the greatest impact on the CCFI. Finally, from a business perspective, we provide some suggestions for China’s container shipping industry.

Analysis of Carbon Emission Reduction at the Port of Integrated Logistics: The Port of Shanghai Case Study

With the goal of achieving carbon neutrality in the shipping industry, the issue of sustainable port development is becoming more and more valued by the port authorities. The shipping industry requires more effective carbon emission reduction analysis frameworks. This paper takes China’s Shanghai Port as the research object and analyzes it from the perspective of port-integrated logistics. Combined with the port data of Shanghai Port from 2008 to 2022, the principal component analysis gray correlation analysis model was used to screen the factors affecting the port’s carbon emissions, and three calculation models for Shanghai Port’s carbon emission sources were proposed. In addition, an expanded stochastic impact model based on the regression of population, affluence, and technology (STIRPAT) was constructed for the influencing factors of Shanghai Port’s carbon dioxide emissions and combined with the method of ridge regression to further identify important influencing factors. At the same time, a gray neural network model was established to predict the carbon emissions of Shanghai Port from 2021 to 2030 and compare them with their real value. The conclusion shows that there is a close relationship between Shanghai Port carbon emissions and container throughput, throughput energy consumption, number of berths, total foreign trade import and export, and net profit attributable to the parent company. Gray neural network model data calculations show that the growth rate of Shanghai Port’s carbon emissions will gradually slow down in the next ten years until the carbon peak is completed around 2033. The study can provide a reference for the sustainable development of other ports.

A Systematic Approach to Identify Shipping Emissions Using Spatio-Temporally Resolved TROPOMI Data

Stringent global regulations aim to reduce nitrogen dioxide (NO2) emissions from maritime shipping. However, the lack of a global monitoring system makes compliance verification challenging. To address this issue, we propose a systematic approach to monitor shipping emissions using unsupervised clustering techniques on spatio-temporal georeferenced data, specifically NO2 measurements obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor satellite. Our method involves partitioning spatio-temporally resolved measurements based on the similarity of NO2 column levels. We demonstrate the reproducibility of our approach through rigorous testing and validation using data collected from multiple regions and time periods. Our approach improves the spatial correlation coefficients between NO2 column clusters and shipping traffic frequency. Additionally, we identify a temporal correlation between NO2 column levels along shipping routes and the global container throughput index. We expect that our approach may serve as a prototype for a tool to identify anthropogenic maritime emissions, distinguishing them from background sources.

Effect of Supply Chain Risk on Port Container Throughput: Focusing on the Case of Busan Port

Effect of Supply Chain Risk on Port Container Throughput: Focusing on the Case of Busan Port

Stagnant logistics growth simulation on West African intermodal corridors

Despite Africa’s high economic growth rate, its logistics costs remain high, and many infrastructure projects and logistics policies are being implemented. Moreover, in Western Africa, where several economic communities have been established, logistics growth is still unstable due to civil conflicts and political changes. These factors are rapidly changing the logistics situation in Western Africa, and there is a need to identify changes in the competitiveness of countries and seaports that handle cargo to/from landlocked countries. The objective of this study is to quantitatively analyse the time-series changes in the logistics situation in West Africa applying the global logistics intermodal network simulation model to the African continent with different parameters by time points. Scenarios regarding political upheavals in Western Africa are examined to clarify the effect on the cargo flow of landlocked countries. The simulation results indicate that Côte d’Ivoire gets greater access to Burkina Faso if border facilities in neighbouring countries stagnate. Moreover, the absence of civil conflicts may raise the presence of Abidjan Port as a regional transhipment hub more prominent and increase its container throughputs. The findings of this study contribute to quantitatively visualising the impact of the events on the logistics situation in Western Africa, which can help formulate future logistics policies and development strategies.

An empirical study on the economic linkage characteristics of Yangtze River port cities based on discrete second-order derivatives

Abstract Rapid economic development cannot be achieved without a well-developed trade in goods of various forms, so it depends on the construction and development of coastal or inland ports. How to coordinate the relationship between ports and cities in the development process is of great significance to the sustainable development of port cities, and is also an important part of the current research on ports. This paper uses gray correlation model to study the correlation between city economic development indexes and port development indexes, and finds that the correlation between GDP and gross industrial output value and port cargo throughput is the largest, and on the basis of gray correlation analysis, the impulse response analysis finds that the growth of total economic volume and gross industrial output value of port cities has an obvious promotion effect on the development of ports in the short term. The research results show that the value added of Nanjing’s tertiary industry drives the port logistics of Nanjing port most significantly; the growth rate stabilizes at 0.006 after the 11th period. The growth of Nanjing port container throughput on the value added of Nanjing’s secondary industry changes most significantly and finally stabilizes at 0.0035.

Port container throughput prediction method based on SSA-SVM

To improve the prediction accuracy of the port cargo throughput and the applicability of the prediction model, and then provide data support for the port construction to meet the needs of port decision-making, take the monthly cargo throughput data of Shanghai Port from January 2009 to December 2022 as an example, use Pearson correlation analysis to screen 12 import and export impact factors. This paper improves the traditional SVM model, uses SSA (Sparrow Search Algorithm) to optimize the parameters c and g in SVM, and uses the model to predict. Compared with the model that uses the grid search algorithm to optimize the parameters of SVM, the model has a significant improvement in fitting and robustness, its predicted value is closer to the actual value, the prediction performance is better, and it can better reflect the actual state of the port.

Resilience Evaluation of Ports along the Maritime Silk Road from the Perspective of Investment and Construction

Since the establishment of the “Belt and Road” initiative, the investment and construction of ports along the 21st Century Maritime Silk Road have received extensive attention from the international community. The evaluation of ports is of great significance to investors’ investments and construction of ports around the world, so it is very necessary to establish a reasonable port evaluation system. At present, there are few studies on defining and evaluating port resilience, and the existing port evaluation index system has defects. Therefore, according to the similarity between cities and ports, this paper introduces the concept of “three-dimensional space” and the “system of systems” theory of cities and divides the resilience of ports along the Maritime Silk Road into three-dimensional spaces of “physical-society-information.” The CRITIC-entropy method and the TOPSIS method constructed a port resilience evaluation model along the Maritime Silk Road and quantitatively evaluated and analyzed the comprehensive resilience and subspatial resilience of 28 ports along the 21st Century Maritime Silk Road. The results show that the route network port degree, the annual throughput of the port container, and the number of fixed broadband subscribers per 100 people are the key indicators that affect the port’s physical space resilience, social space resilience, and information space resilience. Also, coordinated physical, social, and information spatial resilience development plays a catalytic role in improving overall resilience. Therefore, the investment of ports along the Maritime Silk Road should adopt corresponding and more targeted investment plans according to the actual resilience of each port. The research provides new ideas and directions for investors to invest in port construction and has certain practical guiding significance for the increase of investors’ income and the sound development of the national economy.

Effective multi‐step ahead container throughput forecasting under the complex context

AbstractAccurate and effective container throughput forecasting plays an essential role in economic dispatch and port operations, especially in the complex and uncertain context of the global Covid‐19 pandemic. In light of this, this research proposes an effective multi‐step ahead forecasting model called EWT‐TCN‐KMSE. Specifically, we initially use the empirical wavelet transform (EWT) to decompose the original container throughput series into multiple components with varying frequencies. Subsequently, the state‐of‐the‐art temporal convolutional network is utilized to predict the decomposed components individually, during which an improved loss function that combines mean square error (MSE) and kernel trick is employed. Eventually, the deduced prediction results can be obtained by integrating the predicted values of each component. In particular, this research introduces the MIMO (multi‐input and multi‐output) strategy to conduct multi‐step ahead container throughput forecasting. Based on the experiments in Shanghai port and Ningbo‐Zhoushan port, it can be found that the proposed model shows its superiority over benchmark models in terms of accuracy, stability, and significance in container throughput forecasting. Therefore, our proposed model can assist port operators in their daily management and decision making.

Research on the effect of number of yard trucks on container terminal throughput

Container terminal productivity is a benchmark for the level of effectiveness of a container port. One indicator of container terminal productivity level can be calculated through yard throughput. Several factors affect yard throughput, one of which is the number of truck terminals. This study aims to investigate the effect of the number of truck terminals on yard throughput at a container terminal. The investigation was conducted using a container terminal simulation which was based on the discrete event simulation method. As a case study, a simulation of a container terminal with a dock length of 300 m with several quay cranes was two units. The simulation was done by parameters adding the number of truck terminals and variations in the capacity of ships coming. The results of the simulation show that an increase in the number of truck terminals affects the number of outputs, depending on the size of the loading and unloading vessels. From the simulation results obtained, the largest yard throughput capacity of 809 containers with the number of truck terminals is 8 units on a shipload of 1,000 twenty-foot equivalent units. The results of this study provide an overview of the needs of the truck terminal in the container terminal. Highlights The yard throughput of the container terminal has been investigated by a simulation model built based on a discrete event simulation The discrete event simulation has obtained the effect of increasing the number of truck terminals on the yard throughputs with container capacity variations from 200 - 1,000 TEUs The increase in speed at the truck terminal is insignificant to increase yard throughput and necessary to do integrated scheduling between the truck terminals, quay cranes, and gantry cranes The increase in the quay crane operation in container terminals will decrease the dwell time of container throughput