Port Efficiency Research Articles

The spatial spillover effect and its attenuation boundary of urban economy on port efficiency.

Cities are commonly recognized as the immediate hinterland of ports and play a crucial role in fostering the sustainable development of ports. Therefore, it is imperative to investigate the influence of cities on ports. By employing panel data from 2001 to 2021 for both ports and cities in the Bohai Rim region, this study examines the spatial spillover effect of urban economy on port efficiency using the spatial error model (SEM). The findings show that urban economies have a significant spatial spillover effect on port efficiency, but this effect diminishes across different spatial matrices. In particular, the geographical matrix demonstrates a stronger spatial spillover effect of the urban economy on port efficiency. These research findings help to establish a collaborative mechanism for port-city development and provide useful insights for government management decision-making.

Enhancing OCR with line segmentation mask for container text recognition in container terminal

Optical Character Recognition (OCR) plays a pivotal role in enhancing the operational efficiency of container ports. However, challenges such as angle limitations and the complexity of container fonts in traditional OCR systems lead to tilted text and text adhesion, thereby reducing the recognition rate. Recognizing containers at a high speed is equally crucial for port operations. In this study, we address these challenges by introducing an Enhanced OCR (EOCR) system, incorporating Line Segmentation Mask (LSM)-based detection and Scanline-based recognition. LSM tackles the issue of text adhesion caused by traditional segmentation, while recognition based on scan lines accelerates efficiency. Additionally, we propose the arbitrary angle quadrilateral fitting algorithm targeting sloping quad areas in images taken at a container terminal. Experimental results on a dataset of container images from the Shanghai Port demonstrate superior performance compared to existing algorithms, achieving a recognition accuracy rate of up to 98.7%. Furthermore, an ablation study confirms that our EOCR significantly enhances recognition accuracy while ensuring real-time performance.

Factor analysis method for delay dynamics in Nigerian Tin Can Island Port for sustainable development

The effect of efficient and effective port system on the economy viability of any nation cannot be over emphasis. This study investigated factors that could be termed as delay causative factors in Nigerian ports industry using TIN CAN Island port complex as a case study. A well-structured questionnaire was developed for this research and 72 respondents, who are port users (custom officers, employees, and customers), were asked to rank the variables perceived to be causing delay at the port according to their respective perception of the effect of each factor on delay factors at the port. The validity of the research instrument was done using Cronbach Alpha. There are several factors that were thought to be working together in reducing efficiency in Nigerian ports and these factors were analyzed using factor analysis method. It was discovered from the analysis that Lack of Government Authority, Ullage Constraint, Inadequate Berthing, Logistics Delay, Financial Constraint and Equipment Breakdown are major factors that cause delay at Tin Can Island Port Lagos. These highlighted factors should be paid special attention in order to reduce delay in Tin Can Island port which will in turns lead to more revenue for the country.

Contribution of the Central Corridor Transport on the Tanzanian Economic Growth

This study investigates the influence of intratrade within the Central Corridor, the effect of port cargo volume, and infrastructure expenditures on Tanzania's economy. Using quarterly data from 2001 to 2021 using the Ordinary least squares model, we found a positive relationship between cargo volume and economic growth, as well as a significant positive effect of intra-trade on the economy. However, budgetary infrastructure spending and exchange rates had insignificant impacts. The study suggests that the government should enhance regional business ties, improve port efficiency, and support corridor infrastructure development.

Competitiveness and Logistics Performance Index: How does the infrastructure pillar perform in ASEAN countries?

This paper examines the impact of strategic sub-components of the Global Competitiveness Index (GCI) on the Logistics Performance Index (LPI), positing a correlation between the LPI and selected GCI factors, specifically within the infrastructure domain—namely, the indicators of Road Quality, Rail Service Efficiency, Port Efficiency, Air Transport Efficiency, and Electrification. The objective is to identify which indicators within the infrastructure sector most significantly affect the Logistics Performance Index. In this study, the LPI is the dependent variable, while the five previously mentioned competitiveness indicators act as independent variables. Top of Form A panel data regression analysis was employed to evaluate how these independent variables influence the dependent variable. The data for this study were derived from the World Bank, specifically the LPI of the World Bank and the World Economic Forum, covering countries in the ASEAN region from 2012 to 2020. The findings indicate that, among the five indicators, Port Efficiency significantly impacts the Logistics Performance Index in the ASEAN region. Furthermore, both Air Transportation Efficiency and Electrification significantly influence the Logistics Performance Index. Conversely, Road Quality and Rail Service Efficiency do not significantly affect the Logistics Performance Index in the ASEAN region.

Analysis of the Network Efficiency of Chinese Ports in Global Shipping under the Impacts of Typhoons

With the increasing volume of international trade and maritime demand, the requirements for the stability and reliability of the global shipping system are also increasing. The research on the network efficiency of Chinese ports for global shipping can not only examine the importance of Chinese ports in the shipping network but also find out the aspects that need to be improved in the construction of the port’s climate adaptability in the resilience assessment to strengthen port construction and further improve the efficiency of the network. The current study builds a shipping network based on RCEP and systematically examines the key ports in China within the networks. The research paper aims to improve the resilience of the ports and the whole shipping network in response to typhoon disasters. As such, this paper focuses on shipping research based on complex networks and network multi-centricity analysis, followed by a ranking of ports. Firstly, this paper uses UCINET 6 software to build a global shipping network. Such a network evaluates the centrality of ports, calculates the degree of centrality, proximity to centrality, and centrality, and scores them according to the ranking. Then, it selects the top 20 ports in China according to the ranking and researches network efficiency for the listed ports considering the typhoon risks. The analysis of network robustness, average shortest path length, and network efficiency are carried out for the shipping network and China’s essential port nodes in the network. According to the experimental results, no matter the robustness, average shortest path length, or network efficiency, when the important ports of China in the shipping network are affected, they will cause different degrees of impact, and the performance loss caused by multiple ports is higher than that of a single port. They emphasise the significant impact of typhoons on multiple ports and remind people to minimise losses as much as possible based on experimental results, ensuring the stable operation of ports and improving resilience in typhoon prevention under the changing climate. Additionally, they provide a solid foundation to further sustain global shipping network resilience.

Multi-element integrated design of marine landscape in sustainable smart ports

In the era of economic globalization and heightened international competition, the emergence of free trade zones has significantly increased regional openness, introducing both new opportunities and challenges for ports. This paper proposes the enhancement of intelligent design in the maritime landscapes of smart ports, with a focus on optimizing internal pathways and developing a predictive model to gauge the impact of smart port landscapes. Furthermore, the study delves into the assessment of risks in smart port supply chains, employing an innovative approach that integrates rough set theory and neural networks. This novel model significantly improves the accuracy of risk evaluation in port supply chains, thereby providing crucial decision support for port management. Additionally, the economic efficiency of smart ports is scrutinized using the Data Envelopment Analysis (DEA) Malmquist index method. Through meticulous selection of research subjects, port efficiency indicators, and the DEA Malmquist index, this analysis offers a comprehensive insight into the economic operations of smart ports. This research not only offers guidance for port economic management but also establishes a framework for the sustainable development of smart ports, thereby ensuring their long-term viability.

An integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port of Bangladesh

An integrated intermodal freight transportation system is a derived demand to transport shipping containers from/to the seaport to/from the hinterland, instead of undertaking cargo loading and unloading activities in port-protected areas. The concept of the intermodal system is to transfer containers to nearby hinterland nodes, such as dry ports, inland rail, road, and river terminals as a part of port development, as well as increasing port efficiency and productivity. Lloyd’s List ranked Chattogram Port as the 67th busiest container port in the world as per container port throughput in 2022. Chattogram Port has small-scale intermodal facilities for off-docks/ICDs in the port city only. In addition, a pure intermodal system has been developed by one rail ICD in the capital city, Dhaka, and two RICTs nearby Dhaka, but less than 5 % of port throughput. A large-scale intermodal for serving the major cities, SEZs, EPZs, and industrial areas is absent due to planning and policy problems, as well as the unavailability of intermodal infrastructure and network. Due to an improper hinterland intermodal chain, the port faced container supply chain disruptions at the port yard and exceeded port capacity, resulting in container vessel congestion at the outer anchorage of Chattogram Port. By developing rail and road infrastructure, and utilizing natural river connectivity, it is possible to develop road, rail, and river intermodal systems, and shape an integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port. To develop an integrated intermodal system, this research chose a quantitative research methodology for port throughput data analysis and forecasting future throughputs that are advanced to the intermodal model for Chattogram Port. Overall, this paper aims to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness actively. Highlights Intermodal system is a derived demand for managing hinterland and port terminals of a seaport that needs to be implemented in Chattogram Port Container supply chain disruptions to be avoided to increase the port productivity and efficiency Inland intermodal connectivity will help to increase hinterland of a seaport It is necessary to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness globally

Changes in efficiency and physical size of container ports: An integration of genetic matching and stochastic data envelopment analysis

Benchmarking container ports of different physical sizes and figuring out the relationship between size and efficiency is complex due to the heterogeneous environment. In dealing with heterogeneity, the selection bias is often overlooked. Therefore, this study proposes an integrated multivariate genetic matching and stochastic DEA algorithm to evaluate the efficiency of container ports. It paves the way for container ports that differ in a selected feature, such as size, to be benchmarked using well-balanced clusters. Thus, the port managers can identify the most similar-featured peers in benchmarking with DEA or alternative models to acquire robust estimates without dependence on a longitudinal data set. The results of the model applied to international container ports imply the increase in size impacts efficiency negatively, while connectivity does positively, which contradicts the commonly held perception of stakeholders that the larger the container ports, the more efficient. That is, well-managed small container ports can also be as efficient. Therefore, it is concluded that the results of integrating genetic matching into the performance measurement provide beneficial inferences. In future research, clustering the observed container ports according to a specific feature and balancing clusters with multivariate genetic matching can provide valuable insights into the industry.

BESOINS ET DÉFIS D’INTÉGRATION POUR UNE TRANSFORMATION VERTE ET INTELLIGENTE DE L’INDUSTRIE PORTUAIRE BASÉE SUR DES DONNÉES MULTI-SOURCES

This research explores the integration needs and challenges for achieving green and smart transformation in the port industry, leveraging multi-source data and geographic information technology. The study utilizes comprehensive data, including information from the National Enterprise Credit Information Publicity System, the National Catalogue Service for Geographic Information, and road network maps of Jiangsu Province in China. Geographical analysis methods, such as weighted kernel density estimation and standard deviation ellipse analysis, are employed to identify spatial distribution patterns and changes in the port and shipping service industry. The results indicate a spatial distribution pattern with weak expansion from the center, along the "northwest-southeast" direction. Challenges such as decentralized management and competition for interests hinder port integration for sustainable development. By understanding the spatial dynamics, policymakers can make informed decisions for a greener, smarter, and more efficient port sector.

Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: a DEA approach

Container ports play a pivotal role in international trade, facilitating the movement of goods and fostering economic development. While much attention has been given to the efficiency of ports in high-income countries, container ports in lower-middle-income (LMI) countries have received less attention. This paper addresses this research gap by assessing container ports' operational efficiency across diverse LMI countries and determining ways for their efficiency enhancement and management optimization. The cross-sectional data for the year 2012 was collected for 53 container ports in LMI countries. This research utilizes data envelopment analysis, which offers the advantage of considering multiple inputs and outputs. The results show that the overall technical inefficiencies of LMI countries' container ports are mainly due to pure technical inefficiency rather than scale inefficiencies, and the most efficient ports have a combination of large and hub ports. They also reveal that larger ports (as measured by throughput) are not necessarily more efficient than ports with a small production scale. The results of this research can provide government authorities, port authorities, terminal operators, and investors with valuable insights into resource allocation, competitive advantage, and optimization of operating performance.

Estimating the impact of container port throughput on employment: an analysis for African countries with seaports

Ports play a significant role in facilitating international trade and economic development, serving as vital gateways for the movement of goods across the continent and beyond. As global trade volumes continue to rise, efficient port operations hold the potential to not only enhance economic growth but also contribute significantly to job creation across various sectors of the economy. This paper examines the impact of container port throughput on employment in Africa and further tests whether causality runs from employment to container port throughput. To do so, we use a sample of 27 African countries with seaport and data spanning the period from 2010 to 2020 for the analysis. The system- Generalized Method of Moments (SGMM) estimation technique is used as the estimation strategy. We use service, industrial, and total employment percentages of the total population as proxies for employment while annual container throughput measured in Twenty foots Equivalent Units (TEUs) is used as an indicator for port throughput. Based on the empirical results, we establish a positive significant effect of port throughput on employment in Africa. We further show that bidirectional causality exists between port throughput and employment in Africa. Following these findings, we recommend policies that increase port throughput in Africa.

The effects of waiting times on the bunkering decision for tramp ships

This study explores the influence of uncertain waiting times together with uncertain fuel prices, in the selection of bunker fuel stops for a shipowner engaged in tramp shipping. We analyze the stochastic bunkering waiting times in the bunkering optimization problem using scenarios constructed from vessels' Automatic Information System (AIS) records and test their relevance to the bunkering decision. Our findings highlight the tradeoff between port efficiency, as characterized by waiting times, and the economic advantages of purchasing bunkers from cheaper port options and finishing the voyage in higher-priced bunker regions. Although the absence of waiting time would have produced similar results in our empirical setup, introducing waiting times altered the dynamics, making a price-attractive port like Piraeus not as attractive when risk-aversion is modeled, particularly given the risk of prolonged waiting.

Understanding vessel noise across a network of marine protected areas

Protected areas are typically managed as a network of sites exposed to varying anthropogenic conditions. Managing these networks benefits from monitoring of conditions across sites to help prioritize coordinated efforts. Monitoring marine vessel activity and related underwater radiated noise impacts across a network of protected areas, like the U.S. National Marine Sanctuary system, helps managers ensure the quality of habitats used by a wide range of marine species. Here, we use underwater acoustic detections of vessels to quantify different characteristics of vessel noise at 25 locations within eight marine sanctuaries including the Hawaiian Archipelago and the U.S. east and west coasts. Vessel noise metrics, including temporal presence and sound levels, were paired with Automatic Identification System (AIS) vessel tracking data to derive a suite of robust vessel noise indicators for use across the network of marine protected areas. Network-wide comparisons revealed a spectrum of vessel noise conditions that closely matched AIS vessel traffic composition. Shifts in vessel noise were correlated with the decrease in vessel activity early in the COVID-19 pandemic, and vessel speed reduction management initiatives. Improving our understanding of vessel noise conditions in these protected areas can help direct opportunities for reducing vessel noise, such as establishing and maintaining noise-free periods, enhancing port efficiency, engaging with regional and international vessel quieting initiatives, and leveraging co-benefits of management actions for reducing ocean noise.

The effects of the COVID-19 pandemic on connectivity, operational efficiency, and resilience of major container ports in Southeast Asia

The COVID-19 pandemic in 2020 has had significant impacts on the connectivity and performance of container ports in Southeast Asia. The application of social network analysis (SNA) in conjunction with key indicators, such as container throughput, total capacity of ships, number of ship calls, and berth duration, provides a comprehensive understanding of the development of the regional port system. While major ports in the region, namely Singapore, Port Kelang, Manila, and Laem Chabang, have exhibited signs of recovery owing to the expeditious and timely implementation of targeted policies to mitigate the adverse effects of the pandemic, smaller ports in the region, such as Bangkok, Penang, Tanjung Priok, and Tanjung Perak, are grappling with enduring repercussions and encountering challenges in resilience. These challenges stem from inadequate infrastructure, limited accommodation capacity, low loading/unloading productivity, and other significant risk events associated with the pandemic, all of which have weakened their competitiveness. In contrast, ports in Vietnam, including Cai Mep, Hai Phong, and Ho Chi Minh, as well as Malaysia's Tanjung Pelepas, have demonstrated that they are less impacted by the COVID-19 pandemic. This can be attributed to the sustained growth of their respective economies and the continued surge in domestic production to meet the unabated demand for exports. Based on these findings, several policy recommendations can be suggested for port authorities to effectively manage and mitigate the impact of risky events, such as pandemics, in the future while also enhancing the competitiveness of ports.

Enhanced Mild-Slope Wave Model with Parallel Implementation and Artificial Neural Network Support for Simulation of Wave Disturbance and Resonance in Ports

Ensuring sea surface tranquility within port basins is of paramount importance for safe and efficient port operations and vessels’ accommodation. The present study aims to introduce a robust numerical model based on mild-slope equations, capable of accurately simulating wave disturbance and resonance in ports. The model is further enhanced by the integration of an artificial neural network (ANN) to address partial reflection, and its efficiency is optimized by developing a parallel algorithm based on OpenMP, allowing for a reduction in the required simulation times for real port areas spanning several kilometers horizontally. Numerous numerical experiments focusing on wave reflection against a vertical wall were conducted to develop the ANN. This neural network was designed to determine the appropriate value of the eddy viscosity coefficient, a crucial parameter in the momentum equation of the mild-slope model, tailored to incident wave characteristics. The model’s validity was confirmed through rigorous validation against experimental measurements, covering wave disturbance, rectangular harbor resonance, and Bragg resonance. The model consistently demonstrated a more than satisfactory performance across all considered scenarios. In a practical application, the model was deployed in the Port of Rethymno, Crete Island, Greece, effectively capturing and describing dominant phenomena within the port area. The implementation of a parallel algorithm significantly reduced the simulation times by ~92%, compared to the serial algorithm, thereby enhancing the model’s efficiency and applicability in real-world port environments.

Nonparametric estimation of allocative efficiency using indirect production theory: Application to container ports in Norway

AbstractAdaption to prices is an important feature of productivity development. This paper proposes an extension of the StoNED model to accommodate estimation of allocative efficiency. It demonstrates how indirect production theory is suited for assessing allocative efficiency and helps alleviating the curse of dimensionality for stochastic nonparametric estimators compared to conventional measures of allocative efficiency. Furthermore, the paper elaborates on the appropriate cost of capital for the estimation of allocative efficiency. The proposed model framework is utilized to study allocative efficiency of Norwegian container ports, thereby adding to the literature on seaport terminal efficiency studies.

Vessel turnaround time prediction: A machine learning approach

Uncertainty in vessel turnaround time (VTT) is troublesome and would reduce the operational efficiency in port management, potentially causing economic losses. Despite vessels generally providing their estimated departure time (EDT), there is frequently a considerable difference between the EDT and the actual departure time (ADT) of vessels due to various factors such as unexpected port handling inefficiency. This variability complicates the coordination of efficient port operations. Our research aims to address this issue by employing an extreme gradient boosting (XGBoost) regression model to predict the VTT, using vessel arrival and departure data at the Hong Kong Port for the year 2022 and the first quarter of 2023. The proposed machine learning approach can provide more accurate predictions on VTT on average compared to the EDT data reported by vessels themselves, with a substantial reduction in both mean absolute error (MAE) and root mean square error (RMSE) of 23% (from 5.1 h to 3.9 h) and 24% (from 8.0 h to 6.1 h), respectively. These results present a significant leap forward in the predictive capabilities for the VTT and lay the foundation for further research into improving vessel scheduling efficiency, reducing port congestion and enhancing overall port performance.

Analysis of Internal and External Factors Affecting Liquid Chemical Cargo Port Efficiency

The measurement of port efficiency is a crucial requirement in the maritime sector and has been the subject of numerous studies due to its direct impact on international trade. The methods used to determine port efficiency vary depending on the characteristics of the operations under investigation. Depending on which port operations are assessed, port adequacy can be measured in various ways. In the literature, it is evident that port efficiencies are mostly determined using numerical methods. However, when analyzing port efficiency, measuring it solely through numerical processes can lead to misleading results in some cases. To avoid this, it is necessary to analyze non-numerical internal and external factors that affect port efficiency. In this study, non-numerical internal and external factors influencing port efficiency in liquid chemical cargo ports were identified through a literature review and by experts. The identified factors were evaluated through surveys conducted with experts specializing in liquid chemical cargo ports. The survey results were analyzed using SPSS 21.0 statistical software. According to the results obtained from the surveys, factors such as the location and dimensions of the port area, the adequacy of hinterland connections and logistic facilities, well-organized physical surroundings of the port, the use of technological innovations, and the proper functioning of the quality control system were identified as significant factors affecting port efficiency. In addition to these factors, accurate job analysis in the port, satisfactory wages, sufficient education levels, and morale of port personnel were also found to be crucial factors influencing port efficiency. 
 
 Keywords: Port efficiency, Liquid chemical cargo ports, Port analysis, Efficiency analysis

Contextual Comparative Analysis of Dar es Salaam and Mombasa Port Performance by Using a Hybrid DEA(CVA) Model

Background: This research conducts a contextual comparative analysis between Dar es Salaam and Mombasa ports, employing a hybrid data envelopment analysis (DEA) model that integrates the contextual value-added approach (CVA). The assessment incorporates various inputs (quay length, number of cranes, and storage area) and outputs (number of ship calls and cargo throughput) to compute efficiency scores, offering nuanced insights into the strengths, weaknesses, and areas for improvement of both ports. Methods: The hybrid DEA model with CVA is applied to calculate efficiency scores, considering the diverse inputs and outputs. This approach allows for a comprehensive evaluation of the relative performance of Dar es Salaam and Mombasa ports. The study also explores the influence of trade-related externalities on port efficiency, providing a holistic understanding of the factors shaping the ports’ operational effectiveness. Results: The efficiency scores depict distinctive performance trends between Dar es Salaam and Mombasa ports. Notably, Dar es Salaam exhibits maximum efficiency (efficiency value of 1) in 2018 and 2021, while Mombasa attains optimal performance (efficiency value of 1) in 2021. However, efficiency values fluctuate for both ports in other years, ranging between 0.895 and 0.985 for Mombasa and 0.924 and 0.960 for Dar es Salaam. Conclusions: This study highlights the dynamic efficiency levels of Dar es Salaam and Mombasa ports over multiple years and identifies critical factors influencing their performance. The findings contribute valuable insights to the field of port analysis, offering guidance to port management and policymakers in optimizing the efficiency and competitiveness of these vital maritime hubs.