Analysis of Global Competition in Container Port Performance Using the LOPCOW-CRADIS Integrated Method

This thesis aims to develop a new framework of container port/terminal performance measurement, modelling and analysis. There is a need for a new performance measurement framework not only to meet the need of port stakeholders, but also to develop diagnostic tools capable of supporting decision-making in complex port/terminal operations in an uncertain environment. This study follows the related questions of ‘what to measure’, ‘how to measure’ and ‘how to control and improve’ container port performance. In this regard, this study proposes the development of a systematic approach to address the multi-stakeholder dimension in port performance measurement. This was achieved by integrating a multi-stakeholder dimension in a port performance measurement framework which takes into account the corresponding port performance indicators (PPIs). To this end, this study identified six dimensions of crucial interests in major (container) ports investigating stakeholders’ goals and objectives, and discussed them with port stakeholders. The six dimensions defined in this study cover the range of port activities to cope with new evolutionary changes, to measure and communicate their impacts on society, economy and environment and to be consistent with their goals. Then, through a literature review and an analysis of industrial practices the associated PPIs were selected. The semi-structured interviews were applied to assess the suitability of the potential indicators and to test the feasibility of the selected indicators. The multi-stakeholder dimension involves both quantitative and qualitative PPIs in order to reflect complexity of port/terminal business environments. This study develops two hybrid port performance measurement models: PPIs independency model and PPIs interdependency model. In the first port performance measurement model, a hybrid approach of the Analytic Hierarchy Process (AHP) and Fuzzy Logic based Evidential Reasoning (FER) for solving multiple criteria decision making (MCDM) problems is applied to address the challenges in port performance measurement. AHP is applied for a part of the FER to evaluate the relative importance of the selected PPIs. FER is applied for dealing with uncertainties presented in the evaluations of the selected PPIs as well as aggregation of the evaluations of PPIs and their importance. An analysis of 12 container terminals in South Korea is conducted to validate the proposed method. The second approach, a new conceptual PPI interdependency model, is developed using a hybrid approach of a Fuzzy Logic based Evidential Reasoning (FER), a Decision Making Trial and Evaluation Laboratory (DEMATEL) and an Analytic Network Process (ANP). These methods are combined to deal with the inherent data uncertainties and the interdependencies among the port performance indicators (PPIs). Its novelty lies in its capability of dealing with interdependency among the performance measures as well as accommodating both qualitative and quantitative evaluations on the measures simultaneously. An analysis of 4 major container ports in South Korea is conducted to demonstrate the feasibility of the proposed method. The empirical investigations are conducted by taking the perspectives from different port stakeholders. For instance, the quantitative data (i.e. cargo and vessel operations and financial data) are collected directly from terminal operating companies and information systems/databases managed by port authorities, government and credit rating agencies. The qualitative PPIs are collected using questionnaires from three groups of terminal operators, users (i.e. shipping lines, shippers, logistics service providers and freight forwarders) and administrators (i.e. port authority and government) to assess their own associated PPIs to measure each container port/terminal performance. The empirical results indicate that the hybrid approach attempting to use quantitative modelling for dealing with the uncertainties and interdependency problems can be successfully fulfilled. The framework and its supporting method suggest an effective performance measurement tool and offer a diagnostic instrument to ports/terminals to satisfy the port stakeholders in a flexible manner. Finally, this thesis proposes a decision making framework for prioritising and selecting port performance improvement strategies. It can be achieved by the concepts of benchmarking-best practices using the analytic hierarchy process (AHP) incorporating a fuzzy order preference by similarity to ideal solution (FTOPSIS) method. Based on the results obtained from the two performance approaches, the leading performer (i.e. Busan New Port) and the poor performer (i.e. Busan North Port) are analysed as real cases to demonstrate the feasibility of the proposed methodology. The results yielded by the framework present the ranking of strategy options in terms of their preference to different terminal operating companies (TOCs), which enables decision makers to find optimal solutions to improving performance under their own dynamic business environments.

A major goal for port authorities, operators, and investors is to achieve efficient operations and effective environmental protection. This is because the environmental performance of a container port is important for its competitiveness and sustainable development. However, the container ports along the Maritime Silk Road (MSR) have caused numerous problems with the rapid development, among which the most significant problem is environmental pollution. In this paper, we aim to measure and compare the environmental performance and operational efficiency of ten major container ports along the MSR, including the ports of Shanghai, Hong Kong, Singapore, Kelang, Laem Chabang, Colombo, Dubai, Barcelona, Antwerp, and Hamburg. We develop an improved, inseparable data envelopment analysis (DEA) model with slack-based measures (SBMs) to evaluate and compare the environmental performance and operational efficiency, and we incorporate the desirable output of container throughput as well as the undesirable output of CO2 emission. Our results show that. Overall. these container ports perform better in terms of operational efficiency than environmental performance. We also provide insights for management and policy makers for container ports with different levels of operational efficiency and environmental performance.

Purpose- Ports have a leading role on affecting country and regional economy with the development of international trade. With the world trading volume increasing day by day the performance of ports and terminals, which provide export, import, transit, local or regional transportation services, must be examined regularly in order for their maximum capacity to be utilized. Furthermore, due to the high costs of infrastructure and superstructure investments of container ports, long term plans and strategies are required. This study aims to evaluate the performance of 20 container ports operating in Turkey by examining the performance criteria of container ports in the world. Methodology- For this reason, when calculating the maximum capacity utilization of the ports, the main principle is to examine the effective utilization of all the inputs using various methods. In this study, the performance of 20 container ports operating in Turkey, has been analysed with the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, using non-financial data from 2015. Findings- As a result of the analysis, the values that show the overall performance of the ports were converted into a single score with the help of the TOPSIS method and port performances were evaluated by comparatively examining the results obtained. Mersin port, Ambarli Marport and Kumport derived first with the highest performance. Conclusion- Port performance measurement has an important requirement for maritime transport. The high performance of container ports improve the productivity of the production such as labour and capital.

Container ports expect more competitive advantages and performance improvement on their extinctive logistics capabilities in the circumstance of ongoing integration of supply chain and port fields. Whereas, the connotation and denotation of port logistics capabilities and port performance have been undergoing significant changes. Meanwhile, the competition between container ports is presented in multitiered and wide-ranging arena. This research focuses on container ports and conceptualizes port logistics capability from five dimensions (positioning, integration, infrastructure, operation and agility) and port performance from four aspects (productivity, finance, social and satisfactory performance), then tests the relationships among port logistics capability, competitiveness advantages and performance. Data from 30 container ports and 181 responses and results from structural equitation modeling indicate that the comprehensive improvement of port logistics capability can directly raise port efficiency and effectiveness performance concurrently. Moreover, via the competitiveness advantages in market, port logistics capability has an indirect positive impact on performance.

Container ports play a crucial role in global maritime trade by serving as key transportation hubs for the movement of goods. Their performance differs due to unique local characteristics, creating a need for benchmarking to improve. Trends in trade patterns, supply chains and maritime transport operations can substantially impact on the cargo handling requirement at ports and therefore port performance. The aim of this research is two-fold; first, to examine the current situation, main trends and disruptions affecting maritime container transport and ports, and second, to investigate the key criteria for assessing and benchmarking port performance. Regarding the first objective, for the investigation of the global trends in the liner shipping and container port sector, desk research is performed. Regarding the second, a framework is developed by identifying five areas of interest based on the strategic value of data and selecting the best available data. This allows creating a two-layer data framework that enables the collection of data at the country and port level. The developed framework is applied to gather relevant data points for various container ports, and allows drawing conclusions on the performance of the framework. The results of this research contribute to the understanding of container port performance and may serve as a valuable resource for port operators and researchers in the field. By examining the specific factors that influence port performance, this study provides a foundation for enhancing the comparability of container port operational performance.

Purpose The purpose of this paper is to present an integrated model to measure the operational efficiency of the top 40 container ports in the world for a five-year continuous period using a two-stage uncertainty data envelopment analysis (UDEA) combined with fuzzy C-means clustering method (FCM). Design/methodology/approach UDEA model is adopted for measuring the efficiency of container ports to overcome the limitation of the basic model, which is unable to handle uncertain data that are easy to meet in practice. FCM algorithm is implemented to find similar distribution efficiency scores of two stages and the cluster similar efficiency scores of container ports into various groups. Findings The combination of the two-stage UDEA model and the FCM algorithm provided a more comprehensive view when evaluating the performance of container ports. The UDEA results show that most of the container ports have reduced their profitability level in the second stage and most of the efficient container ports have turned into inefficient ones because of their small scale. Originality/value This paper proposes using the two-stage UDEA model to evaluate port efficiency based on two main aspects of productivity and profitability. Moreover, it combines DEA and FCM algorithms to offer a more comprehensive view when measuring the performance of container ports.

Container port and terminal performance is central to the efficiency and resilience of global maritime logistics. This study conducts a systematic review of methodologies used to evaluate container port performance, with a focus on both international practices and applications within Türkiye. The review identifies five methodological families: frontier-based efficiency analysis, simulation and optimization models, statistical regression models, KPI and benchmarking frameworks, and hybrid AI-enhanced methods. A consistent set of core operational metrics appears across all approaches, including vessel turnaround time, berth or crane throughput, and container dwell time. These metrics serve as foundational indicators in performance assessment. However, methodological diversity and context-specific definitions limit cross-port comparability. Turkish case studies demonstrate the integration of MCDM, fuzzy logic, and machine learning to address local efficiency and sustainability challenges. The review proposes a tiered framework that aligns methods with operational, strategic, and technological goals. It recommends a shift from isolated methods to integrated, data-driven systems that support real-time decision making and long-term planning. For emerging economies like Türkiye, adopting such a layered and standardized approach offers a path to greater competitiveness and resilience in the global maritime sector.

Container ports are generally measured and compared using performance indicators such as container throughput and facility productivity. Being able to measure the performance of container ports quantitatively is of great importance for researchers to design models for port operation and container logistics. Instead of relying on the manually collected statistical information from different port authorities and shipping companies, we propose to leverage the pervasive ship GPS traces and maritime open data to derive port performance indicators, including ship traffic, container throughput, berth utilization, and terminal productivity. These performance indicators are found to be directly related to the number of container ships arriving at the terminals and the number of containers handled at each ship. Therefore, we propose a framework that takes the ships' container-handling events at terminals as the basis for port performance measurement. With the inferred port performance indicators, we further compare the strengths and weaknesses of different container ports at the terminal level, port level, and region level, which can potentially benefit terminal productivity improvement, liner schedule optimization, and regional economic development planning. In order to evaluate the proposed framework, we conduct extensive studies on large-scale real-world GPS traces of container ships collected from major container ports worldwide through the year, as well as various maritime open data sources concerning ships and ports. Evaluation results confirm that the proposed framework not only can accurately estimate various port performance indicators but also effectively produces port comparison results such as port performance ranking and port region comparison.

An increase in container traffic, larger tonnage of vessels, scarcity of port area, and shorter turnaround times have driven terminals to process more containers in less time and less space. Thereby, the increasing focus on costs, safety, and environmental control is forcing terminal operators to search for innovative solutions. Automated container terminals are the potential candidates to improve the performance of container terminals and represent a challenge to any subsequent future fluctuations in maritime transport. In this study, we examine the improvement in the performance of container ports by adopting automation through simulation modeling. The effect of the automated guided vehicles and automatic stacking cranes-based automatic container terminal system (AGV-ACT/Automated Guided Vehicles - Automatic Container Terminal system) on container handling operations was evaluated. To create a complete port simulation model, the main objects of the container terminal such as tugboats, berths, quay cranes, stacking blocks, stacking cranes, horizontal transport vehicles, external trucks, and the layout of the terminal are simulated as a whole. Firstly, we created a model representing the existing port to evaluate the overall performance of the port and to validate the simulation model by comparing the actual data with those of the real system. Then, a simulation model for the proposed automatic system was created and evaluated. The simulation model was divided into four main logics: ships arrival and berth allocation, ship loading/unloading, external trucks arrival, and containers storage/retrieval logic. The results of the two systems were compared based on the performance criteria such as ship turnaround time, external trucks turnaround time, and equipment utilization rate. Automation has reduced the turnaround time of the ships and provided a smooth movement for the equipment which showed a high utilization rate. The automated system decreased the ship turnaround time from 9.52 hours to 7.81 hours (18%). The reduction in the waiting times of the container transport vehicles for quay cranes reached 47% and 30% in berths 1 and 2, respectively. On the other hand, external trucks’ turnaround time increased by 124% as only one ASC (Automatic Stacking Crane) is run in each block to perform both seaside and landside operations (seaside operations were prioritized). Automation has improved the overall performance of the terminal. Also, the layout of the automated handling system raised the storage capacity of the port. In the new proposed automated layout, the storage area capacity increased by 27.27%.

South Asia's trade almost doubled in the past decade, but the share of trade in GDP is still smaller (47 percent) than in East Asia (55 percent), and South Asia's economic competitiveness continues to lag that of other regions. Part of the problem is the region's container ports. As a result of inefficiencies, the average cost of exporting or importing a container in the region is more than twice what it is in East Asia. Better port logistics could help increase trade, diversify exports, attract more foreign direct investment, and spur economic growth. As container traffic continues to grow and physical expansion is constrained by the limited supply of available land at most ports, the best way to improve port performance is by increasing productivity. To identify strategies for doing so, this report examines the performance of the 14 largest container ports in the region based on two sets of criteria: operational performance and economic performance. To measure operational performance, the report benchmarks total time at port, waiting time at port, and idle time as a share of total time at berth. To measure economic performance, it benchmarks productivity and efficiency using two useful techniques: total factor productivity decomposition and data envelopment analysis. The report identifies key drivers of port performance and examines how differences in performance across ports are related to those drivers. This analysis is based on an original dataset on private sector participation, governance, and competition in South Asia's container port sector. To highlight the potential gains from improving performance of container ports, the report uses econometric techniques to isolate the impact of efficiency improvements on maritime transport costs and trade. The results suggest that the best strategy for improving port performance in the region is a three-pronged approach that (a) encourages private sector participation through a well-developed enabling environment, including further adoption of the landlord port model; (b) strengthens the governance of port authorities' boards; and (c) promotes competition between and within ports, in part through transparent and competitive concession bidding.

Purpose: This study aims to reveal the sustainability orientations of container port facilities operating in Turkey through sustainability reports and to evaluate the performance of their operational, environmental and social dimensions both separately and in an integrated manner (Environmental, Social, Operational-ESO). Methodology: Sustainability orientations of container port facilities were subjected to qualitative assessment through examination of web pages and sustainability reports. The data obtained through document scanning regarding operational, environmental, and social performance indicators revealed by researching the relevant literature were analyzed using the MULTIMOORA method. The Rank Position Method was used in the performance ranking of port facilities. Findings: The results show that 18% of the container service port facilities publish independent sustainability reports. There are deficiencies in the environmental and especially social performance indicators taken into account in the sustainability reports. Among the port facilities examined, Mersin International Port, which has the highest operational performance, is also ranked as the facility with the lowest integrated performance (ESO). The port facility with the highest integrated performance (ESO) was Socar. Originality: The study contributes to filling the gap in the literature regarding the evaluation of environmental, social and operational performance of container ports in Turkey with the MULTIMOORA method. More importantly, the integrated examination of relevant performance dimensions represents the originality of this study.

One of the container port performance is the ratio of Effective Time to Berth Time (ET:BT). A thorough study of all the ground handling processes is required to improve it. This study aimed to design proposed improvements to the performance of the ground handling process. Data collection was carried out by direct observation through interviews, as well as measuring time using a stopwatch, and various manual distance measurements. Data obtained were analyzed by using Big Picture Mapping (BPM) followed by Process Activity Mapping (PAM). Activities that categorized to be non-value added (NVA) are examined in detail using the Root Cause Analysis (RCA) method and 5 Why’s Analysis. Results obtained are several factors that cause waste. These factors, then, would be reviewed to produce four classifications of improvement recommendations namely scheduling, management, human error and tools/facilities. After knowing the causes of various activities that did not add value to the process, then the improvement proposals were ready to be made.

Performance measurement and improvement are essential activities that ports use to enhance their competitive position in the global market. This study investigates this topic in container ports. The aim of this study is to explore the sensitivity of the performance enablers in the port performance model of Jaffar and Berry [1]. The performance measure that is used in this model for the container ports is the Twenty Equivalent Unit (TEU), and the port performance predictor variables were: leadership commitment to excellence, modern technology, the efficiency of the terminal, port size, and the port hinterland. This paper investigates the change of the TEU over 5 years (start of 1999–end of 2003) using time series analysis. The sample that was used in this study includes container ports in the Middle East, Far East and Europe. Based on the sample used, the paper suggests that the most sensitive enablers in affecting the performance of container ports are the port capacity and the crane productivity.

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

The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA), an effective tool for relative efficiency assessment, is utilized for measuring the performances and benchmarking of the 77 world container ports in 2007. The used approaches in the current study consider four inputs (Capacity of Cargo Handling Machines, Number of Berths, Terminal Area and Storage Capacity) and a single output (Container Throughput). The results for the efficiency scores are analyzed, and a unique ordering of the ports based on average cross efficiency is provided, also cluster analysis technique is used to select the more appropriate targets for poorly performing ports to use as benchmarks.