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Competition among seaports is rapidly increasing due to various factors such as the global recession, resurgence of COVID-19, tight environmental regulations of IMO, sharp rise in ocean freight charges, increasing global uncertainties and growth in ship sizes. It is essential to have precise knowledge of shipping companies' port selection factors to secure the competitive advantage of seaports. This study aims to empirically analyze recent changes in the importance of port selection factors.

By employing a longitudinal study, this study conducted the t-test analysis. The first survey was conducted from January 2005 to April 2005. Then, the second survey was conducted in May 2021.

First, the importance of port facilities (berth length and the number of berths, shed and terminal areas, possession of adequate equipment and maximum berth size) increased significantly. Second, while ship and cargo safety were the critical port service factors in previous studies, speed, flexibility and reliability for handling cargo and berthing schedule were found to be crucial in this study. Third, the importance of ship arrival/departure frequency, route diversity and ship arrival/departure information systems increased when shipping companies selected the port.

This study has academic significance in that it reveals the changing importance of port selection factors in the 2020s and has taken the form of a longitudinal study on the importance of port selection factors from 2005 to 2021, moving beyond the cross-sectional approach. This study can provide valuable insights into and implications for port policymakers and managers when developing and formulating port policies and strategies.

Container liner shipping companies started expanding their business by investing in container port terminals in the late 1990s. This market entry results in an extensive presence of vertically integrated liners and terminals. This study aims to explore the competition effects of this vertical integration trend based on a regional (European) analysis. In particular, it extracts lessons from the European Commission (EC) cases on the competition effects of vertical integration. The critical analysis of the cases examined at the institutional level intends to reach conclusions on whether liner–terminal vertical integration harmed or advanced competition in the relevant markets and/or the extent that there is a need to revise the current policy practices.

This study critically assesses the EC’s decisional practices in port container terminal vertical mergers in the last 25 years (1997–2021). Based on a literature review comparing maritime and competition economists' perspectives, it reviews the types of mergers examined, the methodology followed for relevant market definition and calculation of market shares and the estimated competition effects. The Hamburg–Le Havre area is the port range used as a case study for comparing the decisional practice with actual market developments. These container ports serve the greatest consuming market of final and intermediate goods in Europe and are gateways to Central and Eastern Europe.

The assessment identifies a need for expanding the investigation as a precondition for reaching conclusions on both the anti- and pro-competitive effects. First, only a limited number of transactions have been notified to the EC. Second, the empirical research identified a gap in this process, as there were no decisions (phase I) on vertical mergers between 2008 and 2016. Third, the exante assessment has not applied a phase II in-depth analysis to any case due to the absence of competition concerns. Finally, due to the absence of complaints, there is a lack of any ex post assessment of the effects of vertical integration.

This assessment is important for understanding the current and emerging features of intra-port and inter-port competition and the potential effects that the continuation and expansion of liner companies' vertical integration strategies will have along maritime supply chains. It also contributes to the broader discussion on liner companies' strategies, such as the research and policy-making efforts around the globe to understand the impact of both vertical and horizontal integration.

These discussions are critical for a diversity of businesses that use liner shipping services or provide facilities and services to container shipping lines or ports. They are important for the interests of customers and consumers as they could inform any needed re-visiting of competition policy to protect from the dominance of any market developments that would lead to conditions limiting competition. Expanding analysis on the competition effects of non-notified mergers would help a better understanding of market changes.

Enhancing competition and limiting monopolies is valuable from a consumer's perspective. This is more so in the case of maritime trade that serves the needs of societies. The study contributes by generating a better understanding of how decision-makers have worked towards that direction and what realignments are worthy.

There are no previous comprehensive reviews and analyses of the ways that policy-makers at the regional level have addressed the competition effects of vertical integration strategies of liner shipping companies when enhancing competition is valuable from a consumer perspective. Comparing maritime economists and competition, the study, via its literature review, also offers a comparison of maritime and competition perspectives on these competition effects, allowing positioning of how effective decisional-making practices have been.

The purpose of this study is to examine the effects of inclination angle on the thermal energy storage capability of a phase change material (PCM) within a disc-shaped container. Different container materials are also tested such as plexiglass and aluminium. This study aims to assess the energy storage capacity, melting behaviour and temperature distributions of PCM with a specific melting range (22°C–26°C) for various governing parameters such as inclination angles, aspect ratios (AR) and temperature differences (ΔT) and compare the melting behaviour and energy storage performance of PCM in aluminium containers to those in plexiglass containers.

A finite volume approach was adopted to evaluate the thermal energy storage capability of PCMs. Five inclination angles ranging from 0° to 180° were considered and the energy storage capacity. Also, the melting behaviour of the PCM and temperature distributions of the container with different materials were tested. Two different AR and ΔT values were chosen as parameters to analyse for their effects on the melting performance of the PCM. Conjugate heat transfer problem is solved to see the effects of conduction mode of heat transfer.

The results of the study indicate that as AR decreases, the effect of the inclination angles on the energy storage capacity of the PCM decreases. For lower ΔT, the difference between the maximum and minimum stored energies was 20.88% for AR = 0.20, whereas it was 6.85% for AR = 0.15. Furthermore, under the same conditions, the PCM stored 8.02% more energy in plexiglass containers than in aluminium containers.

This study contributes to the understanding of the influence of inclination angle, container material, AR and ΔT on the thermal energy storage capabilities of PCM in a novel designed container. The findings highlight the importance of AR in mitigating the effect of the inclination angle on energy storage capacity. Additionally, comparing aluminium and plexiglass containers provides insights into the effect of container material on the melting behaviour and energy storage properties of PCM.

Due to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.

In this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.

Competitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.

The findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.

This study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

Selection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.

A group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.

A closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.

The presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

The purpose of this work is to construct a grey entropy comprehensive evaluation model to measure the regional green innovation vitality (GIV) of 31 provinces in China.

The traditional grey relational proximity and grey relational similarity degree are integrated into the novel comprehensive grey evaluation framework. The evaluation system of regional green innovation vitality is constructed from three dimensions: economic development vitality, innovative transformation power and environmental protection efficacy. The weights of each indicator are obtained by the entropy weight method. The GIV of 31 provinces in China is measured based on provincial panel data from 2016 to 2020. The ward clustering and K-nearest-neighbor (KNN) algorithms are utilized to explore the regional green innovation discrepancies and promotion paths.

The novel grey evaluation method exhibits stronger ability to capture intrinsic patterns compared with two separate traditional grey relational models. Green innovation vitality shows obvious regional discrepancies. The Matthew effect of China's regional GIV is obvious, showing a basic trend of strong in the eastern but weak in the western areas. The comprehensive innovation vitality of economically developed provinces exhibits steady increasing trend year by year, while the innovation vitality of less developed regions shows an overall steady state of no fluctuation.

The grey entropy comprehensive relational model in this study is applied for the measurement and evaluation of regional GIV, which improves the one-sidedness of traditional grey relational analysis on the proximity or similarity among sequences. In addition, a three-dimensional evaluation system of regional GIV is constructed, which provides the practical guidance for the research of regional development strategic planning as well as promotion paths.

A comprehensive grey entropy relational model based on traditional grey incidence analysis (GIA) in terms of proximity and similarity is proposed. The three-dimensional evaluation system of China's regional GIV is constructed, which provides a new research perspective for regional innovation evaluation and expands the application scope of grey system theory.

India should hold a privileged position in maritime transportation due to its extensive coastline and advantageous location. However, the country heavily relies on other maritime nations like Singapore and Colombo for transshipment due to insufficient infrastructure and policy framework, and this has created disadvantage to Indian goods in the international market. The government has launched a significant drive to promote three transshipment ports in southern India with top-notch amenities in response to this worrying circumstance. It is anticipated that these ports would compete with the existing transshipment ports, particularly with Colombo, and divert the transshipped goods back to India. The move is expected to make Indian exports more competitive besides making India less prone to geopolitical and economic disturbances in the region. However, these initiatives have been met with many challenges. In fact, the first attempt of the Indian government to set up an International Container Transshipment Terminal (ICTT) at Vallarpadam in Cochin Port has met with failure despite its best infrastructure and connectivity. High-cost structure seems to deter the competitiveness of this port. Furthermore, the development of Vizhinjam into a transshipment hub in the same region has put additional pressure on Vallarpadam. This chapter draws attention to certain factors that might be considered to enhance the competitiveness of Cochin Port. Also, the study highlights the snags that could have well been avoided while implementing the project and might as well be avoided while implementing other projects in line.

This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors causing traffic jams and assess the outcomes of resolving the issue through an optimal model for incoming container truck traffic.

The study employed a one-way ANOVA and a one-way MANOVA to examine the impact of congestion-causing factors on the waiting time of trucks in each lane at the entrance gate. The purpose of this was to comprehend the intricate issue and demonstrate the outcomes of the resolution. We used the identified factors that were causing congestion to develop a management strategy for the port gate. As part of this strategy, we implemented a policy where traffic flows in the opposite direction in certain lanes. The Simulation of Urban Mobility program introduced the microscopic traffic simulation model as a discrete event simulation.

The examination of variables influencing the congestion at the port entrance revealed that there were four factors contributing to the congestion: (1) the quantity of lanes; (2) the level of bookings; (3) the factors related to the traffic signal cycle and (4) the assignment of lane types. The one-way MANOVA analysis of the three factors yielded significant evidence for a single pair of interactions. (1) The factors to consider are the quantity of lanes, the level of booking and the assignment of lane types. If the entrance to the rear alley consists of two lanes with a width of 1.85 at the 50% capacity level, and if the critical value of the uneven queue coefficient is reached, it can result in a maximum reduction of the average waiting time by 15.02%.

This study is unique because it examines the surrounding environment and operational behavior of the port to identify how individual and group congestion factors interact. It uses various statistical tools to determine the allocation of the number of port entrances with a reversible lane policy and appointment level. Additionally, it analyzes the detailed results using microscopic traffic simulation modeling. The established foundational model can assist operators in simulating the queue length and mean waiting time of trucks for this specific waiting line in other ports with comparable entrance characteristics.

This present study uses political, economic, social, technological, legal and environmental (PESTLE) analysis and the strategic management theory to examine how external factors, namely the coronavirus (COVID-19) pandemic, the industrial revolution (IR) 4.0 technologies, the fuel price crisis and Sultanate of Oman Logistics Strategy (SOLS) 2040, affect the performance of container terminals in Oman.

A hybrid decision-making method that combined the analytical hierarchy process technique and Bayesian network model was used to achieve the objective of the present study.

The COVID-19 pandemic (54.60%) most significantly affected the performance of container terminals in Oman, followed by IR 4.0 technologies (19.66%), SOLS (17.00%) and fuel price crisis (8.74%). Container terminals in Oman were also found to perform “moderately,” considering the uncertainty of external factors.

This study enriches existing literature by using PESTLE analysis to assess the impact of the external business environment on firm performance in the context of the maritime industry as well as highlights how challenging external environmental factors affect the performance of container terminals in Oman.

This study contributes to developing novel study models and determining the performance level of container terminals in Oman considering integrated uncertainties and external factors such as the COVID-19 pandemic, IR 4.0 technologies, the SOLS 2040 and the fuel price crisis.

The first purpose is to assess the quality of containerized multimodal export and the second is to develop and demonstrate the design of a service network with quality approach.

The article used the structural equation model to develop a model to measure the quality of multimodal transportation for containerized exports and finalized the model with an alternative approach. The evolutionary algorithm had been used to design a service network based on quality.

Provided factors affecting quality of multimodal transportation and reverse to one hypothesis, the construct variation in cost, time shape and quantity did not affect the quality of multimodal transportation for containerized exports. The model without variation construct was finalized by exploring causality.

This research had scope till container loading onto the vessel and assessed the quality for containerized cargo only, and second research purpose is limited by assumed values of fitness function and the limited number of nodes, in service network design demonstration.

This research provided a tool to measure the quality of multimodal transportation for containerized exports and demonstrated the field application of the model developed in service network design. This approach included all factors applicable across the container movement. The integrated approach of the article provided an organized method to design a service network for containerized exports.

This work provided the tool to assess the quality of multimodal transportation for containerized exports and developed an approach to design a service network of multimodal transportation based on quality. This approach has considered the factors of multimodal transportation comprehensively in contrast to the optimization approaches based on operation research techniques.