The Corona Virus Disease 2019 (COVID-19) outbreak took a heavy toll on the global tourism industry in 2020, and affected the value realization of coastal recreational ecosystem service. From the micro perspective, this paper combines travel cost method with contingent behaviour method to obtain residents' actual behaviour and contingent behaviour data, and discusses the impact of the outbreak of COVID-19 on the value realization of coastal recreational resources from the perspective of the change in residents' recreational behaviour in Qingdao, China. Residents are observed to significantly reduce their outdoor activities in response to the COVID-19. The number of visits to the beach decreases by 25.2% when there is an outbreak, and decreases by 0.064% for every 1% increase in the number of confirmed cases, which is used to represent the severity of the epidemic. The asymmetries effects of epidemic situation on residents' recreational behaviour show that the improvements lead to larger and more significant impacts than the deteriorations. The disappearance of the pandemic crisis will provide considerable welfare for the citizens in Qingdao, which reaches to 1.9323 billion CNY/year. If the number of confirmed cases deteriorates to 900, the environmental welfare loss will be 0.3366 billion CNY/year. Additionally, we test the effects of residents' cognitive variables, and find that risk perception can strengthen the negative impacts of COVID-19 cases. Furthermore, the deteriorations in the environmental attributes are found to have stronger impacts on the number of visits than the improvements. This paper provides empirical-support results about the change of coastal recreational value through the evaluation of recreational behaviours in the post-epidemic period, which will give important implications for government's marine ecosystem restoration and coastal management work.

With the COVID-19 pandemic evitably becoming the "New Normality" and will continue to impact human society much longer than anticipated, it is essential to explore effective measures that global ports can take to adapt to unexpected challenges in the post-COVID-19 era. This paper builds a port resilience index system based on the entropy weight method from a multistakeholder's view. We utilize the port resilience index system for 22 major Chinese ports during 2020-2021. We further investigate the direct impact of port resilience on port governance performance. Our results indicate that resiliently-governed ports can guarantee higher port throughput while sustaining lower congestion when facing challenges from the global pandemic.

The emergency of COVID-19 leads to almost all unnecessary activities being banned because of city lockdowns, which results in the economy and human mobility being strictly restricted. While affecting economic development, it has brought some environmental benefits. As a critical link to collection and distribution, ports have been deeply impacted by COVID-19, including quarantine time and operational efficiency, and even cause unexpected port congestion. This study empirically examines the relationship between the COVID-19 pandemic, port congestion and air quality in Chinese port cities using classical and system panel models. We find that the COVID-19 pandemic and port congestion significantly influence air quality in port cities. Managerial implications include the ensuring of port workers' shifts, the unblocking of port logistics, and the cooperation between transportation, customs, and quarantine departments, which can reduce the time of ships at berths and improve the air quality in port cities.

Since the COVID-19 ravaged the global terminals, the Automated Container Terminal (ACT) has become one of important approach to promote the stronger quick response capacity to deal with the uncertainty that COVID-19 brought to the terminal. This research takes Automated Guided Vehicle (AGV) and their effects into account the multi-resource collaborative scheduling model to tradeoff ACT operational efficiency and energy savings. Firstly, the dual-cycle strategy of QC and the pooling strategy of AGV are given, which coordinates the scheduling of Quay Cranes (QCs), Yard Cranes (YCs) and other equipment. Furthermore, a multi-resource collaborative scheduling optimization model is proposed which roots from the principle of the Blocking-type Hybrid Flow Shop Problem (B-HFSP) with the objectives of minimizing the makespan of QC and the transportation energy consumption. And simultaneously, a mixed algorithm SA-GA is designed for solving this mixed integer programming model by an optimizing effect of Simulated Annealing on Genetic algorithms. Numerical experiments show that the model in this research is effective. The convergence of SA-GA is effective for small-scale cases and superior for large-scale cases. Considering both goals of high efficiency and energy saving, the Pareto solution set and collaborative scheduling solution take a priority to ensure that the bottlenecked QC runs efficiently. Here and now the average idle rate of QC is about [14%, 35%] lower than that of other equipment. The collaborative scheduling model constructed above not only has reference value for other multi-device and multi-stage scheduling problem, but also enhance the integrated decision-making ability of the ACT in the post-epidemic era.

In the post COVID-19 pandemic era, collusion strategy has been attempted to confront fierce market competition in container shipping supply chains. Three typical collusion scenarios are constructed as follows: i) none of the two pairs of shipping chains colludes; ii) both pairs collude; and iii) only one pair colludes. This paper developed a two-stage game model to study the optimal strategies of the container terminals and corresponding liner companies. The container ports set terminal handling charge (THC) to pursue optimal profits at the first stage, and then liner companies choose freight rate to obtain corresponding optimal profits at the second stage. Further, we analyzed the collusive incentives of the THC difference between heterogeneous terminals and the impact of the freight rate difference between heterogeneous container liners. In particular, the possibility of deviation from collusion and the decision of capacity expansion of container terminal are discussed through theoretical analysis. The results show that the optimal THC of a container terminal and freight rate of a container liner are both highly related to the capacity of the container terminal, which is profoundly influenced by the different structures of its collusion. Finally, the empirical study proves the theoretical result and the implications of port governance are subsequently discussed.

Maritime transport chain is facing huge information asymmetry after the outbreak of major emergencies, such as COVID-19 epidemic. The previous literature has proved that information investing and information sharing are two effective tactics to relieve information asymmetry between supply chain nodes, and help them improve the performance of the supply chain. This paper assumes random demand disruption is the main cause of the information asymmetry in a maritime transportation chain. To explore how the random demand disruption and channel competition jointly impact operational decisions in a dual-channel maritime transport chain composed of one port, two carriers and shippers, we construct a game-theoretical basic model, and proposed two strategies, i.e., information investing and information sharing. Several significant managerial insights are derived. First, we find that inaccurate disruption information leads to inaccurate decisions and huge losses; Second, investing in precise information benefits the port only if the chain members are optimistic about the market, and improves the revenue of the carrier who invested in information if the investment cost is reasonable; Third, accepting information sharing benefits the port only when the precise disruption and the distortion of information are relatively large, as well as the misappropriate rate is relatively small; and only when the port is pessimistic about the market or the channel competition is weak, sharing information may hurt the carrier who invested in information. Finally, the strength of the channel competition will enhance the impact of information inaccuracy on the maritime transport chain.

Driven by globalization, the COVID-19 outbreak has severely impacted global transport and logistics systems. To better cope with this globalization crisis, the Belt and Road Initiative (BRI)-based on the concept of cooperation-is more important than ever in the post-pandemic era. Taking the BRI as the background, we design an intermodal hub-and-spoke network to provide reference for governments along BRI routes to improve their cross-border transportation system and promote economic recovery. In the context of the BRI, local governments at different nodes have incentives to subsidize hub construction and/or rail transportation to boost economic development. We consider co-opetition behavior among different levels of government caused by subsidies in this intermodal hub location problem, which we call the intermodal hub location problem based on government subsidies. We establish a two-stage mixed-integer programming model. In the first stage, local governments provide subsidies, then the central government decides the number and location of hubs. In the second stage, freight carriers choose the optimal route to transport the goods. To solve the model, we design an optimization method combining a population-based algorithm using contest theory. The results show that rail subsidies are positively correlated with construction subsidies but are not necessarily related to the choice of hubs. Compared with monomodal transportation, intermodal transportation can reduce costs more effectively when there are not too many hubs and the cost of different modes of transportation varies greatly. The influences of local government competition and hub construction investment on network design and government subsidies are further examined.

The stability of shipping and port operations are crucial for international trade and global supply chain. However, the COVID-19 pandemic hit the shipping and port industry enormously in late 2019, and continues till now. It is important to identify the impacts of the pandemic on shipping and port operations and evaluate the potential economic impacts for better setting future development strategies and policies. A System Dynamics (SD) model is proposed to depict the impact transmission within the supply chain considering 5 sub-systems (shipping, port, transportation, manufacturing and social). Potential economic impacts which are represented by the shipping loss and port loss will be assessed. 6 scenarios with different epidemic durations and capacity recovery degrees have been set to investigate the economic impacts. The port of Shanghai, together with the container shipping business is selected as input for case study. Results indicate that in the first few months the port and carriers may suffer economic loss due to shrunken demand caused by COVID-19. But later carriers may enjoy an increase of income compared to non-pandemic scenario owing to strong recovery in most scenarios. Moreover, we found that manufacturing, transportation and port operation capacities would jointly affect the recovery process and economic impacts. The findings can facilitate policy makers in making port management and future industry development decisions.

Despite the significant fluctuations in global trend due to the rising trade friction and the COVID19 pandemic, the container terminals are continuously working in three technology areas including automation, electrification and digitalization. This study reviewed recent technology trends as well as relevant research topics related to the container terminals, and investigated how the trends and topics would facilitate the terminals to achieve their strategic objectives. We also studied the trends in the container terminal industry before and after the pandemic outbreak. Recent progress shows that generally the long-term plans remain unchanged while there are some changes in timeline and priorities. The findings suggest that despite the common interest in long-term plans, gaps are still identified between academia and industry interests. Future directions are discussed for these technology areas, particularly in the context of the post-pandemic world, where the limited resources should be invested to the most urgent areas.

In the post-COVID-19 epidemic era (PCEE), the supply of empty containers will face stronger uncertainty. Estimating the amount of self-owned and leased empty containers that need to be allocated to each inland freight station in a specific area becomes a critical issue for liner companies in PCEE. However, owing to the high degree of unpredictability of the demand and the limited flexibility of empty container relocation, the abovementioned issue has not been fully addressed. This paper provides a model for empty container allocation without knowing the probability distribution function of empty container demand in advance. The abovementioned model can jointly optimize the quantities of self-owned empty containers and leased containers allocated to each inland freight station. To solve the model, a largest-debt-first policy is adopted to simplify the complicated model, and a differential evolutionary (DE) algorithm is developed to solve the simplified model. Compared with some commonly used algorithms, DE has advantages considering the ability to explore the optimal solution. In addition, the utility of the largest-debt-first policy proposed in this paper is compared with that of the traditional method. Experimental results show that in the case of high demand fluctuations, the proposed policy is better in controlling the operational and management costs. Overall, the theory and method proposed in this paper can effectively help the carrier set a reasonable regional empty container stock level and determine the number of self-owned and leased empty containers.

Corona Virus Disease 2019 (COVID-19) outbreak leads to a significant downturn in the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8% in 2020 compared with 2019. To explore the impacts of COVID-19 on ship visiting behaviors, a framework is proposed to analyze the impact of COVID-19 on port traffic using Automatic Identification System (AIS) data. Firstly, a ship travel behavior-based model is proposed to identify the vessel anchoring and berthing. Then, the diversity in vessel anchoring and berthing time are analyzed, reflecting the impact of COVID-19. The port congestion caused by COVID-19 is quantified by accounting for the number of visiting ships and their residence time. Finally, a case study is carried out on vessels in the Beibu Gulf, China, operating from 2019 to 2020. The results show that the average anchoring time and berthing time increase by 62% and 11% for cargo ships and by 112% and 63% for oil tankers after the outbreak of COVID-19 compared with that before COVID-19. And the density of ships increases in the port area in 2020. Accordingly, the relevant improvements and countermeasures are proposed to reduce the adverse impact of the epidemic on the port navigation system. The paper has the potential to provide a reference for port management and improving port navigation efficiency in the post-pandemic era.

In this study, we use the sample data from Jan 22, 2020 to Jan 21, 2022 to investigate the impacts of added infection number on the volatility of BDI. Under this structure, the control variables (freight rate, Brent crude oil price, container idle rate, port congestion level, global port calls) are added to test whether the information contained in the added infection number is covered. In the GARCH-MIDAS model, we divide the volatility of BDI into the long-term and short-term components, then employ in the least squares regression to empirically test the influences of added infection number on the volatility. From the analysis, we find the added infection numbers effectively impact the BDI volatility. In addition, whether the freight rate, Brent crude oil price, container idle rate, port congestion level, global port calls and other variables are considered alone or at the same time, further the added infection number still significantly influences the volatility of BDI. By studying the ability of the confirmed number to explain the volatility of BDI, a new insight is provided for the trend prediction of BDI that the shipping industry can take the epidemic development of various countries as a reference to achieve the purpose of cost or risk control.

The Government of Barbados welcomed cruise ships during the early COVID-19 period of 2020, allowing them to seek safe harbour at a time when many countries were turning them away. A total of 28 cruise ships were given unprecedented permission to anchor along the west and south coasts of the island during this period (1 March – 1 September 2020). This study examines the 132 anchoring events of these cruise ships, using automatic identification system (AIS) data to determine anchored locations and track vessel swing at anchor in relation to sensitive coral-rich habitat. These data, together with SCUBA surveys on several anchoring sites were used to describe the nature of the habitat damage and to assess the potential area of impacts on coastal marine habitats. The huge anchors and hundreds of metres of chain required to secure these mega-vessels, together with their typical wide swinging motion dragging the anchor chain over the bottom are estimated to have caused thousands of square metres of structural damage to the island’s valuable coral reefs. This study revealed weaknesses in coral conservation policy and practise to which the Government of Barbados has responded. A stated new Government policy prohibits cruise ships from anchoring on the coral-rich west coast and restricts anchoring to the designated anchorage on the south coast. Additional cruise ships that cannot be accommodated in the anchorage are now being asked to use their dynamic positioning system or to drift offshore.

A container shipping network connects coastal countries with each other and facilitates most of the world merchandise trade. Reliable maritime connectivity ensures the availability of commodities and economic growth. The global spread of COVID-19 has led to port failures and service cancellations, resulting in decreased connectivity level of container ports. To mitigate the impact of the pandemic, a graph theory approach is proposed to strength the container shipping network connectivity by considering topology and the possibility of opening new shipping links between ports. It is designed to maximize network connectivity with limited addable routes. The network connectivity is measured by algebraic connectivity, and the possibility of opening new shipping links is estimated by an extended gravity model. A heuristic algorithm based on Fiedler vector is introduced to obtain the optimal solutions. The performance of the proposed model and algorithm are verified by testing on a real-world container shipping network based on the Alphaliner database. Experimental results illustrate that the presented model is efficient and effective for strengthening the connectivity. Policy makers can refer to the suggested optimal shipping links to facilitate better shipping network connectivity in the context of the COVID-19 pandemic.

Port congestion has become a key factor restricting the international trade and economic development, especially during the COVID-19 epidemic. It is essential for the port to implement the effective alleviation strategies for handling the uncertain congestion. This paper aims to investigate the performance of the epidemic prevention alliance strategy (EPAS), shared berths strategy (SBS) around adjacent ports and their hybrid strategy in alleviating the port congestion. To simulate the effect of these three strategies, a system dynamics model of dual-port operation is developed considering the factors of the integrated service level of liner routes, empty container allocation, port congestion and regional economics, and so forth. The results indicate that the key issue of port congestion stems from the implementation of epidemic preventive measures. Among these three strategies, the hybrid strategy performs the best in alleviating the port congestion, improving integrated service levels, and curbing the fluctuation of container price. Moreover, the measures of investing more human resources and fixed assets are always taken in many current ports to alleviate the issue of port congestion. Therefore, the impacts of various investment in human resources and fixed assets on alleviating the port congestion are discussed. Finally, some suggestions are provided for the government to strengthen the cooperation between ports and promote the construction of port facility resources.

Underwater noise from human activities is now widely recognised as a threat to marine life. Nevertheless, legislation which directly addresses this source of pollution is lacking. The first (and currently only) example globally is Descriptor 11 of the Marine Strategy Framework Directive (MSFD), adopted by the European Union in 2008, which requires that levels of underwater noise pollution do not adversely affect marine ecosystems. The MSFD has stimulated a concerted research effort across Europe to develop noise monitoring programmes and to conduct research towards specifying threshold values which would define 'Good Environmental Status' (GES) for underwater noise. Here, we chart the progress made during the first decade of Descriptor 11's implementation: 2010-2020. Several international joint monitoring programmes have been established for impulsive and continuous noise, enabling ecosystem-scale assessment for the first time. Research into the impact of noise on individual animals has grown exponentially, demonstrating a range of adverse effects at various trophic levels. However, threshold values for GES must be defined for 'populations of marine animals.' Population-level consequences of noise exposure can be modelled, but data to parameterise such models are currently unavailable for most species, suggesting that alternative approaches to defining GES thresholds will be necessary. To date, the application of measures to reduce noise levels (quieting/noise abatement) has been limited. To address this, the EU in 2021 identified an explicit need to reduce underwater noise pollution in its waters. Delivering on this ambition will require further research focused on the development and implementation of quieting measures.

Sea level rise threatens the coastal landscape, including coastal wetlands, which provide a unique natural habitat to a variety of animal and plant species as well as an array of ecosystem service flows of value to people. The economic valuation of potential changes in coastal wetland areas, while challenging, allows for a comparison with other types of economic impacts from climate change and enhances our understanding of the potential benefits of greenhouse gas mitigation. In this study, we estimate an ensemble of future changes in coastal wetland areas considering both sea level rise, future greenhouse gas emissions, and accretion rate uncertainty, using outputs from the National Ocean and Atmospheric (NOAA) marsh migration model. By the end of the century, total wetland losses range from 2.0 to 10.7 million acres across sea level rise scenarios. For Representative Concentration Pathway (RCP) 4.5 and RCP8.5, respectively, cummulative net wetland area loss is 1.8 and 2.4 million acres by 2050 and 3.5 and 5.2 million acres by 2100. We then estimate economic impacts with two distinct approaches: restoration cost and ecosystem services. The ecosystem services considered are limited by what can be reliably quantified-namely, coastal property protection from coastal flooding and carbon sequestration, the latter using a social cost of carbon approach. By the end of the century, annual restoration costs reach $1.5 and $3.1 billion for RCP 4.5 and RCP8.5, respectively. The lost ecosystem services, together, reach annual economic impacts that are much higher, reaching $2.5 billion for RCP4.5 and $6.1 billion for RCP8.5.

With the advent of the post-COVID-19 era, corporate managers of import and export trade are now more sensitive in their daily work, and their decisions are more likely to be influenced by the emotional bias of public opinions, especially regarding cooperation with trade ports of frequent circulation. Therefore, how to manage public opinion and sentiment in the post-COVID-19 era will be a new opportunity and challenge for the marketing management of ports. For the above considerations, through the same frequency verification between public opinions and sentiment on ports and corporate choice of import and export trade, and through analysis of the influence mechanism, the present study demonstrates the positive effects of public opinions and sentiment on ports in corporate choice of import and export trade in the post-COVID-19 era, verifies the significance of shaping word of mouth in port management, puts forward the great role of public opinions and sentiment in the cognitive and emotional empathy in the choice of import and export trade, and provides theoretical guidance for port managers' strategic choices in the post-COVID-19 era.

Covid-19 has disrupted the lives of employees all over the world. After experiencing a prolonged yet ongoing destructive event (i.e. Covid-19), finding an effective and non-invasive way to get employees back and engage in work is a huge challenge for scholars. Few studies have focused on returning to work after a traumatic event (limited time), but the post-pandemic psychological stress caused by the Covid-19 (PAPIST) has not received much attention. Current research addresses this gap and uses a comprehensive model drawn from the transactional model of stress and the Kahn psychological framework to advance the work of predicting PAPIST. Specifically, the current research investigates how PAPIST is related to job engagement, and emotional exhaustion and how job reattachment mediates the relationship. In addition, we use health support climate (HSC) as a boundary condition in our model, which can weaken the impact of PAPIST and enhance the effectiveness of job reattachment in reducing emotional exhaustion and increasing job engagement. To test our model, we collected data in multiple waves from Chinese seaports, where seafarers came to work after the restrictions were lifted in China. The current research is one of the earliest scholarly contributions. It paved the way for the research to solve the problem of workers returning to work after large-scale destructive events, and discussed important implications.

Galicia is the most important fishing region in Spain. Nearly 50% of the volume of catches and of the national fishing fleet are concentrated in this region. During the Covid-19 pandemic, the fishing sector had the status of an essential sector and was not forced to stop its activity by the national Government. However, its economic performance has deteriorated in 2020. This article aims to analyze the impact of the pandemic on the extractive fishing sector in Galicia. For this purpose, the performance of the main economic and financial variables of the 246 companies that constitute this industry has been studied. The companies pertain to different extractive sectors (the national, offshore and large-scale fleets) and are in 9 different areas (Vigo, Pontevedra, Arousa, Muros, Fisterra, Costa da Morte, A Coruña-Ferrol, Cedeira and A Mariña). The results of the analysis show that the 9 fishing zones share a generalized negative trend but that there is heterogeneity in the results. Among the most determining factors are the predominant fleet extract, the target species caught, or the perception of public subsidies.

Understanding the disruption of fishing activities due to COVID-19 and closed fishing season can provide an immediate reference for policy directions that help the government direct its resources to the most affected agricultural sectors. This study examined the impact of COVID-19 and closed fishing season on the commercial fishers' fishing operation and economic well-being in Davao Gulf, Mindanao. A total of N = 66 commercial fishers, 33 ringnet and 33 bagnet fishers were interviewed one-on-one in their homes and in the landing sites using a semi-structured questionnaire. Data was further validated using four focus groups in the study areas (N = 55). The findings of the study showed that the average catch per fishing trip for ringnet and bagnet fishers were 1,719 kg and 417 kg. The common catch species of ringnets were bigeye scad , bullet tuna , roundscad , skipjack tuna (), and yellowfin tuna While the common catch species of bagnet fishers were roundscad , Bali sardinella , moonfish , short mackerel , anchovy , and bigeye scad . Both types of fishers operated at the height of the pandemic but met difficulties selling the fish due to travel restrictions. Thus, they had lesser income. Other impacts include disruption in their children's education, feeling fearful and frustrated. In addition, during the closed fishing season, the bagnet fishers find alternative livelihoods such as hired labor and construction. In contrast, ringnet fishers fish beyond the Davao Gulf and continue to do so until the closed fishing season ends.