Maritime Business Review
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Published By Emerald (Mcb Up )

2397-3757

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jihong Chen ◽  
Renjie Zhao ◽  
Wenjing Xiong ◽  
Zheng Wan ◽  
Lang Xu ◽  
...  

PurposeThe paper aims to identify the contributors to freight rate fluctuations in the Suezmax tanker market; this study selected the refinery output, crude oil price, one-year charter rate and fleet development as the main influencing factors for the market analysis.Design/methodology/approachThe paper used the VEC (vector error correction) model to evaluate the degree of impact of each influencing factor on Suezmax tanker freight rates, as well as the interplay between these factors.FindingsThe conclusion and results were tested using the 20-year data from 1999 to 2019, and the methodology and theory of this paper were proved to be effective. Results of this study provide effective reference for scholars to find the law of fluctuations in Suezmax tanker freight rates.Originality/valueThis paper provides a decision-making support tool for tanker operators to cope with fluctuation risks in the tanker shipping market.


2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thanh-Thuy Nguyen ◽  
Dung Thi My Tran ◽  
Truong Ton Hien Duc ◽  
Vinh V. Thai

PurposeThis paper presents a systematic review of the literature in the domain of maritime disruption management, upon which future research framework and agenda are proposed. Two review questions, i.e. the measures that are employed to manage disruptions and how these contribute to resilience performance, were pursued.Design/methodology/approachThe systematic literature review procedure was strictly followed, including identification and planning, execution, selection, and synthesis and analysis. A review protocol was developed, including scope, databases and criteria guiding the review. Following this, 47 articles were eventually extracted for the systematic review to identify themes for not only addressing the review questions but also highlighting future research opportunities.FindingsIt was found that earlier studies mainly focused on measures, which are designed using mathematical models, management frameworks and other technical support systems, to analyse and evaluate risks, and their impacts on maritime players at the levels of organisation, transport system and region in which the organisation is embedded. There is, however, a lack of research that empirically examines how these measures would contribute to enhancing the resilience performance of maritime firms and their organisational performance as a whole. Subsequently, a Digitally Embedded and Technically Support Maritime Disruption Management (DEST-MDM) model is proposed.Research limitations/implicationsThis review is constrained by studies recorded by the Web of Science only. Nevertheless, the proposed research model would expectedly contribute to enhancing knowledge building in the specific domain of maritime disruption management and supply chain management overall while providing meaningful managerial implications to policymakers and managers in the maritime industry.Originality/valueThis research is perhaps one of the first studies which presents a systematic review of literature in maritime disruption management, and proposes a future research framework that establishes the link between disruption management and resilience and organisational performance for empirical validation.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Takuma Matsuda ◽  
Enna Hirata ◽  
Kawasaki Tomoya

PurposeSince the 2010s, market conditions for container shipping companies have been deteriorating owing to decreasing container cargo trade and increasing supply capacity. This study aims to contribute to the empirical literature on the container shipping industry market structure. Specifically, this study aims to investigate the extent of market competition.Design/methodology/approachThis study analyzes the market structure and evaluates the market power of shipping companies through a non-structural test.FindingsThe H-statistic for the entire period of 2004–2018 was 0.37, which is significantly different from zero. This indicates the absence of monopoly pricing throughout the entire period. For the time-phased estimates, the H-statistic between 2004 and 2008 is 0.15, which is not significantly different from zero. On the other hand, the H-statistic from 2009 to 2018 was 0.40, which differs significantly from zero.Originality/valueAs the Far East Freight Conference had released tariffs and charge rates by item for container shipping routes, monopolistic pricing is said to have appeared until the European Union abolished the European Economic Community (No. 4056/86) in 2008, before the economic crisis. However, this study indicates that pricing in the container shipping industry has been distinctly non-monopolistic; further, competition seems to have intensified since 2008. Industry competitiveness is of interest not only to academics but also to practitioners, including policymakers, especially when considering competition policies.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mei-Ling Cheng ◽  
Ching-Wu Chu ◽  
Hsiu-Li Hsu

PurposeThis paper aims to compare different univariate forecasting methods to provide a more accurate short-term forecasting model on the crude oil price for rendering a reference to manages.Design/methodology/approachSix different univariate methods, namely the classical decomposition model, the trigonometric regression model, the regression model with seasonal dummy variables, the grey forecast, the hybrid grey model and the seasonal autoregressive integrated moving average (SARIMA), have been used.FindingsThe authors found that the grey forecast is a reliable forecasting method for crude oil prices.Originality/valueThe contribution of this research study is using a small size of data and comparing the forecasting results of the six univariate methods. Three commonly used evaluation criteria, mean absolute error (MAE), root mean squared error (RMSE) and mean absolute percent error (MAPE), were adopted to evaluate the model performance. The outcome of this work can help predict the crude oil price.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chun Pong Wong

PurposeThis study examines the impact of the COVID-19 pandemic on the well-being and mental health of the seafarers who had to overstay on ships after their contracts expired, identifies topics that affect their mental distress, and recommends measures to overcome these.Design/methodology/approachFour research questions about the impacts on the seafarers before and during the COVID-19 pandemic were raised. A literature review and a questionnaire survey were conducted to find answers. Ship officers were asked to assess and fill in the questionnaires for the stranded seafarers onboard in order to collect sufficient samples rapidly for this study.FindingsDespite the guidelines provided by the shipping companies are adequate to protect the seafarers from COVID-19, their mental distress levels have been worsened under the pandemic. The crew change crisis causes anxiety and negatively impacts on their working performance; however, the repatriation expectation of the stranded seafarers is of the highest concern. Three topics were identified as having impacts on the mental health of the stranded seafarers: crew change crisis, low vaccination rate, and the lack of key worker recognition. While international stakeholders are advocating for support in these issues, the shipping companies and the seafarers need to do their parts to exacerbate the mental distress, and to survive and thrive beyond the pandemic.Originality/valueThe findings of this study will help the shipping companies to navigate the challenges, and the seafarers to overcome issues caused by the COVID-19 pandemic.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Francesco Vitellaro ◽  
Giovanni Satta ◽  
Francesco Parola ◽  
Nicoletta Buratti

PurposeThe research objective of the paper is twofold. First, it scrutinises the current state of the art concerning adopting the most popular social media by European port managing bodies (PMBs). Second, it investigates the use of social media in the corporate social responsibility (CSR) communication strategies of European PMBs.Design/methodology/approachThe paper carries out online field research on the use of social media by the top-25 European ports. Then, it provides an in-depth case study of the use of Twitter by the Port of Rotterdam for CSR communication. Finally, a content analysis of the tweets published in the 2017–2019 timeframe is performed.FindingsEmpirical results demonstrate the extensive use of social media by European PMBs to reach a wider array of stakeholders. Uneven approaches emerge considering port sizes and cultural clusters. The content analysis shows that one-third of tweets published by the Twitter account of the Port of Rotterdam address CSR issues, especially green initiatives, advocating the use of social media to communicate CSR.Research limitations/implicationsThe study focuses on the European domain. A broader sample of ports worldwide should be examined to further investigate the drivers affecting PMBs' strategic adoption and use of social media, mainly to communicate CSR.Practical implicationsThe paper provides port managers with insights to strengthen CSR communication. Given the increasing pressure of the public opinion on environmental and social issues, the ability of European PMBs to communicate their CSR commitment through social media represents a key driver when searching for consensus of stakeholders and “licence to operate”.Originality/valueThe paper adds to the existing maritime logistics literature by introducing a promising field of research.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chu Cong Minh ◽  
Nguyen Van Noi

PurposeTruck appointment systems have been applied in critical container ports in the United States due to their potential to improve handling operations. This paper aims to develop a truck appointment system to optimise the total cost experiencing at the entrance of container terminals by managing truck arrivals and the number of service gates satisfying a given level of service.Design/methodology/approachThe approximation of Mt/G/nt queuing model is applied and integrated into a cost optimisation model to identify (1) the number of arrival trucks allowed at each time slot and (2) the number of service gates operating at each time slot that ensure the average waiting time is less than a designated time threshold. The optimisation model is solved by the Genetic Algorithm and tested with a case study. Its effectiveness is identified by comparing the model's outcomes with observed data and other recent studies.FindingsThe results indicate that the developed truck appointment system can provide more than threefold and twofold reductions of the total cost experiencing at the terminal entrance compared to the actual data and results from previous research, respectively.Originality/valueThe proposed approach provides applicably coordinated truck plans and operating service gates efficiently to decrease congestion, emission and expenses.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Enna Hirata ◽  
Takuma Matsuda

PurposeThis research aims to uncover coronavirus disease 2019’s (COVID-19's) impact on shipping and logistics using Internet articles as the source.Design/methodology/approachThis research applies web mining to collect information on COVID-19's impact on shipping and logistics from Internet articles. The information extracted is then analyzed through machine learning algorithms for useful insights.FindingsThe research results indicate that the recovery of the global supply chain in China could potentially drive the global supply chain to return to normalcy. In addition, researchers and policymakers should prioritize two aspects: (1) Ease of cross-border trade and logistics. Digitization of the supply chain and applying breakthrough technologies like blockchain and IoT are needed more than ever before. (2) Supply chain resilience. The high dependency of the global supply chain on China sounds like an alarm of supply chain resilience. It calls for a framework to increase global supply chain resilience that enables quick recovery from disruptions in the long term.Originality/valueDiffering from other studies taking the natural language processing (NLP) approach, this research uses Internet articles as the data source. The findings reveal significant components of COVID-19's impact on shipping and logistics, highlighting crucial agendas for scholars to research.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dimitrios V. Lyridis ◽  
Georgios O. Andreadis ◽  
Christos Papaleonidas ◽  
Violetta Tsiampa

PurposeThe current study addresses how blockchain can deal with the challenges that the midstream liquefied natural gas (LNG) supply chain poses combined from a management standpoint. Such challenges are: the volume of transactions, communication hurdles and the lack of contemporary management tools. The paper proposes a comprehensive framework to assess the impact of blockchain implementation in the midstream LNG supply chain in order to tackle those barriers.Design/methodology/approachThe basis of the research is the business process modelling (BPM), through which entities, roles, tasks, resources and transactions can be modelled and simulated. The modelling of the midstream LNG supply chain, via BPM, is based on guidelines of the Society of International Gas Tanker and Terminal Operators (SIGGTO) and common industry business models. A quantitative analysis is employed to support the motivation and the potential impact of blockchain implementation. The methodology is used to identify (1) inefficiencies related to large volume of transactions between stakeholders and (2) critical areas of an LNG shipping company, where blockchain can be implemented.FindingsProcess repeatability, numerous shared documentation forms, excessive paperwork and communication imbroglios are mapped from the modelling section. Up to 327 processes are repeated during a typical vessel voyage, and up to 122 shared documentation forms are exchanged. Excessive paperwork and communication imbroglios are tracked through, which correspond to 25 severe errors as detected. By implementing the methodology, stakeholders can quantify the possible impact of blockchain on the operational performance of each stakeholder's operations separately and the supply chain as a whole in terms of real-time monitoring, transparency and paperwork reduction, time and cost savings.Research limitations/implicationsThe research has certain limitations deriving from its conceptual nature. The business processes' modelling is based on standard procedures described in the guidelines by SIGGTO and may need further adjustment for specific use cases. A structured case study has not been realisable as corporate data for an LNG shipping company regarding processes and other commercial sensitive information are required.Practical implicationsPotential practitioners may exploit the proposed framework as a low cost and seamless tool to evaluate how blockchain could disrupt their operations. Thus, the blockchain implementation's improvements or weaknesses can be pinpointed, and enabling the interested stakeholder of the LNG supply chain with specific feedback, it can guide them towards informed decisions on their operations.Originality/valueThe research has a novel approach as it combines the creation of practical management framework, with a comprehensive visualization of the midstream LNG supply chain. Thus, the reader can identify in which parts of the midstream LNG supply chain can blockchain be implemented, and what impact it could have in terms of supply chain operations.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Junwoo Jeon ◽  
Emrah Gulay ◽  
Okan Duru

PurposeThis research analyzes the cycle of the dry bulk shipping market (DBSM) as a representative of spot and period charter rates in dry bulk shipping to develop strategies for investment timing (i.e. asset play) and fleet trading (chartering strategy).Design/methodology/approachSpectral analysis is a numerical approach to extract significant cyclicality, which may be utilized to develop trading strategies. Instead of working with a single dataset (univariate), a system approach can be utilized to observe a significant shipping market cycle in its multi-variate circumstance. In this paper, a system dynamics design is employed to extract cyclicality in the DBSM in its particular industrial environment. The system dynamic design has competitive forecasting accuracy relative to univariate time series models and artificial neural networks (ANNs) in terms of forecasting outcomes.FindingsThe results show that the system dynamic design has a better forecasting performance according to three evaluation metrics, mean absolute scale error (MASE), root mean square error (RMSE) and mean absolute percentage error (MAPE).Originality/valueCyclical analysis is a significantly useful instrument for shipping asset management, particularly in market entry–exit operations. This paper investigated the cyclical nature of the dry bulk shipping business and estimated significant business cycle periodicity at around 4.5-year frequency (i.e. the Kitchin cycle).


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