The vital role of container liner shipping in international trade suggests that understanding why container liner firms go bankrupt is crucial to the sustainability of the maritime supply chain to improve resilience. Considering the insolvency of Hanjin Shipping as a case study, this paper investigates the probabilistic relationships among the bankruptcy causal factors that are disclosed qualitatively and quantitatively, exploiting a fuzzy Bayes network approach. A sensitivity analysis is conducted to increase the accuracy of the findings. Outcomes of the paper reveal that an integrated approach comprising of both endogenous and exogenous causal factors is a more powerful approach to explain the demise of Hanjin Shipping. Compared to exogenous factors, endogenous factors account more for the collapse of the firm. Furthermore, it is found that government support would have been a more influential measure to mitigate the negative effects of the demise compared to the merging and acquisition practice. Competitor liner operators, policymakers, and stakeholders in the maritime supply chain ecosystem can utilize the outcomes of this research to mitigate the bankruptcy risk and improve the maritime supply chain resilience capacity.

Decision-making is often performed intuitively, yet formal decision-making by logical reasoning is needed for crosschecking or advocating despite its being burdensome and comprehensive. Prescriptive and descriptive approaches have been introduced for formal decision-making. Former regards decision makers as, metaphorically, rational computers whereas latter considers the human perception of value and probability differentiating in case of loss and gain. To the best of our knowledge, no research has been conducted on a ship sale and purchase problem based on a descriptive method to explain human risk aversive nature, perception of value, and probability. This study is therefore unique in the academic literature. This research includes the presentation of formal decision-making, related approaches, methods, and theories, the application of cumulative prospect theory (CPT) on a ship sale and purchase problem. An empirical study has been created and modeled, including statistical data concerning fuel oil prices and freight rate profit margins. A voyage estimation based on the empirical study is performed, calculations are carried out by utilizing the expected value method and CPT. Results obtained are quite useful for a better understanding formal decision-making, prescriptive, and descriptive approaches, and interpreting status-quo in demand for bulk carriers.

Recently, the marine industry has been under a paradigm shift toward adopting increased automation, and initiatives to enable the autonomous operations of ships are ongoing. In these cases, power plants require advanced monitoring techniques not only for the performance parameters but also to assess the health state of their critical components. In this respect, this study aims to develop a monitoring functionality for power plants that captures the performance metrics while considering the overall system and its components’ reliability. A hybrid power plant of a pilot boat is considered a case study. A rule-based energy management strategy is adopted, which makes the decisions on the power distribution to the investigated power plant components. Additionally, a dynamic Bayesian network is developed to capture the temporal behavior of the system’s/components’ reliability accounting for the power plant’s operating profile. Results demonstrate that the selected hybrid power plant monitoring capabilities are enhanced by providing the power plant performance along with the estimation of the system’s health state. Furthermore, these extended monitoring capabilities can provide the essential metrics to facilitate decisionmaking, enabling the autonomous operation of the power plant.

Navigation is a significant part of shipping safety as it directs and delivers the physical mass of commercial assets. In addition to navigation, ship domain is a frequently used navigation safety concept in mariner’s terminology. However, the perception of ship domain lacks the terse representation because of multidimensional factors of the sea environment. This study has proposed not only a data-driven ship domain that can be compared with theoretical counterparts to validate navigation safety understanding in open waters but also a unique minimum distance passage representation for ship domain. This study proposes ship domain visualization for ship-ship encounters only in the closest passages rather than all ship trajectories. Results show that ship domain boundaries are consistent with former studies, but such results provide in-depth inference.

This research aimed to determine and prioritize a set of criteria for the development of logistics centers. Both qualitative and quantitative data collection methods were used to achieve the research aim. Content analysis and semistructured interview techniques were used as the qualitative research methods. Semistructured interviews were conducted with 14 experts, including seven logistics center managers and seven logistics company managers who have worked in a logistics center. The qualitative research revealed eight main criteria and their subcriteria, including location, infrastructure, activities and services, ownership and management, market conditions, regulations, benefits, and horizontal collaborations. The fuzzy analytic hierarchy process was conducted with 18 professionals/experts from different groups of logistics center stakeholders to prioritize the set of criteria. The results were interpreted based on the findings. Among the eight selected criteria, “location” (22%) was the most important criterion, followed by “market conditions” (20%).

The risks associated with the navigation of large tankers in restricted waterways have resulted in continuing development of routing measures such as Traffic Separation Schemes (TSS). This is generally subject to discussion between the administration and ship operators which may find some navigational rules and regulations unnecessarily restrictive. Motivated by the need for an objective and scientific method to determine the vessel characteristics and environmental conditions for a safe passage through a restricted waterway, this paper presents an optimized routing procedure based on maneuvering simulations and non-linear direct search techniques which can be used to determine the best attainable route for large tankers in restricted waterways and specified environmental conditions. The mathematical model for predicting the maneuvering performance is based on a modular approach in which the hydrodynamic, propeller and rudder forces are computed separately, while environmental forces are estimated by semi-empirical methods. The objective of the optimization procedure is to determine the required number and magnitude of rudder control commands for remaining within a specified TSS and minimizing a grounding or collision possibility.

Instagram posts of sail training centers were examined and a comprehensive content analysis of photographs was used to comprehend the patterns of social media marketing and services offered. Two coders analyzed the Instagram profiles of five Turkish and five international yacht/sail training centers generating five main codes for a total of 288 codes with the Cohens cappa intercoder reliability calculated as 86%, which is considered reliable. The photographs were coded and analyzed using MAXQDA qualitative research software, and variables such as point of view, mood, and boat parts were explored. Qualitative analyses such as code distances mapping, code-subcodes analysis, and two-cases models comparative analyses were conducted, and results were discussed. The patterns that emerged were race focused, learning focused, license training, natural scenery/touristic appeal, warm, friendly/social, and lackadaisical/low social media activity. Several qualitati-ve analyses were carried out, and the results were presented in terms of their contribution to the literature and managerial applications.

Forecasting freight rates has been a topic of discussion for decades. Even though freight rate forecasting is regarded as a critical research topic in shipping, the literature lacks a systematic empirical account of how to obtain more reliable and accurate freight rate forecasts. This study uses meta-regression to synthesize the literature on freight rate forecasting and to test various accuracy influencers. The study confirms that the accuracy of the freight rate forecasts depends significantly on data frequency, forecasting horizon and method, market type, sample size, and the inclusion of explanatory variables.