Search results

Container shipping companies face various risks with different consequences that are required to be mitigated. Limited empirical research has been done on identifying and evaluating risk management strategies in shipping operations with different risk consequences. This paper aims to identify the appropriate risk mitigation strategies and evaluate the relative importance of these strategies.

Literature review and interviews were used to identify and validate the appropriate risk mitigation strategies in container shipping operations. A questionnaire with a Likert five-point scale was then conducted to rank the identified risk mitigation strategies in terms of their overall effectiveness. Top six important strategies were selected to evaluate their relative importance under three risk consequences (i.e. financial, reputation and safety and security incident related loss) through using another questionnaire with paired-comparison. Fuzzy analytic hierarchy process (AHP) was then conducted to analyse the paired-comparison questionnaire.

After conducting a systematic literature review and interviews, 18 mitigation strategies were identified. The results from the first questionnaire show that among the 18 strategies, the top three are “form alliances with other shipping companies”, “use more advanced infrastructures (hardware and software)” and “choose partners very carefully”. After conducting fuzzy AHP, the results show that shipping companies emphasize more on reducing the risk consequence of financial loss; and “form alliance with other shipping companies” is the most important risk mitigation strategy.

This paper evaluates the risk mitigation strategies against three risk consequences. Managers can benefit from the systematic identification of mitigation strategies, which shipping companies can consider for adoption to reduce the operational risk impact.

The literature on Maritime Transportation (MT) is experiencing a transition phase where the focus of the research is repositioning. It registered steep growth in recent years with its beginning articles on the concepts of cost minimization to the current focus on achieving sustainable operational effectiveness using Information and Communication Technologies (ICTs). Thus, this becomes a right time to investigate the trajectory of research on MT.

The proposed study aims to explore the potential of data analytics techniques such as data mining and network analytics to reflect the trajectory of research in the maritime supply chain over time. This study identifies the eight main dimensions of the research published under maritime paradigm through network analytics. The in-depth review of these dimensions rendered us to segregate them further into sub-dimensions for the ease of understanding and interpretability. Further, the text mining is employed to extract thematic evolution of the research.

The evolved themes are completely exclusive from the conventional MT research with artificial intelligence, digital storage, waste management and biofuels emerging as contemporary themes. It is found that although there are a sufficient amount of literature on sustainable port practices but their policy implications are still underexplored. The inter-dimension research is needed to achieve the motive of economic efficiency and environmental sustainability simultaneously.

The study has contributed on the methodology side of conducting literature reviews. The dimensions, sub-dimensions and themes are obtained using data analytics tools and techniques. This omits the possibility of personal bias and thus making the results verifiable.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Effective risk management is vital for shipping container firms to combat different forms of risk. Use of a select number of relevant strategies can enable a cost-effective approach to the mitigation of risks associated with financial loss and issues relating to safety and security.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This paper aims to present an adaptive robust sliding mode tracking controller for a 6 degree-of-freedom industrial assembly robot with parametric uncertainties and external disturbances. The controller is used to achieve both stringent trajectory tracking, accurate parameter estimations and robustness against external disturbances.

The controller is designed based on the combination of sliding mode control, adaptive and robust controls and hence has good adaptation and robustness abilities to parametric variations and uncertainties. The unknown parameter estimates are updated online based on a discontinuous projection adaptation law. The robotic dynamics is first formulated in both joint spaces and workspace of the robot’s end-effector. Then, the design procedure of the adaptive robust sliding mode tracking controller and the parameter update law is detailed.

Comparative tests are also conducted to verify the effectiveness of the proposed controller, which show that the proposed controller achieves significantly better dynamic trajectory tracking performances as compared with conventional proportional derivative controller and sliding mode controller under the same conditions.

This is a new innovation for industrial assembly robot to improve assembly automation.