International Journal of e-Navigation and Maritime Economy最新文献

It has been well acknowledged that Vessel Traffic Services (VTS) has played a growing important role to ensure the safety of navigation in the busy ports and waterways. However, the benefits produced by VTS are usually ignored by the public and private sectors. Besides, the previous evaluations generally exist following problems: (1) It is difficult to collect the data for the parameters in the evaluation models and/or the parameters are designed illogically; (2) Those models did not take the following factors into consideration such as reducing the frequency of coastal vessel patrolling and saving human and material resources; (3) It is difficult to clearly discriminate the benefits derived from VTS and non-VTS. In this paper, a framework is presented to calculate the benefits of VTS in China. Four key indicators (safety, traffic efficiency, environmental protection and reducing supervising cost) and quantitative methods have been introduced into the framework. When calculating the benefits quantitatively, the traffic condition before the construction (expansion) of the VTS has acted as a benchmark. For a case study, the project of the expansion of VTS in Zhoushan Port, East China was evaluated with 10-year data. According to the results, the largest contribution is from the benefit of environmental protection. Via Cost-benefit analysis the benefit cost ratio (B/C) of the VTS is up to 5.248, which shows the benefits produced by VTS are considerable. The research could provide references for VTS benefits evaluation and investment optimizing.

The global economic and financial conditions in 2010 and 2011 were positive and the business trade grew at about twice of the rate of that in 2009. The container shipping players started to enjoy a new chapter of international business trade having struggled to operate their vessels since 2008. So we now have to consider if the shipping business will return to its old strategy? What will happen to the container shipping sector in 10 years from now still remains uncertain. Recently, the uncertain situation globally has been giving shipping companies in difficulty the opportunity to make decision as to whether it is necessary to use super slow steaming for containerships. Therefore, the aim of this study is to analyse the necessity of super slow steaming on containerships despite such uncertainty. A Fuzzy Rule-based Bayesian Reasoning method has been used which incorporates the membership function and 14 selected nodes. Finally, the outcome of this study is 48 rules which have been proposed to assist shipping companies in their decision making processes when dealing with the dynamic business environment. Each rule gives a clear-cut understanding of the result which is able to be applied to real situations the containership industry faces.

Workplace safety continues to be an area of concern in the maritime industry due to the international nature of the operations. The effectiveness of extensive legislation to manage shipboard safety remains in doubt. The focus must therefore shift towards the human element - seafarers and their perceptions of safety. The study aims to understand the alignment that exists between safety culture and safety climate on board ships as perceived by seafarers. The underlying factors of safety climate were identified using factor analysis which isolated seven factors - Support on Safety, Organizational Support, Resource Availability, Work Environment, Job Demands, ‘Just’ Culture, and Safety Compliance. The perception of safety level of seafarers was found to be low indicating the existence of misalignments between safety culture values and the actual safety climate. The study also reveals that the safety perceptions of officers employed directly by ship owners and those by managers do not differ significantly, nor do they differ between senior and junior officers. A shift in perspective towards how seafarers themselves feel towards safety might provide more effective solutions – instead of relying on regulations - and indeed aid in reducing incidents on board. This paper details practical suggestions on how to identify the factors that contribute towards a better safety climate on board ships.

In the tanker industry, there are a lot of uncertain conditions that tanker companies have to deal with. For example, the global financial crisis and economic recession, the increase of bunker fuel prices and global climate change. Such conditions have forced tanker companies to change tankers speed from full speed to slow speed, extra slow speed and super slow speed. Due to such conditions, the objective of this paper is to present a methodology for determining vessel speeds of tankers that minimize the cost of the vessels under such conditions. The four levels of vessel speed in the tanker industry will be investigated and will incorporate a number of uncertain conditions. This will be done by developing a scientific model using a rule-based Bayesian reasoning method. The proposed model has produced 96 rules that can be used as guidance in the decision making process. Such results help tanker companies to determine the appropriate vessel speed to be used in a dynamic operational environmental.

The ownership structure which has a huge impact on company operation performance is the foundation of corporate governance structure choice. At present, the number of China's listed port companies is the largest in the world; however, they have a very complex ownership structure. This study discusses the impact of ownership structure on the operation performance of the Chinese ports. This empirical research applies factor analysis to evaluate the operation performance of listed port companies, and then adopts linear regression analysis based on the evaluation results to explore the impact of ownership structure to operation performance. Finally, it proposes recommendations for optimizing the ownership structure of listed port companies, in order to promote a better and faster development of China's port industry. The empirical results show that for most of the listed port companies, the largest shareholder is in the absolute controlling position, and the gap between the largest shareholder and the second largest shareholder is very large, which means the ownership concentration is relatively high. Meanwhile, the top five shareholders equity ratio squared is in negative correlation with operation performance.

Transportation problem is an optimization problem. In general, it was studied under random or uncertain condition. Considering the recent complexity, it is not enough to make should be a perfect transportation plan only based on. Usually, there is not only uncertainty but also randomness in many systems. In this paper, the aim is to investigate a transportation problem under uncertain and random environment. As a result, a conceptual uncertain random model is proposed for the problem, where the supplies are considered as random variables, and the costs and the demands are uncertain variables. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, transforming the model into a crisp mathematical form is the main conclusion. By minimizing the expected value of uncertain objective function and taking confidence levels on constraints, the above model can be turned to a mathematical form. Then transforming the model into a typical mathematical programming model is the main conclusion by using uncertainty theory and probability theory. At the end, a numerical example is given to show the feasibility of the model.

Adaptive assessment e-platform is being promoted in the world to make teachers understand students’ e-learning performance on the Internet. However, system's load testing for an adaptive assessment is a very important issue during development of such an e-platform. In this paper, we have adopted the genetic fuzzy markup language (GFML) to infer the performance of an adaptive assessment e-platform. Firstly, we collected the data and information of the e-platform loading in two different mechanisms. With the collected data, the proposed CPU usage calculation mechanism is first implemented to acquire the CPU usage information from the screenshot of Ganglia. Next, we used the fuzzy c-means (FCM) clustering mechanism to construct the knowledge base according to the collected data. Then, number of threads, constant timer, MySQL parameter, CPU usage, and testing time of the e-platform were utilized to infer the e-platform load performance. Finally, the genetic learning algorithm was utilized to learn the knowledge and rule base to optimize the proposed approach. From these experimental results, the proposed method is feasible for verifying the performance of an adaptive assessment e-platform. In the future, the adaptive assessment e-platform can be utilized to e-Navigation systems and applications.