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EN
Maritime and coastal areas are the lifeblood of many countries. They are vital to the prosperity of countries because they provide trade routes, regulate the climate, are a source of organic and inorganic resources and energy, and provide a place for the public to live and relax. Increasingly, however, there are divergences and barriers to the use of marine areas. On the one hand, available and developed technology and knowledge enable increasingly improved use of the sea. On the other hand, the combined effect of these activities leads to conflicts of interest and the deterioration of the marine environment. The purpose of this study is to analyze the feasibility of using automatic identification system (AIS) maritime traffic data, in terms of its suitability, to correctly assess the utilization of the potential of a specific fleet within the offshore shipping industry. In addition, the authors undertake the task of determining to what extent activities relating to the GPS position of the ship, ship type (i.e., cargo or passenger), ship status (i.e., aground, anchored, moored, not under command, restricted maneuverability, underway sailing, or underway using its engine), ship draught, service speed, total engine power, and deadweight constitute areas and methods for optimizing the use of the offshore fleet under all the conditions previously described that limit this optimization. Given the stated goal, this paper uses both a literature review procedure and statistical methods to conduct a comparative analysis.
EN
Maritime and coastal areas are the lifeblood of many countries, being essential to their well-being. They provide trade routes, regulate the climate, and supply both organic and inorganic resources, along with energy, a crucial requirement for living and recreation. However, there are emerging disparities and barriers in terms of marine exploitation. On the one hand, existing and evolving technologies and knowledge allow better utilization of the sea, while on the other hand, the cumulative effect of human activity leads to conflicts of interest and to a deterioration of the marine environment. This article aims to consider the impact of changes in the world economy on the evolution of the fishing fleet, including the characteristics of vessels produced in consecutive years. We also attempt to determine the most common type of vessel presently operating in the world fleet. A number of external factors impact the organization and operation of the world’s fishing fleet, including economic, geographical, and political factors. The strength of each factor varies depending on the conditions in which the fleet operates. Also, we would also like to establish to what extent efforts aimed at energy demand reduction have affected the characteristics of the current fleet, determining the scale and direction of change, while also identifying any relevant constraints and limitations. The intention behind this paper is to discover the size and structure of the fishing fleet and whether it is changing as a result of environmental transformation. With this objective in mind, we have outlined a review of the literature and used statistical methods in order to carry out a comparative analysis of the size and structure of the world’s fishing fleet.
EN
Globalization poses new challenges, while also providing development opportunities for strong and dynamic enterprises and new sectors which shape the world markets and economy and contribute to a more global approach to business activities. The business activities undertaken in each country depend on a number of factors, and these factors are often similar due to globalization, though their impacts appear to vary. In addition, changes in economies progress at different speeds, thus this article aims to determine how the impact of change in the global economy influences transformations in ownership in container shipping. The organization and operation of global container shipping is shaped by numerous external factors, i.e. economic, geographical, and political factors. The impact of these factors varies depending on the specific aspect of the container shipping industry being discussed. This paper was motivated by the need to determine the container fleet size and ownership structure in container shipping, and whether these are changing as the industry evolves. The stated aim of this research requires the use of statistical methods and a literature review to allow for a comparative study of the size and ownership relations in container shipping.
4
Content available Global trends in maritime cruise fleet development
EN
The exercise of the economic and social functions of maritime tourism has undergone significant changes in recent years. A case in point is the development of the maritime cruise fleet, in both quantitative and qualitative terms, across various regions. This is a result of, among other things, the changing needs of international tourists in particular regions. The worldwide expansion of globalization has also marked a turnaround in preferences, with customers now willing to visit regions formerly unattractive or rarely considered by tourists. These changes are also visible in the variety of transport modalities available to passengers for both domestic and international voyages. To a large extent, these changes stem from technological developments. New possibilities for quick and efficient passenger transport have contributed to transforming maritime tourism in many countries. This, in turn, has led to increasing volumes of tourist traffic, generating economic growth for such nations. This article discusses contemporary trends in the world’s cruise ship fleets in the context of the technical parameters of global cruise shipping. The authors have attempted to determine the basic quantitative parameters and metrics expected for characterizing the global cruise ship fleet. To accomplish this, the method of linear regression has been used, with the input data being the sizes of cruise ship fleets and some other characteristic parameters, during particular time periods, carrying capacities, registered tonnages, numbers of passenger cabins, main and auxiliary engine powers, and levels of fuel consumption. The econometric model of linear regression has allowed calculating the projected values for the nearest future.
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