D
2020
Geographical distribution of sustainable tourism development of the countries of the European Union using the machine learning method
BOTLÍKOVÁ, Milena, Josef BOTLÍK, Petr JANÍK and Jana STUCHLÍKOVÁ
Basic information
Original name
Geographical distribution of sustainable tourism development of the countries of the European Union using the machine learning method
Authors
BOTLÍKOVÁ, Milena (203 Czech Republic, guarantor, belonging to the institution),
Josef BOTLÍK (203 Czech Republic), Petr JANÍK (203 Czech Republic, belonging to the institution) and
Jana STUCHLÍKOVÁ (203 Czech Republic, belonging to the institution)
Edition
36th. USA, 36th IBIMA Conference: Sustainable Economic Development and Advancing Education Excellence in the Era of Global Pandemic, p. 11090-11097, 8 pp. 2020
Publisher
INT BUSINESS INFORMATION MANAGEMENT ASSOC-IBIMA
Other information
Type of outcome
Stať ve sborníku
Field of Study
50901 Other social sciences
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
RIV identification code
RIV/47813059:19240/20:A0000706
Organization unit
Faculty of Philosophy and Science in Opava
Keywords (in Czech)
Udržitelnost; cestovní ruch; enviroment; Evropská unie
Keywords in English
Sustainable; tourism; environment; European Union
Tags
International impact, Reviewed
V originále
On the one hand, the long-term growth of tourism leads to the development of the environment. The mass nature of tourism in recent years has created negative pressures on the social and natural environment. For these reasons, development needs to be geared towards sustainability. Creating an environment in which social, economic and environmental areas are consistent. Measuring the sustainability of tourism in the EU is based on the methodology of European indicators for assessing sustainable development. The article deals with the comparison of sustainable tourism of EU countries on the basis of selected indicators from individual areas of sustainability year-on-year comparison of 2012 and 2017 through machine learning methods and comparative analysis. The results show that there are countries that are still lagging behind in achieving sustainability goals in terms of renewables or waste production.
Displayed: 27/12/2024 00:30