Education is a factor for economic prosperity and social development in modern society. As well education allows its owner to receive a higher income and gives the opportunity for self-expression, creative fulfilment, as well as moral satisfaction from current activities. The life of educated people is not only longer, but also more interesting and informative. Moreover people with a higher level of education are happier also. In this aspect the purpose of the article is to determine the relationship between the quality of education, the degree of economic freedom, the level of income and the feeling of happiness. This paper presents results of the correlation analysis between indicators of education, income, happiness and economic freedom for 145 countries for 2018. The author of the work calculated Pearson (product-moment) correlation, the Spearman rank correlation, and Kendall’s Tau correlation in the Statistica. The analysis showed that Education Index has a strong relationship with Happiness Index, Economic Freedom of the World Index, Index of Economic Freedom and GDP. The analysis showed that education is closely related to the level of income and selfawareness of happiness. Education is also closely related to economic freedom. Also, the results of the study suggest that education not only contributes to an increase in income, but also makes persons happier.
The article substantiates the expediency of using the interactive training technologies of teaching in the educational process for students of tourism specialities since training of the specialists for tourism sphere is one of the most important issues because the quality of personnel is a key factor of the tourism development. The essence of interactive teaching methods as compared to the traditional ones has been analysed. The advantages and features of using the interactive methods in the educational process which help to achieve learning objectives, enhance motivation to study, mould professional creative thinking, increase students' interest, stimulates teamwork, overcome shyness and insecurity in the real working environment have been highlighted. In the context of the tourism specialists' professional competences formation, a conceptual structure of the training including content blocks, methods of work, expected results has been proposed. On the basis of the interactive teaching technologies, a training concerning the development of an advertising campaign for a tourism company has been developed. Taking into account the specifics of the tourism industry, the authors have suggested a step-by-step running of an advertising campaign of the tourism company including a complex of interconnected advertising activities developed in accordance with the company's marketing program, covering a certain period of time and aimed at a given target audience in order to provoke a reaction that helps the company solve its strategic and tactical tasks. The article also highlights the advantages and disadvantages of advertising in tourism industry, its effectiveness in different media.
AUTHORSOlena Stryzhak ARTICLE INFOOlena Stryzhak (2019). Assessment of the relationship between the tourism sector development and other sectors of economy. AbstractAn assessment of a relationship between aggregated and partial indicators of the tourist sector development on one hand and other sectors of economy and society on other hand are investigated in the paper. Indicators are expressed in both direct monetary terms and rating scales. The study covers 149 countries in 2016. The results of the study indicate a positive relationship between the development of the tourist sector and the level of economic welfare of the country. This is explained by fact that tourist goods and services are subject of a second necessity and demand for they increases significantly with growth of income level. Found that there is a positive correlation between indicators of tourism sector development and indicators of quality of socio-economic environment. This may be due to fact that, on one hand, high quality socioeconomic environment stimulates visits to country; on other hand, travels stimulate growth of economy and welfare of citizens who live in territory that visited. Further analysis of aggregate of countries, divided into 4 groups by income, showed mixed results. Thus, a stronger correlation between all analyzed indicators is observed in low and highincome countries, weakening in transition to averages by a sample of values. However, such a weak relationship for some countries may be a consequence of a small share of the tourism sector in the economy. This paper differs from previous researches by focusing on a large sample of countries and reveals the relationship between tourism sector development indicators and socioeconomic environment indicators. One can speak of objectivity of results obtained, since they are confirmed both using Spearman's correlation coefficient and Kendall's Tau correlation. Keywords JEL ClassificationA13, C13, F62, O11 Анотація
The digital transformation of society affects socio-economic relations in all spheres of life; however, the degree of this influence differs depending on countries and regions. Various industries and sectors of the economy are also affected by digitalization to one degree or another.In this context, the purpose of the paper is to determine the dependence of human capital in the tourism industry on the digitalization level of the economy.The following methods were used: data standardization, cluster analysis, analysis of variance, K means, and SWOT analysis.The panel sample includes indicators from 61 countries for 2018. The analysis revealed distinctive features that allowed allocating the countries into clusters. Cluster 1 (14 cases): countries with average Human Capital Index (HCI) and World Digital Competitiveness (WDC) values, depending on tourism. Cluster 2 (13 cases): countries with slightly above average HCI and WDC values that are less dependent on tourism. Cluster 3 (15 cases): countries with HCI and WDC values below average, not particularly dependent on tourism. Cluster 4 (1 case): outliers. Cluster 5 (18 cases): countries with above average HCI and WDC that are tourism dependent. The calculation results made it possible to identify the cluster principles. The use of the identified distinctive features in the SWOT analysis allows formulating the key elements of human capital strategies in the tourism sector for each group of countries.
Based on a bibliographic analysis of the literature, it is determined that most current studies point to the impact of digitalization on tourism. Digital technologies are changing tourism preferences, consumption, and the essence of the interaction of tourism business entities. In this context, the study aims to identify the specifics of the relationship between the level of international tourism development and digital technologies. The purpose of the study is to determine the features of the relationship between the level of international tourism development and digital technologies. Methods such as bibliographic, standardization, correlation analysis, factor analysis without rotation and, factor analysis with rotation using the Varimax method, comparative analysis, graphical analysis were used in the article. The World Bank International Tourism Indicators (such as expenditures, the number of arrivals, the number of departures, and receipts) and the Network Readiness Index were used for the analysis. The data covers 130 countries for 2020. The research identified correlations between indicators of international tourism development and the Networked Readiness Index and its components. The analysis shows that there is a direct relationship between the analyzed indicators. Also, factor loadings were calculated in the paper using factor analysis without rotation and factor analysis with rotation by applying the Varimax method. The Varimax rotation method made it possible to identify two well-defined factors, one closely related to the Networked Readiness Index sub-indices and the second – to the international tourism indicators. By using factor analysis without rotation, one factor was identified. Based on this analysis, it was concluded that the level of international tourism development and the degree of digitalization of the economy are linked. In the case of determining the relationship between the sub-index Networked Readiness Index Technology and expenditures and the number of arrivals, this relationship was not identified. The results highlight the importance of digitalization in the tourism business. In doing so, the paper points out that in addition to digital technologies, tourism companies should also pay attention to other factors such as security, risks, fluctuating economic situation, changing geo-economic and social conditions, etc.
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