scholarly journals Domestic tourism, its potential to compensate the outage of international arrivals caused by COVID-19 and the vulnerability of different groups of countries (a cluster analysis)

2021 ◽  
Author(s):  
Zuzana Kv�tkov� ◽  
Zdenka Petrů ◽  
Alžběta Zíková
Keyword(s):  
Cluster Analysis ◽  
Significant Role ◽  
International Organizations ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
Domestic Tourism ◽  
Universal Solution ◽  
Per Capita ◽  
Competitiveness Index

Tourism is the most affected industry by the pandemic COVID-19 and will be probably also the last one to recover. International organizations UNWTO, WTTC, and others suppose that domestic tourism will play a significant role in 2020 and after. However, domestic tourism is not a universal solution for all destinations. This paper aims to identify the factors that might play a role in the domestic tourism results in 2020 and later and to which extent domestic tourism can compensate the outage of international arrivals in different countries. Two types of factors were analysed: (1) economic factors (GDP, GDP per capita, share of tourism on GDP) and (2) characteristics of tourism (domestic tourism intensity, Travel &Tourism Competitiveness Index, domestic tourism share etc). Based on the data from 2018 and 2019 from 41 countries, the cluster analysis identified six groups of countries with different potential of domestic tourism to support the survival of the tourism businesses and drive recovery in the post-pandemic period.

Golf, supply and demand

2016 ◽  
Vol 23 (6) ◽  
pp. 1220-1234 ◽  
Author(s):  
E Bárcena-Martín ◽  
M Rodríguez-Fernández ◽  
S Borrego-Domínguez
Keyword(s):  
Panel Data ◽  
Financial Crisis ◽  
Stock Market ◽  
Supply And Demand ◽  
Dynamic Panel Data ◽  
Economic Situation ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
Stock Market Index ◽  
Per Capita

Macroeconomic conditions can have a substantial effect on the economic circumstances of individuals and therefore on the golf demand in a country. Using panel data on golf demand (number of golf players) and supply (number of courses), and indicators of the economic situation for 15 European countries, encompassing years 2000 through 2014, we estimate a dynamic panel data model in order to evaluate the influence of the economic conditions and golf supply on the number of registered golfers. Economic situation is assessed through two variables: the gross domestic product (GDP) and the main stock market index of each country. We also test the hypothesis of uneven effects of the GDP before and after the beginning of the economic recession. The most crucial finding is that from the start of the financial crisis, the level of GDP imposes statistically significant effect on golf demand, making those countries with higher GDP per capita the ones whose golf demand is harmed the least by the financial crisis. The number of golf players responds to the state of the economy after the start of the economic downturns, while the high persistence of the golf demand makes it rather difficult to find significant differences in the changes in GDP before the recession. We also find that the number of golf courses is not seen to bear a close relationship with the number of players unless we control for economic factors and business cycle. Within the economic factors, the level of development of a country, as measured by GDP per capita, outweighs stock market role in determining the demand for golf.

Energy consumption flow and regional economic development: evidence from 25 economies

2017 ◽  
Vol 12 (1) ◽  
pp. 96-118 ◽  
Author(s):  
Bao-jun Tang ◽  
Pi-qin Gong ◽  
Yu-chong Xiao ◽  
Huai-yu Wang
Keyword(s):  
Cluster Analysis ◽  
Economic Development ◽  
Energy Consumption ◽  
Negative Relationship ◽  
Regional Economic Development ◽  
Embodied Energy ◽  
Gdp Per Capita ◽  
Regional Economic ◽  
Content Type ◽  
Per Capita

Purpose This paper aims to figure out the relationship between energy consumption flow from a new perspective of embodied energy inventory index (EEII) and regional economic growth. Design/methodology/approach The input-output approach has been applied to calculate embodied energy inventory (EEI) and EEII using the data of 25 economies. Meanwhile, cluster analysis and panel data modeling were applied to carry out detailed research. Findings The results of cluster analysis show that there is a roughly negative relationship between EEII and gross domestic product (GDP) per capita, although there are some exceptions, such as Russia and Taiwan (Province of China). Panel data model results provide further evidence that there is a negative relationship between EEII and GDP per capita. Population is an important productive factor in the regional economic development. The study showed a positive relationship between EEII and population. Therefore, energy consumption flow is closely related to regional economic development. Originality/value The value of this paper is to use EEI and EEII to comprehensively clarify the energy consumption flow. The advantage of EEII is that it can reflect the energy embodied in fixed assets and infrastructure.

scholarly journals An Analysis of Domestic Tourism Consumption Based on R Software

2018 ◽  
Vol 228 ◽  
pp. 05006
Author(s):  
Hongyu Ding
Keyword(s):  
Gdp Per Capita ◽  
Capita Consumption ◽  
Linear Regression Models ◽  
Factors Affecting ◽  
Consumption Data ◽  
Travel Agencies ◽  
Dependent Variables ◽  
Domestic Tourism ◽  
Per Capita ◽  
Per Capita Consumption

R is a software system which can be used for data processing, calculation and mapping. The syntax of this language is superficially similar to C, but semantically it is functional programming language. It is widely used in statistical analysis. So this paper used it to analyze China domestic tourism consumption data during 1999-2015, and analyzed the main factors affecting the consumption level of domestic tourism in China from residents’ disposable income, GDP, per capita consumption of tourists, tourists, the mileage of railways and the number of travel agencies. Finally it established and solved the multiple linear regression models, taking domestic tourism consumption as dependent variable and taking GDP, and per capita consumption of tourists, the number of tourists and the mileage of railways as dependent variables. The results show that there is significant positive correlation between domestic tourism consumption, GDP, per capita consumption of tourists, the number of tourists and the number of travel agencies.

scholarly journals Migration among EU Countries: Underlying Fundamentals

2018 ◽  
Vol 14 (3) ◽  
pp. 191-198
Author(s):  
Nahid Kalbasi Anaraki
Keyword(s):  
Unemployment Rate ◽  
European Countries ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
Push Factors ◽  
Quarterly Data ◽  
Eu Countries ◽  
Per Capita

This paper investigated the immigration flow among periphery and core European countries to find out what are the most important factors shaping immigration trends. Using quarterly data for the period of 1990-2016 for immigration from Greece, Italy, Portugal, and Spain to core European countries including: Germany, Netherlands, and Sweden, the results of this study suggest that pull economic factors such as GDP per capita and unemployment rate in the destination countries are the more important factors shaping the immigration trend than the push factors including labor reforms. The higher the unemployment rate in the destination the less migrants flow to these countries. The results indicate that the labor reforms in the origin country don’t have statistically significant impacts on the immigration trends.

scholarly journals Social-economic drivers overwhelm climate in underlying the COVID-19 early growth rate

2021 ◽  
Author(s):  
Zhenghua Liu
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Early Growth ◽  
The Other ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
List Type ◽  
Per Capita ◽  
Negative Relationships ◽  
Socio Economic Factors

AbstractIdentifying the drivers underlying the spatial occurrence and spreading rate of COVID-19 can provide valuable information for their preventions and controls. Here, we examine how socio-economic and climate drivers affect the early growth rates of COVID-19 in China and the other countries, the former of which have consistently stricter quarantine during early epidemic and thus are used to enquire the influences of human interventions on trainsimissions. We find that the early growth rates of COVID-19 are higher in China than the other countries, which is consistent with previous reports. The global spread is mainly driven by the socio-economic factors such as GDP per capita, human movement and population density rather than climate. Among socio-economic factors, GDP per capita is most important showing negative relationships in China, while positive in the other countries. However, the predicability of early growth rates by socio-economic and climate variables is at least 1.6 times higher in China’s provinces than the other countries, which is further supported by metapopulation network model. These findings collectively indicate that the stochasticity of transimission processes decrease upon strict quarantine measures such as travel restrictions.Key findingsGDP per capita is most important in driving the spread of COVID-19, which shows negative relationships within China, while positive in the other countries.Socio-economic and climate factors are key in driving the early growth rate of COVID-19, while the former is more important.Socio-economic and climate features explain more variations of early growth rates in China due to the decreased stochasticity of transimission processes upon strict quarantine measures.

scholarly journals The Role of ICT and Entrepreneurship in forming Sustainable Supply Chains: Before and After the Covid-19 Pandemic

2021 ◽  
Vol 20 (3) ◽  
pp. 461-488
Author(s):  
R. S. Rogulin ◽  
Keyword(s):  
Cluster Analysis ◽  
Supply Chains ◽  
High Efficiency ◽  
Well Being ◽  
Efficiency Index ◽  
Entrepreneurial Activity ◽  
Gdp Per Capita ◽  
Crisis Period ◽  
Per Capita

Supply chain management is currently undergoing a significant digital transformation driven by the COVID-19 pandemic. The purpose of this study is to assess the role of digital technologies and entrepreneurship in improving the efficiency of supply chains in the pre-crisis and post-crisis periods. The paper considers GDP per capita as a value characterizing the degree of the country's well-being in the pre-crisis period; the LPI logistics efficiency index which determines the degree of development of the logistics environment in the country; the TIDL digital life index, which assesses the degree of development of the economy from the standpoint of digitalization; the GEI entrepreneurship index reflecting the degree of development of entrepreneurship in the country. A cluster analysis of countries by regression coefficients of the dependence of GDP per capita on the year is carried out. The result of the cluster analysis was the division of many countries into clusters, from which two economies were taken for further analysis. The work resulted in conclusions about a significant relationship between ICT and logistics efficiency, between the level of entrepreneurship and the efficiency of logistics in the pre-crisis period. It is shown that developed economies have high efficiency of logistics systems, high values ​​of the rating of digital life and the level of entrepreneurship, which cannot be argued for countries with a level of development starting from the middle and below. The main conclusion of the study is the fact that, firstly, the active introduction of ICT makes it possible to restore supply chains destroyed by the crisis, to increase their efficiency, and secondly, the development of entrepreneurial activity in the country gives a serious impetus to the efficiency of supply chains, as a result of which businesses get a chance not only to survive amid a pandemic, but also gain significant benefits. This work is constrained by the lack of post-crisis data, so there is a huge spectrum to complement the current research on the stability and resilience of supply chains during and after pandemics.

scholarly journals Inequality in the Income of the Population as a Determinant of the Country's Economic Growth

2020 ◽  
Vol 68 (6) ◽  
pp. 987-994
Author(s):  
Tamara Kocurová ◽  
David Hampel
Keyword(s):  
Economic Growth ◽  
Cluster Analysis ◽  
Regression Analysis ◽  
Income Inequality ◽  
Economic Performance ◽  
Negative Impact ◽  
Gdp Per Capita ◽  
Ratio Analysis ◽  
Eu Countries ◽  
Per Capita

In this article, there is explored the dependence of economic performance and economic growth on income inequality expressed by Gini coefficient and S80/S20 ratio. Analysis is based on data collected upon EU countries in years 2007, 2012 and 2017. Cluster analysis points out to heterogeneity of EU countries in observed characteristics and enables creation of three groups of countries: post-socialistic, southern and northern. Regression analysis, which takes into account groups of countries, was used to assess and illustrate the dependence. The results show that income inequality has a negative impact on the country's GDP per capita, and its impact on economic growth differs for particular groups of countries.

scholarly journals Breast cancer and socio-economic factors

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Anees B. Chagpar ◽  
Mario Coccia
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Purchasing Power Parity ◽  
Breast Cancer Incidence ◽  
Alternative Interpretation ◽  
Gdp Per Capita ◽  
Economic Factors ◽  
Power Parity ◽  
Per Capita ◽  
Socio Economic Factors

Purpose: The aim of this study is twofold – on the one hand, to analyze the relationship between incidence of breast cancer, income per capita and medical equipment across countries; after that, the study here discusses the drivers of the incidence of breast cancer across countries in order to pinpoint differences and similarities. Methods: The indicators used are incidence of breast cancer based on Age-standardized rate (ASW); Gross domestic product (GDP) per capita by purchasing power parity (current international $); computed tomography (CT) for cancer diagnosis. Data include 52 countries. The statistical analysis is carried out by correlation, ANOVA and an econometric modeling based on a multiple regression model of the breast cancer incidence on two explanatory variables. Results: Partial correlation is higher: rbreast cancer, GDP  CT=60.3% (sign.0.00). The estimated relationship shows an expected incidence of breast cancer increase of approximately 0.05% for a GDP increase of 1% and an expected incidence of breast cancer increase of approximately 3.23% for a CT increase of 1%. ANOVA confirms that incidence of breast cancer is higher across richer countries, ceteris paribus. Conclusions: Empirical evidence shows that the breast cancer tends to be higher across richer countries, measured by GDP per capita and number of Computed Tomography. The main determinants of these findings can be due to several socio-economic factors, mainly localized in richer countries. In addition, this research may provide an alternative interpretation to the theory of Oh et al. (2010) on the influence of latitude on breast cancer, focusing on socio-economic factors rather than biologic root causes.

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