DIGITAL COMPETITIVENESS OF UKRAINE: GENERAL TRENDS AND IMPACT MODELING

2018 ◽  
Author(s):  
Nadiya Yavorska ◽  
◽  
Tetyana Danko ◽  
Keyword(s):  
Inverse Relationship ◽  
New Technologies ◽  
Statistical Significance ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Multiple Regression Equation ◽  
Individual Factors ◽  
Decisive Influence ◽  
The Impact ◽  
The Relationship

The object of the study is the digital competitiveness of the country and its impact on GDP. The paper summarizes the methodology for determining the rating of global digital competitiveness and investigates the impact of digital competitiveness on GDP using econometric analysis methods. The methodological basis of the study was the fundamental principles of economic theory, statistics and econometrics. To develop a statistical model of the relationship between digital competitiveness and GDP, correlation analysis was performed using the pairwise regression equation, and to influence individual factors - a linear multiple regression equation. The parameters of the constructed models by the method of least squares are estimated and their statistical significance is checked. The results of the study show that there is a close inverse relationship between the rating on the Digital Competitiveness Index and GDP. This is due to the fact that the linear correlation coefficient is -0.819, and the value of the coefficient of determination (0.6712) shows the decisive influence of digital competitiveness on GDP. Verification of the statistical significance of the constructed model allowed to recognize it as statistically reliable, which allows to use it for forecasting. Instead, the resulting econometric model of the relationship between individual factors of digital competitiveness rating and GDP is characterized by a strong inverse relationship between the two factors "Knowledge" and "Technology" and a direct relationship between the factor "Readiness for the future". The factor of "Knowledge", which characterizes the process of digital transformation of Ukraine through understanding, studying and creating new technologies, has a decisive influence on the volume of GDP. The developed model of the relationship between individual factors of digital competitiveness rating and GDP, as adequate and statistically significant, can be used for further analysis and forecasting. It is proved that the process of digitalization is an urgent need for the existence of the economic system at present, namely the introduction of digital technologies can increase the competitiveness of the country on the world stage.

scholarly journals أثر الإنفاق العام على البطالة في السودان خلال الفترة (1992-2018)

2022 ◽  
Vol 17 (2) ◽  
pp. 129-155
Author(s):  
د مصطفى أحمد قمر الدين عبد الله
Keyword(s):  
Unemployment Rate ◽  
Vocational Training ◽  
Inverse Relationship ◽  
Statistical Significance ◽  
Practical Importance ◽  
Public Spending ◽  
Steady Increase ◽  
Capital Spending ◽  
The Impact ◽  
The Relationship

The study deals with the impact of current and capital public  spending  on unemployment in Sudan during the period (1992-2018), and the importance of the study, from the fact that it deals with topics of great scientific and practical importance, and the aim of the study to know the nature of public spending in the current and capital aspects, the nature of unemployment, in addition to an alysing the relationship between these variables, and the problem of  study was that there is a steady  increase  in Current and capital  public  spending during the study period and therefore the unemployment situation in Sudan did not improve,  as the study used the descriptive and analytical approach, in addition to the standard method to know the relationship between the variables studied, and the study reached many results, the most important of which is: that there is a expulsionrelation ship with statistical significance Between current spending and the unemployment rate, there is also a morally inverse relationship between capital spending and the unemployment rate. The most important recommendations recommended by the study are to increase capital spending and direct this spending in creating and expanding the scope of productive projects, as well as to spend on vocational training centers and develop them and to transfer the experience of the countries that preceded Sudan in this area, which contributes to reducing the unemployment rate

The Impact of Trauma Center Volume on Observed/Expected Mortality: Does Size Matter?

2018 ◽  
Vol 84 (7) ◽  
pp. 1236-1239
Author(s):  
Adel Elkbuli ◽  
Alyssa Eily ◽  
Shaikh Hai ◽  
Mark McKenney ◽  
Orlando Morejon
Keyword(s):  
Trauma Center ◽  
Injury Severity ◽  
Statistical Significance ◽  
National Sample ◽  
Coefficient Of Determination ◽  
P Value ◽  
All Cause Mortality ◽  
Size Matter ◽  
The Impact ◽  
The Relationship

Relationship between trauma center patient volume (TCV) and mortality remains inconclusive. Our aim was to determine the relationship between TCVs and observed/expected (O/E) all-cause mortality. This is the first study to evaluate the relationship between trauma center (TC) volumes and O/E all-cause mortality with no exclusion. Review of prospectively collected data from 94 TCs using the National Sample Program from the National Trauma Data Bank 2013. TCs were stratified into five groups based on TCV: <701, 701 to 1200, 1201 to 1700, 1701 to 2200, and >2200 yearly patient encounters. Chi-square and coefficient of determination were used for data analysis with a statistical significance defined as P-value < 0.05. A total of 139,324 trauma patients with blunt and penetrating injuries were evaluated from the National Sample Program. Of which, 63.6 per cent were male, 70.6 per cent white, and the average age was 41 years. The data were stratified by TCV into five groups with average O/Es ranging from 0.69 to 0.86 (P > 0.05). The coefficient of determination between TCV and O/E was r = 0.14 and r2 = 0.02. When controlling for Injury Severity Score, the correlation between mechanism of injury (blunt vs penetrating) and O/E mortality was r = 20.025. The group with the lowest average volumes had statistically significantly worse outcomes than the group with next higher volumes and also worse than the group with the highest volumes (Group 5, P = 0.04). Higher TC volumes correlated with higher injury severity and lower O/E mortality.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

INTERACTION BETWEEN NEW TECHNOLOGIES AND THE EXPERIENCE OF THE GUESTS IN THE HOSPITALITY INDUSTRY

2020 ◽  
Author(s):  
Kosara Gotseva ◽  
Keyword(s):  
New Technologies ◽  
Positive Experience ◽  
Positive Interaction ◽  
Global Trends ◽  
Visitor Satisfaction ◽  
Scientific Report ◽  
The Impact ◽  
The Relationship

The scientific report aims to highlight the positive interaction between technology and hotel guests. The relationship between technology and customer experience is examined. The role of innovation as a tool for enhancing the positive experience of tourists is highlighted. The focus is on digital applications and their relationship to satisfaction. The main global trends that demonstrate the impact of hotel automation on visitor satisfaction are outlined. Attention has been focused on research from recent years. The author defends the thesis that guests seek interaction with automation as it directly affects the quality of service and thus enhances their positive experience. Innovation is a key tool for creating a quality experience.

scholarly journals Family Climate Patterns and Its Relationship with Self-Concept among Students at the University of Islamic Sciences in light of the Variables of Gender and Age

2017 ◽  
Vol 9 (1) ◽  
pp. 145
Author(s):  
Fatima Mohammad Rashed Al Talahin ◽  
Hana Khaled Al –Raqqad ◽  
Eman Saeed Al- Bourini ◽  
Bilal Adel Al-Kateeb
Keyword(s):  
Pearson Correlation ◽  
Statistical Significance ◽  
Self Concept ◽  
Family Climate ◽  
Gender And Age ◽  
Climate Patterns ◽  
The Difference ◽  
The University ◽  
The Impact ◽  
The Relationship

The aim of this study is to clarify the relationship between self-concept and patterns of family climate among students at the University of Islamic Sciences, and also aimed to investigate the effect of gender and age on this relationship.The sample of the study consisted of a group of students were selected randomly, totaling (139) students; (58) male and (81) female students.Two questionnaires were distributed on 139 students. The first questionnaire was on the impact of patterns of family climate on self-concept and the second one about self-concept. Then the researcher analyzed the results of each item in the questionnaire using appropriated statistical methods, calculated the correlation between self-concept and patterns of family climate using the Pearson correlation coefficient, and G-test to find the difference between correlation coefficients.The results showed a positive statistical significance relationship between family climate patterns on one hand and between self-concept in all its dimensions on the other hand.

scholarly journals Relationship between Cognitive Style and Habits of Mind

2019 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
Hayatun Nufus ◽  
Rezi Ariawan
Keyword(s):  
Linear Regression ◽  
Cognitive Style ◽  
Significance Test ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Habits Of Mind ◽  
Linear Regression Equation ◽  
Research Subjects ◽  
Analysis Technique ◽  
The Relationship

This research is a correlational study that examines the relationship between cognitive style and habits of mind. The research subjects involved 4th semester students in the Department of Mathematics Education at the Faculty of Tarbiyah and Teacher Training of UIN Suska Riau which consisted of students with heterogeneous academic abilities. Cognitive style data was collected using the GEFT question instrument with test techniques. Habits of mind data were collected using a questionnaire instrument with a questionnaire distribution technique. The data analysis technique begins with the Pearson Product Moment correlation test which is continued with the significance test and the calculation of the magnitude of the relationship that occurs using the coefficient of determination. Because the data is positively correlated, it continues with determining the linear regression equation. The results showed that there was a significant weak correlation between cognitive style and habits of mind with a relationship score of 6% and a linear regression equation y '= 36.35 + 0.31 x.

scholarly journals Research on China's Population Structure in the New Situation

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Jingxuan Cui ◽  
Mengshuai Yin ◽  
Zerong Liu
Keyword(s):  
Population Structure ◽  
Rural Population ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Female Ratio ◽  
Men And Women ◽  
Child Policy ◽  
Dynamic Perspective ◽  
The Difference ◽  
The Impact

To analyze the impact of the “two-child policy” on the population size and structure, first of all, the birth rate, the ratio of men and women, and the ratio of urban and rural population are used as indicators. Before and after the dispersion, then establish a PDE model, and compare it with the population predicted by the gray forecast to analyze the mitigation of the ageing of the second child policy; continue to analyze the impact of changes in the population structure on the national economy, and select the male and female ratio and the labor population The urban-rural population ratio is used as an index to establish a multiple regression equation for analysis, and a related regression equation is obtained. Finally, the future marriage problem is analyzed, considering only the difference in the number of men and women entering the marriageable period at the same time. The difference in the number of marriageable populations is analyzed through the difference in the number of men and women born at birth, focusing on a dynamic perspective.

Leadership and Innovation on Business Tourism

2020 ◽  
pp. 10-27
Author(s):  
Nadia Mansour Bouzaida ◽  
Mohamed El Amine Abdelli
Keyword(s):  
Hospitality Industry ◽  
New Technologies ◽  
Recent Developments ◽  
The Impact ◽  
The Relationship

This chapter analyses the impact of innovation on business tourism success and the relationship between leader and employee to develop the hotel's ability to become competitive. Recent developments in the hospitality industry are a challenge not only for leader, but also for employees, and then they are forced to perform innovations activities. Today, the most visible innovation in tourism is that brought by new technologies, which modify behavior and facilitate and enrich travel experiences in multiple ways. So, the leaders of this industry must always be very close to their employees and must really encourage participation and innovative ideas within the organization.

The relationship between the number of erupted primary teeth and the child's height and weight: a cross-sectional study

2005 ◽  
Vol 29 (4) ◽  
pp. 357-362 ◽  
Author(s):  
Ana Estela Haddad ◽  
Maria Salete Nahás Pires Correa
Keyword(s):  
Primary Teeth ◽  
Population Based ◽  
Cross Sectional Study ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Systematic Sampling ◽  
Sectional Study ◽  
Cross Sectional ◽  
Independent Variables ◽  
The Relationship

The objective of this study is to determine the correlation between the number of erupted primary teeth, the age, sex and the somatic measures of weight and height (length) in a Brazilian population based cross sectional study. A systematic sampling was used. Complete and consistent data were obtained from 870 of a total of 908 children from birth to 36 months of age. Statistical analysis comprised a multiple regression equation, where the number of erupted primary teeth was modeled as the dependent variable and the initial specification included the following independent variables: age, sex, birth-length, birth-weight, weight and length measured at the examination of the child. Results showed that in this study, 86% of the variation of the number of erupted primary teeth was explained by age and height of children (p&lt;0.001). Age and height showed a stronger correlation with the number of erupted primary teeth than all the tested variables together. It was concluded that primary teeth eruption is highly influenced by age and height (length) of the child. Using the best regression equation found, a chart was constructed where the variation of the number of erupted primary teeth is given according to age and height of the child.

Can Earnings Innovations Explain The Inverse Relationship Between Unanticipated Inflation And Stock Returns?

2011 ◽  
Vol 9 (2) ◽  
pp. 10 ◽  
Author(s):  
Jon A. Hooks
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Inverse Relationship ◽  
Explanatory Power ◽  
Earnings Forecast ◽  
Capitalization Rate ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship ◽  
Unanticipated Inflation

Hooks (1991) argues that the explanatory power of unanticipated inflation in stock return models appears to result from the relationship of unanticipated inflation with the earnings capitalization rate and not the impact inflation has on the level or growth rate of earnings. Here we extend this line of investigation by examining the relationship between unanticipated inflation and the earnings innovation extracted from a univariate earnings forecast. We show that unanticipated inflation has no significant relationship with innovations in conventional earnings. However, we find that unanticipated inflation has a significant positive relationship with the magnitude of the earnings innovation during the 1955-85 period when earnings are adjusted to account for the effects of inflation on firms assets and liabilities.

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