"Scientific research" Almanac

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  TRENDS AND CHALLENGES TO MOTOR INSURANCE IN THE CONDITIONS OF DYNAMIC ECONOMIC DEVELOPMENT

  The present study focuses on the results of a survey on car insurance in Bulgaria carried out in 2018, under project No.6-2018 at the Institute for Scientific Research. The main objective of the survey is to outline the state of the motor insurance market in Bulgaria after the adoption of the Insurance Code. Emphasis is placed on the state and ... The present study focuses on the results of a survey on car insurance in Bulgaria carried out in 2018, under project No.6-2018 at the Institute for Scientific Research. The main objective of the survey is to outline the state of the motor insurance market in Bulgaria after the adoption of the Insurance Code. Emphasis is placed on the state and development of premium income and insurance benefits. The thesis is that motor insurance is a decisive factor for the formation of premium income and the development of insurance companies. The thesis has been proven by solving the following important tasks: - outlinå the state and trends in the development of the insurance market for the period 2005-2017; - outline the state and trends in the development of motor insurance for the period 2005-2017; - outline the relationship between the automotive sector and the motor insurance performance indicators for the period 2005-2017. Based on the study, the following important results were achieved: the rate of growth of premium income and insurance payments on the insurance market lagged behind that of the motor insurance. The pace of development of Casco insurance outpaced the pace of developing Motor Third Party Liability insurance. Proposals were formulated to solve the problems in the research findings. Within the survey period, the average insurance premium on motor insurance was on the increase, as well as the scope of motor insurance.

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  OPPORTUNITIES FOR INCREASING THE QUALITY OF DATA FROM ONLINE SURVEYS

  The emergence and evolution of Internet and related applications have changed many areas of public life. The methods of gathering marketing information have also changed. Less and less often surveys are printed on paper and are conducted in a web environment. The reasons are simple – online surveys are conducted faster and cheaper, they are easy ... The emergence and evolution of Internet and related applications have changed many areas of public life. The methods of gathering marketing information have also changed. Less and less often surveys are printed on paper and are conducted in a web environment. The reasons are simple – online surveys are conducted faster and cheaper, they are easy to spread, they offer useful functionalities. A major challenge for marketing researchers is to ensure that online surveys are representative. The main purpose of this study is to examine whether the structure of a sample, drawn from an online survey, corresponds to the structure of the studied aggregation. Another objective of the study is to examine how respondents react to incentives offered for participation in an online survey. This study presents the results of three online surveys. Each survey examines specific aggregation: Facebook page fans; visitors to a web site; population of Bulgaria aged 13-54. Two surveys were conducted through Facebook advertising. One survey was conducted among the visitors of a web site. To compare the sample and general aggregation, we have used χ2 criterion for one sample and Kiril Gatev’s integral coefficient. In the case of studying Facebook page fans, the sample matches the set of variables "sex" and "residence". In order to validate the three samples, the following information sources were used: The National Statistical Institute; Facebook page Insights; Google Analytics reports. In both surveys made via Facebook advertising, a very low cost was obtained for a response. In the survey of site visitors, the cost of a response is practically zero. To test how incentives affect respondents' activity, two types of prizes are offered – USB Flash memory stick (3 pcs.) and External hard disk drive (2 pcs.). In this study, we have found that the incentives offered do not increase respondents’ responsiveness to a degree justifying the costs of purchasing and delivering the prizes.

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  MEASURING POVERTY IN BULGARIA: STATISTICAL ASPECTS

  Fighting poverty and social exclusion is among the biggest issues of modern social development and a priority of the social policy at both national and European level. The main goal of this paper is to explore the statistical dimensions of poverty in Bulgaria via theoretical justification and empirical analysis of the level, dynamics and ... Fighting poverty and social exclusion is among the biggest issues of modern social development and a priority of the social policy at both national and European level. The main goal of this paper is to explore the statistical dimensions of poverty in Bulgaria via theoretical justification and empirical analysis of the level, dynamics and determining factors of poverty for the period 2008–2017. The research thesis of the study is that the Gini coefficient and the multiple binary logistic regression models are appropriate analytical tools for analyzing the relationships and identifying the part of the population that is at risk of poverty and social exclusion. In this paper, we present the conceptual basis of poverty as a subject of the statistical analysis. We clarify the organizational and methodological aspects of the data provision. We have performed empirical analysis of the dynamics and factor relationships of poverty in Bulgaria on the basis of the statistical information, obtained from NSI and Eurostat. We have developed multiple regression models and estimated the socio-demographic conditions of poverty. The main results of the study can be summarized in several areas. The application of the statistical approach is a necessity for identifying the level and the factor relationships of poverty. The quantitative measure of poverty is based on comprehensive statistical information that is collected in accordance with the Eurostat methodology and adapted at a national level by the NSI. The dynamics of the Gini coefficient reveals that income inequality of the population is rising. The multiple logistic regression model states that the impact of the variables “gender”, “age” and “region” are statistically significant. The derived probabilities and odds ratios can be used in developing policies for poverty reduction.