Current Contents / Social & Behavioral Sciences

Robots have started to be used in the service sector as well as in the manufacturing industry. The use of service robots in airport services such as tourism and hospital services also brings many advantages. Due to the Covid-19 pandemic, reducing physical contact and providing hygiene are essential benefits of service robots. For this purpose, the effect of Covid-19 fear on perceived trust in service robots and intention to use them at airports was investigated in this study. For analysis, data were collected from 730 participants from 64 different countries by questionnaire. The data were analyzed with SPSS and AMOS package programs. As a result of the structural equation model analysis determined that Covid-19 fear affects perceived trust in service robots and intention to use them positively, and perceived trust also affects intention to use service robots positively. In addition, as a result of the Process Macro analysis, it was found that perceived trust has a high mediating effect on the effect of Covid-19 fear on intention to use. Research results show that people's attitudes towards Covid-19 shape the perception of robot usage in air transport services.

In the context of accelerating urbanization, cities must ensure a viable economy, social well-being, and a healthy environment. Transport is one of the key conditions for economic development and meeting the needs of countries, regions, and cities. However, transport must meet not only the physiological but also the social needs of society, one of which is environmental security. Urban transport accounts for around 40% of CO2 emissions and 70% of other pollutants from road transport. Thus, one of the most difficult issues for any city to address when building bypasses is the growing number of cars in the city, traffic congestion, and the reduction of all greenhouse gas emissions. The documents adopted in July 2020 aim to revitalize the EU’s economy by moving towards a green economy and sustainability. In addition to the systematic and comparative analysis of concepts published in the scientific literature, the article also presents an analysis of the concepts of a sustainable city, sustainable transport, as well as a study of the social impact of bypasses and the assessment of the security of the social environment in the Baltic capitals. The aim of the article is to assess the impact of the growing number of vehicles on the security of the city’s social environment. Research results show that the number of pollutants, a direct dependence between the number of pollutants and the driving speed was established. So, that’s why it needs to make investments in the transport sector: improve roads, construction of bypasses, and technical parameters of purchased cars.

During the past few decades, competition between countries has intensified. Every country seeks to become an essential player in international economic relations and take a prominent place in the world market. In this context, foreign direct investment inflows are accepted as a source of competitiveness through knowledge, know-how and technology transfer, but competitiveness is also accepted as a significant determinant of foreign direct investment attraction. Therefore, the specification of foreign direct investment inflow determinants is also important to improve competitiveness. In this research article, we aim to evaluate the impact of shadow economies and human development on foreign direct investment inflows as a possible determinant of competitiveness in 11 post-transition EU members over 1995-2015 period. The methodology employed in the applied section includes comparative and systematic literature analysis as well as second generation panel cointegration and causality analyses regarding both cross-sectional dependence and heterogeneity. The empirical analyses revealed that both the shadow economy and human development are significant determinants of foreign direct investment inflows. The causality analysis revealed a mutual interaction between foreign direct investment inflows and human development for all the countries in the sample, but a two-way causality between the foreign direct investment inflows and shadow economies only for Bulgaria, Croatia, and Romania and a one-way causality from shadow economies to the foreign direct investment inflows in the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia. The long-run analysis revealed that shadow economies negatively affected foreign direct investment inflows, while human development positively affected foreign direct investment inflows.

A country's competitiveness depends primarily on its economic development which in turn is affected by a number of factors. Some of these, such as investment, favorable business conditions, legal environment, etc., promote economic development, while others, such as low labor productivity, insufficient staff qualification that fails to meet the requirements of the labor market, etc., slow down the pace of economic development. The latter category describes the phenomenon of the shadow economy (SE). Research into shadow economies is dominated by the analysis of the local impact factors. Nevertheless, the results of such analyses do not reveal the general patterns of the shadow economy, without the knowledge of which it is difficult to develop effective preventive measures. The basic determinants of the shadow economy must first and foremost reflect national economic development, as these particular determinants have the most significant impact on the size of the phenomenon of the shadow economy. National economic development can be expressed by employing various indicators, but recently it has most commonly been expressed by GDP per capita. GDP reflects national competitiveness, integrates a number of domestic factors, and is easily accessible and publicly available in national and international statistical sources. In addition, this indicator is calculated by employing a unified methodology, which makes it universal, allowing the comparison of countries in different situations. As presented in this article, the analysis of the relationship between economic development and the size of the shadow economy allows the division of all the EU member states into characteristic groups by the level of their economic development as well as size of the country's SE. Our research attempts to reveal the regularity of the above-mentioned relationship: the higher the level of national economic development, the lower the size of the shadow economy.

In the conditions of market economy all business entities, which can be viewed as socio-economic systems (SES), must be competitive. This also applies to the regions in the country. From the regions competitiveness depends effective solving of a whole range of social problems: jobs, social welfare, crime, migration and etc., in turn country region’s competitiveness depends on how it is adjusted its economic, social and ecological development. It’s important because it could be that some of the development components are developing at other component’s expenses. For example, economic development could be at social and ecological expenses. This would prevent the creation of the necessary living conditions not only today, but also for future generations. In order to survive, an SES must be constantly developing. During this development, both quantitative and the qualitative changes of the system parameters take place. The quantitative changes are reflected by the development dynamics, which encompass the equability and the intensity; while the qualitative changes are reflected by changes in the internal structure of the development process. For a system to be able to function in the long term, the quantitative development of its components must be mutually compatible. However, the existing measurements of SES development do not take this into account. The aim of the article is to propose and approve a methodology that would allow quantitatively evaluate the sustainability of the country regions development. For this purpose the multi-criteria evaluation methods are used. Based on the proposed methodology the sustainability of the country regions economic development is identified.

As pedestrian zones are public spaces in urban areas, they are important in terms of meeting people’s needs. However, it is worth noting that attention should be paid not only to the development of the physical infrastructure, but also to a sustainable balance between the socio-economic and environmental aspects. To guide urban planning and management initiatives towards more sustainable patterns, it is essential to re-examine the already existing characteristics of cities, establishing how they are used and perceived by inhabitants. The present research suggests environmental, economic and social criteria that determine a greater vitality of pedestrian zones in cities and better life quality for the inhabitants. A questionnaire survey was used to assess common attitudes regarding the research topic in major cities in Lithuania. The multiple criteria decision-making COPRAS (COmplex PRoportional ASsessment) method was used for the formation of a priority queue. The research results showed the attitudes of inhabitants towards pedestrian zones in Vilnius, Kaunas and Klaipėda. The inhabitants of these three cities regarded social and environmental criteria groups as the most significant. Contrary to what was expected and anticipated, respondents do not consider economic criteria as playing a key role in the sustainable preservation and development of pedestrian zones.

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).

Many factors influence the identification of the best real estate alternatives, such as supply and demand and the social, cultural, psychological and personal factors affecting buyer behavior and the emotional state of a buyer. What are the most effective ways of choosing a property, when the selection is so vast and complex? An aid is developed here to accomplish this, based on a new advertising format, an iterative method and the NEuro-Advertising Property Video Recommendation System (NEAR). A known methodology involves behavioral operational research and the emotions involved in decision-making. Three advanced research contributions are unique to the proposed method and NEAR, in contrast to innovative behavioral operational research. Firstly, data are compiled for a neuro decision matrix, based on housing attributes and the valence, arousal, emotional state and physiological parameters of a potential real estate buyer. Secondly, the performance of a multiple criteria neuroanalysis occurs as well as the selection of the most personalized and effective video clip ad variants drawn from many alternatives. Finally, NEAR is found to present the most effective video clips ads for real estate buyers for as long a period as possible, according to Multiple Resource Theory.

The devastating Japan earthquake (magnitude 9.0) and tsunami (39-metre high) of 2011, also called the Great Tohoku or Sendai earthquake, was a record-breaker natural disaster causing enormous damage and a nuclear meltdown at Fukushima nuclear power plant. This paper attempts to analyse the long and short run effects of this record-breaking natural disaster on the Japanese equity, debt and FX markets as well as Gold as one of the most popular metals and investment options, using daily data. A variance bound test proposed by Fakhry & Richter (2018) underpinned by the C-GARCH-t model of volatility is adopted. The results seem to indicate that the natural disaster influenced the efficiency of the market in the immediate terms more than the long term. In a global financial market where the key is competitiveness, it is essential to analyse the efficiency and therefore stability of the Japanese financial market. Therefore, analysing the impact of the natural disaster on the competitiveness of the Japanese financial market.

In the National Communication Development of 2014–2022 Program and Guidelines of the Development of the Public Electric Vehicle Charging Infrastructure confirmed by the Government of the Republic of Lithuania, it is planned that, until the year of 2025, among newly registered vehicles, electric ones should make at least 10%. Analysis of the trend of electric vehicles makes evident that the target does not have a real chance to be achieved without targeted efforts. In order to improve the infrastructure of electric vehicles in major cities and resorts of Lithuania, we have carried out a comparative analysis of public infrastructure for electric vehicles in 18 Lithuanian cities and resorts. For the quantitative analysis, we proposed eight criteria describing such an infrastructure. As perception of the infrastructure by owners of electric cars depends on complex factors, we used multiple criteria evaluation methods (MCDM) for evaluation of the current state of its development by four such methods: EDAS, SAW, TOPSIS, and PROMETHEE II. Based on the evaluation results, prominent and lagging factors were understood, and proposals for effective development of public infrastructure of electric vehicles were proposed for improvement of the infrastructure.