This paper attempts to investigate the co-integration relationship between consumption, income and GDP per capita (as a proxy of the level of standard of living) in time-series cross-section data. To conduct this analysis, we have applied tests to verify if the time series are non-stationary and co-integrated. The panel data covers a large sample formed from 79 countries, divided in three categories depending on their income level – low, middle and high. The study regarded annual observations for a period of 31 years, from 1980 to 2010. The results have shown that the association between consumption and income is stronger in low and high income countries, compared with middle income countries. A small level of income determines its use especially for consumption and a high level of income increases consumption as there are more available resources to cover large investments as well. The relation between consumption, income and GDP is stronger for low and middle income countries, a logical conclusion since the high income countries allocate more capital to investments and are intense specialized in research and development activities

Recently, the variety of the financial frauds have increased, while the number of victims became difficult to estimate. The purpose of this paper is to present the main profiles of financial frauds’ victims using a reviewing method. The analysis captures the main theoretical and empirical background regarding the motives and circumstances of becoming a victim, the dynamics of several social and demographical characteristics of this type of victims, as well as a sample of relevant case studies from some developing countries. The main finding is that, in literature, most of the victims are male people of different ages, employed, married or single, regardless the level of education. For developing countries such as China, India and Nigeria, the majority of victims act out of naivety and desire to escape from poverty, while some victims from Latin America, China and Nigeria are influenced by greed and lack of empathy, without thinking of further consequences for their families and friends involved. Moreover, most of the victims are convinced to invest in financial schemes by family members, friends, or acquaintances.

Fiscal policy plays an important role in stimulating economic activity, but it also has a significant influence in securing monetary stability in an economy. Our study aims to analyse the asymmetric effects of fiscal policy on inflation and economic activity on twelve post-communist European countries that are associated with the European Union (EU) by either membership or by being members of the Eastern European Partnership (EaP). We explore the asymmetric effects on inflation and economic activity by using a Pooled Mean Group (PMG) estimator. The results show that in the long run, the fiscal policy instrument negatively influences both inflation and economic activity; in the short run, the effects are not significant. A Nonlinear Autoregressive Distributed Lag (NARDL) model was estimated individually for each country. Our main findings are that the cumulative impact of fiscal policy generates an inflationary growth effect for the EU countries in our sample.

The COVID-19 pandemic has made the world face a whole new reality, and the measures taken for slowing the spread of the disease included social distancing, as well as national, regional, or local lockdowns and restrictions regarding the movement of people. For such an important sector of the Romanian economy as the construction industry, the restrictive measures imposed by the authorities led to postponing, delaying, or stopping the current projects. This paper aims at investigating the main effects of the COVID-19 pandemic on the Romanian construction sector, as well as the role of the digitalization process in mitigating the negative impact on the companies activating in this domain, in the context of the current levels of use of information technologies. The research involved the use of qualitative (exploratory in-depth interviews) and quantitative (online surveys applied to members of the local building sector, such as engineers, architects, contractors, and managers) data collection methods, respectively descriptive statistics for data categorization and interpretation. In general, the Romanian construction sector was only slightly affected, with the most significant negative effects being the delays and cost overrun due to safety and health issues. This paper is one of the first studies to explore and assess the effects of COVID-19 on the Romanian construction industry and the role of digitalization in reducing the pandemic impact. The main findings reveal that the companies in this industry that have a high digitalization degree overpassed in a smoother manner the current pandemic situation.

Purpose: As satisfaction is one of the most important conditions for loyalty, this study aims to investigate the main factors affecting online satisfaction for buying clothes from the internet. In this research, the authors followed two main objectives: (1) to identify factors influencing online satisfaction and (2) to determine the importance of the main determinants that explain online satisfaction in the retailing clothing sector.Design/methodology/approach: The research combines qualitative and quantitative research methods. The authors used the focus group technique and a survey based on a questionnaire. For the first exploratory phase of the research, we conducted four focus groups with 21 women, 18–39 years old, who have at least two years experiences as online buyers and who made at least two acquisitions for clothing products in the past six months, from the same website. The purpose of this qualitative method was to understand the young women's perception about online satisfaction and to collect items to be included in the questionnaire. For the second quantitative phase of this study, the sample consisted of 241 participants. To analyse the data, two different types of inferential analysis were used: factor analysis (for identifying the factors that compose online customer satisfaction) and analysis of regression (to determine the most important factors that determine and predict online buyers' satisfaction).Findings: The main results indicate that the significant factors determining a satisfactory experience in an e-retailing market are: good deal (savings), product expectations, customer service and website reputation.Originality/value: The study is more relevant in the current pandemic context, when the consumer’s behaviour has changed and online shopping has substantially increased. The research can be used by companies that sell clothing on the internet and are interested in increasing their financial results and also their customers' satisfaction.