Fintech, which is a shorthand expression for financial technology, is basically referring to all the technological innovations in the financial sector that started to develop exponentially, especially in the second decade of the 21st century, in the era of the mobile internet revolution. The Generation Z, also called Gen Tech, who was growing up using the internet and especially the mobile internet on a daily basis, will probably be the larger adopter and beneficiary of these innovative financial technologies. The current generation of students, born about twenty years ago, is part of this cohort and this is why we decided to initiate a study regarding their perception and behavior concerning the fintech area with the help of a questionnaire applied on some of the students of the Faculty of European Studies from Babeș-Bolyai University. Because the fintech is covering financial innovations from a very broad area (including cryptocurrency, online payments, financial transfers, openbanking, investments, regtech, insurtech, etc.) we decided to focus in this preliminary study, only on the blockchain technology and cryptocurrencies and in relation to these, on the online payments.

The purpose of the current article is to determine the sustainability of international accreditations for business schools. As international accreditations are viewed as a costly process, universities must think if this endeavor could have a positive impact in the long run. From an impact point of view, we look at the intake of students, focusing on the factors that impact the decision of students in their choice of university. We have noticed that these international accreditations are pursued by business schools to increase their outreach and to receive a certification of quality that is recognized overseas. We consider the hypothesis that international accreditation is a key factor in the decision-making process of candidates, and we tested it by applying a questionnaire to 400 business and economics students that are studying in two business schools. From the 400 students that answered the questionnaire, only 199 responses were considered fully answered and proper for our study. Our results show that there is a difference between French and Romanian students in the choice of universities. While both groups agree that internationalization is important, their decisions are based on different elements. Our research is among the few that look both at the student choice and at the impact of the international accreditation on the student numbers.

While the moral argument for gender diversity has already been made and is incontestable, and more and more economical arguments have been brought to support the business case for the presence of women on the boards of directors of publicly listed companies, the bottom-line issue of what kind of impact gender diverse boards have on firm financial performance is still unclear. The aim of this paper is to deliver a comparative analysis of the impact of gender diverse boards on firm financial performance in France and Romania. Our results do not to provide any evidence of a link between boards’ gender diversity and companies’ financial performance, but while the analysis has failed to find a positive link between female presence and firm financial performance, it has not outlined a negative one.

One of the essential properties of a machine learning model is to be able to capture nuanced connections within data. This ability can be enhanced by considering alternative solution concepts, such as those offered by game theory. In this article, the Nash equilibrium is used as a solution concept to estimate probit parameters for the binary classification problem. A non-cooperative game is proposed in which data variables are players that attempt to maximize their marginal contribution to the log-likelihood function. A differential evolution algorithm is adapted to solve the proposed game. The new method is used to study the price changes of the Romanian oil company, OMV Petrom SA Romania, relative to the price of oil (crude and Brent) and the evolution of two other major oil companies with influence in the region. Results show that the proposed method outperforms the baseline probit and classical classification approaches in predicting price changes.

No abstract