Information about VMGs

1. Virtual Mobility Grant

Title: Finance Sector Survey: Choices, Transparency, and Literacy
Grant holder: Dr. Belma Ozturkkal
Description of Activities and results: The study aims to understand the investment behavior of individuals and their perception of the transparency of financial assets. The survey is distributed to COST 19130 Action members, their universities, students, and financial sector employees. The project will help the collaboration of different countries. A report will be produced by the end of 2021.

2. Virtual Mobility Grant

Title: Fin-AI PODCASTS
Grant holder: Vasile Alecsandru STRAT
Description of Activities and results: The project will represent a series of short videos and will be a collection of PODCASTS. The main objective of the project is represented by the increase of the visibility of the activities of the CA network members. It will also help the produced research, papers, and use cases, have wider visibility among the nontechnical public and will generate therefore collaboration opportunities.

3. Virtual Mobility Grant

Title: Bitcoin Mining and Its Environmental Effects; Nexus of Green FinTech
Grant holder: Dr. Esra KABAKLARLI
Description of Activities and results: This research study examines Bitcoin mining and investigates the high amounts of energy consumed by Bitcoin and its environmental effects. It is argued that the energy consumed as a result of increased *Bitcoin mining will have environmental and social consequences, such as global warming and climate change. The main aim of VMG is to create a multi-national network of participants examining the practices, issues relating to green FinTech, to gain a deeper and more understanding of the phenomenon.

4. Virtual Mobility Grant

Title: Using Machine Learning Techniques to Assess Taxpayers' Perception
Grant Holder: Codruța MARE
Description of Activities and results: The main objective of the VMG is to evaluate taxpayers’ perceptions at an international level, by evaluating factors that influence the attitude towards paying taxes, using Machine Learning techniques. A secondary goal is the consolidation of an international research team on the subject. A questionnaire will be constructed and distributed through the CA 19130 members, internationally, to their peers, in order to be able to address and map similarities and differences in perception at the national or regional level. For this, spatial econometrics tools will be employed in addition to the ML ones. Results will be presented in the form of a descriptive report, map analysis, and research articles in top-tier journals.

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