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After graduation in 2013 at the Faculty of Organizational Sciences, he got his MSc at the same Faculty, where he specialized in business intelligence and decision making. In 2014, he enrolled in a post-graduate program at the same Faculty, where he is specializing in business statistics.

Decision makers and government representatives use numbers in the process of policy making in various spheres of life (Porter, 1995). Higher education is just one of thoe that saw the introduction of scores into its assessment methods through university rankings (Daraio & Bonaccorsi, 2017). Since 2003 and the first global university ranking, the university rankings have proliferated. The three world-acknowledged and most often analysed rankings are the Academic Ranking of World Universities (ARWU), the Times Higher Education (THE), and the Quacquarelli Symonds World University Ranking (QS). However, these rankings led to the creation of dozens separate rankings and subrankings: by region, by subject, by field and so on (Hazelkorn & Gibson, 2016). This information goes to show several facts: that there is a need for university rankings, that their scope is changing, and that university rankings have become a serious industry (Hazelkorn & Gibson, 2016). Therefore, the conclusion can be made that university rankings are here to stay (Nature News, 2007). Throughout the years, institutions that publish university rankings aimed to answer the needs of students, on one hand, and the needs of universities, on the other hand. One such case is the case of the Alternative ARWU ranking. Namely, the ARWU ranking tends to take into account the prestige of the institution by including indicators such as the number of alumni and staff who received the Nobel Prize or the Fields Medal. However, it is tough for an institution to receive any of them. On the other hand, if a university receives one of the two prestigious awards, its rank skyrockets in the next edition of the ranking. For example, the Toulouse School of Economics received its first Nobel prize in 2014 in Economic sciences and entered the ARWU ranking straight into group 201-300 in 2015. Similarly, the London School of Economics received its first Nobel Prize in 2010 and went from group 201-302 to group 102-150. Also, once a university has received the Nobel Prize or Fields Medal its rank position improves and stays constant for a certain period of time (Piro & Sivertsen, 2016). Many universities worldwide pointed such situations out to the Shanghai Ranking Consultancy and suggested an alternative ranking without the Award Factor (Alumni and Award indicators) (ARWU, 2014). Their valuable observation led to the creation of the Alternative ARWU ranking.

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This paper explores main drivers that influence consumers’ decision related to the usage of a sharing economy service: trust, interaction, and experience. These three driving forces are put together in the functional form in order to explore its synergy influence on potential consumers’ interest in SES. The theoretical contribution of the paper is reflected in the design of the original simulation model for predicting the number of potential sharing economy users. Our findings and qualitative cluster analysis provide an insight into the behaviour of sharing economy customers which might help sharing economy providers to thoroughly analyse target users in order to meet their preferences. The proposed approach is tested through a small-scale experiment for the peer-to-peer carsharing service.