This paper aims to examine the links between university-industry collaboration (UIC) predictors (inputs) and the results of UIC cooperation (outputs). The focus of the research is UIC within the European Union member states and the Western Balkan countries. The analysis was conducted using the partial least squares structural equation modeling (PLS-SEM). This method enabled examining the links between variables that are not directly observable. The authors used data for the period of three years, 2015–2018. The results prove that countries investing in UIC predictors (inputs) have better UIC performance (outputs). Based on the statistical analysis, the authors identified the investments in knowledge, networking, and research and development (R&D), in general, as the most significant that impact UIC performance.

The paper investigates the gap in the number of patent applications by European countries in the period 2010‐2018. During the observed period, World Intellectual Property Organization (WIPO) received an average of 1.9 applications per million inhabitants per year from the countries of the Western Balkan (WB‐5), which is as much as 98% less than the average for the whole of Europe. The purpose of the paper is to create a model for increasing the number of patent applications in developing countries, which should lead to a higher number of granted patents. The author analyses variables that have an impact on the number of the patent applications (functional literacy, human development index, university/industry research collaboration, and gross domestic spending on R&D) in the developed (EU‐28) and developing (WB‐5) countries. The WB‐5 firms, especially small and medium enterprises (SMEs), do not use of the opportunities offered by intellectual property (IP) protection. They find the system too costly, complex, and difficult to manage. Based on the results of statistical analyses and conclusions from recent literature that tackles the usage of IP, the author builds a model for increasing the number of patent applications among European SMEs that is based on the support of international business support organizations (BSOs). Moreover, the author recognizes the positive impact of international IP support programs (such as EU IPR Helpdesk ambassador scheme) on the work of local BSOs that deal with IP rights.

This study is the first to examine recent migration from Bosnia and Herzegovina to China in the 21^st century. It gives an overview of new Chinese geopolitical and economic circumstances, a historical analysis of migration flows between China and the rest of the world from the 19th to the 21st century, and a survey of recent emigration flows from Bosnia and Herzegovina. The second part presents the results of an empirical study of labour migration from Bosnia and Herzegovina to China and the experiences of 25 migrants, which was conducted using structured interviews The research results show that most in the group plan to stay in China permanently. Some would like to move to North America or Australia. It is characteristic that there are no gender gaps in terms of qualifications or career ambitions. The measures to combat COVID-19 implemented by the Chinese government affected the respondents in different ways.

The purpose of this paper is to examine the relationship between ?soft? support infrastructure (SSI) and the performance of small and medium enterprises (SMEs). The study encompasses European countries? economic activity and SMEs? output in 2015 and 2018. The focus of the research is SMEs in the European Union member states and the Western Balkan countries. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). This method enabled the examination of links between variables that are not directly observable. The results show that countries investing in SSI have better SME performance. Based on the statistical analysis, among other things, the authors identify the Human Development Index and the use of information and communication technology at the company level as the two most significant factors that impact on SMEs? performance.

This paper aims to examine the links between university-industry collaboration (UIC) predictors (inputs), and the results of UIC cooperation (outputs). The focus of the research is UIC within the European Union member states and the Western Balkan countries.The analysis was conducted using the partial least squares structural equation modeling (PLS-SEM). This method enabled examining the links between variables that are not directly observable. The authors used data for the period of three years, 2015–2018. The results prove that countries investing in UIC predictors (inputs) have better UIC performance (outputs). Based on the statistical analysis, the authors identified the investments in knowledge, networking, and research and development (R&D), in general, as the most significant that impact UIC performance.