Developing Methods for Assessing the Social Impact of Scientific Study




social impact assessment, methods for assessing the social impact, bibliometric research, social sciences


In many countries, there is a need to introduce new or improved existing methods for evaluating the social impact of scientific study on the environment of scientific institutions and universities. It is necessary to apply complex methodological solutions that should consider using research results by the non-academic world. The results of this evaluation are often crucial for building a university's position in national and international rankings. They may influence decisions regarding the level of financing of scientific institutions and the distribution of public funds for subsidies, scholarships, and financial aid concerning research grants. The paper aims to review existing methodological solutions and identify key trends in developing methods for assessing the social impact of scientific study. In this case, the scope of the research was limited to evaluating the study conducted within the field of social sciences. Running such assessments is more complicated than for the technical domain, for which more easily measurable bibliometric indicators and patents are available. The research used quantitative bibliometric analyzes based on the Scopus citation database, supported by bibliometric network analyzes. The results enable the identification of crucial methodological trends, potential opportunities and directions for developing research conducive to improving methods for assessing the social impact of study. Providing an overview of existing knowledge in this field creates a foundation for continuing further research.

Author Biography

Tadeusz A. Grzeszczyk, Warsaw University of Technology, Faculty of Management, Poland

Tadeusz A. Grzeszczyk is associate professor in the Faculty of Management at Warsaw University of Technology and engages in scientific activities focused on research methodologies, encompassing qualitative, quantitative, and mixed methods approaches in management, social sciences and evaluation studies. His interests also include knowledge management and applications of artificial intelligence decision-support systems.