The challenge of social innovation : approaches and key mechanisms of development

Recently, a key motive for innovation has been the generation of economic value. Currently we are facing a challenge to develop new approaches to involving the public in solving social problems through innovation based on collaboration and cooperation. Consequently, there is an urgent requirement to shape a favorable environment for innovation, creating both economic and social value. The purpose of this study is to reveal mechanisms for the development of social innovation that can be successfully introduced and implemented in Russia. The advantage of a systems-based approach to social innovation is that social innovation is defined as institutional change leading to the emergence of new routines (traditions) or practices. The use of benchmarking, along with comparative and historical analysis, to study foreign experiences of social innovation makes it possible to identify best practice in creating the conditions needed to develop social innovations, organize innovation processes and promote systemic innovations. On the basis of information received, key mechanisms of social innovation were identified, including that of innovation mediation. The system capabilities of Living Labs in the promotion of social innovations were, in particular, investigated.peer-reviewe

Comparative Analysis of Socioeconomic Models in COVID-19 Pandemic

Certain features of socioeconomic models can be distinctly determined in different countries and regions. However, such models are quite flexible under external and internal influences. Their changes can be observed under the impact of unpredictable factors, the COVID-19 pandemic being one. The aim of the work is to identify differences in the structure of socioeconomic models under the influence of the pandemic. The object of the study is the socioeconomic models of various states. The subject of the study is the transformation of socioeconomic models at different stages of the pandemic. Research methods include analysis of statistical data, correlation and comparative analysis, and graphical methods of presenting results. A comparison of data from the most well-known socioeconomic models was carried out for the first time. It is determined that the countries of the Chinese model adopted restrictive measures of high Stringency Index. The countries of the Japanese model used unique crowd management methods, and the countries of the Scandinavian, German and Anglo-Saxon models resorted to unprecedented monetary injections into the social and economic spheres. It was revealed that quarantine measures eventually cost countries less than monetary injections. It was shown that a decrease in the Pandemic Uncertainty Index stabilized the economic behavior of the population and businesses and increased the volume of export-import operations. It was found that the pandemic affected the economy indirectly through the level of uncertainty and rigidity of preventive measures. It is assumed that the intensity and severity of measures could be influenced by global trends leading to certain types of preventive measures rather than by the COVID-19 statistics of a particular country

Sectoral Transformation of the Economic System during Crisis and Stable Growth Periods (A Case Study of the European Countries)

Sectoral structures are one of the critical and dynamic components of any social system subjected to either external or internal factors. The purpose of the paper is to reveal and validate characteristic features of transformation regarding economic sectoral structures during the crisis of the socio-economic system and the period of its coordinated development in order to determine the most stable industry sectors. This paper reveals the specificity of sectoral transformations in European countries during the crisis of 2008–2009 and the stable growth of 2010–2019. The analysis is premised on Robert B. Reich’s sectoral structure, comprising production, in-person, intellectual, and communication services sectors. To conduct the research, statistical data analysis using the Gatev coefficient, and correlation and comparative analysis are applied. It is concluded that the mutable nature of sectoral dynamics depends on the planned changes resulting either from business expectations and interests, or state intervention. Yet, transformation is likely due to external and internal shocks (economic upheavals and wars), and unexpected events (natural disasters, epidemics, and pandemics). Over the last 15 years, the sectoral structure has been subjected to most of the above collisions. In-person, intellectual, and communication services sectors are least affected during the economic crisis. In the European countries, the period of economic growth is characterized by the growing dominance of intellectual and communication services sectors. There is a trend of decreasing the share of mining and quarrying in the sectoral production structure in favor of manufacturing industries and services