INDICATORS AFFECTING VIDZEME REGION SMART DEVELOPMENT

The study aims to determine the main indicators of rural smart development concept for territorial development analysis and decision-making in Vidzeme region (Latvia). In the framework of the study the theoretical literature and planning documents were analysed, focusing on the indicators of rural areas and sustainable development. For a long time the development was associated primarily with the economic growth - GDP, employment and income growth. In recent years, the economic dimension is supplemented with social, environmental, cultural and political aspects. A holistic approach interprets close relations and balanced integration between the economic, social, political, ecological and cultural dimensions of local and regional development. Such approach requires the search for new indicators that describe the development of rural areas and are directly relevant to each individual area. The results present that in the development of Vidzeme smart specialization, the local governments and the state has the greatest impact. It is most affected by the local government's capacity to develop cooperation with residents and entrepreneurs, and a stable and sustainable economic situation in the country

DYNAMIC SIMULATION MODEL FOR SUSTAINABLE MUNICIPALITY DEVELOPMENT IN VIDZEME REGION, LATVIA

Authors in this research paper publish the results of system dynamic simulation modelling in the field of sustainable development planning, monitoring and evaluation for all 26 Latvia Vidzeme region municipalities. As the most notable research outcome, authors created original socio-technical system dynamic simulation model in STELLA modelling environment valid for sustainable development evaluation purposes. After successful verification and validation process of this model authors reached the significant results for improved methodology of dynamic systems evaluation process reliability of sustainable development in Vidzeme region municipalities. Methodology, proposed by authors roots into the quantitative statistical data analysis and system dynamic process simulation modelling