Analysis of smart specialization in European regions using fuzzy classification

Abstract

The major areas of specialization assessment cover for example export, R&D expenditure, employment rate, high-tech products (e.g. patents). Many measures indicated in the subject literature for specified areas cannot be currently determined at regional level due to data unavailability.The article attempts to identify the areas and directions of changes in the smart specialization development of the European regions. An analytical approach, based on the application of fuzzy classification in the analysis of dynamic data, was used for this purpose. The analysis covered 265 European regions at NUTS 2 level, described by variables characterizing employment shares in economic sectors. The level of membership to the separated classes was estimated for each region in particular years of the adopted research period 2000-2010, which facilitated analyzing the directions of their location changes in the European area divided into classes. The obtained results allowed for the positive verification of the proposed hypotheses about the usefulness of fuzzy classification in the identification of areas and directions for smart specialization changes in regions establishing the European regional area. Both, the regions characterized by the changing sector system and the ones maintaining their sector specialization profiles in the adopted research period, were identified in the course of the conducted analyses.

A multivariate approach to the identification of initial smart specialisations of Polish voivodeships

“…The source literature offers various approaches presented in the research on smart specialisations. The latter are defined through the prism of saturation with human capital, knowledge and innovation (Markowska et al, 2016;Sobczak & Bal-Domańska, 2013;Sobczak, 2013;Sobczak, 2012) or result from the entrepreneurial discovery process. In the first case, their identification is carried out through the statistical analysis of the resources available in the economy.…”

Розкриття Потенціалу Смарт-Спеціалізації Для Подолання Регіональної Структурної Інертності В Україні

“…Найбільш близьким до авторської позиції є розкриття регіональної спрямованості смарт спеціалізації. У цих дослідженнях смарт спеціалізація справедливо визначається як новий підхід до встановлення регіональної спеціалізації, який унеможливлює при мусовий (або штучний) вибір будь якої спеціалізації регіональної економіки за допо могою державної політики секторальної підтримки або підтримки всієї промислової діяльності на рівні регіонів [12]. На смарт спеціалізації як підході до визначення на прямів диверсифікації економічної діяльності у регіонах наголошують Д. Ахнер та М. Ландабасо [13].…”

Innovation Capability Maturity Model as a Mean for Data Policy Standardisation in Smart Specialisation Cycle

“…R. Kemp (2014) introduced the common legal framework for big data and conceptualized it in a legal analytical model which was explored in this paper and adopted referring SSG. From the beginning of the introduction of SS, it has been necessary to indicate the feasibility of big data measurements, though there had only been a few studies conducted (Markowska et al,2016;David et al, 2009) on how to establish how SS could be presented in a measurable manner. In Figure 3 a complex picture of an innovative standardization is presented while merging both Kemp's legal framework of big data with two areas of SS crucial for data processes: 'the discovery process' and 'the tracking progress'.…”

“…One of the SS characteristics is the growing importance of a particular sector as the background of the remaining ones (Markowska et al,2016). Therefore, in this paper, the big data is defined as the source of comparative advantages among regional economic actors and its emergence has hence not remained isolated to the technology, health, or bank sectors.…”