Кластерные отношения в России и региональная политика развития кластеров
Recently, a three-stage version of K-Means has been introduced, at which not only clusters and their centers, but also feature weights are adjusted to minimize the summary p-th power of the Minkowski p-distance between entities and centroids of their clusters. The value of the Minkowski exponent p appears to be instrumental in the ability of the method to recover clusters hidden in data. This paper advances into the problem of finding the best p for a Minkowski metric-based version of K-Means, in each of the following two settings: semi-supervised and unsupervised. This paper presents experimental evidence that solutions found with the proposed approaches are sufficiently close to the optimum.
This document presents results of non-quantitative observations application and their processing methods, which significantly widen the analytical capabilities of the statistical measurement of the Russian IT market. The need to expand statistical tools that allow to reflect current and future trends in the sectoral development of IT sphere in a fast and visible manner, due to the rapid character of penetration of these services into the Russian market, is argued in the paper.
With the help of business climate indicators and construction of different homogeneous behavior models, analysis of business trends in the financial and economic activities of IT organizations is presented, highlighting the specifics of them functioning within the various cyclic episodes of 2010-2017.
Modern development of regional innovations is influenced by two trends: the increasing role of global connections and the persistent importance of geographical proximity of actors. This dual nature of spatial factor in regional innovations and the need to take into account multilevel dimensions ranging from local to global, foregrounds the need to study the phenomenon, which can be described as “glocalization of innovations”. This paper aims at reviewing the theoretical basis of local - global trends in regional innovation process, articulating a working definition for “regional innovation system glocalization”, analyzing various scenarios of regional innovation policy development regarding global connectivity and local density dimensions. Special emphasis is put on outlining practical guides for regional innovative performance based on the best use of local assets and fitting the global networks, with an in-depth analysis of clusters as the most suitable intervention for all regions to support glocalization of innovations.