Кластерные отношения в России и региональная политика развития кластеров

Cluster policy is recognized as one of the pivotal elements of state of art innovation policy. State support for clusters helps to take into account regional peculiarities and engage the most innovative local actors into the process of innovation policy drafting and implementation. Cluster development stimulates trust building and enhances knowledge spillovers among different organizations in the region. Finally the cluster approach makes innovation policy more systemic by coordinating measures aimed to support different actors (large companies, SMEs, universities, venture funds) towards comprehensive efforts linking the most perspective localized industries (ecosystems). The development of clusters has been determined as one of the priorities of the Strategy of Innovative Development of the Russian Federation for the period to 2020 which was confirmed end 2010. In the framework of this Strategy the first national cluster program was launched in 2012. The paper is devoted to the detailed description of the background of the national cluster program in Russia and its first phase the selection of the pilot innovative clusters which was implemented last year. Special attention is given to the comparison of planned design of the Russian cluster program with such widely known cluster programs as the BioRegio, InnoRegio and Les pôles de compétitivité. The similarities and peculiarities of the Russian program have been defined that allowed to identify several most significant areas for improvement

Added: Jun 25, 2013

Сетевой бизнес и кластерные технологии

Edited by: В. П. Третьяк, М. Ю. Шерешева М.: Издательский дом НИУ ВШЭ, 2011.

Added: Mar 6, 2013

Проблемы инновационного развития регионов

Ходачек А. М. Инновации. 2018. № 10(240). С. 27-31.

The article addresses the implications and preconditions for designing innovation policy for regions. Specifically the text shows the role and place of innovations in official socio-economic forecasts of Saint Petersburg and assesses the impact of clusters on enhancing competitiveness of the region.

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Added: Nov 28, 2018

Loop groups, Clusters, Dimers and Integrable systems

Marshakov A., Fock V. arxiv.org. math. Cornell University, 2014

We describe a class of integrable systems on Poisson submanifolds of the affine Poisson-Lie groups PGLˆ(N), which can be enumerated by cyclically irreducible elements the co-extended affine Weyl groups (Wˆ×Wˆ)♯. Their phase spaces admit cluster coordinates, whereas the integrals of motion are cluster functions. We show, that this class of integrable systems coincides with the constructed by Goncharov and Kenyon out of dimer models on a two-dimensional torus and classified by the Newton polygons. We construct the correspondence between the Weyl group elements and polygons, demonstrating that each particular integrable model admits infinitely many realisations on the Poisson-Lie groups. We also discuss the particular examples, including the relativistic Toda chains and the Schwartz-Ovsienko-Tabachnikov pentagram map.

Added: Oct 29, 2014

Социальное неравенство в мире: тенденции 2000—2016 гг.

Павлюшина В. А., Григорьев Л. М. В кн.: Вопросы экономики. М.: Некоммерческое партнерство "Редакция журнала "Вопросы экономики", 2018. С. 29-52.

Added: Oct 22, 2018

Кластерный подход в описании географии промышленности России (на примере отраслей автомобилестроения)

Корнеева Д. В., Голованова С. В. В кн.: Современные проблемы в области экономики, менеджмента, бизнес-информатики, юриспруденции и социально-гуманитарных наук: материалы VIII научно-практической конференции студентов и преподавателей НФ ГУ-ВШЭ. Н. Новгород: Нижегородский филиал НИУ ВШЭ, 2010. С. 133-140.

Added: Mar 14, 2013

ИННОВАЦИОННАЯ СРЕДА КРУПНЫХ РОССИЙСКИХ КОМПАНИЙ: ПОИСК МЕХАНИЗМОВ ВЗАИМОДЕЙСТВИЯ

Веселитская Н. Н. ИНФРА-М, 2018.

Added: Sep 12, 2018

Неколичественные наблюдения и методы их обработки в части статического анализа развития российского рынка информационных технологий

Лола И. С. Вопросы статистики. 2018. № 3. С. 25-42.

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.

Added: Feb 26, 2018