В условиях экономических санкций, введенных в отношении России рядом зарубежных партнеров в 2014 г., особое значение приобретают высокотехнологичные отрасли хозяйства как важнейший источник замещения импортной продукции на внутреннем рынке. Одной из ключевых мер поддержки таких отраслей служит развитие специализированных кластеров за счет установления новых и укрепления существующих связей между субъектами малого и среднего бизнеса, крупными предприятиями и научными организациями. Отправной точной эффективной кластерной политики служит идентификация регионов с высоким потенциалом кластеризации указанных отраслей.В работе представлена оригинальная методика выявления потенциальных кластеров и приведены результаты ее апробации в регионах России. Авторы демонстрируют, что большинство поддерживаемых государством пилотных инновационных проектов реализуются в регионах и отраслях, обладающих высоким кластерным потенциалом. Произведена типологизация пилотных инновационных территориальных кластеров в зависимости от потенциала кластеризации регионов их расположения, выраженного в соответствующем индексе. Определены регионы со сходными или более благоприятными условиями для формирования кластеров в инновационных отраслях, отобранных в качестве пилотных.Примечание: Уважаемые читатели, обращаем Ваше внимание, что в печатной версии статьи на картосхемах (рис. 1-7) цвета в легенде ошибочно приведены в обратном порядке. Следует читать: красным показаны наибольшие значения индекса, синим - наименьшие.

Proceedings of the International conference

Ongoing climate change most pronounces itself in northern latitudes, including in the Arctic zone of the Russian Federation (AZRF). Climate change is a complex multidirectional process that is characterized by both positive and negative effects on the functioning of territorial economic systems. In this regard, an analysis of the impacts of climate change on economic development is a particularly urgent scientific and practical task that requires comprehensive study. This research was devoted to assessing the probable impacts of climate transformations on the parameters of the economic development of the AZRF regions. The authors created a methodological approach to the assessment of the costs of the effects of climate change for the economy of the AZRF regions, taking into account the average predicted dynamics of surface air temperature and key regional economic specializations, as well as the degree of susceptibility of various industries to the climate change. The energy industry was considered in particular detail since it is the basis for all of the other industries and is the guarantor of life support for the populations that live in the extreme Arctic climate. Calculations have shown that the accumulated economic effects of climate change as a whole for the AZRF economy during the period 2020–2050 will be negative and have been estimated as having a cost of more than RUB 8 trillion (or nearly USD 111 billion in 2020 prices), which would be about 3% of total Russian Arctic GRP in average annual terms.

The article is devoted to the problem of clustering possibility in Russian information technology industry (IT). The clustering potential concept and its significance in the framework of cluster policy measures modeling are considered. The article uses the example of the Russian IT industry to test the European Cluster Observatory model for clustering potential assessing. The main trends characterizing the change of the IT industry clustering potential in Russian regions were identified. The verification of the current cluster development priorities within the framework of the current state cluster policy was carried out. The regions of Russia that have a high potential for the new IT-cluster formation were identified. The directions for improving the methodological approach to assessing the clustering potential, taking into account the main factors of the information technology industry development, were proposed. The analysis helps to identify few important problems of the Russian IT industry development within the framework of the cluster development model, including a trend towards a decrease in indicators of the IT industry clustering potential for the most socially and economically developed Russian regions, an increase in the level of IT industry monopolization, and also an increase in the negative impact of barriers which preventing new companies from entering the Russian IT market.

The Pechoro-Kara region occupies a special place in the Arctic zone of the Russian Federation as the centre of hydrocarbon exploration, which is the main Russian export. At the same time, this is the area with the highest climate risks on the Arctic coast of Russia. The study aims to estimate the value of buildings and structures planned for construction as part of large investment projects in the coastal areas of the Pechora and Kara Seas by the mid-21st century. Regulatory documents, data from official websites and investment portals of various companies and public authorities were examined to create a database of 36 investment projects in the mining and manufacturing industries, transport scheduled to be commissioned in 2017–2050. The authors’ method analyses the time series of indicators of investment in fixed capital and new fixed assets, as well as the structure of fixed assets in the examined industries. Calculations reveal that after the construction phase of each of the projects under consideration, new fixed assets amounting to 8.2 trillion roubles are expected. These include buildings and structures of the mining industry (approximately 6.2 trillion roubles), transport (0.8 trillion roubles), manufacturing industry (0.1 trillion roubles). As an example, the obtained results were compared with the forecast of thermal abrasion and ice-gouging hazards on the coasts of the Pechora and Kara seas. The estimated value of fixed assets that will be located in areas of maximum risk is about 4 trillion roubles (in 2023 prices). This finding confirms the urgent need for early implementation of adaptation protective measures during the construction and operation of infrastructure in order to minimise potential damage.

The article discusses modern approaches to measuring, evaluating and predicting cluster effects, proposes their classification, taking into account directly the effects of the activity of cluster formations, as well as effects outside the cluster formations—potential cluster effects. It offers an integral definition of the concept of “cluster effect,” the relationship of cluster effects with agglomeration effects is considered, and a methodology for assessing the potential of the socioeconomic environment of a region for the formation of clusters has been developed and tested.