Sustainable development (SD) of territories is becoming an increasingly important task both at the national and regional level. On the other hand, there is a little research on applicability of the SD concept on the territories with special economic regimes, including Advanced special economic zones (ASEZ) implemented in the Russian Far East. This paper analyses management of ASEZ in the Far East considering SD concept. The article provides an overview of the current practice of applying SD concept in modern special economic zones and considers the applicability of SD practices in the framework of the Far Eastern ASEZs. The authors used a program management approach to analyzing the functioning of ASEZs, identified key problems in the operation of ASEZs, and provide suggestions and recommendations for solving existing problems, taking into account the SD concept. In conclusion, the authors formulated directions for further research in this area.
Introduction. Reduction of project cost overruns is a key objective of Russian production facilities against the background of tightening domestic and international market competition, a spike in the number of projects implemented within the framework of the investment programme, including large strategic investment projects, scarcity and high costs of sources of financing. The mission of this research is to offer an approach to the development of a system of key risk indicators of an construction project that will allow the management team to make decisions ahead of the occurrence of risk-bearing events to reduce cost overruns and to stay within the pre-set budget values in terms of capital costs of a project. Materials and methods. The co-authors have analyzed currently used approaches, instruments and methods, applicable to the development of the system of key project indicators, and classified project risks using the Ishikawa diagram. Their approach encompasses instruments and methods of the risk theory (identification and assessment of risks and key project indicators), as well as instruments of the regression correlation analysis. Results. The co-authors present an algorithm for the development of a system of key risk indicators and an approach to the listing of key project indicators broken down by project significance criteria. Conclusions. The application of the proposed approach to highly significant projects will ensure a detailed project-specific listing of key project indicators applicable to monitor the project implementation. A standard set of instruments and methods, requiring minimal human resources and time, can be applied to other projects. Besides the new approach, the co-authors offer a description of a list of potential key project indicators that enable to forecast changes in capital costs, broken down by risk factors.
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