Risk assessment of innovative projects: development of forecasting models
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Дата
2021
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Анотація
The purpose of this article is development a systematic dynamic complex model of generation and risk assessment of innovative project, on the bases of which a scenario modeling of many risks influence arising at certain stages of project implementation in the target area. For article purpose realization, the paper proposes a complex toolkit for modeling the innovative projects risks in the direction of their impact on performance indicators in scenarios, which involves the implementation of the following stages of modeling: Stage 1. Collection and processing of project data; Stage 2. Evaluation of innovation project efficiency indicators; Stage 3. Formation and assessment of many risks of innovation project by components, nature and impact strength; Stage 4. Modeling of innovative project development scenarios. The implemented set of models makes possible to compare all components of efficiency and riskiness, which determine the integrated aggregate level of project risk by components of life cycle risks, target project risks and scenarios depending on environmental factors and managers propensity to take risks, and solves the problem of positioning the real indicators state of innovation project efficiency in a comparative dynamic context based on three-level assessment, due to structural elements of risks and identification of possible and promising deadlines and time horizons by stages of the project life cycle, critical paths and reserves which allow us to achieve the main goal of improving the innovative projects implementation efficiency.
Опис
Ключові слова
innovative project, life cycle, simulation model, business entities, challenges, scenario modeling, efficiency criterion
Бібліографічний опис
Risk assessment of innovative projects: development of forecasting models [Electronic resource] / V. Gorokhovatskyi [et al.] // CEUR Workshop Proceedings. – 2021. – Vol. 2927. – Machine Learning Methods and Models, Predictive Analytics and Applications : proc. of the Workshop on the 13th Intern. Sci. Practic. Conf. Modern problems of social and economic systems modelling (MPSESM-W 2021), Kharkiv, Ukraine, April 9, 2021. – Electronic text data. – Kharkiv, 2021. – P. 18-37. – URL: http://ceur-ws.org/Vol-2927/paper3.pdf, free (accessed 04.10.2021).