Створено економіко-матема-тичну модель формування коман-ди проекту. Для комплексної оцін-ки оптимальності складу команди проекту запропоновано врахува-ти показники професійної, інте-лектуальної, соціальної складової та знання, зацікавленість і дос-від вирішення аналогічних задач. У моделі застосуються елементи комбінаторики, експертне опи-тування та метод безпосередньої оцінки Ключові слова: команда проек-ту, економіко-математичне мо-делювання, вагові коефіцієнти, комплексна оцінка Создана экономико-математи-ческая модель формирования ко-манды проекта. Для комплекс-ной оценки оптимальности соста-ва команды проекта предложено учесть показатели профессиональ-ной, интеллектуальной, социаль-ной составляющей и знания, заин-тересованность и опыт решения аналогичных задач. В модели при-менятся элементы комбинато-рики, экспертный опрос и метод непосредственной оценки Ключевые слова: команда про-екта, экономико-математиче-ское моделирование, весовые коэф-фициенты, комплексная оценка UDC 331.101.262:330.46

The article proposes an economic-mathematical model for determining a comprehensive risk assessment of the investment project of the enterprise which are based on the approaches of A. Nedosekin. The model is built using fuzzy logic and takes into account the probability of occurrence of each of the identified risks and the level of impact of each of them on the project. The probability of risk is set by experts in the form of points and converted into linguistic terms, and the level of influence of each of them on the project – the ratio of benefits and is determined using Fishburne scales. The proposed Project Risk Model consists of the following stages: formation of initial data using expert opinions; construction of a hierarchical project risk tree; determination of weight coefficients (Fishburne weights) of project risks; selection and description of membership function and linguistic variables; conversion of input data provided by experts from a score scale into linguistic terms; recognition of qualitative input data on a linguistic scale; determination of a complex indicator of investment project risks; interpretation of a complex indicator. The developed model allows managing the risks of the project to maximize the probability of its successful implementation, to compare alternative projects and choose less risky, to minimize the level of unforeseen costs of the project.

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The economic-mathematical model of formation of complex estimation and definition of level of risk of system of management of knowledge of the enterprise with use of the gray relational analysis and a method of the analysis of hierarchies is developed in work. An enterprise knowledge management system, an example of a “gray” system, is usually a variant of “black”, in which all criteria are fuzzy, and “white”, in any there is a complete set of data on criteria and constraints, are between them and is a system. with incomplete description. The proposed model consists of the following stages: problem statement; determination of criteria and indicators of knowledge management system; evaluation of indicators of the knowledge management system (in numerical form and in linguistic terms) and determination of their reference values; preliminary data processing (reduction of all indicators to one order); calculation of gray relational classes (determination of gray relational coefficients; determination of weight coefficients; determination of gray relational classes); construction of a matrix of estimates; formation of a comprehensive assessment of the knowledge management system of enterprises; determining the maturity of the enterprise for knowledge management; interpretation of the obtained results. Three general criteria and 43 indicators (in terms of quantitative and qualitative characteristics) were selected: People (11 indicators), Technology (9 indicators), Processes (23 indicators). Criterion Processes include blocks: Learning (2 indicators), Innovation (5 indicators), Innovation processes (7 indicators), Innovation cooperation (2 indicators), Core activity (7 indicators). The model consists of constituent elements (people, technologies, processes), levels (individual, group, organizational, inter-organizational), stages (phases) of knowledge management (Formation – accumulation, exchange – generation – storage and documentation – use – result of knowledge management) and allows the interaction of the level of maturity of the enterprise for knowledge management. The weights of the criteria and indicators of knowledge management of the enterprise analysis of the definition system occur using the method of hierarchy (pairwise comparison method). The practical implementation of the model was implemented for public utilities of Ukraine. The developed model is universal and can be used for enterprises of different spheres of activity to comprehensively assess the knowledge management system in comparison with the benchmark enterprise, determine the level of maturity of the enterprise with management and identify problems of effective management decisions to improve competitiveness.