Investment project

This paper focuses on the problems of company’s sustainable management in an emergent environment. The authors’ vision of the functioning peculiarities in the formulation of a company’s strategy based on the information support is presented in the article. The world experience of studying the development of investment projects in companies of different industry sectors is investigated and analyzed according to the economic and mathematical modeling. A multivariate model of evaluation and selection of the investment project based on the hierarchy criterion of company's economic objectives with the information technology is developed as an embodiment of the strategic goal of ensuring the company's sustainability. The essence of the hierarchy criterion method is to determine the order and the value of priority of each individual criterion, thus, application of this method allows providing recommendations for making an effective management decision in unpredictable environment. The proposed model based on the hierarchy criterion of company’s economic tasks allows providing sustainability in emergent environment. The analysis and substantiation of the necessity of applying the proposed model with the information technology support is presented in this paper.

The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.