MODELING OF TERRITORIAL AND ENTERPRISE DEVELOPMENT
Over recent years, our team of scientists has developed a number of models and methods for optimization of complex systems development management, as well as has opened a new dependency in the economy.
The following developments are the most significant of them.
Simulation model of scientific and technological development of economic activity types of Ukraine
This model was created within the State program of forecasting scientific and technological development of Ukraine for 2008-2012. The model allows simulating 11 types of economic activity of Ukraine, united in the following branches of industry: Power industry; Mechanical engineering; Metallurgy; Food industry.
This simulation model contains over 2000 variables and parameters and provides a medium-term change forecast of the following parameters for any of the simulated economic activity: the volume of completed research engineering; the volume of completed development activities; the amount of fixed assets; the amount of working capital; the amount of intangible assets; the number of staff involved in production; the level of the staff shortage in production; net profit, and many others.
On the basis of experiments with the simulation model forecasting and analytical research up to 2017 were carried out and proposals concerning the development of scientific, technological and staff support of 11 economic activity types of Ukraine and innovative strategy improvement were formulated. Different development scenarios of these economic activity types were designed and simulated and key performance indicators forecasts of their functioning were obtained.
Selected publications
1. Кононенко И.В., Репин А.Н. Метод прогнозирования инновационного и научно-технологического развития страны // Вестник Национального технического университета „ХПИ”. Сборник научных трудов. — Харьков: НТУ „ХПИ”. — 2005. — № 54. — с. 100-105.
2. Igor Kononenko, Anton Repin. The Modeling and Forecasting of the Technological and Innovational Development of a Transition- Economy Country. — 3rd International Conference on Project Management (ProMac2006). Sydney. Australia. 27-29September 2006. — 7 p.
3. Igor Kononenko, Igor Babych. Forecasting of Results of the State-Level Projects Implementation. The 7th International Conference on Business, Management and Economics (ICBME 2011). E-Proceedings. Cesme, Izmir, Turkey. 06-08 October 2011. —15 p.
4. Кононенко И.В., Бабич И.И. Модель оптимизации планов развития отрасли промышленности Украины // Вісник Національного технічного університету „Харківський політехнічний інститут”. Збірник наукових праць. — Харків: НТУ „ХПІ”. — 2010. — № 67. — с. 161-170.
5. Кононенко И.В., Бабич И.И. Метод многокритериальной оптимизации планов развития отрасли промышленности Украины // Восточно-Европейский журнал передовых технологий. — № 1/10 (55), 2012. — с. 8-12.
Regularity of GDP growth rate change influence on fixed capital investments into the country’s economy
This new tendency in the global economy has been established for dependencies between investment inflows into a country’s economy and GDP growth rate indicator as for the same year, so as for a one-year delay of the investment volume.
The essence of the regularity is as following. First, when GDP growth rate is bigger, than certain threshold value, investments into a country’s economy increase. Moreover, the investment inflows increase regardless of the direction of GDP growth rate change as long as this rate remains above the threshold level. Secondly, the decline or stabilization of investment inflows can be expected if GDP growth rate decreases within the sub-threshold zone.
The third scenario occurs when GDP growth rate increases within the sub-threshold zone subsequently entailing the growth or stabilization of investment inflows. If GDP growth rate increase occurs in the area of negative growth rate values, then this process can be followed by the investment inflows decrease. With the increase of GDP growth rate in the area of minor positive growth rate values (within the sub-threshold zone) the decrease of investment inflows can be also observed.
The regularity has been established for dependencies between investment inflows into a country’s economy and GDP growth rate indicator as for the same year, so as for a one year delay of the investment volume.
The regularity was investigated on economic processes in 32 countries of Europe, and also in Australia, Canada, Japan, and the USA. These countries were divided into groups according to the World Bank classification based on GNI per capita.
We explored the dependencies in such countries of Europe: Austria, Belgium, Bulgaria, Czech Republic, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and United Kingdom.
Selected publications
1. Кононенко И.В., Репин А.Н. Закономерность влияния изменений прироста ВВП страны на объем капитальных инвестиций в ее экономику для стран с различным экономическим состоянием // Бизнес-информ. — № 11, 2010. — с. 53-56.
2. Кононенко И.В., Репин А.Н. Закономерность влияния изменений прироста ВВП страны на объем капитальных инвестиций в ее экономику для стран с различным экономическим состоянием. Свідоцтво про реєстрацію авторського права на твір № 25801. МОН України. Державний департамент інтелектуальної власності. 24.09.2008.
3. Igor Kononenko, Anton Repin. „Rule of GDP Growth Rate Change Influence on Fixed Capital Investments into the Country Economy”. The Third International Conference on Business, Management, and Economics (ICBME 2007). Cesme. Turkey. 13-16 June 2007. — 11 p.
4. Igor Kononenko, Anton Repin. The Modeling and Forecasting of the Technological and Innovational Development of a Transition- Economy Country. — 3rd International Conference on Project Management (ProMac2006). Sydney. Australia. 27-29 September 2006. — 7 p.
5. Кононенко И.В., Репин А.Н. Метод прогнозирования инновационного и научно-технологического развития страны // Вестник Национального технического университета „ХПИ”. Сборник научных трудов. — Харьков: НТУ „ХПИ”. — 2005. — № 54. — с. 100-105.
Simulation technique of the state-level projects introduction impact on Ukrainian industry
This technique allows simulating the impact of the introduction of the newest technologies in the thematic direction „Energy and Energy Efficiency” on the state of Ukrainian industry.
It makes it possible to predict the following impact indicators of the introduction of new technologies in the power industry and other affected industries: real output of innovative products; amount of production costs reduction due to the introduction of the newest technology; amount of the net profit increase for economic activity types affected by the implementation of the newest technology; economic efficiency of the implementation of the state project, and others.
This technique is implemented as a separate unit in the previously mentioned simulation model.
Selected publications
1. Igor Kononenko, Igor Babych. Forecasting of Results of the State-Level Projects Implementation. The 7th International Conference on Business, Management and Economics (ICBME 2011). E-Proceedings. Cesme, Izmir, Turkey. 06-08 October 2011. — 15 p.
2. Кононенко И.В., Бабич И.И. Модель оптимизации планов развития отрасли промышленности Украины // Вісник Національного технічного університету „Харківський політехнічний інститут”. Збірник наукових праць. — Харків: НТУ „ХПІ”. — 2010. — № 67. — с. 161-170.
3. Кононенко И.В., Бабич И.И. Метод многокритериальной оптимизации планов развития отрасли промышленности Украины // Восточно-Европейский журнал передовых технологий. — № 1/10 (55), 2012. — с. 8-12.
STRATEGIC MANAGEMENT OF PROJECTS, PROGRAMS AND PORTFOLIOS OF BUSINESS AND TERRITORY DEVELOPMENT
Project portfolio selection methods
A project portfolio selection method has been suggested, which is focused to systemic accounting for factors affecting the efficiency of a set of projects. In solving the task, the focus was on studying the impact of the human factor and the subjective component. The key point of the method is acquisition and assessment of information on the market, the organisation’s strategy, the projects, the organisation’s potential to implement the projects, and the influence of stakeholders. The set of projects selected for the portfolio is validated for admissibility in regard to the profit gained, income, financial feasibility, and the company’s resource load. A model for optimising the project portfolio with algorithmic constraints has been suggested. The method can be applied for large and medium businesses.
In further research the fuzzy model and method of optimization of enterprise project portfolio for the planning period are developed. A process model of portfolio management of a company for the planning period is proposed . On the basis of this method a computer program „Portfolio optimization” is developed.
Developed methods and software are used in selection of the portfolio of projects of modernization of engineering production and the selection of the portfolio of projects in the energy field.
Selected publications
1. Кононенко И.В., Букреева К.С. Метод формирования портфеля проектов предприятия для планового периода при нечетких исходных данных //Управління розвитком складних систем. Збірник наукових праць. Випуск 7, 2011. Київський національний університет будівництва і архітектури. — с. 39-43.
2. Кононенко И.В., Букреева К.С. Модель и метод оптимизации портфелей проектов предприятия для планового периода // Восточно-Европейский журнал передовых технологий. — № 1/2 (43), 2010. — с. 9-11.
3. Igor V. Kononenko, Karina Bukrieieva. Project Portfolio Selection Method Considering Possibilities and Influence of Project Stakeholders. The Human Side of Projects in Modern Business. International Project Management Association. Scientific Research Paper Series. Helsinki. Finland. 2009. — p. 559-570.
Mathematical models and methods of the project scope optimization with precise and fuzzy input data
A mathematical model and method of the project scope optimization has been suggested, which has fuzzy input data and includes five objective functions. One of the functions reflects the profit for the entire project product life cycle. The other reflects the time of its realization. The third is the cost of the project. The fourth is the value of the generalized indicator of project product quality and the fifth is a risk assessment associated with the project. The model and method takes into account the restrictions on the lack of financial debt after each phase completion, the duration of the project, the quality of the separate stages products.
In solving the task a mathematical model and method of the project scope optimization has been suggested with precise input data and fuzzy input data.
On the basis of this method a computer program „PTCQR Optimization of Project Scope” is developed.
Selected publications
1. Кононенко, И.В. Модель и метод многокритериальной оптимизации содержания проекта при нечетких исходных данных / И.В. Кононенко, М.Э. Колесник // Восточно-Европейский журнал передовых технологий. — 2013. — № 1/10 (61). — с. 9-13.
2. Кононенко И.В., Колесник М.Э. Оптимизация содержания проекта по критериям прибыль, время, стоимость, качество, риски // Восточно-Европейский журнал передовых технологий. — № 1/10 (55), 2012. — с. 13-15.
3. Igor V. Kononenko, Valeriy A. Fadeyev, Mariia E. Kolisnyk. Project scope optimization model and method on criteria profit, time, cost, quality, risk. Integrating Project Management Standards. Proceedings of the 26th IPMA World Congress, 29-31 October 2012, Conference Centre Creta Maris, Hersonissos, Crete, Greece, 2012, pp.286-292.