INFORMATION MODEL OF SYSTEM OF SUPPORT OF DECISION MAKING DURING MANAGEMENT OF IT COMPANIES
Yehor TATARCHENKO
gosahi@gmail.comVolodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast (Ukraine)
Volodymyr LYFAR
Volodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast (Ukraine)
Halyna TATARCHENKO
Volodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast (Ukraine)
Abstract
An information model has been carried out, with the help of which it is possible to implement methods that ensure the growth of competitiveness of IT companies. Growth conditions for companies provide mergers and acquisitions (M&A). The analysis of the data obtained as a result of the P&L financial report is mainly based on current indicators and can be partially used to prolong economic indicators for a certain (most often limited) period. The authors propose using methods for assessing stochastic indicators of IT development processes based on the solution of a number of problems: (1) Development of models to assess the impact of indicators in the analysis of the financial condition of companies; (2) Creation of an information model and methods for processing current stochastic data and assessing the probability of the implementation of negative and positive outcomes.
Keywords:
IT company, risk, decision making, mergers and acquisitions, FTA, ETAReferences
Darnall, R., & Preston, J. M. (2016). Project Management from Simple to Complex. University of Minnesota Libraries Publishing.
Google Scholar
Draft Federal Information Processing Standards Publication 183. (1993). Integration Definition For Function Modeling (IDEF0).
Google Scholar
Draft Federal Information Processing Standards Publication 184. (1993). Integration Definition For Information Modeling (IDEF1X).
Google Scholar
IEC 60300-3-9:1995. (1995). Dependability management – Part 3: Application guide – Section 9:Risk analysis of technological systems.
Google Scholar
Iovanella, A. (2017). Vital few e trivial many. In Il Punto (pp. 10–13).
Google Scholar
Kringel, D., Ultsch, A., Zimmermann, M., Jansen, J. P., Ilias, W., Freynhagen, R., & Resch, E. (2017). Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses. The pharmacogenomics Journal, 17(5), 419–426, https://doi.org/10.1038/tpj.2016.28.
DOI: https://doi.org/10.1038/tpj.2016.28
Google Scholar
Pagach, D., & Warr, R. (2011). The Characteristics of Firms That Hire Chief Risk Officers. The Journal of Risk and Insurance, 78(1), 185–211.
DOI: https://doi.org/10.1111/j.1539-6975.2010.01378.x
Google Scholar
Pawelek, B., Pociecha, J., & Baryla, M. (2017). ABC Analysis in Corporate Bankruptcy Prediction. In Abstracts of the IFCS Conference (p. 17). Tokyo, Japan.
Google Scholar
SS-IEC 1025:1990. (1990). Fault tree analysis (FTA).
Google Scholar
Ultsch, A., & Lötsch, J. (2015). Computed ABC analysis for rational selection of most informative variables in multivariate data. PLOS One, 10(6), e0129767. https://doi.org/10.1371/journal.pone.0129767
DOI: https://doi.org/10.1371/journal.pone.0129767
Google Scholar
What are the Main Valuation Methods? (2019). Retrieved August 12, 2019 from https://corporatefinanceinstitute.com/resources/knowledge/valuation/valuation-methods
Google Scholar
Authors
Yehor TATARCHENKOgosahi@gmail.com
Volodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast Ukraine
Authors
Volodymyr LYFARVolodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast Ukraine
Authors
Halyna TATARCHENKOVolodymyr Dahl East Ukrainian University, Faculty of Information Technology and Electronics, Department of Programming and Mathematics, Tsentralnyi Ave., 59A, Severodonetsk, Luhansk Oblast Ukraine
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