Linear Programming as a Data Mining Tool in Assessing Competitiveness in the Face of Uncertainty
Оlena Sadchenko1, Maryna Karpitskaya2, Kateryna Stasiukova3, Mariia Popova4, Volodymyr Tytykalo5, Olena Makoveieva6
1Оlena Sadchenko, Department of Marketing and Business Administration Odessa I.I. Mechnikov National University, Odessa, Ukraine.
2Maryna Karpitskaya, Faculty economics and management, Yanka Kupala State University of Grodno, Grodno, Belarus.
3Kateryna Stasiukova, Department of Accounting and Audit, Odessa National Academy of Food Technologies, Odessa, Ukraine.
4Mariia Popova, Department of Management Environmental Performance, Odessa state environmental university, Odessa, Ukraine.
5Volodymyr Tytykalo, Department of HR and labor Economics, Interregional Academy of Personnel Management, Kyiv, Ukraine.
6Olena Makoveieva, Department of Economics of Industry, Odessa National Polytechnic University, Odessa, Ukraine.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 1475-1478 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7535068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Entrepreneurial activity in the market is associated with risk and with a situation of uncertainty, which ultimately characterizes the random component in the functioning of enterprises, their competitiveness. The development of mathematical models and methods to improve competitiveness in conditions of uncertainty are relevant and are essential for theory and practice.In the article, the authors study the concept of competitiveness and competitive advantages. An outstanding achievement in the article is a visual representation of the linear programming method and testing it on a real practical example.
Keywords: Risk, Uncertainty, Linear Programming, Competitiveness, Competitive Advantages, Sustainable Competitive Advantage.
Scope of the Article: Data Mining