Journal of Open Innovation: Technology, Market and Complexity (Sep 2020)

Predictive Scenarios of the Russian Oil Industry; with a Discussion on Macro and Micro Dynamics of Open Innovation in the COVID 19 Pandemic

  • Vadim Ponkratov,
  • Nikolay Kuznetsov,
  • Nadezhda Bashkirova,
  • Maria Volkova,
  • Maria Alimova,
  • Marina Ivleva,
  • Larisa Vatutina,
  • Izabella Elyakova

DOI
https://doi.org/10.3390/joitmc6030085
Journal volume & issue
Vol. 6, no. 85
p. 85

Abstract

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The decrease in the economic activity level around the world due to the COVID-19 pandemic spread has led to a sharp decrease in the crude oil price and provoked an oil war outbreak in the global energy market. The current situation has provoked the need for a total decrease in the crude oil production in the world. Considering that Russia is one of the main oil exporters on the world market, the need to determine the supply and demand levels for Russian oil is becoming relevant. The aim of the paper is to model predictive scenarios of Russian oil industry development, considering the specifics of the current economic environment given the COVID-19 pandemic. The multifactor correlation modeling method was used to form the system of indicators determining the level of demand and supply for Russian oil used and the total level of their influence. The functions determine the probability of implementing various scenarios of oil industry development depending on the predicted values of demand and supply. The three-sigma rule and the fuzzy sets method were used to estimate three scenarios of oil industry development for 2020–2021. Changes in revenues of the industry under the influence of forecast indicators of supply and demand for oil have been assessed and the probability of implementation of each of the scenarios has been reasoned. The results obtained are of a practical nature and can be used by government agencies, financial intermediaries, and scientists to diagnose Russian oil industry development. The results will be useful for oil companies to develop a strategy of open innovations for further design of the scientific information field for the effective functioning of the industry in complete uncertainty conditions.

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