The methodology of economic recovery of commercial companies in crisis conditions
Author(s) -
Oana Panazan,
Cătălin Gheorghe,
Gavrilă Calefariu
Publication year - 2021
Publication title -
iop conference series materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1009/1/012044
Subject(s) - function (biology) , creditor , business , set (abstract data type) , face (sociological concept) , covid-19 , point (geometry) , financial crisis , production (economics) , economics , industrial organization , risk analysis (engineering) , computer science , microeconomics , finance , macroeconomics , medicine , debt , social science , geometry , mathematics , disease , pathology , evolutionary biology , sociology , infectious disease (medical specialty) , biology , programming language
Even though commercial companies play a really important role in the economic functioning and development, now, in crisis conditions, the future for some of them is unknown. As a result of the release of crisis caused by „Coronavirus severe acute respiratory syndrome 2, abbreviated SARS-CoV-2”, these companies are facing novel negative situations, not being able to manifest temporarily or normally the activity. From a systematic point of view, this crisis has the role of a really powerful disturbing factor. The creditors and investors are in a similar fragile situation. This paper identifies some scientific methods which can decrease the negative appeared problems, building models that take into account the limited resources that companies face and that they can lead to improving their economic situation. As an application, part of the essay presents the synthesis of the main assets and malfunctions of a company established in Romania. The elaboration of future strategies will be achieved through the systematic research of the admissible bases, aiming at maximizing the objective function. The type of equilibrium by reverse induction will be established, thus obtaining the set of the best cost variants. Linear programming will generate the optimal solution capable of exploiting the opportunities offered by the market with a minimal impact of disruptive factors.
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