Impact of Carbon Emission Factors on Economic Agents Based on the Decision Modeling in Complex Systems

Nikolay Didenko, Djamilia Skripnuk, Sergey Barykin (), Vladimir Yadykin, Oksana Nikiforova, Angela B. Mottaeva, Valentina Kashintseva, Mark Khaikin, Elmira Nazarova and Ivan Moshkin
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Nikolay Didenko: Graduate School of Business Engineering, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Djamilia Skripnuk: Graduate School of Business Engineering, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Sergey Barykin: Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Vladimir Yadykin: World-Class Research Center «Advanced Digital Technologies», Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Oksana Nikiforova: World-Class Research Center «Advanced Digital Technologies», Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Angela B. Mottaeva: Department of Management and Innovations, Financial University under the Government of the Russian Federation, 125167 Moscow, Russia
Valentina Kashintseva: Department of General and Applied Physics, Moscow State University of Civil Engineering (MGSU) National Research University, 129337 Moscow, Russia
Mark Khaikin: Department of Economic Theory, Saint-Petersburg Mining University, 199106 St. Petersburg, Russia
Elmira Nazarova: Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
Ivan Moshkin: Graduate School of Service and Trade, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia

Sustainability, 2024, vol. 16, issue 10, 1-14

Abstract: This article presents a methodology for modeling the impact of both internal and external environmental carbon emission factors on the resulting indicators of an international company. This research uses picture fuzzy rough sets to model the impact of factors on the resulting indicators as a research method. The proposed model is based on a dataset that includes the company’s profit, revenue, valuation, share price, and market share from 2012 through 2022. This empirical period is optimal for such a type of modeling. An approach of picture fuzzy rough sets based on the time series of endogenous and exogenous variables can provide an opportunity to analyze and consider the consequences of feedback changes in the systems of which they are a part. The article proposes a valuable framework for understanding the complex relationship between carbon emissions, economic factors, and the performance of international companies. The researchers of this study recommend a discussion that attempts to gain a deeper understanding of the challenges and opportunities that lie ahead for international companies in the context of climate change and technological innovation.

Keywords: impact; environmental factors; innovative economy; picture fuzzy rough sets (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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