Vol. 13 No. 73 (2024)
Articles

Integration of environmental indicators into the management decision-making system

Serhii Poplavets
Ivan Kozhedub Kharkiv National Air Force University (KNAFU), Kharkiv, Ukraine.
Bio
Anatolii Nikitin
National Defence University of Ukraine, Kyiv, Ukraine.
Bio
Ivan Meshcheriakov
National Defence University of Ukraine, Kyiv, Ukraine.
Bio
Dmitro Kozlov
Ivan Kozhedub Kharkiv National Air Force University (KNAFU), Kharkiv, Ukraine.
Bio
Yevgen Vorobiov
Ivan Kozhedub Kharkiv National Air Force University (KNAFU), Kharkiv, Ukraine.
Bio
Dmytro Konov
Ivan Kozhedub Kharkiv National Air Force University (KNAFU), Kharkiv, Ukraine.
Bio

Published 2024-01-30

Keywords

  • management decision, environmental performance, eco-efficiency, climate change.

How to Cite

Poplavets, S., Nikitin, A., Meshcheriakov, I., Kozlov, D., Vorobiov, Y., & Konov, D. (2024). Integration of environmental indicators into the management decision-making system. Amazonia Investiga, 13(73), 231–240. https://doi.org/10.34069/AI/2024.73.01.19

Abstract

Climate change demands integrating environmental indicators into management decision-making systems, highlighting shifts towards environmental safety and stricter emissions regulations. This research develops a scheme for such integration, filling the gap in literature on the relationship between environmental factors and management decisions. Literature analysis and data examination through scientific and mathematical methods, including linear and multicriteria analysis, have led to a model emphasizing the importance of embedding environmental considerations into decision-making. The findings highlight the role of multi-criteria decisions in various conditions and establish a comprehensive model for the interplay between economic and environmental indicators, enhancing eco-efficiency in management practices. This approach introduces a novel method for incorporating environmental sustainability into management strategies, underscoring its significance for ongoing research and application in eco-efficient management decision-making.

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