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Article . 2020 . Peer-reviewed
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Cognitive analysis of eco-economic processes

Authors: Mikhail Rozin; Zhanna Tumakova; Anton Ivanov; Valery Svechkarev; Lidiya Novoseltseva;

Cognitive analysis of eco-economic processes

Abstract

It has been noted that the 21st century saw significant changes in public views on the economy-ecology relationship. Growing number of applied studies of eco-economic issues as well as the need to comprehend achieved results brought the use of cognitive analytics to the fore. Cognitive model provides a holistic view on the existing eco-economic process through its graphic representation reflecting nature and dynamics of causal relationships. Cognitive analysis of the conventional models of eco-economic process revealed that they mainly focus on economic procedures while environmental issues being shifted towards the periphery. Likewise, the traditional model essentially limits production development by ecological requirements while environmental condition is inherently impaired and requires further restoration or, at the very least, decontamination. The new models of manufacturing organization must aim to improve human environment as a whole and base on a zero-waste production principle where underused resources and raw materials are considered as waste. This article presents a cognitive model of green manufacturing in the shape of a multi-circuit system with all the circuits involved in the zero-waste production cycle. Considering that all circuits employ positive feedback, they initiate growth and mutually support consistent operation of an enterprise. A zero-waste enterprise can and should develop in cooperation with other enterprises that consciously or implicitly (formally) implement sustainable manufacturing plans.

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Keywords

Environmental sciences, GE1-350

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold