| Title | Analysis Of Green Economy Dimension In The Context Of Circular Economy: The Case Of Baltic Sea Region |
|---|---|
| ID_Doc | 1518 |
| Authors | Stankeviciene, J; Nikanorova, M; Çera, G |
| Title | Analysis Of Green Economy Dimension In The Context Of Circular Economy: The Case Of Baltic Sea Region |
| Year | 2020 |
| Published | E & M Ekonomie A Management, 23, 1 |
| Abstract | The circular economy is based on the synergy of economic, environmental and social dimensions on -micro, -meso and -macro levels. Integration of circular economy would help to shift from a linear economy, which promotes "take-make-waste" industrial model to a more effective economic system that is based on business models, which replace the "end-of-life" concept with reducing, alternatively reusing, recycling and recovering materials in production/distribution and consumption processes. This alternative model would encourage producers to develop innovative solutions to reduce production waste, be in the line of "green" production and resource-efficient usage. A circular economy would help to solve problems of resource shortage, negative environmental impact, production and consumption waste by developing closer relationships between suppliers, manufacturers, retailers and consumers. Regulation and policy determents may influence consumer behaviour by promoting investment into environmental and social drivers, subsidiaries for eco-innovation and eco-technology development, and supporting inefficient consumption taxes and production pollution taxes. The purpose of the article is to propose a way of analysing of green economy dimension in the context of circular economy, by providing empirical tests on economic data of Baltic Sea Region countries. The current paper includes the observation of green economy dimension in the context of circular economy in Baltic Sea Region including Green investment, Green fiscal policy, and Technological development. A multi-criteria decision analysis methods TOPSIS and MULTIMOORA were used to compare the set of indicators by identifying weights for each criterion. TOPSIS and MULTIMOORA are quite useful methods to rank and make selection of several indicators. |
| https://doi.org/10.15240/tul/001/2020-1-001 |
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