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Consumption behavior towards the circular economy Cover

Figures & Tables

Figure 1a.

The Linear Economy (AkzoNobel, 2015)
The Linear Economy (AkzoNobel, 2015)

Figure 1b.

The Circular Economy (AkzoNobel, 2015)
The Circular Economy (AkzoNobel, 2015)

Figure 2.

Factors influencing consumer decision-making in the Circular Economy (Shevchenko et al., 2023)
Factors influencing consumer decision-making in the Circular Economy (Shevchenko et al., 2023)

Figure 3.

Factors influencing consumers’ decisions to replace, repair or lease products (EC, 2018)
Factors influencing consumers’ decisions to replace, repair or lease products (EC, 2018)

Figure 4.

Presentation for the country, generation and knowledge “Have you come across the concept of the circular economy?”. Source: Own elaboration using Statistica 13.3
Presentation for the country, generation and knowledge “Have you come across the concept of the circular economy?”. Source: Own elaboration using Statistica 13.3

Figure 5.

Presentation for the country, generation and knowledge for the question “Which of the following terms do you associate most with the term circular economy?” A - Includes sharing, renting, reusing, repairing, refurbishing and recycling existing materials and products; B - Actions that can lead to a reduction in waste; C -activities that may lead to reductions in total annual greenhouse gas emissions; D -providing consumers with more durable products that will provide savings and a better quality of life. Source: Own elaboration using Statistica 13.3
Presentation for the country, generation and knowledge for the question “Which of the following terms do you associate most with the term circular economy?” A - Includes sharing, renting, reusing, repairing, refurbishing and recycling existing materials and products; B - Actions that can lead to a reduction in waste; C -activities that may lead to reductions in total annual greenhouse gas emissions; D -providing consumers with more durable products that will provide savings and a better quality of life. Source: Own elaboration using Statistica 13.3

Figure 6.

Presentation for country, generation and responses to “Where do you most often buy used products?” Source: Own elaboration, using Statistica 13.3.
Presentation for country, generation and responses to “Where do you most often buy used products?” Source: Own elaboration, using Statistica 13.3.

Figure 7.

Presentation for country, generation and “What used products do you buy most often?” Source: Own elaboration using Statistica 13.3
Presentation for country, generation and “What used products do you buy most often?” Source: Own elaboration using Statistica 13.3

Summary of research results_

No.Analysed dependenceSummary
1.Knowledge of the assumptions of the circular economy concept and the nationality and generation of the respondentGenerations X and Z from Albania indicated the answer variant: “No, I have never heard that sentence before.” The answer “Yes, I know what the circular economy is” was clear from Polish Millennials, Albanian Baby Boomers, and Portuguese Generation X.
2.The variants of the respondents’ answers to the question „Which of the following terms do you most associate with the term ‘circular economy’”, and nationality and generation„Includes sharing, renting, reusing, repairing, refurbishing and recycling existing materials and products” The most relevant group's answers to this option were Polish respondents from three different generations (X, Millennials and Z).
3.The place of purchase of used products respondents’ and nationality and generationConsumers from Poland (born: 1965 – 2012) prefer OLX and Vinted as a place to buy second-hand goods. Consumers from Albania (all generations) most often indicated the answer option “Other.” The distribution of answers of respondents from Portugal did not clearly indicate preferred shopping place.
4.Types of second-hand goods and the nationality and generation of respondentsConsumers represented by Portuguese generation Z and Polish generation X mainly purchase clothes. Polish generation Z and baby boomers tend to buy used computers and laptops.

Row and column coordinates and contribution to inertia for country, generation and “Where do you most often buy used products?” Source: own elaboration_

Row and column coordinatesAggregate statistics for row and column points
Rows
RowDimension1Dimension2MassQuality
Albania 1995 to 20121.000−1.314−0.3750.0710.907
Albania 1980 to 19942.000−1.196−0.0060.0710.929
Albania 1965 to 19793.000−0.973−0.1620.0360.873
Albania Before 19654.000−1.3650.3000.0140.948
Poland 1995 to 20125.0000.543−0.1280.4820.997
Poland 1980 to 19946.0000.6160.2610.0240.890
Poland 1965 to 19797.0000.6300.2780.0200.817
Poland Before 19658.0000.6171.1510.0040.840
Portugal 1995 to 20129.000−0.3470.2330.0610.960
Portugal 1980 to 199410.0000.0850.4500.0570.929
Portugal 1965 to 197911.000−0.2590.1910.1400.885
Portugal Before 196512.000−0.3370.3630.0200.998
Columns
Other1.000−1.1560.0360.2450.997
Vinted2.0000.322−0.1810.3700.936
OLX3.0000.4200.2610.3300.963
Wallapop4.000−1.073−0.9390.0100.457
Allegro5.0000.808−0.3900.0400.888
Facebook6.0000.797−0.5660.0040.888

Row and column coordinates and contribution to inertia for country, generation and “What used products do you buy most often?” Source: own elaboration_

Row and column coordinatesAggregate statistics for row and column points
Rows
RowDimension1Dimension2MassQuality
Albania 1995 to 20121−0.1918490.5348240.0707070.472894
Albania 1980 to 199420.0519600.7068000.0707070.708095
Albania 1965 to 19793−0.584115−0.2201380.0363640.545227
Albania Before 19654−1.198459−0.2727820.0141410.733096
Poland 1995 to 201250.307759−0.1246940.4808080.974455
Poland 1980 to 199460.0907760.3039640.0242420.251457
Poland 1965 to 197970.095099−0.0006630.0202020.014137
Poland Before 196580.431796−0.1075560.0040400.352646
Portugal 1995 to 20129−0.0235270.0012380.0626260.004099
Portugal 1980 to 199410−0.259301−0.2885810.0565660.359246
Portugal 1965 to 197911−0.4529110.0031870.1393940.461722
Portugal Before 196512−1.311056−0.3511630.0202020.778023
Columns
Other1−1.35968−0.2213620.0383840.823015
Clothing20.16687−0.0295200.6404040.847949
Books3−0.221940.4541500.0747470.365518
Footwear4−0.312520.9553840.0242420.575607
Household goods (e.g., toasters)5−0.556510.5194370.0262630.323437
Furnishings of the apartment6−0.80131−0.4469380.0545450.820918
Phones70.144801.3565210.0060610.783974
Computers & Laptops80.39371−0.1426790.0262630.248796
RTV equipment (Cooperation radio and television)90.08642−0.1904680.0989900.188273
Sports equipment100.79637−0.4543250.0040400.778476
Games110.79637−0.4543250.0020200.778476
Car accessories120.79637−0.4543250.0020200.778476
Auto130.79637−0.4543250.0020200.778476

Row and column coordinates and contribution to inertia for country, generation and knowledge for the question “Which of the following terms do you associate most with the term ‘circular economy’?”_ Source: own elaboration_

Row and column coordinatesAggregate statistics for row and column points
Rows
RowDimension1Dimension2MassQuality
Albania 1995 to 20121−0.1830.1390.0720.873
Albania 1980 to 19942−0.2770.2440.0720.988
Albania 1965 to 197930.0390.5710.0370.991
Albania Before 196540.3160.4460.0140.862
Poland 1995 to 201250.124−0.0470.4880.962
Poland 1980 to 199460.072−0.2410.0251.000
Poland 1965 to 197970.622−0.1700.0200.689
Poland Before 19658−0.256−0.4270.0040.560
Portugal 1995 to 20129−0.3650.0750.0550.998
Portugal 1980 to 199410−0.3690.0940.0531.000
Portugal 1965 to 197911−0.158−0.2750.1390.879
Portugal Before 1965120.7250.4140.0200.722
Columns
Providing consumers with more durable products that will provide savings and a better quality of life1−0.2690.2940.1480.835
Includes sharing, renting, reusing, repairing, refurbishing and recycling existing materials and product2−0.060−0.0850.6930.798
Actions that can lead to a reduction in waste30.5110.3320.1110.985
Activities that may lead to reductions in total annual greenhouse gas emissions40.496−0.4360.0490.759

Correspondence analysis operation diagram (Trzęsiok, 2016)

1Creation of a correspondence matrix based on the contingency table, i.e., a relative frequency matrix
2Transform columns and mailing matrix rows separately to get points (called row and column profiles) that represent the categories of nonmetric variables being studied
3Finding a space with a smaller dimension and projecting into it (with possible rotation) points (profiles) obtained in point 2. The choice of space, as well as its rotation, is made in such a way that the loss of information contained in the original data is as small as possible
4Creation of a perception map – a graphical presentation of the relationships between the categories of variables studied
5Inference of dependencies and interpretation of results

Row and column coordinates and contribution to inertia for country, generation and knowledge of the question: “Have you come across the concept of the circular economy?”_ Source: own elaboration

Row and column coordinatesAggregate statistics for row and column points
Rows
RowDimension1Dimension2MassQuality
Albania 1995 to 20121−0.487−0.0600.0711.000
Albania 1980 to 19942−0.233−0.3190.0711.000
Albania 1965 to 19793−0.513−0.1290.0361.000
Albania Before 196540.258−0.3470.0141.000
Poland 1995 to 201250.0850.0630.4811.000
Poland 1980 to 199460.360−0.1000.0241.000
Poland 1965 to 19797−0.2290.2560.0201.000
Poland Before 19658−0.548−0.7080.0041.000
Portugal 1995 to 20129−0.4460.2880.0631.000
Portugal 1980 to 1994100.3450.1580.0571.000
Portugal 1965 to 1979110.255−0.1530.1391.000
Portugal Before 196512−0.1900.0320.0201.000
Columns
“Yes, I know what the circular economy is”10.193−0.1740.3641.000
“No, I’ve never heard that phrase before”2−0.481−0.0500.2241.000
“I don’t know exactly what's going on”30.0910.1810.4121.000
DOI: https://doi.org/10.2478/ceej-2023-0019 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001
Language: English
Page range: 323 - 342
Published on: Oct 31, 2023
Published by: Faculty of Economic Sciences, University of Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Altin Kulli, Małgorzata Grzywińska-Rąpca, Nelson Duarte, Enkelejda Goci, Carla Pereira, published by Faculty of Economic Sciences, University of Warsaw
This work is licensed under the Creative Commons Attribution 4.0 License.