Cite

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 dependence Summary
1. Knowledge of the assumptions of the circular economy concept and the nationality and generation of the respondent Generations 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 generation Consumers 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 respondents Consumers 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 coordinates Aggregate statistics for row and column points
Rows
Row Dimension1 Dimension2 Mass Quality
Albania 1995 to 2012 1.000 −1.314 −0.375 0.071 0.907
Albania 1980 to 1994 2.000 −1.196 −0.006 0.071 0.929
Albania 1965 to 1979 3.000 −0.973 −0.162 0.036 0.873
Albania Before 1965 4.000 −1.365 0.300 0.014 0.948
Poland 1995 to 2012 5.000 0.543 −0.128 0.482 0.997
Poland 1980 to 1994 6.000 0.616 0.261 0.024 0.890
Poland 1965 to 1979 7.000 0.630 0.278 0.020 0.817
Poland Before 1965 8.000 0.617 1.151 0.004 0.840
Portugal 1995 to 2012 9.000 −0.347 0.233 0.061 0.960
Portugal 1980 to 1994 10.000 0.085 0.450 0.057 0.929
Portugal 1965 to 1979 11.000 −0.259 0.191 0.140 0.885
Portugal Before 1965 12.000 −0.337 0.363 0.020 0.998
Columns
Other 1.000 −1.156 0.036 0.245 0.997
Vinted 2.000 0.322 −0.181 0.370 0.936
OLX 3.000 0.420 0.261 0.330 0.963
Wallapop 4.000 −1.073 −0.939 0.010 0.457
Allegro 5.000 0.808 −0.390 0.040 0.888
Facebook 6.000 0.797 −0.566 0.004 0.888

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 coordinates Aggregate statistics for row and column points
Rows
Row Dimension1 Dimension2 Mass Quality
Albania 1995 to 2012 1 −0.191849 0.534824 0.070707 0.472894
Albania 1980 to 1994 2 0.051960 0.706800 0.070707 0.708095
Albania 1965 to 1979 3 −0.584115 −0.220138 0.036364 0.545227
Albania Before 1965 4 −1.198459 −0.272782 0.014141 0.733096
Poland 1995 to 2012 5 0.307759 −0.124694 0.480808 0.974455
Poland 1980 to 1994 6 0.090776 0.303964 0.024242 0.251457
Poland 1965 to 1979 7 0.095099 −0.000663 0.020202 0.014137
Poland Before 1965 8 0.431796 −0.107556 0.004040 0.352646
Portugal 1995 to 2012 9 −0.023527 0.001238 0.062626 0.004099
Portugal 1980 to 1994 10 −0.259301 −0.288581 0.056566 0.359246
Portugal 1965 to 1979 11 −0.452911 0.003187 0.139394 0.461722
Portugal Before 1965 12 −1.311056 −0.351163 0.020202 0.778023
Columns
Other 1 −1.35968 −0.221362 0.038384 0.823015
Clothing 2 0.16687 −0.029520 0.640404 0.847949
Books 3 −0.22194 0.454150 0.074747 0.365518
Footwear 4 −0.31252 0.955384 0.024242 0.575607
Household goods (e.g., toasters) 5 −0.55651 0.519437 0.026263 0.323437
Furnishings of the apartment 6 −0.80131 −0.446938 0.054545 0.820918
Phones 7 0.14480 1.356521 0.006061 0.783974
Computers & Laptops 8 0.39371 −0.142679 0.026263 0.248796
RTV equipment (Cooperation radio and television) 9 0.08642 −0.190468 0.098990 0.188273
Sports equipment 10 0.79637 −0.454325 0.004040 0.778476
Games 11 0.79637 −0.454325 0.002020 0.778476
Car accessories 12 0.79637 −0.454325 0.002020 0.778476
Auto 13 0.79637 −0.454325 0.002020 0.778476

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 coordinates Aggregate statistics for row and column points
Rows
Row Dimension1 Dimension2 Mass Quality
Albania 1995 to 2012 1 −0.183 0.139 0.072 0.873
Albania 1980 to 1994 2 −0.277 0.244 0.072 0.988
Albania 1965 to 1979 3 0.039 0.571 0.037 0.991
Albania Before 1965 4 0.316 0.446 0.014 0.862
Poland 1995 to 2012 5 0.124 −0.047 0.488 0.962
Poland 1980 to 1994 6 0.072 −0.241 0.025 1.000
Poland 1965 to 1979 7 0.622 −0.170 0.020 0.689
Poland Before 1965 8 −0.256 −0.427 0.004 0.560
Portugal 1995 to 2012 9 −0.365 0.075 0.055 0.998
Portugal 1980 to 1994 10 −0.369 0.094 0.053 1.000
Portugal 1965 to 1979 11 −0.158 −0.275 0.139 0.879
Portugal Before 1965 12 0.725 0.414 0.020 0.722
Columns
Providing consumers with more durable products that will provide savings and a better quality of life 1 −0.269 0.294 0.148 0.835
Includes sharing, renting, reusing, repairing, refurbishing and recycling existing materials and product 2 −0.060 −0.085 0.693 0.798
Actions that can lead to a reduction in waste 3 0.511 0.332 0.111 0.985
Activities that may lead to reductions in total annual greenhouse gas emissions 4 0.496 −0.436 0.049 0.759

Correspondence analysis operation diagram (Trzęsiok, 2016)

1 Creation of a correspondence matrix based on the contingency table, i.e., a relative frequency matrix
2 Transform columns and mailing matrix rows separately to get points (called row and column profiles) that represent the categories of nonmetric variables being studied
3 Finding 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
4 Creation of a perception map – a graphical presentation of the relationships between the categories of variables studied
5 Inference 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 coordinates Aggregate statistics for row and column points
Rows
Row Dimension1 Dimension2 Mass Quality
Albania 1995 to 2012 1 −0.487 −0.060 0.071 1.000
Albania 1980 to 1994 2 −0.233 −0.319 0.071 1.000
Albania 1965 to 1979 3 −0.513 −0.129 0.036 1.000
Albania Before 1965 4 0.258 −0.347 0.014 1.000
Poland 1995 to 2012 5 0.085 0.063 0.481 1.000
Poland 1980 to 1994 6 0.360 −0.100 0.024 1.000
Poland 1965 to 1979 7 −0.229 0.256 0.020 1.000
Poland Before 1965 8 −0.548 −0.708 0.004 1.000
Portugal 1995 to 2012 9 −0.446 0.288 0.063 1.000
Portugal 1980 to 1994 10 0.345 0.158 0.057 1.000
Portugal 1965 to 1979 11 0.255 −0.153 0.139 1.000
Portugal Before 1965 12 −0.190 0.032 0.020 1.000
Columns
“Yes, I know what the circular economy is” 1 0.193 −0.174 0.364 1.000
“No, I’ve never heard that phrase before” 2 −0.481 −0.050 0.224 1.000
“I don’t know exactly what's going on” 3 0.091 0.181 0.412 1.000
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