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Multidimensional Analysis of Consumer Behaviour on the European Digital Market

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Perspectives on Consumer Behaviour

Abstract

Most marketing specialists recognise that consumer behaviour can be explained by knowing the system of factors and variables that influence it. The purpose of our research is to get to know and analyse the behaviour of EU consumers within the online environment. In order to do so, we have selected a group of indicators and variables of consumer behaviour from the Eurostat database. The specific values for each EU Member State were processed using cluster analysis, by means of which we aimed to identify clusters with as many similar elements of the same class as possible (minimal variability within classes) and as many elements which differ from each other as possible if these elements belong to different classes (maximum variability between classes). Our research led to the identification of five clusters in which the EU states are grouped according to the characteristics of consumer behaviour in the online environment. An overview of consumer behaviour on the digital European market is provided and different types of generally similar consumers are identified. The results of our research could be interesting to specialists and experts in the marketing departments of companies doing business on the digital market of the European Union. We further suggest some future research opportunities.

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Correspondence to Armenia Androniceanu .

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Appendix: Data in Clusters

Appendix: Data in Clusters

Cluster

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

CL1

40.2

35.8

23.4

34.8

27.6

71.0

24.2

7.2

18.0

13.8

13.8

CL2

17.0

13.0

8.0

14.0

10.0

54.0

10.0

5.0

37.0

34.0

35.0

CL3

14.8

13.9

7.8

13.1

8.6

23.4

8.3

3.6

4.6

4.1

5.1

CL4

30.5

19.5

20.0

21.3

24.8

59.0

22.5

7.0

23.3

14.8

19.3

CL5

27.2

27.1

13.4

24.2

14.3

41.8

12.3

5.5

8.0

7.1

9.2

EU-28

26.1

23.3

14.3

22.1

16.4

44.6

14.6

5.5

12.0

9.5

11.2

Cluster 1

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

Denmark

47

44

23

23

34

72

26

9

11

11

24

Germany

27

45

28

36

25

67

20

7

9

17

12

Luxembourg

38

26

22

39

22

73

21

6

32

18

10

Netherlands

44

39

20

37

26

68

23

6

12

10

10

UK

45

25

24

39

31

75

31

8

26

13

13

Cluster 2

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

Ireland

17

13

8

14

10

54

10

5

37

34

35

Cluster 3

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

Bulgaria

9

7

6

7

7

15

6

2

4

2

3

Greece

21

22

6

19

6

28

6

3

3

4

5

Croatia

21

25

6

23

7

28

6

5

3

6

4

Italy

13

11

9

12

9

27

9

1

7

5

7

Cyprus

15

16

11

15

11

27

11

3

3

3

3

Lithuania

18

13

10

14

14

30

12

4

8

5

6

Portugal

13

11

11

10

11

25

12

6

8

7

10

Romania

8

6

3

5

4

7

4

5

1

1

3

Cluster 4

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

Belgium

23

20

18

20

21

52

20

5

15

14

13

France

34

13

19

25

27

61

21

5

31

12

14

Finland

32

18

21

23

25

59

22

8

27

14

20

Sweden

33

27

22

17

26

64

27

10

20

19

30

Cluster 5

V1

V2

V4

V3

V6

V11

V5

V10

V8

V7

V9

Czech Rep.

21

23

19

17

20

42

17

4

6

7

10

Estonia

29

33

15

27

17

48

14

8

10

13

12

Spain

24

31

11

30

8

41

7

3

5

9

6

Latvia

26

23

13

18

15

42

14

2

7

6

11

Hungary

24

25

11

18

13

33

10

6

4

4

8

Malta

30

21

14

31

11

42

12

7

17

6

8

Austria

34

23

13

30

14

54

15

3

20

10

14

Poland

24

26

13

22

15

39

12

3

3

5

5

Slovenia

27

27

9

22

12

32

9

8

4

4

7

Slovakia

33

39

16

27

18

45

13

11

4

7

11

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Androniceanu, A., Kinnunen, J., Georgescu, I., Androniceanu, AM. (2020). Multidimensional Analysis of Consumer Behaviour on the European Digital Market. In: Sroka, W. (eds) Perspectives on Consumer Behaviour. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-47380-8_4

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