Multivariate exploration of the questionnaire and typology of the surveyed people The results are provided by the EnQuireR package July 28, 2010

Contents 1 Quick overview of the questionnaire

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2 Multivariate exploration of the questionnaire 2.1 Graphical representations of the questionnaire . . 2.2 Highlights on the two principal axes of variability 2.2.1 First axis . . . . . . . . . . . . . . . . . . 2.2.2 Second axis . . . . . . . . . . . . . . . . .

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3 Typology on the individuals 3.1 Choice of the number of clusters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Simultaneous comparison of the clusters with respect with the most relevant variables 3.2.1 Number of individuals by cluster for the variable Products.not.satisfying . 3.2.2 Number of individuals by cluster for the variable Global.appreciation . . . 3.2.3 Number of individuals by cluster for the variable Products.appreciation . . 3.2.4 Number of individuals by cluster for the variable Image . . . . . . . . . . . 3.2.5 Number of individuals by cluster for the variable Kind.of.consumer . . . . 3.2.6 Number of individuals by cluster for the variable Would.be.missed.if.gone . 3.2.7 Number of individuals by cluster for the variable Good.value.for.money . . 3.2.8 Number of individuals by cluster for the variable Pleasure . . . . . . . . . 3.2.9 Number of individuals by cluster for the variable Poor.nutritionnal.quality 3.2.10 Number of individuals by cluster for the variable Consume.chips.potatoes . 3.3 Automatic description of each cluster . . . . . . . . . . . . . . . . . . . . . . . . . .

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List of Figures 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Representations of the individuals and of the categories on axes 1 and 2 . . . . . . Representation of the individuals using density curbs and enhanced representation of the categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of clusters chosen by the analyst; representation of the individuals according to their cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Centers of gravity with confidence ellipses; representation of the individuals according to their cluster with density curbs . . . . . . . . . . . . . . . . . . . . . . . . . Number of individuals per cluster . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Products.not.satisfying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Global.appreciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Products.appreciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Kind.of.consumer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Would.be.missed.if.gone . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Good.value.for.money . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Pleasure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Variable Poor.nutritionnal.quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

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Variable Consume.chips.potatoes . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1

Quick overview of the questionnaire

The analysis was performed on 166 individuals described by 20 variables: •

Image ( very bad , bad , normal , good , very good )

•

Expensive ( not expensive , a little expensive , average , quite expensive , very expensive )

•

Good.value.for.money ( very bad , bad , average , good , very good )

•

Kind.of.consumer ( very bad , bad , normal , good , very good )

•

Not.balanced.meals ( not balanced , badly balanced , average , quite well balanced , well balanced )

•

Products.appreciation ( not at all , not much , average , quite a lot , enormously )

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Not.enough.to.eat ( disagree , slightly disagree , agree , slightly agree , agree )

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Poor.nutritionnal.quality ( disagree , slightly disagree , neither agree nor disagree , slightly agree , agree )

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Pleasure ( no pleasure , sure , great pleasure )

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Fast.food.pollute ( disagree , slightly disagree , agree , slightly agree , agree )

•

not much pleasure ,

neither agree nor dis-

average ,

quite a lot plea-

neither agree nor dis-

Convivial ( not convivial , not much convivial , average , quite convivial , very convivial )

•

Practical ( not much practical , average , quite practical , very practical )

•

Pleasant.side ( nothing pleasant , few pleasant things , average , some pleasant things , a lot of pleasant things )

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Not.varied.enough ( disagree , slightly disagree , agree , slightly agree , agree )

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Adapted.to.everybody ( disagree , slightly disagree , neither agree nor disagree , slightly agree , agree )

•

Would.be.missed.if.gone ( not at all , not much , average , quite a lot , enormously )

•

Feel.bad.about.oneself ( not at all , a little , average , not much )

•

Diet.after.fastfood ( never , rarely , sometimes , often , always )

• •

neither agree nor dis-

Products.not.satisfying ( disagree , slightly disagree , neither agree nor disagree , slightly agree , agree ) Cheaper.meal ( disagree , slightly disagree , neither agree nor disagree , slightly agree , agree )

Moreover, the dataset contained 0% of missing values.

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2

Multivariate exploration of the questionnaire

2.1

Graphical representations of the questionnaire

The following results are obtained by performing a Multiple Correspondence Analysis (MCA) on the previous 20 variables. This method provides two important graphical displays, a representation of the individuals (surveyed people) and a representation of the categories (answers given by the surveyed people). The first two main axes of variability explain 10.77% of the information contained in the dataset (6.58% for the first factorial axis and 4.19% for the second one). In some cases the analyst may want to introduce supplementary quantitative variables.

MCA factor map

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MCA factor map

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With.friends_No Consume.fruits_Yes

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Products.appreciation_not much more than 11 Euros Products.not.satisfying_slightly agree Cheaper.meal_neither agree nor disagree Consume.chips.potatoes_No Not.balanced.meals_average Not.enough.to.eat_neither agree nor disagree Image_good Poor.nutritionnal.quality_slightly disagree Pleasure_not much pleasure Fastfood.at.night_Yes Would.be.missed.if.gone_enormously Would.be.missed.if.gone_quite a Cheaper.meal_disagree lot rarely Adapted.to.everybody_agree Kind.of.consumer_good Quick Kind.of.consumer_very Would.be.missed.if.gone_not at allbad Good.value.for.money_good satisfying Feel.bad.about.oneself_a Pleasant.side_average Expensive_quite expensive little neverConvivial_average Feel.bad.about.oneself_not much Not.varied.enough_disagree not satisfying Fast.food.pollute_slightly agree Fastfood.in.the.evening_No Practical_very Pleasant.side_few pleasant things Adapted.to.everybody_slightly disagree Agglomeration between 8practical and 11 Euros Consume.salads_Yes Not.varied.enough_slightly agree Poor.nutritionnal.quality_agree Consume.fizzy.drinks_Yes Convivial_very convivial M Regular.sport.practice_Yes less than 5 Euros Consume.ice.cream_Yes Alone_Yes Adapted.to.everybody_slightly agree Country Couple_No Consume.light.fizzy.drinks_No Good.value.for.money_bad Consume.nuggets_No Convivial_quite convivial Adapted.to.everybody_neither agree nor disagree With.family_Yes Week−end Consume.water_No On the premises Consume.dessert_No Expensive_average With.friends_Yes Fastfood.at.midday_No Fastfood.in.the.afternoon_No Consume.fruit.juice_No Consume.fruits_No Fastfood.in.the.morning_No Products.not.satisfying_slightly disagree Consume.hamburger_Yes Consume.hamburger_No Alone_No With.family_No Fastfood.at.midday_Yes Consume.salads_No Fastfood.in.the.evening_Yes Fast.food.pollute_slightly disagree Fastfood.at.night_No Poor.nutritionnal.quality_neither agree nor disagree Fast.food.pollute_agree Not.varied.enough_neither agree nor disagree F disagree Consume.chips.potatoes_Yes between 5Take−away and 8 Euros Consume.fruit.juice_Yes Not.varied.enough_slightly Not.enough.to.eat_disagree Pleasure_quite aMc lotDonald's pleasure Expensive_very expensive ● always City Feel.bad.about.oneself_not at all Not.enough.to.eat_slightly disagree Regular.sport.practice_No Image_bad Consume.ice.cream_No Consume.water_Yes Products.appreciation_quite aWeek lotbalanced balanced Not.balanced.meals_not Not.balanced.meals_badly Kind.of.consumer_normal Couple_Yes Consume.dessert_Yes Consume.fizzy.drinks_No Consume.nuggets_Yes Fast.food.pollute_neither agree nor disagree Convivial_not much convivial Not.enough.to.eat_slightly agree Consume.light.fizzy.drinks_Yes sometimes Expensive_a little expensive Pleasant.side_some pleasant things Would.be.missed.if.gone_average Poor.nutritionnal.quality_slightly Image_normal Kind.of.consumer_bad Cheaper.meal_slightly disagree agree Practical_quite practical often Good.value.for.money_average normal satisfying Products.not.satisfying_neither agree nor disagree Fastfood.in.the.morning_Yes Pleasure_average Cheaper.meal_slightly agree Pleasant.side_nothing pleasant Feel.bad.about.oneself_average

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Figure 1: Representations of the individuals and of the categories on axes 1 and 2

Density curbs

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MCA factor map

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Good.value.for.money_very bad Products.appreciation_enormously Pleasure_great pleasure Practical_average Products.not.satisfying_disagree Products.appreciation_notagree much Products.not.satisfying_slightly Cheaper.meal_neither agree Consume.chips.potatoes_No nor disagree agree nor disagree Not.balanced.meals_average Not.enough.to.eat_neither Image_good Pleasure_not much pleasure Fastfood.at.night_Yes Would.be.missed.if.gone_quite a lot Kind.of.consumer_good Cheaper.meal_disagree Kind.of.consumer_very bad Would.be.missed.if.gone_not at all Good.value.for.money_good satisfying Expensive_quite expensive Feel.bad.about.oneself_a little not satisfying Feel.bad.about.oneself_not much Not.varied.enough_disagree Pleasant.side_few pleasant things Consume.salads_Yes Poor.nutritionnal.quality_agree Consume.fizzy.drinks_Yes Adapted.to.everybody_slightly agree Couple_No Consume.light.fizzy.drinks_No Convivial_quite convivial With.family_Yes With.friends_Yes Products.not.satisfying_slightly disagree With.family_No Consume.salads_No Fastfood.at.night_No Poor.nutritionnal.quality_neither agree nor disagree Consume.chips.potatoes_Yes Not.enough.to.eat_disagree Pleasure_quite a lot pleasure ● Image_bad Products.appreciation_quite a lot Couple_Yes Consume.fizzy.drinks_No Convivial_not much convivial Consume.light.fizzy.drinks_Yes Poor.nutritionnal.quality_slightly Image_normal Kind.of.consumer_bad Cheaper.meal_slightly disagree agree Practical_quite oftenpractical Good.value.for.money_average normal satisfying Products.not.satisfying_neither Pleasure_average Cheaper.meal_slightly agree agree nor disagree Feel.bad.about.oneself_average Products.appreciation_average Would.be.missed.if.gone_not much Convivial_not convivial Adapted.to.everybody_disagree

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Figure 2: Representation of the individuals using density curbs and enhanced representation of the categories

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2.2 2.2.1

Highlights on the two principal axes of variability Characterization of the first factorial axis

The most meaningful variables characterizing the first factorial axis are: •

Image

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Products.appreciation

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Products.not.satisfying

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Pleasure

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Kind.of.consumer

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Good.value.for.money

•

Would.be.missed.if.gone

•

Convivial

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Not.balanced.meals

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Not.varied.enough

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Poor.nutritionnal.quality

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Not.enough.to.eat

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Practical

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Adapted.to.everybody

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Fast.food.pollute

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Pleasant.side

•

Feel.bad.about.oneself

The most meaningful categories characterizing the positive side of the first axis are: •

Image_very bad – Contribution: 6.62 – V-Test: 7.73 – Frequency in the population: 6.02 %

•

Kind.of.consumer_very bad – Contribution: 5.8 – V-Test: 7.89 – Frequency in the population: 21.08 %

•

Products.not.satisfying_agree – Contribution: 3.61 – V-Test: 5.56 – Frequency in the population: 1.2 %

•

Would.be.missed.if.gone_not at all – Contribution: 3.75 – V-Test: 6.5 5

– Frequency in the population: 24.7 % •

Good.value.for.money_very bad – Contribution: 4.19 – V-Test: 6.14 – Frequency in the population: 6.02 %

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Pleasure_no pleasure – Contribution: 4.01 – V-Test: 5.93 – Frequency in the population: 3.61 %

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Products.appreciation_not much – Contribution: 6.62 – V-Test: 8.02 – Frequency in the population: 12.65 %

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Products.appreciation_not at all – Contribution: 2.03 – V-Test: 4.18 – Frequency in the population: 1.2 %

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Not.balanced.meals_well balanced – Contribution: 1.96 – V-Test: 4.09 – Frequency in the population: 0.6 %

•

Image_bad – Contribution: 1.78 – V-Test: 4.58 – Frequency in the population: 28.31 %

The most meaningful categories characterizing the negative side of the first axis are: •

Products.not.satisfying_slightly disagree – Contribution: 2.01 – V-Test: -5.4 – Frequency in the population: 41.57 %

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Products.not.satisfying_disagree – Contribution: 1.21 – V-Test: -3.38 – Frequency in the population: 10.24 %

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Products.appreciation_quite a lot – Contribution: 1.33 – V-Test: -4.84 – Frequency in the population: 51.81 %

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Products.appreciation_enormously 6

– Contribution: 1.88 – V-Test: -4.29 – Frequency in the population: 13.25 % •

Pleasure_quite a lot pleasure – Contribution: 1.27 – V-Test: -4.67 – Frequency in the population: 50.6 %

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Image_good – Contribution: 3.17 – V-Test: -5.69 – Frequency in the population: 16.87 %

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Pleasure_great pleasure – Contribution: 0.95 – V-Test: -3.01 – Frequency in the population: 11.45 %

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Image_very good – Contribution: 0.94 – V-Test: -2.85 – Frequency in the population: 1.81 %

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Kind.of.consumer_good – Contribution: 2.73 – V-Test: -5.31 – Frequency in the population: 18.07 %

•

Convivial_quite convivial – Contribution: 1.69 – V-Test: -4.66 – Frequency in the population: 34.34 %

2.2.2

Characterization on the second factorial axis

The most meaningful variables characterizing the second factorial axis are: •

Products.not.satisfying

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Products.appreciation

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Image

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Pleasure

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Good.value.for.money

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Kind.of.consumer

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Would.be.missed.if.gone

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Not.balanced.meals

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Practical 7

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Cheaper.meal

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Adapted.to.everybody

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Pleasant.side

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Not.enough.to.eat

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Diet.after.fastfood

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Feel.bad.about.oneself

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Expensive

The most meaningful categories characterizing the positive side of the second axis are: •

Products.not.satisfying_agree – Contribution: 6.98 – V-Test: 6.17 – Frequency in the population: 1.2 %

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Image_very good – Contribution: 5.19 – V-Test: 5.34 – Frequency in the population: 1.81 %

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Not.balanced.meals_well balanced – Contribution: 4.23 – V-Test: 4.79 – Frequency in the population: 0.6 %

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Kind.of.consumer_very good – Contribution: 2.78 – V-Test: 3.91 – Frequency in the population: 1.81 %

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Good.value.for.money_very good – Contribution: 3 – V-Test: 4.04 – Frequency in the population: 1.2 %

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Would.be.missed.if.gone_enormously – Contribution: 1.68 – V-Test: 3.1 – Frequency in the population: 6.02 %

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Practical_average – Contribution: 1.76 – V-Test: 3.26 – Frequency in the population: 10.84 %

•

Products.appreciation_not at all 8

– Contribution: 1.64 – V-Test: 2.99 – Frequency in the population: 1.2 % •

Pleasant.side_a lot of pleasant things – Contribution: 1.48 – V-Test: 2.85 – Frequency in the population: 1.81 %

•

Pleasure_great pleasure – Contribution: 3.72 – V-Test: 4.76 – Frequency in the population: 11.45 %

The most meaningful categories characterizing the negative side of the second axis are: •

Products.not.satisfying_neither agree nor disagree – Contribution: 2.76 – V-Test: -4.9 – Frequency in the population: 37.95 %

•

Image_bad – Contribution: 1.44 – V-Test: -3.29 – Frequency in the population: 28.31 %

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Products.appreciation_average – Contribution: 3.72 – V-Test: -5.04 – Frequency in the population: 21.08 %

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Image_normal – Contribution: 0.63 – V-Test: -2.54 – Frequency in the population: 46.99 %

•

Products.not.satisfying_slightly disagree – Contribution: 0.03 – V-Test: -0.51 – Frequency in the population: 41.57 %

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Pleasure_average – Contribution: 2.13 – V-Test: -3.93 – Frequency in the population: 25.9 %

•

Good.value.for.money_average – Contribution: 0.79 9

– V-Test: -2.64 – Frequency in the population: 38.55 % •

Good.value.for.money_bad – Contribution: 0.4 – V-Test: -1.79 – Frequency in the population: 32.53 %

•

Products.appreciation_quite a lot – Contribution: 0.53 – V-Test: -2.43 – Frequency in the population: 51.81 %

•

Kind.of.consumer_bad – Contribution: 1.46 – V-Test: -3.28 – Frequency in the population: 27.11 %

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3

Typology on the individuals

3.1

Choice of the number of clusters

The ascendant hierarchical clustering (AHC) lead to a partition made of 3 clusters. Those clusters are displayed in the following representations: a graphical representation of the individuals according to the cluster they belong to, a representation of the center of gravity of each group enhanced by a confidence ellipse, a representation of the individuals according to the cluster they belong to by the use of density curbs.

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Choice of the number of clusters by cutting the dendrogram

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10 ● 2 ● 7 124 ● 69 ● 8 ● 42133 41 ● 104 31 ● ● ●4678 79 ●1443 66 ●● 44 ● 72 139 ● 29 ● 25 67 120 ● ● 165 50 ● ● 24 74 ●37 ● ● ● 92 ● 6166 150 ● ●● ● ● 152 19 68 ● 98 ● 21 ● ● 12 ● ● 108 ● 15 ● 91 ● ●30 109 153 ● 36 ● ● ● 138 ● 64 ● 115 ● 54 ● ● ● 163 48 106 141 155 137 110140 ● 34 ● 100 101 ●● ● ● 83 ● 162 ● 63 ● 28 ● 157 ● ● 76 134 ● 56 158 ● 107 33 ● 18 ● ● 75●●● 16 143 70 9 ●●129 ● ● 71 103 ● 128 61 27 ● 160 87121 ● ● 20 145 ●● 4 112 32 ● 113 151 ● ● 2288147 ● 6255●● ● 39 ●122 ● ● ● ● ● 127 ● ●●● ● ● 94 ● ● 130 96 ● 90 53 51 ● ● 77 154 ● ● 161 ● ● 95 135 118 ●114●●● 60 ● 80 ● 23 73 ● 59 102 11 89 26 ● 65 146 ●● 148 ● ● ● 99 ● ● ● ● ● ● 117● ● 126 ● 49 93 125 142 84 116 ● ●● ● ● ● 38 149 ● ● ● ● ● 119 8557 17 58 105 ● ● ● 45 ● ●

86 131 52 97 136 82 100 159 13 81 115 104 123 21 34 83 89 10 132 4 155 54 18 94 103 39 50 76 163 99 116 142 40 119 102 125 45 148 49 60 93 51 85 149 22 105 53 84 56 38 134 137 146 91 129 95 112 71 121 48 87 23 130 7 43 88 138 80 161 16 25 26 153 92 96 32 36 15 28 17 110 114 144 151 58 73 157 75 128 158 31 66 1 101 5 164 61 65 107 59 162 106 135 57 147 139 33 127 6 19 2 12 30 166 3 64 24 156 69 160 9 98 113 141 29 42 77 117 154 62 63 118 41 74 150 79 165 37 140 14 122 46 124 35 44 111 47 133 68 70 78 108 8 67 120 90 20 55 72 109 152 11 126 145 27 143

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Figure 3: Number of clusters chosen by the analyst; representation of the individuals according to their cluster

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Figure 4: Centers of gravity with confidence ellipses; representation of the individuals according to their cluster with density curbs

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Figure 5: Number of individuals per cluster

12

3.2 3.2.1

Simultaneous comparison of the clusters with respect with the most relevant variables Number of individuals by cluster for the variable Products.not.satisfying

Products.not.satisfying by cluster

70

1st bar: Products.not.satisfying_disagree 2nd bar: Products.not.satisfying_neither agree nor disagree 3rd bar: Products.not.satisfying_slightly agree 4 th bar: Products.not.satisfying_slightly disagree

60

50

40

30

20

10

0 group 1

group 2

group 3

Figure 6: Variable Products.not.satisfying

13

3.2.2

Number of individuals by cluster for the variable Global.appreciation

Global.appreciation by cluster 80

1st bar: normal satisfying 2nd bar: not satisfying 3rd bar: not satisfying at all 4 th bar: satisfying 5 th bar: very satisfying

60

40

20

0 group 1

group 2

Figure 7: Variable Global.appreciation

14

group 3

3.2.3

Number of individuals by cluster for the variable Products.appreciation

Products.appreciation by cluster 80

1st bar: Products.appreciation_average 2nd bar: Products.appreciation_enormously 3rd bar: Products.appreciation_not much 4 th bar: Products.appreciation_quite a lot

60

40

20

0 group 1

group 2

group 3

Figure 8: Variable Products.appreciation

15

3.2.4

Number of individuals by cluster for the variable Image

Image by cluster

1st bar: Image_bad 2nd bar: Image_good 3rd bar: Image_normal 4 th bar: Image_very bad 60

40

20

0 group 1

group 2

Figure 9: Variable Image

16

group 3

3.2.5

Number of individuals by cluster for the variable Kind.of.consumer

Kind.of.consumer by cluster

1st bar: Kind.of.consumer_bad 2nd bar: Kind.of.consumer_good 3rd bar: Kind.of.consumer_normal 4 th bar: Kind.of.consumer_very bad

60

50

40

30

20

10

0 group 1

group 2

Figure 10: Variable Kind.of.consumer

17

group 3

3.2.6

Number of individuals by cluster for the variable Would.be.missed.if.gone

Would.be.missed.if.gone by cluster 70 1st bar: Would.be.missed.if.gone_not at all 2nd bar: Would.be.missed.if.gone_not much 3rd bar: Would.be.missed.if.gone_average 4 th bar: Would.be.missed.if.gone_quite a lot 5 th bar: Would.be.missed.if.gone_enormously

60

50

40

30

20

10

0 group 1

group 2

group 3

Figure 11: Variable Would.be.missed.if.gone

18

3.2.7

Number of individuals by cluster for the variable Good.value.for.money

Good.value.for.money by cluster

1st bar: Good.value.for.money_average 2nd bar: Good.value.for.money_bad 3rd bar: Good.value.for.money_good 4 th bar: Good.value.for.money_very bad

60

50

40

30

20

10

0 group 1

group 2

group 3

Figure 12: Variable Good.value.for.money

19

3.2.8

Number of individuals by cluster for the variable Pleasure

Pleasure by cluster 80

1st bar: Pleasure_average 2nd bar: Pleasure_great pleasure 3rd bar: Pleasure_not much pleasure 4 th bar: Pleasure_quite a lot pleasure

60

40

20

0 group 1

group 2

Figure 13: Variable Pleasure

20

group 3

3.2.9

Number of individuals by cluster for the variable Poor.nutritionnal.quality

Poor.nutritionnal.quality by cluster

60

1st bar: Poor.nutritionnal.quality_agree 2nd bar: Poor.nutritionnal.quality_neither agree nor disagree 3rd bar: Poor.nutritionnal.quality_slightly agree 4 th bar: Poor.nutritionnal.quality_slightly disagree

50

40

30

20

10

0 group 1

group 2

group 3

Figure 14: Variable Poor.nutritionnal.quality

21

3.2.10

Number of individuals by cluster for the variable Consume.chips.potatoes

Consume.chips.potatoes by cluster

1st bar: Consume.chips.potatoes_No 2nd bar: Consume.chips.potatoes_Yes 80

60

40

20

0 group 1

group 2

group 3

Figure 15: Variable Consume.chips.potatoes

22

3.3

Automatic description of each cluster

The cluster 1 (87 individuals) includes the individuals possessing the following categories: •

Global.appreciation= satisfying 34.34 % of the individuals possess this category in the global population versus 55.17 % in the cluster 1 . Moreover, 84.21 % of the individuals possessing this category belong to the cluster 1 .

•

Image=Image_good 17.47 % of the individuals possess this category in the global population versus 29.89 % in the cluster 1 . Moreover, 89.66 % of the individuals possessing this category belong to the cluster 1 .

•

Kind.of.consumer=Kind.of.consumer_good 18.67 % of the individuals possess this category in the global population versus 31.03 % in the cluster 1 . Moreover, 87.1 % of the individuals possessing this category belong to the cluster 1 .

•

Would.be.missed.if.gone=Would.be.missed.if.gone_quite a lot 27.11 % of the individuals possess this category in the global population versus 41.38 % in the cluster 1 . Moreover, 80 % of the individuals possessing this category belong to the cluster 1 .

•

Poor.nutritionnal.quality=Poor.nutritionnal.quality_neither agree nor disagree 28.92 % of the individuals possess this category in the global population versus 41.38 % in the cluster 1 . Moreover, 75 % of the individuals possessing this category belong to the cluster 1 .

•

Products.not.satisfying=Products.not.satisfying_slightly disagree 42.77 % of the individuals possess this category in the global population versus 56.32 % in the cluster 1 . Moreover, 69.01 % of the individuals possessing this category belong to the cluster 1 .

•

Good.value.for.money=Good.value.for.money_good 21.69 % of the individuals possess this category in the global population versus 32.18 % in the cluster 1 . Moreover, 77.78 % of the individuals possessing this category belong to the cluster 1 .

•

Pleasure=Pleasure_quite a lot pleasure 51.81 % of the individuals possess this category in the global population versus 64.37 % in the cluster 1 . Moreover, 65.12 % of the individuals possessing this category belong to the cluster 1 .

•

Convivial=Convivial_quite convivial 34.34 % of the individuals possess this category in the global population versus 45.98 % in the cluster 1 . Moreover, 70.18 % of the individuals possessing this category belong to the cluster 1 .

•

Adapted.to.everybody=Adapted.to.everybody_slightly agree 24.1 % of the individuals possess this category in the global population versus 34.48 % in the cluster 1 . Moreover, 75 % of the individuals possessing this category belong to the cluster 1 . 23

The cluster 2 (60 individuals) includes the individuals possessing the following categories: •

Products.not.satisfying=Products.not.satisfying_neither agree nor disagree 37.95 % of the individuals possess this category in the global population versus 66.67 % in the cluster 2 . Moreover, 63.49 % of the individuals possessing this category belong to the cluster 2 .

•

Would.be.missed.if.gone=Would.be.missed.if.gone_not much 22.29 % of the individuals possess this category in the global population versus 45 % in the cluster 2 . Moreover, 72.97 % of the individuals possessing this category belong to the cluster 2 .

•

Image=Image_bad 29.52 % of the individuals possess this category in the global population versus 50 % in the cluster 2 . Moreover, 61.22 % of the individuals possessing this category belong to the cluster 2 .

•

Cheaper.meal=Cheaper.meal_slightly disagree 36.75 % of the individuals possess this category in the global population versus 55 % in the cluster 2 . Moreover, 54.1 % of the individuals possessing this category belong to the cluster 2 .

•

Expensive=Expensive_very expensive 6.02 % of the individuals possess this category in the global population versus 15 % in the cluster 2 . Moreover, 90 % of the individuals possessing this category belong to the cluster 2 .

•

Products.appreciation=Products.appreciation_average 21.69 % of the individuals possess this category in the global population versus 36.67 % in the cluster 2 . Moreover, 61.11 % of the individuals possessing this category belong to the cluster 2 .

•

Global.appreciation= normal satisfying 46.39 % of the individuals possess this category in the global population versus 63.33 % in the cluster 2 . Moreover, 49.35 % of the individuals possessing this category belong to the cluster 2 .

•

Adapted.to.everybody=Adapted.to.everybody_disagree 15.66 % of the individuals possess this category in the global population versus 28.33 % in the cluster 2 . Moreover, 65.38 % of the individuals possessing this category belong to the cluster 2 .

•

Kind.of.consumer=Kind.of.consumer_bad 27.71 % of the individuals possess this category in the global population versus 41.67 % in the cluster 2 . Moreover, 54.35 % of the individuals possessing this category belong to the cluster 2 .

•

Pleasure=Pleasure_average 27.11 % of the individuals possess this category in the global population versus 40 % in the cluster 2 . Moreover, 53.33 % of the individuals possessing this category belong to the cluster 2 .

The cluster 3 (19 individuals) includes the individuals possessing the following categories: 24

•

Products.appreciation=Products.appreciation_not much 12.65 % of the individuals possess this category in the global population versus 73.68 % in the cluster 3 . Moreover, 66.67 % of the individuals possessing this category belong to the cluster 3 .

•

Products.not.satisfying=Products.not.satisfying_slightly agree 9.04 % of the individuals possess this category in the global population versus 63.16 % in the cluster 3 . Moreover, 80 % of the individuals possessing this category belong to the cluster 3 .

•

Kind.of.consumer=Kind.of.consumer_very bad 21.08 % of the individuals possess this category in the global population versus 84.21 % in the cluster 3 . Moreover, 45.71 % of the individuals possessing this category belong to the cluster 3 .

•

Would.be.missed.if.gone=Would.be.missed.if.gone_not at all 24.7 % of the individuals possess this category in the global population versus 78.95 % in the cluster 3 . Moreover, 36.59 % of the individuals possessing this category belong to the cluster 3 .

•

Image=Image_very bad 6.02 % of the individuals possess this category in the global population versus 42.11 % in the cluster 3 . Moreover, 80 % of the individuals possessing this category belong to the cluster 3 .

•

Global.appreciation= not satisfying at all 3.61 % of the individuals possess this category in the global population versus 31.58 % in the cluster 3 . Moreover, 100 % of the individuals possessing this category belong to the cluster 3 .

•

Pleasure=Pleasure_not much pleasure 9.04 % of the individuals possess this category in the global population versus 47.37 % in the cluster 3 . Moreover, 60 % of the individuals possessing this category belong to the cluster 3 .

•

Global.appreciation= not satisfying 15.06 % of the individuals possess this category in the global population versus 52.63 % in the cluster 3 . Moreover, 40 % of the individuals possessing this category belong to the cluster 3 .

•

Good.value.for.money=Good.value.for.money_very bad 6.02 % of the individuals possess this category in the global population versus 31.58 % in the cluster 3 . Moreover, 60 % of the individuals possessing this category belong to the cluster 3 .

•

Consume.chips.potatoes=Consume.chips.potatoes_No 7.83 % of the individuals possess this category in the global population versus 31.58 % in the cluster 3 . Moreover, 46.15 % of the individuals possessing this category belong to the cluster 3 .

25