MSc thesis - Marketing and Consumer Behaviour

Buying Moments & Mars brand 's:

impulse buying of chocolate bitesizes affected

by brands and situational goals.

Source: http://www.wipix.fr/portfolio/mms-tv-advert/?iframe=1

Iris Kempers Supervisor: dr.ir. Arnout Fischer Co-reader: dr. Erica van Herpen

MME, consumer studies Marketing and Consumer Behaviour

February 20, 2018

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Buying Moments & Mars brand 's: impulse buying of chocolate bitesizes affected by brands and

situational goals.

Author: Iris Kempers

Student number: 941112427060

Study programme: Master Management, Economics and Consumer studies

Specialisation: Consumer studies

Supervisor: dr.ir. Arnout Fischer

Co-reader: dr. Erica van Herpen

Chairgroup: Marketing and Consumer Behaviour (MCB)

Organisation: Wageningen University & Research

Thesis: MSc-Thesis (MCB-80433)

Research start: September 1, 2017

Completion date: February 20, 2018

E CTS: 33

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Preface

The thesis you are reading is written as part of the master Management, Economics and Consumer

studies of Wageningen University. I wrote my thesis at the chairgroup Marketing and Consumer

Behaviour. This thesis is written in collaboration with Mars the Netherlands.

The subject of this thesis was established through a combination of factors. Personally, I am very

interested in consumer categorisation processes as well as the retail environment. Psychology has

always been one of my major interests. Using psychology applied to consumer behaviour and the

actual retail environment is a more than interesting combination to me. Once Mars offered me the

possibility to write my MSc thesis about a combination of those subjects while using and touching up

elements of real-world retail settings, I became very enthusiastic about this great chance. I was very

happy that my supervisor dr. ir. Arnout Fischer could guide me in the thesis writing process. My

personal interest and a business opportunity for Mars thus brought me to the subject of the thesis.

The target group of this thesis consists of people interested in how consumer behaviour, and in

particular psychology, determines and explains the effectiveness of retail settings. The thesis is an

interesting read for marketing managers in e.g. category management on how to position their

products in relation to consumption moments and why this may (not) work. This applies in particular

to marketing or category managers of the Mars company, since their products are used.

I would like to take the chance to thank my supervisor dr. ir. Arnout Fischer. He deserves a big thank

you. He has supervised me in a very pleasant and positive way. His comments were always on point,

since for every meeting he prepared himself extensively. Thank you for your supportive guidance. I

have experienced the supervision as pleasant and informative. I would like to thank Gerdine Roubos,

MSc, for giving me the chance to write my thesis in collaboration with Mars the Netherlands. This

made my thesis writing much more lively. I would like to thank her for her guidance and her useful

insights. I would like to thank dr. Erica van Herpen for her feedback as second reader. I would like to

thank my friends, especially Lise van den Bosch for her support and our weekly thesis lunch which

always motivated me. I would like to thank my parents and my boyfriend for the moral support

during the whole writing process.

I wish you a lot of reading pleasure!

Iris Kempers

Wageningen, February 2018

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Abstract

Changing impulse buying behaviour induces marketeers to shift to in-store marketing based on consumption moments (Bellini, Cardinali & Grandi, 2017; Mars, 2017). Adequate knowledge is however missing. Scientific literature needs new studies on the effect of situational factors on impulse buying (Muruganantham & Bhakat, 2013). This study addresses both these practical and scientific knowledge gaps by analysing the effect of branded products (M&M's) and situational goals (TV evening) on (respectively pure/planned) chocolate bitesizes impulse buying. Categorisation was expected to link branded products and situational goals to a behavioural script and eventually to impulse buying. The study used an experimental 2 (branded product) x 2 (situational goal) between subjects factorial design based on a supermarket scenario setting. The results partially supported that the situational goal activated goal-derived categorisation, which complements previous research. Goal-derived categorisation did not activate a snacking behavioural script. The hypothesis that such a script results in impulse buying was partially supported. Branded product did not stimulate taxonomic categorisation based on an exemplar or primary and secondary categorisation. Impulsiveness as a personality trait stimulated the activation of a snacking behavioural script directly, goal-derived categorisation was not involved. The situational goal was more effective in stimulating chocolate bitesizes impulse buying than the branded product or the combination of both. Based on this study, marketing managers of chocolate bitesizes are advised to use the situational goal to stimulate planned impulse buying. These managers should acknowledge the relatively large share of crisps in the situational goal. Retailers are not advised to replace taxonomic departments by goal-derived departments.

Keywords: Impulse buying, situational goal, brand, goal-derived categorisation, behavioural script,

snacks, chocolate bitesizes

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Executive summary

This MSc thesis was written at the marketing and consumer behaviour chairgroup as a part of the

Management, Economics and Consumer studies educational program of Wageningen University. The

thesis was written with the support of Mars the Netherlands.

Recently, changing consumer impulse buying behaviour induces manufacturers and retailers to shift

their focus on marketing from creating awareness with traditional marketing levers (e.g. advertising)

to in-store marketing (Bellini et al., 2017) based on consumption moments in order to stimulate

impulse purchases (Mars, 2017). Knowledge is missing on how to construct this in-store marketing

effectively. Manufacturer Mars faces such a situation as well. This thesis aims to answer the question

of Mars whether and how consumption moments can be used in their marketing in combination with

the promotion of their brands to stimulate impulse purchases of chocolate bitesizes (M&M's). The

study aims to acquire insights which can help to create more effective in-store marketing and store

lay-outs to address today's changing impulse buying behaviour. In order to achieve this, the effects of

brands and consumption moments on impulse buying were analysed.

A conceptual framework was build based on a literature review. Consumption moments (referred to

as situational goals) were expected to activate goal-derived categorisation in consumer's mind.

Brands were expected to activate initially taxonomic categorisation and secondarily goal-derived

categorisation. Goal-derived categorisation was seen as intuitive process which activates a snacking

behavioural script and therefore impulse buying. The brand was expected to affect pure impulse

buying, as it disrupts the planned purchase plans. The consumption moment was expected to affect

planned impulse buying, as this moment induces the consumer to enter the supermarket with a not

completely specified intention to buy, the actual buying decision is made in the store (Stern, 1962).

The effects of the brand (M&M's) and consumption moment (TV evening) on impulse buying as well

as the conceptual framework were tested by means of an empirical study. An online study with an

experimental 2 (branded product) x 2 (situational goal) between subjects factorial design simulated a

supermarket scenario. Participants were given a shopping list. They saw depictions of several

supermarket shelves and could click on desired products in these shelves. The sample consisted of

226 Dutch women (178, 78.8%) and men of 18 years and older (median of 24 years). Most

participants (46%) were highly educated (HBO, WO bachelor). The variables of the conceptual

framework as well as characteristics and preferences of the participants were measured.

The data analyses of the empirical study showed that the consumption moment was more effective

in stimulating chocolate bitesizes, crisps and general impulse buying than the brand or a combination

of both. The effect of the consumption moment had a larger effect on crisps impulse buying than on

chocolate bitesizes impulse buying. Regarding the theoretical underpinning, there was partial

evidence that the consumption moment activated goal-derived categorisation. There was partial

evidence that the activation of a snacking behavioural script made impulse buying more likely. The

other hypotheses were not supported. The data-analyses controlled for age and gender. Younger

participants were more likely to purchase chocolate bitesizes impulsively and to have an activated

snacking behavioural script than older participants. Women were more likely to conduct a chocolate

bitesizes impulse purchase and more likely to have an activated snacking behavioural script than

men.

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The findings of this study have several managerial implications. In order to answer the question of

Mars, the results of the study show that the consumption moment (TV evening) is more effective in

stimulating chocolate bitesizes impulse buying than the brand. Marketing managers could use the

consumption moment to effectively increase the impulse purchases of chocolate bitesizes and in

particular M&M's. However, marketing managers should be aware of the relatively large share of

crisps in this consumption moment. Marketing managers therefore need to consider whether the use

of the consumption moment of the TV evening in their marketing is beneficial enough to increase

profit. These managers are hence advised to compare the share of chocolate bitesizes and crisps in

the consumption moment with the context of the total revenue of both products. Marketing

managers of M&M's are advised to examine how large the share of the TV evening consumption

moment is compared to all the chocolate bitesizes consumption moments. A consideration could be

that, because of the stronger association, the promotion of the consumption moment of the TV

evening benefits crisps sales more than M&M's sales. Furthermore, marketing managers at Mars

could consider to search for a consumption moment which is more exclusively related to M&M's in

order to create a more cost efficient promotion of M&M's.

The retail industry is not advised to replace taxonomic departments by goal-derived departments.

This applies in particular when the retailer focuses on consumers who search for a particular product.

The study has shown that most participants search chocolate bitesizes by means of taxonomic

categories. Consumers have in general more experience with taxonomic than goal-derived

departments. This means that consumers are more likely to search products based on traditional

taxonomic departments than based on consumption moments. Goal-derived departments can

nevertheless potentially be used as complement on the taxonomic departments in a store in order to

stimulate pure impulse buying. Pure impulse buying does not focus on planned purchase plans and

thus does not focus on consumer's searching process.

The aim of this study was to provide insights in how to create more efficient in-store marketing of

chocolate bitesizes in order to stimulate impulse buying. The findings of this thesis revealed that the

consumption moment (TV evening) is more effective in stimulating impulse buying than the brand.

Marketing managers at Mars are therefore advised to use the consumption moment in the

promotion of M&M's.

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Table of contents

Preface .................................................................................................................................................... iii

Abstract .................................................................................................................................................... v

Executive summary ................................................................................................................................. vi

List of tables and figures .......................................................................................................................... x

1 Introduction ......................................................................................................................................... 1

2 Theoretical framework ........................................................................................................................ 4

2.1 The activation of associative networks ......................................................................................... 4

2.2 Categorisation ............................................................................................................................... 8

2.3 Categorisation and impulse buying ............................................................................................. 12

3 Method ............................................................................................................................................... 17

3.1 Experimental design & manipulations ........................................................................................ 17

3.2 Participants .................................................................................................................................. 19

3.3 Measures ..................................................................................................................................... 20

3.4 Manipulation check ..................................................................................................................... 23

3.5 Procedure .................................................................................................................................... 23

3.6 Pilot .............................................................................................................................................. 23

3.7 Pre-test ........................................................................................................................................ 24

4 Results ................................................................................................................................................ 25

4.1 Reliability of scales ...................................................................................................................... 25

4.2 Defining variables ........................................................................................................................ 25

4.3 Relationship between measures of the same construct ............................................................. 26

4.4 Manipulation check ..................................................................................................................... 27

4.5 Tests on demographics and characteristics ................................................................................ 28

4.6 Main effect and interaction effect with selected covariates ...................................................... 31

4.7 Hypotheses testing ...................................................................................................................... 34

5 Discussion ........................................................................................................................................... 42

5.1 Main results ................................................................................................................................. 42

5.2 Limitations and directions for further research .......................................................................... 45

5.3 Theoretical implications .............................................................................................................. 47

5.4 Managerial/practical implications ............................................................................................... 48

References............................................................................................................................................. 50

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Appendix ............................................................................................................................................... 55

Appendix A. Flowchart. ..................................................................................................................... 55

Appendix B. Outcomes of the pre-test. ............................................................................................. 56

Appendix C. Materials used in the empirical study. .......................................................................... 58

Appendix D. Linear regressions third measure of categorisation. .................................................... 76

x

List of tables and figures

Table 1. Experimental design. .............................................................................................................. 18

Table 2. Participants per condition. ..................................................................................................... 20

Table 3. Cronbach's alpha per scale. .................................................................................................... 25

Table 4. Frequency of chosen intention equal to the situational goal per condition. ......................... 28

Table 5. Outcomes of the binary logistic regressions regarding the additional variables on the first

measure of impulse buying .................................................................................................................. 30

Table 6. Outcomes of the linear regression regarding the additional variables on the second measure

of impulse buying ................................................................................................................................. 31

Table 7. Outcomes of the binary logistic regressions regarding the independent variables, their

interaction effect and the covariates on the first measure of impulse buying. ................................... 32

Table 8. Outcomes of the linear regression regarding the independent variables, their interaction

effect and the covariates on the second measure of impulse buying. ................................................. 33

Table 9. Frequency of mentioned exemplar (M&M's vs. other) per level of branded product. .......... 35

Figure 1. Conceptual framework ............................................................................................................4

Figure 2. An example of context effects in conceptually driven processing. ..........................................5

Figure 3. Manipulation of branded product.. ....................................................................................... 17

Figure 4. Non-manipulated shelves of the supermarket scenario ...................................................... 19

Figure 5. Map of the hypothetical supermarket. ................................................................................. 21

Figure 6. Interaction effect of branded product and situational goal on CIS.. ..................................... 33

Figure 7. Frequency indicated department per condition. .................................................................. 36

Figure A.1. Flowchart of the procedure of the study. .......................................................................... 55

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1 Introduction

Consumers in today's western societies are constantly exposed to opportunities for impulse buying.

Impulse buying is defined as the sudden, often powerful and persistent urge a consumer experiences

to buy something immediately (Rook, 1987) and refers to unplanned buying behaviour (Hausman,

2000). Impulse buying is strongly present: 90% of the consumers conduct this behaviour (Mielach,

2012).

The ways consumers conduct impulse buying are changing recently through a.o. more preparation

activities of the consumer (Bellini, Cardinali & Grandi, 2017). During the last two decades,

manufacturers and retailers shifted their focus from creating awareness with traditional marketing

levers (e.g. advertising) to in-store marketing in order to stimulate impulse purchases (Bellini et al.,

2017). However, knowledge is missing on how to construct this in-store marketing effectively.

Likewise, a recent question for manufacturer Mars is whether and how consumption situations can

be used in in-store marketing in combination with the promotion of their brands to stimulate

impulse purchases of snacks. It is unknown how consumers will react and why.

Buying snack products is related to impulse buying for several reasons. Snack products, like a Mars

bar, are usually pleasurable to eat. The literature states that both snacking and impulse buying seem

to be driven by consumer's pursuit of hedonistic goals (Hausman, 2000; Verplanken, Herabadi, Perry

& Silvera, 2005). Moreover, the tendency to buy on impulse is strongly related to the habit of eating

snacks, because of similar driving forces related to self-esteem and affect. Impulse buying and

snacking are both behaviours that lead to short-term pleasure (Verplanken et al., 2005).

The current study focuses on a specific kind of snacks, namely chocolate bitesizes, for several

reasons. Chocolate is bought most impulsively out of all products in the supermarket as 55% of the

chocolate purchases is conducted impulsively (GFK, 2015). Chocolate is very recognisable to the

consumer, since 95.9% of the consumers buys chocolate (GFK, 2015). Chocolate is a part of

confectionery snacks and fulfils the need of sweet snacking. The category chocolate can be

segmented in candy bars, bitesizes, bars & tablets, season, specialities and children products (Mars,

2017). This study focuses on bitesizes (e.g. M&M's, Maltesers of Mars), because such a regular and

mainstream product provides the most applicable insights for the category of snacks. Consuming

bitesizes can originate from a wide range of goals (e.g. pleasure, hunger, sharing) and relates to the

impulse tendency because of their small size. Bitesizes have a share of 10.1 % in the category

chocolate (Nielsen, 2017).

The preference for snacks, and thus chocolate bitesizes, is influenced by the expected consumption

situation (Belk, 1974). A difference in the expected consumption situation implies the consumer to

have different goals. For instance, buying a snack for a party is different from hunger fulfilment after

sporting. Different situational goals imply that different associative networks in relation to the snack

are activated. Situational goals are defined here as suggested consumption situations for snacks.

Prior research has found that goals in general can influence consumer categorisation (Ratneshwar,

Barsalou, Pechmann & Moore, 2001). The congruence of consumer categorisation with the external

categorisation provided by the store influences purchase decisions (Morales, Kahn, McAlister &

Broniarczyk, 2005). Hence, it is relevant to know how the categorisation of in particular situational

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goals possibly affects impulse buying. More knowledge regarding the unclear relationship between

situational goals, associative networks and categorisation is needed in order to provide insights on

the effect of situational goals on impulse buying.

Besides situational goals, brands can activate associative networks as well. Associative networks are

known to give insights in the equity that a consumer attaches to a brand (Krishnan, 1996; Cheng-Hsui

Chen, 2001; Henderson, Iacobucci & Calder, 1998), since the perceptions about a brand are reflected

in the associative network (Keller, 1993; Ariely, 2000). Brand preference positively affects purchase

intentions of snacks (Wang, 2010). This means that there is a difference between branded and non-

branded products and their relation to the purchase intention of snacks.

Situational goals and brands presumably affect different kinds of impulse buying. Seeing a branded

product affects pure impulse buying, as the confrontation with the product breaks the planned

purchased plans (Stern, 1962). A situational goal is likely to affect planned impulse buying. The

situational goal causes the consumer to enter the supermarket with a general intention to buy and

the choice of the product depends on the offer of the supermarket. The actual buying decision is

made at the point of purchase (Stern, 1962).

Previous research points out that studies on the effect of situational factors on impulse buying are

needed in order to understand its complex nature better (Muruganantham & Bhakat, 2013). This

highlights the scientific relevance of the present study. This study sheds new light on the effect of

situational effects on impulse buying by combing the influence of branded products and situational

goals which refer to different ways of processing. The categorisation process activated by branded

products and situational goals is instrumental for this understanding, as congruent consumer and

external categorisation stimulate purchasing (Morales et al., 2005), but has not been studied yet.

Therefore, the relation between brands, situational goals, associative networks and categorisation

remains unclear, resulting in a first knowledge gap. The second knowledge gap addressed is how

categorisation affects impulse buying. In order to understand the effect of the situational factors on

impulse buying, it is important to know whether either situational goals or branded products

influence impulse buying more effectively, resulting in the third knowledge gap.

Understanding the link between the categorisation of branded products and situational goals and

impulse buying will help to comprehend how different kinds of impulse buying are influenced by

different kinds of categorisation. Hence, by closing the three knowledge gaps this study provides an

opportunity to advance the scientific understanding of impulse buying. In order to reach this aim,

one overarching research question has been identified, along with three sub questions. The numbers

of the sub questions correspond to the mentioned knowledge gaps.

How do situational goals and branded products affect impulse buying in the domain of chocolate

bitesizes?

1. How do branded products and situational goals activate associative networks and therefore

categorisation towards a snack?

2. How does categorisation affect impulse buying?

3. Is promoting situational goals more effective in stimulating impulse buying than promoting a

brand?

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The societal relevance of this study concerns the purpose of acquiring insights which can help to

create more efficient in-store marketing and store lay-outs to address today's changing impulse

buying behaviour. This will result in recommendations for the retail and snacking industry. These

insights are essential in order to keep selling snacks in a profitable way and hence to ensure the

continued existence of the industry. As this thesis is written with the support of Mars the

Netherlands, the term branded product refers to M&M's as being one of the most successful brands

of Mars and present in the category bitesizes. The managerial relevance of this study is reflected in

the recommendations regarding the in-store marketing based on situational goals and branded

products. The question is whether Mars should use situational goals or the brand. These

recommendations will focus on the most effective way to stimulate the purchases of the Mars

chocolate bitesizes in order to stimulate profit in today's world.

This study starts with a theoretical framework concerning associative networks, categorisation and

the relationship towards impulse buying. In the following chapter the operationalisation and

methodology are explained. This is followed by an overview of the results. The last chapter concerns

a discussion of the findings, critical notes to this study and recommendations for further research.

The study is ended with implications of the findings.

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2 Theoretical framework

This chapter serves to explain how consumer behaviour can link branded products and situational

goals to impulse buying. In order to understand the behavioural process underlying the conceptual

framework (Figure 1), the chapter starts with understanding the activation of associative networks.

Different types of categorisation are explained. Sections 2.1 and 2.2 refer to how brands and

situational goals activate associative networks and categorisation (sub question 1). In section 2.3, a

construct linking categorisation to impulse buying is explained (sub question 2). A short overview of

the theoretical framework can be found in Figure 1.

Figure 1. Conceptual framework.

The combination of the concepts branded product and situational goal as independent variables in

the conceptual framework is relevant for several reasons. Today, changing consumer impulse buying

behaviour induces a new focus on in-store marketing based on consumption moments (Bellini et al.,

2017; Mars, 2017). Such in-store marketing makes use of both a branded product and a situational

goal, but knowledge of those effects on impulse buying is missing. Branded product and situational

goal can be presented as promotion material, which enables to study the effect of the independent

variables in the retail setting. The independent variables refer to different ways of processing and

hence to different organisations of the retail environment. Branded product appeals to taxonomic

categories. Situational goal requires imagination of the consumer and appeals to goal-derived

categories. For the retail sector it is relevant to know whether taxonomic or goal-derived categories

are dominant in consumer's mind, as purchases depend on the congruence of consumer

categorisation with the external product organisation of a store (Morales et al., 2005). Scientifically,

the combination of the independent variables allows to contribute to the incomplete and wanting

knowledge of situational effects on impulse buying (Muruganantham & Bhakat, 2013). These

particular independent variables enable to examine the influence of situational factors which appeal

to different ways of processing.

2.1 The activation of associative networks

The assumption in this study is that brands and situational goals can activate associative networks.

Associative networks are needed in order to conduct the process of categorisation. In order to

understand this assumption, a theoretical underpinning is provided. This underpinning starts with

how information processing allows the activation of associative networks.

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2.1.1 Routes of information processing

Consumers can process the incoming information via two routes in order to keep this processing

manageable and useful. Using these routes, consumers can process information either bottom-up or

top-down. This determines the depth with which the incoming information is analysed, ranging from

processing of sensory features to semantic and conceptual processing (Colman, 2002). Both routes

classify the information into useful concepts and attach meaning to the information, which makes

inference making possible (Goldstein, 2007).

Bottom-up information processing focuses on the physical features of a product, which create

sensory stimuli. The sensations result in perceptions due to belief formation. Afterwards, preference

formation results in (dis)liking of the product (Goldstein, 2007; Krishna, 2012). Such a preference or

positive attitude plays an important role in whether behaviour is actually conducted, according to the

theory of planned behaviour (Ajzen, 1991). This type of information processing makes use of the

sensory memory. This memory is a short-term memory for information being processed by the

senses (Colman, 2002).

As this study focuses on branded products and situational goals, top-down information processing is

more relevant, since it focuses on the use of long-term human memory. Following this route, the

consumer forms a hypothesis about what an object might be on the basis of the existing prior

experience, influenced by existing beliefs, expectations and cognitions. This means that consumers

form their perceptions starting with a larger object, idea or concept before working to the more

detailed information. Therefore, top-down processing is also known as conceptually driven

processing (Colman, 2002). Hereafter, top-down processing is referred to as conceptually driven

processing. Conceptually driven processing makes use of semantic memory, which is a long-term

memory. Semantic memory stores information about the world and is necessary for the use of

language (Colman, 2002). Relevant for this study is that the concepts in conceptually driven

processing can also be brands and situational goals.

Conceptually driven processing can be useful for recognising patterns in our environment and hence

enables classification and inference making. However, the use of the existing concepts in the brain

can hinder the ability to perceive things in different ways. An example of this can be found in Figure

2, used by Neisser (1967).

Figure 2. An example of context effects in conceptually driven processing. Source: http://www.psywww.com/gst/top-down-bottom-up.html Usually, the same component is first interpreted as an H, then as an A. The knowledge of words (the

and cat) guides the interpretation of individual letters, because of conceptually driven processing.

Hence, the context effect of words plays an important role here. The same mechanism could apply

for situational goals. Different contexts, because of different situational goals, guide different

interpretations by conceptually driven processing. This translates to consumer products as well.

Depending on the context or situational goal, consumers may interpret products in different ways.

6

For instance, in the morning with a cup of coffee, the consumer reads the newspaper. The consumer

interprets the newspaper as reading material. When packing fragile objects during a move, the

consumers uses the same newspaper as wrapping material. Another example is about being

confronted with a tomato in the kitchen or during a political protest. In the first case the consumer

interprets the tomato as being food, in the second case as a protest object. This demonstrates the

influence of context on attaching meaning to objects.

2.1.2 Associative networks

In order to interpret and attach meaning to the context, consumer's information processing makes

use of associative networks. Perception enables the interpretation of the context (Colman, 2002) and

is a part of the greater action of information processing (Goldstein, 2007). Information processing

makes use of existing knowledge structures (Stayman, Alden & Smith, 1992). These knowledge

structures are represented in the human memory as a network of interconnected informational

nodes that activate each other in relevant contexts, according to the Human Associative Memory

(HAM) model (Anderson & Brower, 1973). These networks are called associative networks. When

using associative networks, consumers strive to comprehend the meaning of an object by relating it

to information stored in the memory. Whether the object confirms or disconfirms the prior

knowledge is noted very early in the stage of comprehension (Srull, Lichtenstein & Rothbart, 1985).

The node is the basic element of an associative network. A node is a piece of information stored in a

person's mind (Teichert & Schöntag, 2010). According to the HAM model, the nodes which are

primarily activated constitute the current context of the associative network. These nodes act as

source nodes, activating adjacent nodes in the flow of thoughts, according to the concept of

Spreading Activation (Collins & Loftus, 1975). The stronger the links between individual nodes, based

on the frequency of its usage, the more likely the spread of activation between those nodes (Teichert

& Schöntag, 2010). This facilitates a search process for additional information coming from the long-

term memory depending on the source node (Srull, Lichtenstein & Rothbart, 1985). The searching

process in the associative memory is hence cue dependent (Raaijmakers & Shiffrin, 1981).

Situational goals and branded products can both be seen as such a source node, activating other

nodes. This means that linked products, brands, situations and other knowledge to the branded

product/situational goal are activated in the mind if the consumer. This process results in the

activation of an associative network. When such a source node is absent, the corresponding

associative network is not activated. Hence, due to conceptually driven processing, situational goals

and branded products activate associative networks. This leads to postulation 1.

Postulation 1: Branded products and situational goals serve as source node and hence activate an

associative network.

2.1.3 Associative networks and schematic processing

Going back to the more abstract level of the activation of associative networks, knowledge structures

are important. The human memory is represented by knowledge structures, according to the HAM

model (Anderson & Brower, 1973). These knowledge structures are also referred to as schema: the

organised structures of prior knowledge stored in memory (Stayman, Alden & Smith, 1992).

Consumers maintain schema-level presentations in order to efficiently store and retrieve information

learned from experience with products and brands (Rosch & Lloyd, 1978). These memory-based

representations play an important role in product evaluation. Some researchers hence focus on the

7

determination of a product's congruence with a schema in order to predict whether a product is

accepted and liked by the consumer (Stayman, Alden & Smith, 1992).

Schematic organisations in the human memory enable greater recall than taxonomic organisation

(Rabinowitz & Mandler, 1983). The greater recall of schematic organisations can be explained by the

different principles of organisation of taxonomic and schematic structures. Taxonomic organisation

classifies based on the surface level features of objects. Thus, taxonomic organisation is based on

surface similarity. When a schema is activated in a schematic organisation, a coherent scene is

created which links objects to a scenario. The context is important for this. For instance, the retrieval

of associations regarding a newspaper in the scenario of drinking coffee in the morning is different

than in the scenario of moving. Because of this scenario retrieval, the schematic connections among

items may provide more and better ordered retrieval cues to recall information (Rabinowitz &

Mandler, 1983). These schemata are relevant for this study, since schemata can represent

consumption situations. These schemata enable the retrieval of prior knowledge and consequently

the activation of an associative network.

2.1.4 Associative networks and brands

A considerable amount of research has been done about associative networks and brands.

Associative networks give insights in the equity that a consumer attaches to a brand (Krishnan, 1996;

Cheng-Hsui Chen, 2001; Henderson, Iacobucci & Calder, 1998). Brand equity is defined as "the

differential effect of brand knowledge on consumer response to the marketing of the brand". Brand

equity requires favourable, unique and strong brand associations (Keller, 1993). Hence, the

perceptions about a brand are reflected in the associative network (Keller, 1993; Ariely, 2000). This

makes it plausible that a brand serves as a source node in an associative network.

In this study, brand refers to M&M's, which is a leading brand in the chocolate bitesizes (Mars, 2017).

2.1.5 Situational goals

Situational goal refers to an ad hoc goal provided by the contextual situation of a consumer.

Situational goal differs from a personal goal as it is provided by the situation. The current study

defines 'situational goal' as a suggested consumption situation for snacks.

Situational goals can be divided into different classes in order to detect their influence on associative

networks. Situational goals can be distinguished by occasion, frequency and need. Referring to

occasion, it makes a difference whether a consumer consumes alone or with others. A situational

goal where consumers consume alone is classified by Mars (2017) as 'my relaxation'. Situational goals

with others could be: 'us time', 'social break', 'in home family time' and 'sharing a good time with

friends'. Frequency refers to whether consumers consume on a special day or on an everyday basis (a

'routine pick me up' situational goal) and whether they consume during the evening or during day

time. The difference in needs clarifies the difference between functional needs (hunger fill, energy

break at work) and emotional needs of snacking and the difference between hunger satisfaction and

indulgence. Mars (2017) identifies the mentioned situational goals as chocolate moments. These

different moments elicit different associations.

Situational goals are defined as such consumption moments. The situational goal used in the current

study comprises a TV evening on the sofa with friends by snacking. An important note is that the goal

of snacking is always involved in the definition of the situational goal in this study.

8

It is important to notice that the situational goal used in this study is not culturally prescribed. This

means that in the suggested consumption situation, consumers are not socialised to choose a

particular product. A TV evening with friends on the sofa does not require a particular culturally

prescribed snack. A culturally prescribed situational goal would be having lunch for Dutch consumers.

Dutch consumers are socialised to eat sandwiches for lunch. To be clear, the used situational goal in

this study is not culturally prescribed and hence consumers are more free to choose a product they

find suitable for this situational goal.

2.2 Categorisation During the activation of an associative network, related categories are activated in the mind of the

consumer. Consumers use categories in order to efficiently store and recall information learned from

experiences with products and brands. A category is defined as a number of objects that are

considered equivalent (Rosch & Lloyd, 1978). Categorisation can be seen as the operation of the

connection of nodes in an associative network. Categorisation hence consists of activating the

learned associations between features of products and brands and their related categories (Shanks,

1991). Thus, the postulation is that the process of categorisation makes use of associative networks.

In this study, either a branded product or a situational goal activates categorisation.

Postulation 2: Categorisation makes use of associative networks.

A category may exist at three levels of generality. The superordinate level is more abstract and

qualitative, for instance snacks. The basic level is more specific and is the level at which objects are

spontaneously named, for instance chocolate. The subordinate level categorises below the basic level

and therefore enables finer distinctions between products (Miller, Malhotra & King, 2005). An

example of the subordinate level may be a Mars candy bar. The lower the level of categorisation, the

higher the informativeness. However, this informativeness is only high when the associations to

objects are already learned. In new cases, when objects do not belong to a category yet, this higher

informativeness is not applicable.

2.2.1 Categorisation based on surface similarity

Categorisation allows classification & inference making about products (Barsalou, 1991) via two

routes: based on surface or deep similarity. In this study, categorisation is based on either a branded

product or on a situational goal. One route of categorisation is based on surface similarity. This route

happens bottom-up, including feature extraction and reflection on stored knowledge (Miller et al.,

2005). This type of categorisation refers to taxonomic organisation. Categorisation based on surface

similarity depends on the surface-level features of an object. Regarding consumer products, for

example an object which is placed in a bowl, is liquid, hot and is made out of vegetables is compared

to prior knowledge. It is classified as soup since the features of the object match with the features of

the category soup. The category soup consists of products which are all liquid and hot. Members of a

taxonomic category thus have extrinsic, surface-level features in common.

Three different views relate to surface similarity based or taxonomic categorisation. The classical

view states that representative features are singly necessary and jointly sufficient (Smith & Medin,

1981). An object is either a full member of that category or no member at all (Smith & Medin, 1981;

Miller et al., 2005), which makes it a restricted view on taxonomic categorisation. For example,

according to the classical view courgetti (pasta made of courgette) cannot be pasta, since it is not

made of wheat. The prototype view is more flexible than the classical view as it states that category

9

membership is rather some sort of measure of a central tendency (Smith & Medin, 1981). The

prototype view states that category membership depends on a degree of feature match of the most

typical features for that category. Objects above a certain level of similarity (i.e. with enough

matching features) are category members (Hampton, 1995). The exemplar view is more flexible than

the prototype view, since exemplars may be affected by the context of a given situation (Miller et al.,

2005) and influenced by personal beliefs (Murphy & Medin, 1985). The exemplar view states that

categories are represented by exemplars rather than an abstract summary (Smith & Medin, 1981).

Categorisation is based on similarity to concrete exemplars of the category, rather than necessary

features (Miller et al., 2005). The exemplars are placed in stored memory as result of prior

experience. For instance, an iPad is an exemplar of the category tablets.

The exemplar view is relevant for leading branded products, which are generally the best known

example of a category. This could be the case because the brand introduced the product as first

producer (e.g. Apple's Ipad for the category tablets and Ipod for the category music players). The

equity of the leading brand can make it the best known example of the category as well (e.g. Eastpak

for the category backpacks). Such best-known examples could trigger taxonomic categorisation

based on an exemplar. In that way, a confrontation with a leading branded product can activate

taxonomic categorisation by means of an exemplar. The used brand in this study is M&M's, which is a

leading brand in the chocolate bitesizes category (Mars, 2017). The stimulus of a leading branded

product in this study can therefore provoke the leading branded product to be the exemplar of a

category as a result of taxonomic categorisation. The absence of a leading branded product does not

provoke a product to be seen as an exemplar by means of taxonomic categorisation. This reasoning is

captured in H1.

H1: Leading branded products are more often taxonomically categorised by means of an exemplar

than non-branded products are.

This best-known example of the category is examined on the basis of the exemplar view, because in

the current study consumers may be confronted with a situational goal. The context of this

situational goal (TV evening) may influence whether the leading brand (M&M's) is named as

exemplar, since this context is likely to involve the leading brand (Mars, 2017). When consumers are

not primed with this situational goal, they might be less likely to mention the leading brand (M&M's)

as exemplar. Thus, the influence of the context is important in this study, which means that the

exemplar view is most appropriate to analyse the categorisation process (Miller et al., 2005). The

classical view and the prototype view are considered to be too rigid to take this contextual effect into

account. However, it is important to keep in mind that the views on surface similarity based or

taxonomic categorisation relate in first instance to the psyche and not to contexts. The exemplar

view focuses on the psyche but acknowledges the influence of the context.

2.2.2 Categorisation based on deep similarity

Since situational goals do not display surface-level features, it is useful to discuss a way of

categorisation which uses a more abstract and deeper form of similarity. The other route of

categorisation does focus on deep similarity rather than similarity based on surface level features.

Categorisation based on deep similarity happens top-down and is based on prior knowledge, prior

experience and implicit theories about the world. Goal-derived categorisation follows this route of

deep-similarity (Miller et al., 2005). An example of goal-derived categorisation is categorisation based

10

on the goal "breakfast". Inferences are made about which products are suitable for this goal, such as

yoghurt, bread, coffee, cereals, juice and fruit. Members of a goal-derived category hence do not

need to have extrinsic, surface-level features in common. Rather, members of a goal-derived

category have in common that they can be used to achieve the goal.

Goal-derived categorisation is relevant for this study, since it assumes that objects are perceived as

similar if they share a set of associations in memory that are organised around common goals

(Huffman & Houston, 1993). This means that products are perceived as similar because of common

associations around the situational goal. When situational goals are salient, on the one hand the

perceived similarity between goal-appropriate products increases. On the other hand, with salient

situational goals the similarity between products decreases when only one product is ideal for that

particular goal (Ratneshwar et al., 2001). This means that a situational goal activates goal-derived

categorisation. Consequently, different products arise in the mind in order to fulfil the situational

goal. The more familiar the consumer is with the situational goal, the more narrowly (i.e. within one

category instead of across categories) he/she categorises (Felcher, Malaviya & McGill, 2001).

Categorisation consists of activating the learned associations between features and their associated

categories (Shanks, 1991). These associations are represented in an associative network (Anderson &

Brower, 1973). For that reason, associative networks are needed in order to conduct the process of

categorisation. Hence, goal-derived categorisation provides the link between situational goals,

associative networks and categorisation. That is, situational goals are likely to activate goal-derived

categorisation, as hypothesised in H2.

H2: The presence of a situational goal results more often in goal-derived categorisation than in case a

situational goal is absent.

The means-end chain of Gutman (1982) can be seen as similar to goal-derived categorisation. This

model states that consumers compose arrays of products which will be instrumental in achieving

valued end states. Gutman (1982) properly acknowledges that categorisation is limited to the point

where it matches the individual capacities of the consumer. This limitation applies presumably as

well to the goal-derived categorisation based on the situational goal. Some consumers have more

experience and thus probably a more extensive associative network, which generates more creative

solutions to fulfil the situational goal than consumers with lower experience. For instance, a world-

traveller might think of exotic snacks for his/her TV evening, while other consumers can only think

about crisps and chocolate. However, the situational goal used in this study is provided by the

context and does not refer to fulfilment of personal values, which is an important characteristic of

the 'valued end states' of the means-end chain model (Woodside, 2004). Therefore, the current

study focuses on goal-derived categorisation based on associative networks according to the HAM

model (Anderson & Brower, 1973). The limitation of individual capacities in categorisation is

acknowledged, but the means-end chain model (Gutman, 1982) is not used as theoretical

underpinning of the conceptual framework (Figure 1).

2.2.3 Situational and personal goals

Although the current study focuses on situational goals, it is valuable to acknowledge the existence

of personal goals in consumer research. Ratneshwar et al. (2001) point out that combination of

personal and situational goals can influence categorisation. Different from situational goals, personal

goals (e.g. eating less unhealthy snacks) are stable over time and are not provoked by the context

11

(Ratneshwar et al., 2001). The influence of situational goals appears to dominate the influence of

personal goals (Belk, 1974). For instance, when a person all of a sudden notices that he/she wants to

enjoy a TV evening with friends by snacking, that person might choose a not so healthy snack,

contrary to the personal goal. Therefore, the current study assumes that categorisation is more

influenced by the situational goal which is suddenly strongly present than by a stable personal goal.

2.2.4 Primary and secondary categorisation

According to Barsalou (1991), categorisation consists of primary categorisation and secondary

categorisation. Common taxonomic categories provide the primary categorisation of an object,

whereas goal-derived categories provide secondary categorisation. People use basic and subordinate

levels for primary categorisation. From such a taxonomic category, the consumer can infer what the

(standard) function of this object is. Processing these functions relate to goal-derived categorisation.

Barsalou (1991) provides the example that people categorize something as a chair initially (primary

categorisation) and later categorise it as something to stand on to change a light bulb (secondary

categorisation). As stated in H1, branded products are presumably taxonomically categorised but

situational goals are not categorised in this way. According to H2, situational goals activate goal-

derived categorisation. Due to the lack of surface level features, it is not likely that situational goals

are taxonomically categorised. Hence, it is conceivable that a branded product is first categorised

taxonomically and in the second stage goal-derived categorisation could be activated as well.

Situational goals are only categorised in a goal-derived way. This reasoning is reflected in H3.

H3: Branded products are more often primary and secondary categorised than situational goals,

which are mostly only secondary categorised.

2.2.5 Relevance of categorisation for the retail sector

The consumer categorisation process is relevant for the retail industry as the effectiveness of the

layout of an assortment on actual purchases is influenced by consumer categorisation. Categorisation

does not only consists in the mind of the consumer: retailers make categories of their assortment

when presenting their products in the store. The amount of variety that consumers perceive and

satisfaction consumers derive from the assortment as well as their purchase decisions depend on

whether the categorisation in the mind of the consumer is congruent with the external organization

provided by the store. Such a congruence makes purchases more likely (Morales et al. , 2005).

Taxonomic and goal-derived categorisation relate in different ways to perceived variety and

consumer satisfaction of the product assortment. For familiar taxonomic product categories, such as

snacks, congruency between consumer's categorisation and the external layout of the store results in

higher perceived variety, more satisfaction with the items chosen from the assortment and probably

more purchases. Goals in general are expected to serve as self-imposed filters (by the consumer) on

the assortment that enable easier navigation through product categories, which increase satisfaction.

When goal-derived categorisation of the consumer is congruent with external displays, consumers

perceive less variety but are more satisfied with the assortment and hence more likely to buy. The

reverse is true when goal-derived categorisation is incongruent with external displays (Morales et al.,

2005). As situational goals are hypothesised to activate goal-derived categorisation, it is assumed

that these effects apply for situational goals. Morales et al. (2005) suggest that further research

should examine the interaction between goals and consumer categorisation for well-developed

internal structures. Such structures are well-developed when goals are familiar to the consumer. This

study conducts this by examining the goal-categorisation process of a familiar situational goal.

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2.3 Categorisation and impulse buying

2.3.1 Different kinds of impulse buying

As introduced by Stern (1962), there are specific kinds of impulse buying. Branded products and

situational goals relate each to a different kind of impulse buying. A branded product is likely to

affect pure impulse buying, as the stimulus of the branded product disrupts the planned purchase

plans (Stern, 1962). A situational goal is likely to affect planned impulse buying. The stimulus of the

situational goal causes the consumer to enter the supermarket with a not completely specified

intention to buy. The situational goal thus influences impulse buying before seeing products. The

actual buying decision is made when the consumer is confronted with the available products and

when the consumer checks the suitability of products to fulfil the situational goal (Stern, 1962).

In order to preserve the clarity of the theoretical and conceptual framework, impulse buying is

referred to as one concept. The overarching concept "impulse buying" is included in the conceptual

framework as dependent variable (Figure 1). It is however valuable to acknowledge the different

kinds of impulse buying which are affected by the branded product and the situational goal in order

to understand the underlying process and its influences. The influence of branded product (pure

impulse buying) is more spontaneous than the influence of situational goal (planned impulse buying).

2.3.2 Two routes resulting in goal-derived categorisation

Branded products are hypothesised to be taxonomically categorised by means of an exemplar. When

associations based on prior knowledge are consistent with this branded product, there is schema

congruity and the product is placed into a taxonomic category. In such a case straightforward

categorisation is very likely. Congruence with a primed product-category schema means that more

holistic processing occurs in state of processing based on attribute level (Fiske & Pavelchak, 1986). It

is conceivable that straightforward categorisation does not require deliberative and effortful

processing, since the consumer does not need to force a fit with prior knowledge, adjust prior

knowledge or process on an attribute by attribute basis. This implies that straight forward

categorisation happens in a low effortful, more automatic way.

After the branded product activates primary and presumably straightforward taxonomic

categorisation, secondary categorisation by means of goal-derived categorisation occurs (H3). Goal-

derived categorisation follows, since taxonomic categorisation activates concepts which are mentally

associated to situations, goals and action (Sheeran et al., 2005; Barsalou, 1991). The pursuit of the

goal in goal-derived categorisation can happen automatically, outside consumer's awareness (Bargh

Gollwitzer, Lee-Chai, Barndollar & Trötschel, 2001). Taken together, this means that both branded

products and situational goals lead to goal-derived categorisation. The difference is that the route of

branded products towards goal-derived categorisation is longer than that of situational goals, as it

involves taxonomic categorisation.

2.3.3 Categorisation as intuitive process

Combining several insights provides the means to link categorisation to intuitive processing. As

stated in postulation 2, categorisation makes use of associative networks. These associative networks

are knowledge structures consisting of learned associations based on experience (Anderson &

Brower, 1973). In a similar vein, intuition is an automatic process that relies on knowledge structures

which are acquired by learning (Glöckner & Witteman, 2010) to process information. This implies

that categorisation operates as an intuitive process.

13

Several approaches apply to intuitive processing. Some researchers (e.g. Chen & Chaiken, 1999;

Kahneman, 2011; Petty & Cacioppo, 1986) aim to draw sharp distinctions between intuitive and

other ways of information processing. These dual-process models of information processing assume

a clear distinction between deliberative and intuitive processes without further differentiation

between and within both categories (Chen & Chaiken, 1999; Kahneman, 2011; Petty & Cacioppo,

1986). Glöckner and Witteman (2010) however argue that the more intuitive process (i.e. system 1,

Kahneman, 2011; the peripheral route, Petty & Cacioppo, 1986; heuristic processing, Chen &

Chaiken, 1999) is not a homogenous concept, but a label used for different cognitive mechanisms.

Relevant mechanisms of intuition for this study are associative intuition and matching intuition

(Glöckner & Witteman, 2010). These mechanisms are relevant, since associative intuition is based on

association learning like categorisation. Matching intuition is a more abstract mechanism of the same

process as associative intuition. Matching intuition concerns acquisition of and comparison with

exemplars, prototypes and schemata in stored knowledge. Such a comparison can result in behaviour

in the end (Glöckner & Witteman, 2010). This implies that the behaviour is satisfactory repeated to

be stored in the memory. This means that in an intuitive way of information processing, a consumer

makes use of stored knowledge structures which can refer to behaviour.

Intuition enables consumers to use patterns to recognise what is going on in a situation and to

activate the typical action script with which one reacts (Glöckner & Witteman, 2010). This typical

action script is conducted so frequently that it is stored in the memory. Following the conceptual

framework (Figure 1) goal-derived categorisation is activated and assumed to function as an intuitive

process. Consequently, the intuitive process of goal-categorisation is hypothesised to refer to stored

knowledge structures including past behaviour and hence to activate a behavioural script (H4). As

this study focuses on snacks, a snacking behavioural script is activated.

H4: Goal-derived categorisation activates a snacking behavioural script.

By combining insights from different types of intuition (associative and matching intuition), it is found

that intuition translates experiences, via categorisation and behavioural scripts, into behaviour. This

is the case, since a behavioural script is included in knowledge structures. A requirement is that the

behaviour is conducted so frequently that it is stored in the memory as a behavioural script. In fact,

this combination results in associative intuition activating a comparison with stored knowledge which

could result by means of a behavioural script in a behavioural action (Glöckner & Witteman, 2010).

Such knowledge structures are also referred to as schemata, which are the organised structures of

prior knowledge stored in memory (Stayman, Alden & Smith, 1992).

Scripts are a specific kind of schemata. Scripts differ from a schema in the sense that the elements of

scripts specify actions. Even more, the connections between actions in scripts are causal, meaning

that calling up one part of a script from memory activates memory of the other, related bits of the

sequence (Aunger, 2007). Scripts are knowledge structures which allow an automatic, default actions

to a well-known, stereotypical situation without (much) mental processing (Schank & Abelson, 1977).

Scripts are related to behaviour by means of a motivational network. The motivational network is a

matrix of interconnected nodes representing script elements connected to goal representations.

Hence, the motivational network activates a behavioural script which is related to a particular goal

(Aunger, 2007). In the current study the presented situational goal is salient. A salient goal makes it

14

plausible that the behavioural script actually translates into behaviour. Applied to this study: when

the consumers wish to achieve the goal of enjoying their TV evening with friends by snacking (i.e. the

situational goal), they activate the snacking script.

In the current study, it is supposed that the required behavioural action in this snacking script is

buying a snack impulsively. Impulse buying is seen as the scripted behaviour for two reasons. First,

the habit of snacking, which refers to a snacking behavioural script, is proven to be strongly related

to impulse buying (Verplanken et al., 2005). Second, the environment the consumer finds

him/herself in the current study is a determining factor. The context of a supermarket provides the

means to possess a snack by buying it. Thus the required behavioural to fulfil the goal is buying. Since

the consumer did not plan to buy a specific product, the action is seen as (planned) impulse buying.

Hence, it is likely that the activation of a snacking behavioural script results in impulse buying.

Three conditions appear crucial for the translation of a script into behaviour (Abelson, 1981). First, a

person needs to have a stable cognitive representation of the particular behavioural script. It is

assumed that the cognitive presentation of a snacking script is build up by the experience and

retrieval of abundant previous snacking situations. Hence, the cognitive representation of the

snacking behavioural script is assumed to be stable. Second, an evoking context for the behavioural

script is needed (Abelson, 1981). This evoking context is guaranteed by the confrontation with the

situational goal in the current study. Third, a person must enter the behavioural script, which

happens often non consciously (Abelson, 1981). This entering or activation of the behavioural script

is elaborated in H4. The activation of the behavioural script is assumed to not require deliberate

processing since goal-derived categorisation, as intuitive process, activates the behavioural script.

Taken together, these studies (Aunger, 2007; Abelson, 1981) support the understanding that the

activation of a behavioural script results in the scripted behaviour. More concretely, it is likely that

the activation of a snacking behavioural script results in impulse buying, as hypothesised by H5.

H5: The activation of a snacking behavioural script results in impulse buying.

2.3.4 habits and scripts

Scripts are represented in a motivational network. In this motivational network, habits are mentally

represented as the relationships between goals and actions that are instrumental in achieving the

goal (Aarts & Dijksterhuis, 2000). When the goal is activated, habits can operate automatically

(Sheeran et al., 2005) and without conscious awareness (Custers & Aarts, 2010).

Habits reflect how frequent and automatic an action is to someone (Verplanken & Orbell, 2003). The

more frequent and consistent the activation of the goal generates the performance of the same

action under the same circumstances, the stronger and more accessible the link between goal and

actions (i.e. the habit) becomes (Aarts & Dijksterhuis, 2000). A habit thus reflects how strong the

goal-action relationship is, which is essential for a script (Aunger, 2007). The more habitual an action

is, the more likely that the behaviour is guided by a script. Applied to this study, it is known that

snacking is likely to be established as an habit and that impulse buying is strongly related to the habit

of snacking (Verplanken et al., 2005). Hence, the more habitual snacking is to someone, the more

likely that intuition actives a snacking script which results in the scripted behaviour (impulse buying).

15

There is no direct measure for the activation of a behavioural script. Because of the

interconnectedness of habits and behavioural scripts, habit will function as an indirect measure of

the activation of a behavioural script in this study. Hence, the assumption in this study is that the

more habitual snacking is to someone, the more likely that a behavioural script is activated.

2.3.5 Impulsiveness as a personality trait

The tendency to buy on impulse is rooted in personality. Persons who possess commonly named

impulsive personality characteristics (e.g. low need for deliberation) are more susceptible to impulse

buying than persons who do not posses these impulsive personality characteristics (Verplanken &

Herabadi, 2001). In the current study, the snacking behavioural script is assumed to be associated to

impulse buying (H5). Thus the activation of a snacking behavioural script is more likely for more

impulsive people than for less impulsive people.

The activation of a snacking behavioural script is hypothesised to result from goal-derived

categorisation (H4). In fact, impulse buying (i.e. the scripted behaviour) and way of information

processing appear to be linked. Youn & Faber(2000) argue that more impulsive people are

susceptible to impulse buying for affective reasons. Less impulsive persons focus more on rational

reasons for impulse buying (Youn & Faber, 2000). Goal-derived categorisation is seen as an intuitive

process which is related to an affective state of mind. In this light, one may suppose that goal-derived

categorisation as intuitive process is stronger associated to a snacking behavioural script (which

includes impulse buying) for persons scoring high on impulsive personality characteristics. Therefore,

impulsiveness as a personality trait moderates the relationship between goal-derived categorisation

and the activation of a snacking behavioural script, as hypothesised in H6.

H6: The more impulsive the personality, the more likely that goal-derived categorisation results in the

activation of a snacking behavioural script.

The theoretical framework and the formed hypotheses result in the conceptual framework (Figure 1).

Since it is hypothesised that branded products are categorised in both a taxonomic as well as in a

goal-derived way, there might be an interaction of branded product and situational goal on impulse

buying. The research of Lange, Selander & Åberg (2003) supports this, since they found that in goal-

derived usage contexts (i.e. situational goals) consumers are more likely to choose a less favoured

and less typical brand from a typical product category than a typical and more favoured brand from a

less typical product category for the domain of snacks. Hence, the presence of a situational goal

could influence the effect of a branded product on impulse buying. In the present study,

M&M's/chocopeanuts (the (non-) branded product) are assumed to be included in the typical

product category for snacks relating to the presented situational goal. This is the case, since Mars

uses M&M's successfully as typical product for the situational goal (Mars, 2017). Chocopeanuts are a

non-branded equivalent of this product. The assumption that the effect found by Lange et al. (2003)

applies to the typical product category for the situational goal is based on the following reasoning: In

general, a branded product may be chosen more often than a non-branded product, because of the

assumed stronger brand equity of the branded compared to the non-branded product. However,

when a situational goal is present, a non-branded product may be chosen more often than in case a

situational goal is absent. The choice for a non-branded product is influenced relatively much by the

goal-derived usage context (i.e. the situational goal) in comparison to a branded product. (Lange at

al., 2003). This difference between the absence and the presence of a situational goal may thus be

16

larger for a non-branded product than the difference for a branded product. This means that the

combined effect of branded product and situational goal could presumably create an interaction

instead of an reinforced effect. Therefore, the effect of the branded product on impulse buying could

possibly be different as a result of different values of the situational goal (absent vs. present).

17

3 Method

3.1 Experimental design & manipulations The hypotheses were tested by an experimental 2 (branded product) x 2 (situational goal) between

subjects factorial design (Table 1) with impulse buying as dependent variable. Participants were

randomly assigned to one of the four conditions. A scenario setting was included in the instruction of

the study: participants were asked to imagine themselves being in the supermarket to do their

groceries. Different supermarket shelves were presented to the participants and they could choose

to buy a product by clicking on it. The complete description of the experiment can be found in

Appendix C.

Branded product was operationalised by using M&M's (branded product) and chocopeanuts (non-

branded product). Chocolate peanuts were chosen, because they are usually familiar to consumers

in both branded and non-branded versions. M&M's are colourful chocolate lentils or in chocolate

covered peanuts. M&M's is a global player in the chocolate brands (Mars, 2017). A display with

either M&M's (branded product) or chocopeanuts (non-branded product) was presented in one of

the pictures of the supermarket shelves (the pasta shelf) (Figure 3). An unrelated shelf (pasta) was

chosen in order to measure the effects of the manipulation as pure as possible. For instance, when

the chocolate peanuts would be placed next to the tea shelf, associations of drinking tea and eating

chocolate peanuts could be made. These associations would intrude the manipulations and thus

create random variance in the conceptual model. Furthermore, this level of the independent variable

branded product is realistic to the consumer and can be constructed in real life. The realism and

usability of this operationalisation makes it a conclusive level of incorporating the independent

variable branded product.

Figure 3. Manipulation of branded product. This figure shows the depiction of the branded product in

the pasta shelf (left) and the depiction of the non-branded product in the pasta shelf (right).

Situational goal was operationalised by the presence or absence of a description of the situational

goal in the instruction of the shopping task. The situational goal was defined as enjoying your

evening moment on the sofa, watching TV together with friends by snacking. This situational goal

was defined and proven suitable as well as realistic by making use of the experience of Mars in

consumer snacking moments in combination with the pre-test. This enhanced the external validity of

the manipulation. The situational goal was presented only textually in order to create similar stimuli

for participants in the experimental and control conditions, which fostered the internal validity of the

18

manipulation. In the control conditions, a depiction of a picture would not be possible. Since both the

internal and external validity of the manipulation were enhanced, this level of operationalisating the

independent variable situational goal was seen as conclusive. The description (in Dutch) of the

situational goal was the following:

Je hebt voor vanavond drie goede vrienden bij je thuis uitgenodigd. Jullie zullen vanavond in de

woonkamer zijn. Je bent van plan om vanavond met je vrienden TV te gaan kijken. Je weet nog niet of

dat jullie favoriete serie, een film of een TV programma is. Wel weet je dat je op de bank gaat zitten

met je vrienden en tijdens het TV kijken lekker wil snacken.

3.1.1 Scenario setting

A supermarket scenario was presented to the participants: they were running out of several products

resulting in a shopping list. This list contained: tea, cookies, toilet paper, spaghetti and pasta sauce.

They were going to do their groceries in the supermarket. While walking around the store, they were

seeing different shelves which were presented to them as pictures on separate screens (Figure 4). In

order to simulate a realistic supermarket scenario, the shelves included products on the shopping list

as well as unrelated shelves. In total 12 shelves were depicted, one of them was used for the

branded product manipulation. In order to increase consistency and therefore realism of the

scenario, the shelves of one Dutch supermarket (Albert Heijn) were used as much as possible. The

shelves were presented in a random order to reduce biases in the results because of order effects.

19

Figure 4. Non-manipulated shelves of the supermarket scenario. These non-manipulated shelves were presented in a random order. Sources: 1: http://maakhetglutenvrij.nl/glutenvrij-in-italie/, 2: http://www.levensmiddelenkrant.nl/nieuws/fabrikanten/fonterra-topman-melkprijs-blijft-dalen, 3: https://www.linkedin.com/pulse/vbat-develops-shop-good-food-constanze-fluhme/, 4: http://www.levensmiddelenkrant.nl/nieuws/algemeen/bewuste-levensstijl-versplintert-theelandschap, 5: https://www.quavita.nl/zelf-sappen-maken-met-vitaal-water, 6: http://moniquevandervloed.nl/grootste-meuk-onzin-top-10/, 7: http://www.distrifood.nl/formules/nieuws/2015/2/ex-leverancier-wc-papier-eist-geld-van-ah-10132371, 8: https://www.eigenwijsblij.nl/gadgets-shoppen/vegansuper-groningen-eerste-veganistische-supermarkt-noord-nederland, 9: http://fitnesschicks.nl/food-haul-mijn-aankopen-bij-de-marokkaanse-supermarkt/, 10: http://www.dixiechikcooks.com/michelada/, 11: http://www.stichtingmerelswereld.nl/blog/keuzestress/

3.2 Participants

The sample consisted of 226 Dutch women (178, 78.8%) and men of 18 years and older (Table 2 for

number of participants per condition). Different from children, adult consumers are experienced in

making their own product choices and experienced with the consequences of buying. A wide range of

adult consumers was involved in the experiment in order to be able to draw conclusions for both

consumers more in general as well as for particular groups of consumers. In this way, results could

give specific insights for the promotion strategy of Mars and could produce specific scientific

knowledge. Participants who had a peanut allergy, who were younger than 18 years and who did not

had the Dutch nationality were excluded from the data analysis (9 participants). The distribution of

men and women was about equal across the conditions. The age of the participants ranged between

18 and 86 years old with a median of 24 years. Most participants (46%) were highly educated (HBO,

WO bachelor). The experiment was conducted in Dutch, in order to avoid noise in the results because

of unintended differences in translation and cultural background. The participants were recruited by

sending personal emails and sending social media messages. In order to motivate people to

participate in the study five Mars chocolate boxes were randomly assigned to participants as a

reward. The participants needed to provide and give permission for the use of their personal data to

receive the reward.

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3.3 Measures

A seven-point likert scale was chosen as a basis for this study in order to create unity in the response

scales for the participants. A seven-point likert scale provided an appropriate balance between few

responding points (easy responding task for the participant) and many responding scales (high

statistical power). It was taken into account that some measures consisted of only one question (i.e.

low statistical power). The odd number of points of a likert scale provided the participant the

possibility to answer in neutral terms. This avoided the situation with a participant feeling awkward

and hence not responding truthfully.

The screening variable peanut allergy was included in order to reduce biases in the associations with

chocolate peanuts. Peanut eating participants were most relevant for this study, since they have

learned associations to chocolate peanuts. Participants who do not eat peanuts lack these

associations. Therefore, allergic participants were thanked for their and time excluded from the rest

of the experiment.

Impulse buying was operationalised in two ways. First, participants could click with their mouse

(cursor) on products of the supermarket shelves they would like to buy. Impulse buying was present

when chosen products were not represented on the initial shopping list. Second, an adjusted version

of the Consumer Impulsiveness Scale (CIS) (Puri, 1996) measured how impulsive participant's buying

decisions were. The CIS was used because of its proven reliability and because it could be

transformed from measuring impulsiveness of a person to impulsiveness of an action. The adjusted

version of the CIS consisted of 11 items and was accompanied by a seven-point likert scale ranging

from "not applicable at all" to "really applicable". Item 8 of the CIS (easily tempered) was deleted in

this study, since there exists no accurate translation in Dutch. The assumption was that the scale

remained reliable, since it still had 11 items.

Goal-derived categorisation was operationalised in three ways. First, the participants were given a

map of the layout of a hypothetical supermarket (Figure 5) based on the research of Moreau,

Markman & Lehmann (2001). Some of the departments were taxonomically classified (e.g. dairy

products, cookies and candy), other departments were classified by their goal (e.g. products for a

party and products suitable for after dinner). The participants were reminded to the branded product

(M&M's) or non-branded product (chocopeanuts) and asked: "If you were shopping in the store

shown below, where is the FIRST place in the store you would go to in order to find

M&M's/chocopeanuts?". The participants indicated with their mouse (cursor) the department they

would visit, which indicated their categorisation. This operationalisation of categorisation was

chosen, since it required less deliberate effort than a word task and hence better simulated a real

shopping situation. Second, the participants chose from a closed list of reasons why they would go

to that department. The proposed reasons referred either to goal-derived or taxonomic

categorisation. Third, the participants rated the appropriateness of several goal-derived (e.g. TV

21

evening with friends) and taxonomic categories (e.g. chocolate) for either M&M's (branded product)

or chocopeanuts (non-branded product). Seven categories, including two distracting categories were

presented. Participants indicated whether they expected the product at this category by means of a

seven-point likert scale ranging from "not likely at all" to "very likely".

Figure 5. Map of the hypothetical supermarket.

Taxonomic categorisation based on an exemplar was measured by the following procedure: first,

participants indicated comparable products to either M&M's (branded product) or chocopeanuts

(non-branded product). Second, participants indicated, according to them, the best-known example

of the before mentioned group. This best-known example was seen as the exemplar. These questions

were open, in order to not influence associative networks and to not create demand effects for the

participant.

The activation of a behavioural script was indirectly measured by habitualness, since there is no

measure of the activation of a behavioural script. The assumption in this study is that the more

habitual snacking is to someone, the more likely that a behavioural script is build and activated.

Habitualness was measured by the Self-Report Habit Index (SRHI) developed by Verplanken and

Orbell (2003). The SRHI measured the presence of a general snacking habit and not the particular

habit of chocolate (peanut) snacking. The SRHI has been developed as a direct measure of habit

strength that does not rely on estimates of behavioural frequency. Rather, habit strength is

measured as a psychological construct, measuring the features automaticity, history of repetition

and expression of one's identity. This makes the SRHI closely linked to behavioural scripts. Hence,

unlike the reasoning of Gardner (2012), all elements of the SRHI were used. Automaticity is necessary

to measure habits, since habits refer to learned sequences of acts that have become automatic

responses to specific cues. This is a crucial element of the behavioural script (Aunger, 2007; Schank &

Abelson, 1977). Measuring automaticity is however not sufficient in this study for indirectly

measuring the activation of a behavioural script. A measure of the history of repetition is needed,

because habits develop and gain strength by satisfactory repetition of behaviour, likewise do

behavioural scripts (Aunger, 2007). Measuring the expression of one's identity is needed, because

habits are a part of how a person organises everyday life and thus reflect personal identity

22

(Verplanken & Orbell, 2003), which refers to a behavioural script as well. Although the SRHI uses self-

report, it shows a high internal reliability by having high Cronbach's alpha's (Verplanken & Orbell,

2003). The SRHI has been successfully applied in many studies (Lindgren et al., 2015; Gardner, de

Bruijn & Lally, 2011).

Impulsiveness as a personality trait was measured with the ABbreviated Impulsiveness Scale (ABIS)

containing 13 items (Coutlee, Politzer, Hoyle & Huettel, 2014). This scale has shown to be an efficient

and reliable shortening of the Barratt Impulsiveness Scale (BIS-11; Patton & Stanford, 1995) (Coutlee

& et al., 2014), which was considered too long for this experiment. The BIS is the most commonly

used self-report to assess the personality construct of impulsiveness, both in scientific research and

clinical settings (Stanford et al, 2009). The ABIS was accompanied by a 4-point response scale

including the responses: rarely/never, occasionally, often, almost always/always.

The study included the control variable frequency of snacking. Frequency of snacking was measured

with a multiple choice question with the response possibilities: rarely/never, once every week, once

every day, several times a day. Snacking was defined as "eating little portions of food in between

meals, meaning that it could be both a banana and crisps". This meant that both healthy and

unhealthy snacking were included, which reduced the social desirability bias.

Frequency of shopping was included as control variable and was measured with a multiple choice

question. Participates indicated whether they do their groceries less than once a week, 1-2 times a

week, 3-5 times a week or (almost) every day. Frequency of shopping influences the goals of the

shopping trips and therefore impulse buying. For instance, when the consumer just needs a few

products quickly, he/she is less susceptible to impulse buying than during a major shopping trip

(Kollat & Willett, 1967).

The study included disposable income as control variable in order to check whether the choice of

either M&M's or chocopeanuts was influenced by the amount of money people can spend. People

with a low disposable income could have the tendency to choose for non-branded products, as these

products usually have a lower price than branded products. Disposable income was measured by

asking whether participants have to make economies or can afford luxury while doing their groceries.

Liking of chocolate and other bitesizes was included as control variable. When people don't like to eat

bitesizes, they may not be interested in the bitesizes of this study. Liking of chocolate and other

bitesizes was measures with a seven-point likert scale ranging from "I don't like this at all" until "I

really like this". The liking of chocolate in general, white chocolate, milk chocolate, dark chocolate,

chocolate with nuts, cocktail nuts, crisps and popcorn was included. Specific bitesizes were included

in order understand the nuance of the liking of some bitesizes and disliking of others.

Brand familiarity of the participants towards M&M's was included as control variable. The

contradiction between branded product (M&M's) and non-branded product (chocopeanuts) was

assumed to be stronger and more explicit for participants with a high brand familiarity. Brand

familiarity was measured with the reliable scale of Zhou, Yang and Hui (2010).The scale with three

semantic differentials was transformed into a scale with three items and a seven-point likert

response scale in order to create unity in the response scales. The items were: this brand is very

familiar to me, I'm very knowledgeable about this brand and I have seen many advertisements about

this brand in the mass media.

23

The study included gender, age and level of education as control variables. These variables were

measured by means of demographic questions (Appendix C).

3.4 Manipulation check

The participants needed to understand the manipulation of situational goal in order to establish a

distinctive difference between the conditions. The manipulation check of situational goal hence

tested whether the participants were aware of the situational goal. Participants selected from a

closed list one or more intention(s) they thought they were given during the shopping scenario. This

closed list included an intention similar to the situational goal. When there was a clear difference in

chosen intention between the conditions with and without a situational goal, the manipulation was

considered successful.

3.5 Procedure The experiment was conducted online and created with Qualtrics. Qualtrics is an online tool which

facilitates setting-up online surveys. First, informed consent of the participants was asked in order to

proceed with the experiment. The cover story stated that the experiment was about different lay-

louts of supermarkets. Then the peanut allergy check was conducted. The remaining participants

were randomly assigned to one of the four conditions. This enabled that causal relations could be

inferred. The participants were instructed with the scenario setting and the shopping task. For

participants in condition 1 and condition 2, the situational goal was presented in this instruction. The

participants saw pictures of the supermarket shelves and could click on desired products. The

manipulation of the (non-) branded product was applied in the picture of the pasta shelf. Then the

measure of impulse buying (CIS) was conducted and goal-derived and taxonomic categorisation were

measured. This was followed by the measure of taxonomic categorisation based on an exemplar.

Then the activation of a snacking behavioural script was measured followed by the measurement of

frequency of snacking, impulsiveness as a personality trait, liking of chocolate and other bitesizes,

brand familiarity, frequency of shopping, disposable income, age, gender and level of education. The

experimented was ended with a manipulation check and a debriefing. Participants could leave their

e-mail address in order to have a chance of winning the reward and/or to be informed about the aim

of the study. This procedure is depicted in a flowchart (Appendix A, Figure A.1).

3.6 Pilot

A pilot of the whole experiment was conducted in order to detect errors and flaws. Five participants

were observed when they participated in the experiment. They provided feedback towards clarity

and readability of the questions and texts. They were asked whether the scenario setting was

understandable and realistic to them. Feedback regarding technical problems was asked as well.

The results of the pilot showed that the participants did not understand the question regarding the

map of the supermarket correctly. Some of them thought they needed to indicate the place in the

supermarket they usually visit first. Hence, the question was changed into: "If you were shopping in

the store shown below, where is the FIRST place in the store you would go to in order to find

M&M's/chocopeanuts?". Based on misunderstandings, a sentence was added to explain that the

selected area will get a colour. The question regarding taxonomic categorisation based on an

exemplar was unclear and difficult for the participants. Hence a description was added: you should

not be thinking too long about this question, everything popping-up into your mind is an answer and

answers can be specific as well. The framing of the consecutive question was changed by stressing

24

that the five products constitute one group. Because of unclarity to the participants, snacking was

defined as something which could be healthy (a banana) and unhealthy (crisps), without mentioning

these judging words which could influence the self-report. Lower order issues, like adding a

definition of 'rational', explaining how to proceed to the next page, changing 'a number of' into

'three' good friends were addressed. It took participants quite long to complete the survey, hence

the estimated time to complete the experiment was changed into 10-15 minutes.

3.7 Pre-test

In order for the situational goal to have a distinctive manipulative effect, it needed to be plausible for

the participant. Even though the situational goal has successfully been used by Mars (Mars, 2017), a

pre-test was conducted in order to ensure the suitability of the situational goal. Seven participants

indicated how realistic, credible, imaginable and frequently occurring six situational goals were to

them based on a seven-point disagree/agree likert scale (Appendix C). The situational goal of

watching TV on the sofa with friends while snacking scored on average the highest on three of these

elements (credible: 6.43; imaginable 6.57; frequently occurring; 5.14). On the element about realism,

the mean was equal to the situational goal of having a party at home with friends (6.14). However,

the situational goal about having a party scored on average lower than the TV situational goal on the

other elements (credibility, imaginability, frequentness)(Appendix B). The range of given assessments

of the TV situational goal was low (i.e. 2 for realism and imaginability and 1 point for credibility on

the likert scale). Hence, the TV situational goal was considered most suitable for this study.

The appropriateness of the supermarket scenario for this study was tested. Seven participants

indicated how realistic, credible, imaginable and frequently occurring the supermarket scenario was

to them, by means of a seven-point disagree/agree likert scale. The supermarket scenario scored

high on all elements (realistic: 5.57, credible: 5.71; imaginable 5.86; frequently; 6.00 ) (Appendix B).

The range for the assessments of all elements was 3, which showed that only positive assessments

were given. Qualitative answers showed that the pictures of the shelves made the supermarket

scenario realistic. Participants indicated that the groceries on the shopping list were very realistic and

common to them. None of the participants bought a product not on the shopping list (i.e. no impulse

purchases were conducted). It was not clear to the participants whether they could choose a

particular version or brand of the products. Hence, based on the pre-test the set-up of the shopping

task was changed from textual to visual. In the final version, participants could click with their mouse

(cursor) on the product they would like to buy. The products were displayed in a picture of a shelf. In

addition, more pictures of both related and unrelated shelves were included to create a realistic

simulation (Figure 4).

25

4 Results

4.1 Reliability of scales The factor analysis of the adjusted version of the CIS scale indicated that the first component

provided an eigenvalue higher than 1 (3.593), 32.660% of the variance was explained. The scree plot

showed an elbow after the first component. The reliability analysis of the adjusted version of the CIS

scale resulted in a Cronbach's alpha of 0.753 (Table 3), which meets the reliability standard of 0.7

(Field, 2013). These results denoted the reliability of the adjusted version of the CIS.

The factor analysis of the SRHI indicated that the first component had an eigenvalue higher than 1

(6.522) and explained 54.349 % of the variance. The scree plot showed a clear elbow after 1

component. The reliability of the SRHI was confirmed with a high Cronbach's alpha of 0.923 (Table 3).

The factor analysis of the ABIS showed that the first component had an eigenvalue higher than 1

(4.487) and explained 34.517 % of the variance. The scree plot demonstrated a clear elbow after one

component. The reliability analysis revealed a good reliability of the ABIS by having a Cronbach's

alpha of 0.828 (Table 3).

The factor analysis indicated that the first component of the scale for brand familiarity had an

eigenvalue higher than 1 (1.866), which explained 62.200 % of the variance. A clear elbow was

recognised in the scree plot after 1 component. The scale of brand familiarity had a Cronbach's alpha

of 0.681 (Table 3). It has to be taken into account that this scale only contained 3 items. Screening of

the items did not provide a reason to remove one of the items.

These analyses indicated that the scales measured the constructs in a reliable way. Therefore, after

reversing the concerned items, the summed average of the items was used in the data-analyses to

represent the scale and the associated construct. This procedure was conducted for all scales.

4.2 Defining variables

Before starting the data analyses, definitions of the measures are given as a start. The independent

variable 'situational goal' referred to the presence or absence of the description of the TV evening.

The independent variable 'branded product' referred to whether M&M's (branded product) or

chocopeanuts (non-branded product) were shown.

There were two measures of the concept impulse buying. The first measure of impulse buying

concerned product choice. Chosen products which were not on the shopping list were considered as

impulse purchases. 'M&M's/chocopeanuts impulse' (binary variable) was most important as subject

of this study. The effects on other snack impulse purchases were tested as well for better

26

understanding of snacks impulse buying, in this study 'crisps impulse' and 'olives impulse' (both

binary variables). The binary variable 'general impulse' was constructed as an concept indicating

whether or not the participant choose an impulse product from all the products in the study. This

could be any product not on the shopping list. The second measure of impulse buying concerned an

adjusted version of the CIS. Participants self-reported how impulsive their product choice was. This

self-report concerned all purchases in one and was referred to as 'CIS'. Analyses were conducted for

the M&M's/chocopeanuts impulse, the other snack impulses, general impulse and for CIS.

There were three measures of the concept dominant goal-derived categorisation. First, goal-derived

and taxonomic categorisation were measured by means of the map of the hypothetical supermarket

(Figure 5). Participants indicated the first department they would go to in order to find

M&M's/chocopeanuts. Only one participant (0.4%) indicated an irrelevant department (pasta, rice

and sauces). The indication of this irrelevant department was not of interest in this study, hence this

one response was not taken into account. A binary variable was constructed to indicate whether the

indicated department was a goal-derived department or not (hereafter referred to as 'indicate

department').

Second, dominant goal-derived and taxonomic categorisation was measured by asking the

participants to indicate why they choose a particular department. The participants chose from a list

of alternatives, which made it a closed question. This measure is hereafter referred to as 'indicate

reason'. A binary variable was constructed regarding whether indicate reason was goal-derived or

not. In addition, a binary variable was constructed regarding whether indicate reason was goal-

derived in terms of snacking or not.

Third, dominant goal-derived and taxonomic categorisation was measured by asking the participants

to rate the appropriateness of several (taxonomic and goal-derived) categories for

M&M's/chocopeanuts. This measure is hereafter referred to as 'appropriateness'.

4.3 Relationship between measures of the same construct In this study, the constructs impulse buying and dominant categorisation were measured with

several measures. The relationship between the different measures of the same construct is analysed

in order to evaluate whether these measures are related and measure the same construct.

4.3.1 Impulse buying

A Pearson correlation was used in order to check whether both measures of impulse buying (product

choice and the adjusted version of the CIS) were related and did measure the same concept. There

was a significant positive relationship between both measures of impulse buying for

M&M's/chocopeanuts impulse (r=0.313, p <0.001) (medium effect size, Field, 2013), crisps impulse

(r=0.256, p <0.001) (small effect size, Field, 2013). The analysis showed a trend towards a significant

positive relationship between olives impulse (r=0.121, p=0.068) (small effect size, Field, 2013) and CIS

(i.e. p≤0.1). There was a significant positive relationship between both measures of impulse buying

for general impulse (r=0.295, p <0.001) (small effect size, Field, 2013).

A binary logistic regression with as independent variable CIS and as dependent variable

M&M's/chocopeanuts impulse (Nagelkerke R2=0.151) confirmed this positive significant relationship

by showing a significant positive effect (B=1.072, df=1, S.E.=0.244, Wald=19.289, p<0.001,

Exp(B)=2.920, 95% CI [1.810; 4.710]). The binary logistic regression with as independent variable CIS

27

and dependent variable crisps impulse (Nagelkerke R2=0.089) confirmed the positive significant

relationship as well (B=0.714, df=1, S.E.=0.191, Wald=13.892, p<0.001, Exp(B)=2.041, 95% CI [1.403;

2.971]). The binary logistic regression with as independent variable CIS and as dependent variable

olives impulse (Nagelkerke R2=0.021) showed a trend towards a positive effect (B=0.338, df=1,

S.E.=0.187, Wald=3.279, p=0.070, Exp(B)=1.402, 95% CI [0.973; 2.021]). A binary logistic regression

with as independent variable CIS and dependent variable general impulse (Nagelkerke R2=0.165)

confirmed the positive significant relationship by showing a significant positive effect (B=1.271, df=1,

S.E.=0.302, Wald=17.756, p<0.001, Exp(B)=3.563, 95% CI [1.973; 6.435]).

Hence, it was supported that both measures of impulse buying measure approximately the same

concept. Caution is needed when comparing both measures of impulse buying for olives impulse,

since the analyses showed a trend towards a significant positive association between olives impulse

and CIS. For the other measures, significant positive associations were present.

4.3.2 Goal-derived categorisation

A Pearson correlation was used in order to check whether the measures of goal-derived

categorisation were related and measured the same concept. There was a significant positive

relationship between the measures goal-derived indicate department and goal-derived indicate

reason (r=0.408, p <0.001). This relationship revealed a medium effect size (Field, 2013). There was

also a significant positive relationship between the measures goal-derived indicate department and

snacking goal-derived indicate reason (r=0.416, p <0.001). This relationship revealed a medium effect

size as well (Field, 2013).

A binary logistic regression with as independent variable appropriateness of the goal-derived

category TV evening and as dependent variable goal-derived indicate department (Nagelkerke

R2=0.031) showed a trend towards a positive relationship (B=0.247, df=1, S.E.=0.127, Wald=3.773,

p=0.052, Exp(B)=1.280, 95% CI [0.998; 1.641]). A binary logistic regression with as independent

variable appropriateness of the goal-derived category TV evening and as dependent variable goal-

derived indicate reason (Nagelkerke R2=0.026) showed a trend towards a positive relationship

(B=0.204, df=1, S.E.=0.108, Wald=3.528, p=0.060, Exp(B)=1.226, 95% CI [0.991; 1.517]). A binary

logistic regression with as independent variable appropriateness of the goal-derived category TV

evening and as dependent variable snacking goal-derived indicate reason (Nagelkerke R2=0.029)

showed a significant positive relationship (B=0.220, df=1, S.E.=0.111, Wald=3.954, p=0.047,

Exp(B)=1.246, 95% CI [1.003; 1.548]).

The Pearson correlations showed that it was supported that goal-derived indicate department and

(snacking) goal-derived department measure approximately the same concept. It was supported that

the appropriateness of the goal-derived category TV evening and snacking goal-derived indicate

reason measure approximately the same concept. Some caution is needed when comparing the

measures of goal-derived categorisation appropriateness of TV evening and goal-derived indicate

department, as well as when comparing appropriateness of TV evening and goal-derived indicate

reason.

4.4 Manipulation check

As manipulation check for the manipulation of situational goal, participants indicated at the end of

the survey which intentions they were given during the experiment. The frequency of chosen

intentions showed a clear difference between the conditions with a situational goal and the

28

conditions without a situational goal (Table 4). The participants in the conditions with a situational

goal indicated the corresponding intention much more often than the participants in the conditions

without a situational goal. Furthermore, the chi-square test showed that there was a significant

association between condition and the situational goal( χ2 (3) =55.927, p< 0.001). This implied that

the participants were aware of the presence of the situational goal which created a successful

manipulation.

4.5 Tests on demographics and characteristics

Analyses were conducted in order to examine the effects of the additional variables (frequency of

snacking, liking of chocolate and bitesizes, brand familiarity (with M&M's), frequency of shopping,

disposable income, gender, age and level of education) in combination with the main effect of the

independent variables (branded product and situational goal) on the dependent variable (impulse

buying).

A binary logistic regression of branded product, situational goal, their interaction effect and the

additional variables on M&M's/chocopeanuts impulse (Nagelkerke R2=0.322) (df=1) showed that

frequency of snacking had a significant negative effect on M&M's/chocopeanuts impulse (Table 5):

the more frequent participants snacked, the less likely was a M&M's/chocopeanuts impulse. Liking of

white chocolate had a positive significant effect, as well as gender (Table 5). This meant that

participants who liked white chocolate more were more likely to impulsively choose to buy

M&M's/chocopeanuts. Women were more likely to choose for an impulsive purchase of

M&M's/chocopeanuts than men. Age had a significant negative effect on the impulse purchase of

M&M's/chocopeanuts (Table 5): the older the participants, the less likely a M&M's/chocopeanuts

impulse choice. Situational goal had a positive significant effect (Table 5). The presence of a

situational goal made M&M's/chocopeanuts impulse buying more likely.

The binary logistic regression of the independent variables, the additional variables and crisps

impulse (Nagelkerke R2=0.479) (df=1) showed that liking of crisps had a positive significant effect as

well as situational goal (Table 5). The presence of a situational goal made crisps impulse buying more

likely.

The binary logistic regression of the independent variables, the additional variables and olives

impulse (Nagelkerke R2=0.304) (df=1) showed that age had a positive significant effect (Table 5). The

older the participant, the more often impulse buying of olives was conducted.

29

The binary logistic regression of the independent variables, the additional variables and general

impulse (Nagelkerke R2=0.326) (df=1) showed that liking of dark chocolate and liking of popcorn had

a significant negative effect (Table 5). The more dark chocolate/popcorn was liked, the less likely was

general impulse buying. Branded product as well as situational goal had a significant positive effect

on general impulse buying. The presence of a branded product/a situational goal made general

impulse buying more likely. The interaction effect of branded product and situational goal had a

significant negative effect: the presence of a branded product in combination with the presence of a

situational goal made general impulse buying less likely (Table 5).

A linear regression was conducted regarding the effect of the independent variables (branded

product and situational goal) and the additional variables on CIS (F(13,212)=3.238, p<0.001) (Table 6).

Liking of chocolate in general had a significant negative effect, liking of chocolate with nuts had a

significant positive effect, liking of crisps had a significant positive effect and disposable income had a

significant positive effect. Branded product had a significant positive effect on impulse buying. The

analysis showed a trend (i.e. p≤0.1) towards a significant negative interaction effect of branded

product and situational goal on impulse buying (Table 6).

In order to minimize noise in the conceptual model in an efficient way, additional variables which had

a significant effect on M&M's/chocopeanuts impulse (focus of the research) were considered as

covariates for hypotheses testing. The variable 'liking of white chocolate' was not included, because

this was a rather specific and less explicable variable in comparison to the variables 'gender' and

'age'. In order to be consistent, none of the types of chocolate was included. A binary logistic

regression of branded product, situational goal, their interaction effect, gender, age and frequency of

snacking on M&M's/chocopeanuts impulse (Nagelkerke R2=0.280) (df=1) did not show a significant

effect of 'frequency of snacking' anymore (B=-0.252, df=1, S.E.= 0.250, Wald=1.018, p=0.313, Exp(B)=

0.777, 95% CI [0.476; 1.269]). Therefore, 'frequency of snacking' was not included as covariate. In this

light, the variables age and gender were included as covariates in the hypotheses testing in order to

clear the data-analyses of the conceptual model.

30

31

4.6 Main effect and interaction effect with selected covariates

First, analyses were conducted in order to give insights in whether the presence of a branded

product or the presence of a situational goal stimulates impulse buying more. Therefore, the effect

of the independent variables branded product and situational goal and their interaction effect

directly on the ultimate dependent variable impulse buying was measured. The insights from these

analyses provide an answer to sub question 3 (whether a branded product or a situational goal is

more effective in stimulating impulse buying). The analyses were conducted for all measures of

impulse buying and included the covariates age and gender.

A binary logistic regression of branded product, situational goal, their interaction effect and the

control variables age and gender on M&M's/chocopeanuts impulse (Nagelkerke R2=0.210) (df=1)

showed that situational goal had a significant positive effect, age had a significant negative effect and

gender had a significant positive effect (Table 7). This meant that the presence of a situational goal

made a M&M's/chocopeanuts impulse more likely. Younger participants/women were more likely to

conduct a M&M's/chocopeanuts impulse than older participants/men.

A binary logistic regression of branded product, situational goal, their interaction effect and the

control variables age and gender on crisps impulse (Nagelkerke R2=0.411) (df=1) showed that

situational goal had a positive significant effect, which was relatively large (B=3.007), age had a

significant negative effect (Table 7).

A binary logistic regression of branded product, situational goal, their interaction effect and the

control variables age and gender on olives impulse (Nagelkerke R2=0.265) (df=1) showed that age had

a significant positive effect (Table 7). The older the participants, the more often olives impulse buying

was conducted.

A binary logistic regression of branded product, situational goal, their interaction effect and the

control variables age and gender on general impulse (Nagelkerke R2=0.217) (df=1) showed that

32

branded product and situational goal both had a significant positive effect (Table 7). The presence of

a branded product/situational goal made general impulse buying more likely. The effect of situational

goal (B=3.357) was larger than the effect of branded product (B=0.933). There was a trend towards a

significant negative interaction effect (i.e. p≤0.1) of branded product and situational goal (Table 7).

A linear regression of branded product, situational goal, their interaction effect and the control

variables age and gender on CIS (F(5,220)=2.118, p=0.064) showed that branded product had a

significant positive effect (Table 8). The presence of a branded product made impulse buying more

likely. The interaction effect of branded product and situational goal had a significant negative effect

(Table 8). The presence of a branded product in combination with the presence of a situational goal

made impulse buying less likely.

33

An ANOVA with branded product, situational goal, their interaction effect and the control variables

age and gender on CIS was conducted. This analysis provided more insight in the interaction effect of

branded product and situational goal on CIS (F(1,220)=6.005, p=0.015) by means of Figure 6.

Figure 6. Interaction effect of branded product and situational goal on CIS. The crossing of the lines

indicates an interaction effect. The analysis of the interaction effect controlled for age and gender.

The meaning of this interaction effect was analysed by looking at the effect of one of the

independent variables at individual levels (absent vs. present) of the other independent variable. This

meant that for instance the effect of the presence of a branded product with both the absence and

presence of a situational goal was analysed. Age and gender were included as covariates. A simple

effects analysis of the effect of branded product on CIS for each level of situational goal was

conducted. There was a significant difference between participants with a branded product and a

non-branded product when a situational goal was absent (F(1,220)=8.931, p=0.003). There was no

significant difference between participants with a branded product and participants with a non-

branded product when a situational goal was present (F(1,220)=0.246, p=0.620). This was interpreted

as follows: when a situational goal is absent participants more often impulsively bought a product

when they were conditioned with a branded product than participants conditioned with a non-

branded product (Figure 6). The difference between a branded and a non-branded product was not

significant when a situational goal was present.

34

A simple effects analysis of the effect of situational goal on CIS for each level of branded product was

conducted. There was no significant difference between participants with a situational goal and

participants without a situational goal with a non-branded product (F(1,220)=2.219, p=0.138). There

was a significant difference between participants with a situational goal and participants without a

situational goal with a branded product (F(1,220)=3.977, p=0.047). This was interpreted as follows:

with a non-branded product there is no significant difference in the effect on impulse buying

between the presence and the absence of a situational goal. With a branded product, there is a

significant difference between the presence and the absence of a situational goal. When a situational

goal is absent, participants with a branded product conducted more often impulse buying than when

a situational goal is present (Figure 6).

Thus, when a situational goal is absent, a branded product caused more often impulse buying than a

non-branded product. A branded product caused more often impulse buying when a situational goal

was absent than when a situational goal is present. This confirmed the statement of the theoretical

framework that the effect of branded product is different for different values of situational goal

(absent vs. present).

The interaction effect is not included in the hypotheses, but does show the power of a branded

product.

Thus, all in all, there were some main effects. The presence of a situational goal made

M&M's/chocopeanuts impulse buying more likely. The presence of a situational goal made crisps

impulse buying more likely and this effect was relatively large (B=3.007). The presence of a branded

product, as well as the presence of a situational goal made general impulse buying more likely. The

second measure of impulse buying showed that the presence of a branded product made impulse

buying more likely. There was a significant negative interaction effect of branded product and

situational goal. This meant that the presence of a branded product in combination with the

presence of a situational goal made impulse buying less likely. The simple effects analyses based on

CIS showed that when a situational goal is absent, a branded product caused more often impulse

buying than a non-branded product. A branded product caused more often impulse buying when a

situational goal was absent than when a situational goal is present.

4.7 Hypotheses testing

4.7.1 The effect of leading branded products on the exemplar (H1)

Hypothesis 1 is about the exemplar, i.e. the product that the participant mentioned as best known

example of the self-constructed product category based on M&M's/chocopeanuts. A crosstab of

branded product and exemplar (4 categories: M&M's (leading brand), goal-derived, taxonomic and

other brands) controlled for gender and age based on a Fisher-Freeman-Halton test, showed that

there is a relation between branded product condition and exemplar (19.453, p<0.001). There was an

underlying relationship between being female and exemplar (17.780, p<0.001). This meant that the

relationship between the presence of a branded product and the indicated exemplar may be the

result of differences in gender.

There was a significant association between branded product and M&M's indicated as exemplar (χ2

(1) = 8.570, p=0.004). This provided support for H1. There was an underlying relationship between

being female and M&M's indicated as exemplar (χ2 (1) = 7.357, p=0.007). The relationship between

35

the presence of a branded product and M&M's indicated as exemplar was influenced by the

difference in gender.

The frequency table (Table 9) showed that participants in the condition branded product indicated

M&M's (i.e. the leading brand) less often as exemplar than participants in the condition non-branded

product. A binary logistic regression with as dependent variable whether or not M&M's was

indicated as exemplar based on branded product controlled for age and gender (Nagelkerke

R2=0.062) confirmed this. The participants in the condition branded product indicated less often the

leading brand (M&M's) as exemplar than participants in the condition non-branded product (B=-

0.988, df=1, S.E.=0.345, Wald=8.202, p=0.004, Exp(B)= 0.372, 95% CI [0.189; 0.732]). Hence, the

relationship seemed to be the opposite direction as expected by H1, which meant that H1 was not

supported.

Thus, both the crosstab and the binary logistic regression showed a significant relation between

branded product and M&M's indicated as exemplar. This relationship existed however in the

opposite direction as was expected by H1.

4.7.2 The effect of branded product and situational goal on type of categorisation (H2) (H3)

The dominant (goal-derived) categorisation was measured in three ways. Analyses were conducted

per measure in order to test H2 and H3.

First measure of categorisation

A binary logistic regression of branded product and situational goal on indicate department

controlled for age and gender (Nagelkerke R2=0.083) showed that the independent variables did not

have a significant effect on dominant goal-derived categorisation: branded product (B=-0.169, df=1,

S.E.=0.557, Wald=0.093, p=0.761, Exp(B)=0.844, 95% CI [0.283; 2.514]), situational goal (B=0.583,

df=1, S.E.=0.502, Wald=1.352, p=0.245, Exp(B)=1.792, 95% CI [0.670; 4.791]). Also the interaction

effect had no significant effect (B=-0.340, df=1, S.E.= 0.754, Wald=0.203, p=0.652, Exp(B)=0.712, 95%

CI [0.162; 3.121]). Gender had a significant negative effect (B=-1.170, df=1, S.E.= 0.410, Wald=8.131,

p=0.004, Exp(B)=0.310, 95% CI [0.139; 0.694]). This meant that women were less likely to indicate a

goal-derived department than men.

The fact that no significant effects of the independent variables regarding goal-derived categorisation

were present could be explained by the frequencies of the indicated departments (Figure 7). In all

conditions participants indicated taxonomic departments most often. This created a ceiling effect,

since taxonomic categorisation was that dominant. The ceiling effect made the analysis of H2 and H3

by means of the measure indicate department inconclusive. It is however unsure whether indicate

department could not measure the categorisation process of the participants well or whether there

36

was no difference in categorisation as result of the manipulations. In needs to be discussed whether

this ceiling effect was created by an empirical or a theoretical problem.

Figure 7. Frequency indicated department per condition. This figure shows the frequency of the

classification of the indicated department per condition to measure dominant categorisation. See

Table 1 for a description of the conditions.

Second measure of categorisation

A binary logistic regression of branded product and situational goal on indicate goal-derived reason

controlled for age and gender (Nagelkerke R2=0.080) showed that branded product had no significant

effect on goal-derived categorisation (B=0.024, df=1, S.E.=0.534, Wald=0.002, p=0.965, Exp(B)=1.024,

95% CI [0.360; 2.914]). Situational goal had a significant effect on goal-derived categorisation,

participants in the conditions with a situational conducted more often goal-derived categorisation

than participants without a situational goal (B=1.064, df=1, S.E.= 0.475, Wald=5.023, p=0.025,

Exp(B)=2.897, 95% CI [1.143; 7.345]). This provided support for H2. The interaction effect of branded

product and situational goal on goal-derived categorisation was not significant (B=-0.325, df=1,

S.E.=0.683, Wald=0.226, p=0.634, Exp(B)=0.723, 95% CI [0.189; 2.756]).

A binary logistic regression of branded product and situational goal on indicate snacking goal-derived

reason controlled for age and gender (Nagelkerke R2=0.082) showed that branded product had no

significant effect on snacking goal-derived categorisation (B=-0.101, df=1, S.E.=0.546, Wald=0.034,

p=0.853, Exp(B)=0.904, 95% CI [0.310; 2.634]). Situational goal had a significant effect on snacking

goal-derived categorisation, participants in the conditions with a situational goal conducted more

often snacking goal-derived categorisation than participants without a situational goal (B=1.067,

df=1, S.E.= 0.474, Wald=5.062, p=0.024, Exp(B)=2.906, 95% CI [1.147; 7.360]). This provided support

for H2. The interaction effect of branded product and situational goal on snacking goal-derived

categorisation was not significant (B=-0.210, df=1, S.E.=0.692, Wald=0.092, p=0.761, Exp(B)=0.810,

95% CI [0.209; 3.148]).

Thus, the binary logistic regressions showed that the presence of a situational goal makes goal-

derived categorisation more likely, which supported H2. This effect applied both to goal-derived

37

categorisation and goal-derived categorisation in terms of snacking. Branded product did not have a

significant effect on the dominant categorisation, which did not supported that participants in the

conditions branded product are more likely to categorise primary in a taxonomic way and secondary

in a goal-derived way. This did not provide support for H3.

Third measure of categorisation

Several linear regression analyses were conducted regarding the appropriateness of the different

goal-derived and taxonomic categories.

The linear regression of branded product, situational goal and their interaction effect on

appropriateness of snacks (taxonomic categorisation) controlled for age and gender (F(5,220)=

10.588, p<0.001) showed that branded product had no significant effect (B=-0.472, S.E.=0.338,

t(220)=-1.395, p=0.164 , 95% CI [-1.138; 0.195]) and that situational goal had no significant effect (B=-

0.062, S.E.=0.332, t(220)=-0.187, p=0.852, 95% CI [-0.717; 0.593]). The interaction effect of branded

product and situational goal was not significant (B=-0.681, S.E.=0.480, t(220)=-1.419, p=0.157, 95% CI

[-1.627; 0.265]). Age had a significant negative effect (B=-0.045, S.E.=0.008, t(220)=-5.592, p<0.001,

95% CI [-0.060; -0.029]). This meant that the older the participant, the less likely that he/she

considered the category snack as appropriate.

The linear regression of branded product, situational goal and their interaction effect on

appropriateness of the category sporting (goal-derived categorisation) controlled for age and gender

(F(5,220)=3.489, p=0.005) showed that branded product had a significant effect (B=0.471, S.E.=0.219,

t(220)=2.155, p=0.032, 95% CI [0.040; 0.901]). This indicated that participants with a branded

product were more likely to consider the category sporting as appropriate for M&M's than

participant without a branded product for chocopeanuts. Situational goal had no significant effect

(B=0.308, S.E.=0.215, t(220)=1.432, p=0.154, 95% CI [-0.116; 0.731]). The interaction effect of

branded product and situational goal was significant (B=-0.844, S.E.=0.310, t(220)=-2.721, p=0.007,

95% CI [-1.456; -0.233]). This indicated that participants with a branded product and with a

situational goal were less likely to consider the category sporting as appropriate than participants

without a branded product and without a situational goal. Gender had a significant negative effect:

women considered the category sporting more often as less appropriate than men (B=-0.537,

S.E.=0.191, t(220)=-2.817, p=0.005, 95% CI [-0.913; -0.161]).The findings did not support a hypothesis

and the goal-derived categorisation was based on sporting instead of snacking. However, the positive

relation between branded product and goal-derived categorisation could result from secondary

categorisation. Another interesting finding was that participants with a branded product and with a

situational goal were less likely to see the goal-derived sports category as appropriate for M&M's.

This effect seemed similar to the interaction effect of branded product and situational goal on CIS.

There, the presence of a branded product in combination with the presence of a situational goal

made impulse buying less likely.

Regarding the linear regressions of the effect of branded product, situational goal and their

interaction effect on dominant categorisation controlled for age and gender, there were no

significant effects of the independent variables for the appropriateness of the other categories

(Appendix D). This did not provide support for H2 and H3.

As a conclusion, all in all, the first measure of categorisation (indicate department) showed a very

dominant effect of taxonomic categorisation. Because of this ceiling effect, no conclusions could be

38

inferred. The very dominant effect of taxonomic categorisation made the analyses of H2 and H3

inconclusive. The second measure of categorisation (indicate reason) provided support for H2:

participants with a situational goal conducted more often goal-derived categorisation than

participants without a situational goal. The effect of situational goal was significant for both goal-

derived categorisation and goal-derived categorisation in terms of snacking. The third measure of

categorisation (appropriateness) did not show significant effects of branded product, situational goal

and their interaction effect on goal-derived categorisation of a TV evening. Hence, the third measure

of categorisation did not provide support for support H2 and H3.

4.7.3 Primary and secondary categorisation (H3)

In order to test H3, the effect of M&M's as exemplar on goal-derived categorisation controlled for

age and gender was measured. This was done for all measures of dominant goal-derived

categorisation. Crosstabs of exemplar (M&M's) and dominant categorisation were constructed

regarding the categorisation measures indicate department and indicate reason. The relationship

between exemplar (M&M's) and goal-derived categorisation regarding the categorisation measure

appropriateness was measured by means of a linear regression.

The crosstabs showed by means of a Pearson chi-square test that there existed no significant

relationships between taxonomic categorisation based on an exemplar (M&M's) and goal-derived

indicate department (χ2 (1) = 0.286, p=0.671), goal-derived indicate reason (χ2 (1) = 0.167, p=0.707)

and snacking goal-derived indicate reason (χ2 (1) = 0.107, p=0.847). These findings did not provide

support for H3.

The linear regression with as dependent variable appropriateness of the TV evening category (goal-

derived categorisation) and as independent variable whether M&M's was indicated as exemplar or

not controlled for age and gender (F(3,222)=15.554, p<0.001) showed that exemplar had no

significant effect on goal-derived categorisation (B=0.348, S.E.=0.245, t(222)=1.419, p=0.157 , 95% CI

[-0.135; 0.831]). This finding did not support H3. Age had a significant negative effect: the older the

participants, the less appropriate they considered the TV evening category (B=-0.042, S.E.=0.007,

t(222)=-6.203, p<0.001 , 95% CI [-0.055; -0.028]).

Thus, the data-analyses showed that there was no support for H3.

4.7.4 Snacking behavioural script and impulse buying (H5)

The effect of the activation of a snacking behavioural script (hereafter 'SRHI') on impulse buying was

measured by analysing the effect of the mean of the SRHI scale on the different measures of impulse

buying controlled for age and gender. The SRHI measured the presence of a general snacking habit,

thus not the particular habit of e.g. chocolate (peanut) snacking. Binary logistic regressions were

conducted in order to test the effect of SRHI on product choice as impulse. A linear regression was

conducted in order to test the effect of SRHI on CIS.

The binary logistic regression of the SRHI on M&M's/chocopeanuts impulse controlled for age and

gender (Nagelkerke R2=0.192) did not show a significant effect of SRHI (B=0.232, df=1,S.E.=0.169,

Wald=1.883, p=0.170, Exp(B)=1.261,95% CI [0.906; 1.755]). Age had a significant negative effect: the

older the participants, the less likely was a M&M's/chocopeanuts impulse (B=-0.062, df=1,S.E.=0.020,

Wald=9.848, p=0.002, Exp(B)=0.940,95% CI [0.904; 0.977]). The binary logistic regression with as

dependent variable crisps impulse controlled for age and gender (Nagelkerke R2=0.024) did not show

39

a significant effect of SRHI (Nagelkerke R2=0.024) (B=0.099, df=1, S.E.= 0.119, Wald=0.697, p=0.404,

Exp(B)=1.104,95% CI [0.875; 1.394]). The effect of SRHI on olives impulse controlled for age and

gender (Nagelkerke R2=0.248) was not significant (B=-0.017, df=1, S.E.=0.135, Wald=0.017, p=0.897,

Exp(B)=0.983,95% CI [0.754; 1.280]). Age had a significant positive effect: the older the participants,

the more likely was an olives impulse (B=0.062, df=1, S.E.=0.011, Wald=31.453, p<0.001,

Exp(B)=1.064,95% CI [1.041; 1.087]). The binary logistic regression on general impulse controlled for

age and gender (Nagelkerke R2=0.010) did not show a significant of SRHI (B=0.126, df=1, S.E.= 0.172,

Wald=0.537, p=0.464, Exp(B)=1.134,95% CI [0.810; 1.588]). Since the data-analyses of the first

measure of impulse buying did not show significant effects of SRHI, there was no support for H5.

A linear regression with SRHI and CIS controlled for age and gender (F(3, 222)= 2.805, p=0.041)

showed a significant effect of SRHI on impulse buying (B=0.120, S.E.= 0.045, t(222)= 2.661, p=0.008,

95% CI [0.031; 0.210]). The more likely the activation of a snacking behavioural script, the more likely

it was that impulse buying was conducted. This provided support for H5.

Thus, there is partial evidence for H5: the first measure of impulse buying is more realistic as it

measured actual choice. The binary logistic regressions did not show significant effects of SRHI on the

product choices. The linear regression regarding the second measure of impulse buying (CIS) is

statistically stronger and showed a significant positive effect of SRHI on impulse buying. This

provided support for H5. However, the second measure of impulse buying is further removed from

reality as being a self-report.

4.7.5 The effect of goal-derived categorisation and impulsiveness on a snacking behavioural script

(H4)(H6)

In order to test H4 and H6, linear regressions were conducted including the three different measures

of dominant (goal-derived) categorisation. These linear regressions included also the measure of the

activation of a snacking behavioural script (SRHI), impulsiveness as a personality trait (hereafter

'ABIS') and the covariates age and gender. 'Mean centering' was used in order to reduce disruptions

because of collinearity.

First, a linear regression was conducted with as dependent variable SRHI and independent variables

ABIS, goal-derived indicate department and their interaction effect controlled for age and gender.

The linear regression (F(5, 220)=10.642, p<0.001) showed that the effect of goal-derived

categorisation was not significant (B=-0.172, S.E.=0.207, t(220)=-0.833, p=0.406, 95% CI [-0.581;

0.236], VIF=1.070), which did not support H4. The interaction effect on the SRHI was not significant

(B=-0.872, S.E.=0.542, t(220)=-1.610, p=0.109, 95% CI [-1.939; 0.195], VIF=1.035), which did not

support H6. There was a significant effect of the ABIS on SRHI (B=0.619, S.E.=0.188, t(220)=3.294,

p=0.001, 95% CI [0.249; 0.989], VIF=1.024). This means that the more impulsive someone is as a

person, the more likely the activation of a snacking behavioural script. There was no hypothesis on

this main effect of ABIS. Age had a significant negative effect: the older the participants the less often

a snacking behavioural script was activated (B=-0.022, S.E.=0.005, t(220)=-4.322, p<0.001, 95% CI [-

0.032; -0.012], VIF=1.069). Gender had a significant positive effect: women were more likely to have

an activated snacking behavioural script than men (B=0.546, S.E.=0.190, t(220)=2.873, p=0.004, 95%

CI [0.172; 0.921], VIF=1.079).

Second, a linear regression with SRHI, ABIS, indicate goal-derived reason and their interaction effect

controlled for age and gender (F(5, 220)=10.284, p<0.001) showed that the effect of goal-derived

40

categorisation was not significant (B=-0.170, S.E.=0.183, t(220)=-0.926, p=0.356, 95% CI [-0.531;

0.192],VIF=1.042), which did not support H4. The interaction effect of ABIS and goal-derived indicate

reason was not significant (B=-0.457,S.E.=0.497,t(220)=-0.919,p=0.359,95%CI[-1.436;

0.523],VIF=1.043), which did not provide support for H6. There was no relevant change in the

significant effect of the ABIS on SRHI (B=0.615, S.E.=0.190, t(220)= 3.241, p=0.001, 95% CI [0.241;

0.989],VIF=1.038), the significant negative effect of age (B=-0.022, S.E.=0.005, t(220)=-4.391,

p<0.001, 95% CI [-0.032; -0.012],VIF=1.074) and the significant positive effect of gender (B=0.564,

S.E.=0.187, t(220)=3.011, p=0.003, 95% CI [0.195; 0.934],VIF=1.042).

A linear regression was conducted in order to test H4 and H6 with the particular goal-derived

categorisation of indicate snacking reason controlled for age and gender (F(5, 220)=10.221 ,p<0.001).

The effects were about the same as the linear regression with goal-derived indicate reason. The

effect of snacking goal-derived categorisation was not significant (B=-0.106, S.E.=0.184, t(220)=-

0.575, p=0.566, 95% CI [-0.469; 0.257],VIF=1.037), which did not support H4. The interaction effect of

snacking goal-derived categorisation and ABIS was not significant (B=-0.511, S.E.=0.497, t(220)=-

1.027, p=0.306, 95% CI [-1.491; 0.470],VIF=1.038), which did not support H6. There was no relevant

change in the significant effect of the ABIS on SRHI (B=0.621, S.E.=0.190, t(220)= 3.279, p=0.001, 95%

CI [0.248; 0.995],VIF=1.034), the significant effect of age (B=-0.022, S.E.=0.005, t(220)=-4.338,

p<0.001, 95% CI [-0.032; -0.012],VIF=1.069) and the significant effect of gender (B=0.568, S.E.=0.187,

t(220)=3.032, p=0.003, 95% CI [0.199; 0.938],VIF=1.040).

Third, a linear regression was conducted with as dependent variable SRHI and independent variables

ABIS, appropriateness of the goal-derived derived category TV evening, and their interaction effect

controlled for age and gender (F(5, 220)= 10.581, p<0.001). The effect of appropriateness of the goal-

derived category TV evening on SRHI was not significant (B=0.058, S.E.=0.050, t(220)=1.166, p

=0.245, 95% CI [-0.040; 0.156], VIF=1.206), which did not support H4. The interaction effect of ABIS

and appropriateness of the goal-derived category TV evening on SRHI was not significant (B=-0.123,

S.E.=0.114, t(220)=-1.082, p=0.281, 95% CI [-0.347; 0.101], VIF=1.021), which did not support H6.

Also here, there was no relevant change in the significant effect of the ABIS on SRHI (B=0.650,

S.E.=0.187, t(220)=3.481, p=0.001, 95% CI [0.282; 1.018],VIF=1.010), the significant effect of age (B=-

0.019, S.E.=0.005, t(220)=-3.500, p=0.001, 95% CI [-0.030; -0.008],VIF=1.237) and the significant

effect of gender (B=0.543, S.E.=0.187, t(220)=2.903, p=0.004, 95% CI [0.174; 0.912],VIF=1.045).

A linear regression with the appropriateness of the goal-derived category sporting controlled for age

and gender (F(5, 220)= 10.445, p<0.001) did not show a significant effect of goal-derived

categorisation (based on sporting) (B=-0.092, S.E.=0.065, t(220)=-1.408, p=0.160, 95% CI [-0.220; -

0.037], VIF=1.044), which did not support H4. The interaction effect of ABIS and goal-derived

categorisation on SRHI was not significant (B=0.066, S.E.=0.168, t(220)=0.395, p=0.693, 95% CI [-

0.265; 0.397], VIF=1.006), which did not support H6. There was no relevant change in the significant

effect of the ABIS on SRHI (B=0.669, S.E.=0.187, t(220)=3.567, p<0.001, 95% CI [0.299; 1.038],

VIF=1.015), the significant effect of age (B=-0.022, S.E.=0.005, t(220)=-4.439, p<0.001, 95% CI [-0.032;

-0.012],VIF=1.049) and the significant effect of gender (B=0.509, S.E.=0.191, t(220)=2.669, p=0.008,

95% CI [0.133; 0.885],VIF=1.081).

As an extra test the appropriateness of the taxonomic category chocolate was analysed regarding H4

and H6. A linear regression was conducted with as dependent variable SRHI and independent

41

variables ABIS, appropriateness of the taxonomic category chocolate and their interaction effect

controlled for age and gender (F(5, 220)=13.526, p<0.001). The effect of appropriateness of the

taxonomic category chocolate showed a trend towards a significant positive effect on SRHI (B=0.124,

S.E.=0.070, t(220)=1.766, p=0.079, 95% CI [-0.014; 0.262], VIF=1.245). The interaction effect of ABIS

and taxonomic categorisation on SRHI was not significant (B=0.161, S.E.=0.183, t(220)=0.877,

p=0.381, 95% CI [-0.200; 0.521], VIF=1.201). There was no relevant change in the significant effect of

the ABIS on SRHI (B=0.628, S.E.=0.188, t(220)=3.348, p=0.001, 95% CI [0.258; 0.998], VIF=1.021) the

significant effect of age (B=-0.021,S.E.=0.005,t(220)=-4.138,p<0.001,95%CI [-0.031;-0.011],VIF=1.071)

and the significant effect of gender (B=0.525, S.E.=0.188, t(220)=2.788, p=0.006, 95% CI [0.154;

0.896],VIF=1.059). The findings of this linear regression do not support a hypothesis, but show a

trend towards a significant positive effect of taxonomic categorisation on the activation of a snacking

behavioural script.

Although there was no main effect of goal-derived categorisation on the activation of a behavioural

script (H4), nor an interaction effect of goal-derived categorisation and impulsiveness as a personality

trait on the activation of a behavioural script (H6), there was a non hypothesised main effect of

impulsiveness as a personality trait (ABIS) on the activation of the behavioural script (SRHI).

42

5 Discussion

5.1 Main results The aim of this study was to research the influence of branded products and situational goals on

impulse buying and thus shining new light on the influence of situational effects on impulse buying.

In order to understand how the consumer links branded products and situational goals to impulse

buying, the categorisation process was analysed. This was done to provide insights in how to create

more efficient in-store marketing of chocolate bitesizes in order to stimulate impulse buying. The

study was focussed around the research question: How do situational goals and branded products

affect impulse buying in the domain of chocolate bitesizes? This chapter aims to answer this question,

provide contributions to the impulse buying literature and discuss the implications of the findings.

5.1.1 Hypotheses

The study did not provide support for H1, instead an opposite effect was found: participants who

were manipulated with a leading branded product (i.e. M&M's) indicated less often the leading

brand (M&M's) as exemplar than participants manipulated with a non-branded product. This

suggests that participants who had already seen M&M's were less inclined to mention the same

brand (M&M's) again as an exemplar than participants who had not seen M&M's before. This

difference could be attributed to the empirical set-up of the study. This implies that showing people

the leading brand (M&M's) made it rather unlikely that they would mention the leading brand later

on as exemplar. The researcher deliberately included a remark that participants could mention

brands that they had already seen or mentioned. This remark apparently did not completely reduce

participant's inclination to mention different brands at different questions. Further research should

focus on a new approach that combines the manipulation of participants with respect to whether or

not they focus on a leading branded product with the possibility that participants name an exemplar

in an unbiased way.

The results of this study provide partial evidence that the presence of a situational goal results more

likely in goal-derived categorisation than in case a situational goal is absent: the second measure of

goal-derived categorisation (indicate reason) supported H2. This finding is in line with the reasoning

that situational goals can alter category representations (Ratneshwar et al., 2001). The first measure

of goal-derived categorisation (indicate department) did not support H2. This inconsistency may be

due to the revealed ceiling effect: in all conditions taxonomic categorisation was exceedingly

dominant. Despite that this measure was chosen based on successful application in prior research

(Moreau et al., 2001), it apparently did not measure categorisation in the current study. This

discrepancy could be attributed to the fact that the research of Moreau et al. (2001) included only

taxonomic departments for a new product in their study (i.a. computers and computer accessories,

cameras). Ostensibly, the current study shows that the measure does not work when both goal-

derived and taxonomic categories are included for existing products. A reinforcing factor of the

ceiling effect is probably the question "where would you go first to find M&M's/chocopeanuts?" in

combination with the learned associations of people who often visit the supermarket. People who

often visit the supermarket have more experience with taxonomic than goal-derived departments.

M&M's/chocopeanuts are usually placed at the chocolate and candy department in the current

supermarket formats. Hence, when the participants were searching for M&M's/chocopeanuts, they

could have recognised the (chocolate and) candy department as the department where

43

M&M's/chocopeanuts belong rather than a goal-derived department. Future studies developing a

suitable measure of goal-derived and taxonomic departments considering this learned associations

for existing products are therefore recommended. The results of the third measure of goal-derived

categorisation (appropriateness) did not provide support for H2, which could be explained as well by

learned associations of the participants regarding where products belong in combination with the

inclusion of both goal-derived and taxonomic categories. In general, people have more experience

with taxonomic than goal-derived departments in a supermarket. Hence, people presumably asses

taxonomic departments as more appropriate than goal-derived departments when they are

searching for a specific product, irrespective of the manipulations in this study. In that case,

categorisation was not measured, but the difference between the acceptance of taxonomic and goal-

derived categories for searching products in the supermarket.

Barsalou (1991) stated that categorisation consists of a primary and a secondary stage. This differs

from the findings presented in this study. No support was found for the hypothesis that branded

products are primary taxonomic and secondary goal-derived categorised (H3). These results are

possibly due to the discussed ceiling effect of the first measure of categorisation, the learned

associations regarding taxonomic and goal-derived categories in the supermarket setting and the

empirical set-up of the measure of the exemplar. It was however partially supported that situational

goals were secondary categorised, since a situational goal resulted in goal-derived categorisation.

The study has been unable to demonstrate that goal-derived categorisation activates a snacking

behavioural script (H4). This outcome does not support the inference that goal-derived

categorisation works as an intuitive process which activates a behavioural script, building on prior

research (Glöckner & Witteman, 2010; Aunger, 2007). These results could be due to the discussed

effects of the empirical set-up of the categorisation measures. It may therefore be that the

categorisation was not measured by means of the first and third measure of categorisation.

Regarding the relationship between the goal-derived categorisation based on a TV evening (second

measure of categorisation) and the activation of a snacking behavioural script, age could explain the

relationship since both are more likely for younger participants.

The current study partially supported that the activation of a snacking behavioural script results in

impulse buying. The analysis regarding the second measure of impulse buying supported H5. This

result is consistent with other research which found that the activation of a behavioural script results

in behaviour (Abelson, 1981; Rumgay, 2004; Glöckner & Witteman, 2010). The discrepancy between

the results of the first and second measure of impulse buying could be attributed to the influence of

age regarding M&M's/chocopeanuts impulse buying. Age explained the relationship between the

activation of a snacking behavioural script and M&M's/chocopeanuts impulse buying, since both are

more likely for younger participants. The effect of age is consistent with earlier findings suggesting

that a snacking behavioural script is more likely for adolescents and young adults than for older

people (Savige, MacFarlane, Ball, Worsley & Crawford, 2007). Such an influence was not present

regarding the second measure of impulse buying. This discrepancy between the first and second

measure of impulse buying displays a characteristic feature of this study: the tension between

internal and external validity. The first measure of impulse buying has a relatively higher external

validity as product choice is closer to the real-world situation, but did not support H5. The second

measure of impulse buying did support H5. The second measure is statistically stronger, because the

used seven-point likert-scale for 11 items generates higher statistical power than just one measure of

44

product choice. Hence, the second measure of impulse buying has a relatively higher internal validity.

It is important to note that the second measure of impulse buying is further removed from reality as

being a self-report instead of product choice. This refers to a relatively lower external validity.

This study has been unable to demonstrate that a more impulsive personality made it more likely

that goal-derived categorisation resulted in the activation of a snacking behavioural script than a less

impulsive personality: H6 was not supported. This finding differs from the reasoning of Youn & Faber

(2000) that more impulsive people are susceptible to impulse buying for affective reasons. Their

reasoning implies that an intuitive process as goal-derived categorisation is stronger associated to a

snacking behavioural script involving impulse buying for more impulsive people than for less

impulsive people. Less impulsive people focus more on rational reasons for impulse buying (Youn &

Faber, 2000). The study did show that impulsiveness as a personality trait made the activation of a

snacking behavioural script more likely. Goal-derived categorisation is not involved, as was expected

in H6. This result is in agreement with Verplanken and Herabadi's (2001) findings that the impulse

buying tendency has a strong basis in personality. Aspects as low need for deliberation, planning,

evaluation and structure, which are seen as impulsive personality traits, stimulated the impulse

buying tendency (Verplanken & Herabadi, 2001). The snacking behavioural script is associated to

impulse buying. For that reason, a modification in the conceptual model is suggested. Impulsiveness

as a personality trait influences the activation of a behavioural script directly in a positive way.

5.1.2 Other findings

Women were more likely to conduct a M&M's/chocopeanuts impulse purchase than men, which is in

line with the findings of Tifferet & Hernstein (2012) and Verplanken and Herabadi (2001). Some

caution is due here, since the meta-analysis of consumer impulse buying (Amos, Holmes & Keneson,

2014) properly points out that the effect of gender on impulse buying is context dependent. Women

were more likely to have an activated snacking behavioural script than men. This finding differs from

the ambivalent attitude of women towards snacking (Grogan, Bell & Conner, 1997). Women perceive

snacking as more unhealthy and more pleasant than men. The snacking of women is influenced by

social pressure, since there exists a belief that restricting snacking is a gender-role appropriate for

women in Western societies (Grogan et al., 1997). A possible explanation for this difference is that

the snacking script in the current study included both healthy and unhealthy snacking. Another

explanation could be that the self-report for snacking used in the study of Grogan et al.(1997) was

less valid than the one used in the current study (SRHI). This could imply that females in the study of

Grogan et al. (1997) untruthfully indicated their snacking frequency, because of social desirability.

The younger the participants, the more likely was a M&M's/chocopeanuts impulse purchase, which

aligns with the results of previous studies (Amos et al., 2014; Verplanken & Herabadi, 2001). In

agreement with previous research (Savige et al., 2007), younger participants were more likely to

have an activated snacking behavioural script than older participants.

Regarding the additional variables the study showed that the more often participants snacked, the

less often they conducted M&M's/chocopeanuts impulse buying. This finding is contrary to that of

Verplanken et al. (2005), who found that the habit of snacking, including the frequency of snacking, is

strongly and positively related to impulse buying. Liking of white chocolate had a stimulating effect

on M&M's/chocopeanuts impulse buying. The more participants liked chocolate in general, the less

likely was impulse buying according to the second measure of impulse buying. Liking of chocolate

45

with nuts and liking of crisps had a stimulating effect on impulse buying. It can therefore be assumed

that the liking of specific bitesizes is positively associated with impulse buying. Consistent with earlier

research (Amos et al., 2014), disposable income had a stimulating effect on impulse buying. The

analysis with the additional variables showed a significant negative interaction effect of branded

product and situational goal on general impulse buying (first measure of impulse buying).

5.2 Limitations and directions for further research

A characteristic feature of this study is the tension between the internal and external validity.

Because of time and money constraints, the empirical study was conducted as an online experiment.

The aim of enhancing both internal and external validity resulted in the inclusion of multiple

measures for the same construct (goal-derived categorisation and impulse buying). A realistic

supermarket scenario was simulated by letting participants click on desired products of supermarket

shelves. The realism of the supermarket scenario was enhanced by conducting a pre-test and a pilot.

The set-up of an online experiment caused to use self-reports instead of measuring actual behaviour.

Although the study aimed to simulate a real shopping experience and the measures of self-report

were known for being reliable (e.g. Verplanken & Orbell, 2003), there is abundant room for future

research measuring actual behaviour in a real-world retail setting. Especially for the variable 'impulse

buying', actual behaviour could create new insights in comparison with self-report.

The sample was focussed around the social network of the researcher. Despite that a wide age group

was present ranging from 18 to 86 years, the median age was 24 years. The sample consisted of

more women (78.8%) than men. Since the study found that most effects were stronger for younger

and female participants, the sample of the study could have generated stronger effects than the

applicable effects for the whole population (adult Dutch citizens). The results of the study are hence

in particular applicable to young Dutch females and caution is needed when generalizing the found

effects to the population. Future studies with a more equally divided and representative sample in

terms of age and gender are therefore recommended. This improves the external validity of the

study. In order to improve the internal validity, using a sample of a restricted age group (e.g. 18-25

years old) and one gender (men) could decrease the effects of age and gender on the direct effects of

the variables. In this way, the effects that younger participants are more likely to buy

M&M's/chocopeanuts and to have an activated snacking behavioural script than older participants

and that women are more likely to conduct impulse buying than men are reduced.

In order to create consistency between the conditions and hence foster the internal validity of the

study, the situational goal was presented only textually. No visual neutral depiction would be

possible in the control conditions without the situational goal. Consequently, the situational goal was

presented before the participant saw the shelves of the supermarket scenario. This presumably

resulted in an active goal in the mind of the participant before the shopping scenario properly

started. Since the situational goal was already some time active, participants could have thought

about several products to fulfil the goal. The study showed that crisps would be a likely choice in such

a case. This situation is very different from a simultaneous confrontation of the situational goal and

the branded product. In the latter situation, a more spontaneous and direct action could be

expected, possibly resulting in the choice for M&M's/chocopeanuts. That is, situational goal refers to

planned impulse buying, whereas branded product refers to pure impulse buying. This limitation in

the empirical set-up of the study could explain the negative interaction effect of branded product

and situational goal on impulse buying. When participants were given a situational goal, they could

46

have thought already about alternative products. The confrontation with M&M's/chocopeanuts had

less impact in these conditions than in the conditions without a situational goal. Pure impulse buying

was presumably not measured when a situational goal was present. An additional explanation

regarding branded product is that participants recognised that the branded product shelf was

deliberately inserted in the depiction of the pasta shelf. In that case, the participants were aware of

the manipulation which could have resulted in hypothesis guessing. When the participants saw

M&M's/chocopeanuts, they presumably choose to not fall prey to the manipulation of the

experimenter and reminded themselves of the other products they could buy. This effect was

expected to be higher for M&M's than for chocopeanuts, since M&M's can be recognised as a well-

known product and suitable for experiments. Future studies that develop an in-store manipulation of

situational goal in a real-world supermarket are recommended to validate this explanation of the

negative interaction effect of branded product and situational goal on impulse buying. Such a

manipulation would focus more on pure impulse buying.

Only one situational goal was used in the study. Since the situational goal seemed to be more related

to crisps impulse buying than to M&M's/chocopeanuts impulse buying, it is a relevant issue for

further research to indentify a situational goal which is more (exclusively) related to

M&M's/chocopeanuts. In addition, effects of the framing of the situational could be researched. In

the present study a promotional focus was used (you are going to watch TV on the sofa together with

friends and you like snacking while doing this). Future research could test the effect of a prevention

focus (e.g. friends are coming to watch TV together on the sofa and you don't want to disappoint

them by having no snacks to offer). Literature regarding the strength of approach versus avoidance

strategic motivations for goal attainment (e.g. Förster, Higgins & Idson, 1998) could be valuable.

Limitations regarding the deliberated placement of the branded product in the simulated

supermarket exist in two ways. On the one hand, the placement of the branded product created a

tension between the internal and the external validity of the study. It is not very common to see

M&M's/chocopeanuts placed next to a pasta shelf. However, in order to analyse the pure effect of

the conceptual framework and to infer causal conclusions, the manipulations should be as unbiased

as possible and controlled by the researcher. When for instance M&M's/chocopeanuts would have

been placed next to the tea shelf, possible associations with M&M's/chocopeanuts and drinking tea

could create random variance in the pure effect of the situational goal. On the other hand, the

placement of the branded product on a separate shelf at the end of the supermarket aisle could

draw relatively much attention to this shelf. Consumers could suppose that such a placement implies

that the product is in discount (Inman, McAlister & Hoyer, 1990). A supposed discount could

stimulate the sales of the concerned product, although price was not the focus of this study. For this

study, the placement of the branded product was appropriate to create the manipulation, since the

internal validity was enhanced. Additional studies could research whether the placement of the

branded product next to several products and in different positions of the supermarket aisle

influences the found effects.

Because, by the knowledge of the researcher, no measures exist for the activation of a behavioural

script, an indirect measure was used (SRHI). Further research should construct a direct measure of

the activation of a behavioural script. This could give more valid insights in the connection between

goal-derived categorisation and intuition. Insights regarding the relationship between categorisation

as intuitive process and impulse buying could be provided as well.

47

The current study deliberately used categorisation measures close the real-world consumer

experiences. However, because of the ceiling effect of the first measure of categorisation and the

limitations in the empirical set-up of the measure of the exemplar, the used methods in this study

could presumably not measure primary and secondary categorisation. Therefore, future studies

should develop new measures to analyse this primary and secondary categorisation.

5.3 Theoretical implications

The study provided partial evidence that situational goals activate goal-derived categorisation. This is

consistent with the reasoning of the theoretical framework. The activation of goal-derived

categorisation suggests that prior knowledge is used to interpret the meaning of the 'TV evening'

(the situational goal) (Colman, 2002). The use of prior knowledge allows the activation of associative

networks (Anderson & Brower, 1973). This finding thus supports the idea that the situational goal

functions as the source node in the activation of an associative network (Collins & Loftus, 1975). The

current study provides evidence that situational goals influence the categorisation process on its

own, which complements previous research indicating that the combination of situational and

personal goals influences categorisation (Ratneshwar et al., 2001). The study has been unable to

demonstrate the relationship between branded products and categorisation.

Concerning how categorisation affects impulse buying, the study did not find evidence that goal-

derived categorisation, as intuitive process, activates a snacking behavioural script. This does not

align with previous research stating that intuition enables consumers to activate the typical action

script (Abelson, 1981; Rumgay, 2004; Glöckner & Witteman, 2010). The study partially supports that

the activation of a snacking behavioural script results in impulse buying. The relationship between

the activation of a snacking behavioural script and M&M's/chocopeanuts impulse buying seemed to

be explained by age, since both were more likely for younger participants. The study has raised

questions about categorisation as intuitive process: the connection between categorisation and

intuition is possibly not as evident as expected. Future studies on the relationship between goal-

derived categorisation, intuition and behavioural scripts are therefore desired. This relationship

could be analysed by focussing on qualitative research which aims to understand how deliberate,

cognitive and affective consumers asses goal-derived categories. In order to achieve a deep

understanding of the perception of goal-derived categories, a laddering interviewing technique is

recommended.

The study showed that the presence of the situational goal is more effective in stimulating

M&M's/chocopeanuts impulse buying than the presence of branded product. Branded product and

situational goal both stimulated general impulse buying, but situational goal had a larger effect.

These findings suggests a role for situational goals in promoting general impulse buying and impulse

buying of chocolate bitesizes. This sheds a new light on the impact of situational effects on impulse

buying. A remarkable finding was that the presence of a branded product in combination with the

presence of a situational goal (i.e. seeing M&M's and having a TV evening with friends) made impulse

buying in general less likely. Branded product stimulated impulse buying more often without a

situational goal than with a situational goal. The situational goal of the TV evening stimulated crisps

impulse buying, whereas branded product did not. The situational goal had a relatively large impact

on crisps impulse buying compared to M&M's/chocopeanuts impulse buying.

48

Regarding the main research question, the study partially supported that situational goal activated

goal-derived categorisation. The expected relationship between goal-derived categorisation and the

activation of a snacking behavioural script was not supported. There was partial evidence that the

activation of a snacking behavioural script made impulse buying more likely. The effect of branded

product on taxonomic categorisation based on the exemplar was not supported, neither was the

primary and secondary categorisation for branded products. Impulsiveness as a personality trait did

not moderate the relationship between goal-derived categorisation and the activation of a snacking

behavioural script. Planned impulse buying was stimulated more effectively than pure impulse

buying (Stern, 1962), since the situational goal was more effective in stimulating

M&M's/chocopeanuts impulse buying, crisps impulse buying and general impulse buying. The effect

of the situational goal on impulse buying was relatively strong compared to the effect of the branded

product. When the situational goal and the branded product were both present, impulse buying was

less likely.

Based on the findings of the study, a modification of the conceptual framework (Figure 1) is

suggested. The study found that impulsiveness as a personality trait directly positively influences the

activation of a snacking behavioural script, which is in agreement with previous research (Verplanken

& Herabadi, 2001). Hence, impulsiveness as a personality trait should not moderate the relationship

between goal-derived categorisation and the activation of a behavioural script, but influences the

activation of a snacking behavioural script directly. Future research should test the not supported

hypotheses with new measures before applying further modifications to the conceptual framework.

The current study has theoretical implications for empirical consumer research. The results show that

the use of the pictures of supermarket shelves with the possibility to click on desired products

successfully simulated a scenario of grocery shopping in the supermarket. Future studies could use

this approach as well when simulating a supermarket scenario in an (online) experiment.

5.4 Managerial/practical implications

5.4.1 General practical implications for the retail sector

Previous research has shown that situational goals can alter category representations in the mind of

the consumer towards goal-derived categorisation (Ratneshwar et al., 2001). In addition, it is known

that consumer purchase decisions depend on the congruence of consumer categorisation with the

external product categorisation of a store (Morales et al., 2005). Most current store lay-outs are

focussed on taxonomic categories (Ratneshwar et al., 2001). Taken together, these findings suggest

that it is beneficial for the retail sector to know whether store-layouts should focus on goal-derived

consumer processing. Considering that by far most participants searched M&M's/chocopeanuts by

means of taxonomic categories, it seems that learned associations of people who often visit the

supermarket structure the searching process of the consumer. Consumers have in general more

experience with taxonomic than goal-derived departments. This implies that consumers are more

likely to search products based on traditional taxonomic departments than based on consumption

moments. Based on the findings of this study, the retail industry is not advised to make use of goal-

derived departments when targeting consumers which plan to search for a specific product. As

consumers presumably search products based on taxonomic departments, it is not advised to replace

taxonomic departments by goal-derived departments. Goal-derived departments can nevertheless

potentially be used as complement on the taxonomic departments in a store in order to stimulate

pure impulse buying. Pure impulse buying does not focus on planned purchase plans and thus

49

consumer's searching process, but breaks with planned purchase plans by means of a spontaneous

stimulus (Stern, 1962).

The current study paid attention to two kinds of impulse buying: pure and planned impulse buying.

The results of the study showed that situational goals influenced impulse buying of chocolate

bitesizes and general impulse buying most effectively. This implies that the current study showed

that influencing planned impulse buying was more effective in stimulating (chocolate bitesize)

impulse purchases than pure impulse buying.

5.4.2 Specific managerial implications for the snacking industry (Mars)

The results of the study show that the presence of a situational goal stimulates impulse buying of

chocolate bitesizes, crisps and general impulse buying. The presence of a branded product stimulates

general impulse buying. An important finding of this study is that the situational goal is more

effective in stimulating chocolate bitesizes impulse buying than the branded product. Hence,

marketing managers could use the situational goal to effectively increase the impulse purchases of

chocolate bitesizes and in particular M&M's.

The study has shown that the situational goal of the TV evening had a larger effect on crisps impulse

buying than on M&M's/chocopeanuts impulse buying. This implies that the participants associated

crisps more strongly with the TV evening consumption moment than they did with M&M's. Thus,

when this situational goal is promoted, consumers might choose crisps over M&M's/chocopeanuts.

Therefore, marketing managers of M&M's and other chocolate bitesizes are advised to consider

whether the share of their products in the consumption moment of the TV evening is worth the

marketing investments. A comparison of the total revenue of chocolate bitesizes and crisps should be

taken into account in order to provide context to the shares of both products in the consumption

moment. Marketing managers of M&M's are advised as well to examine how large the share of the

TV evening consumption moment is compared to all the chocolate bitesizes consumption moments

in order to decide whether their marketing investments are beneficial. A consideration could be that,

because of the stronger association, the promotion of the situational goal of the TV evening benefits

crisps sales more than M&M's sales. This could result in a spillover effect of the promotion of the

situational goal towards crisps. Another consideration is to develop a savoury product which has a

stronger share in this consumption moment and is therefore a more equal competitor of crisps.

Furthermore, marketing managers at Mars could consider to search for a situational goal which is

more exclusively related to M&M's. Such a more related situational goal could create a more cost

efficient promotion of M&M's in comparison to the situational goal of the TV evening.

Thus, the promotion of the situational goal is most effective in stimulating impulse buying of

chocolate bitesizes. Marketing managers at Mars are therefore advised to use the situational goal in

their promotion of M&M's. However, marketing managers should be aware of the relatively large

share of crisps in this consumption moment. Marketing managers therefore need to consider

whether the use of the situational goal of the TV evening in their marketing is beneficial enough to

increase profit.

To conclude, the findings of this thesis revealed that situational goals, which activate goal-derived

categorisation, are more effective in stimulating impulse buying than a branded product or a

combination of a situational goal and a branded product. This has valuable implications for the retail

and snacking industry.

50

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Appendix

Appendix A. Flowchart.

Figure A.1. Flowchart of the procedure of the study.

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Appendix B. Outcomes of the pre-test.

Situational goal 1: Situational goal 2:

Situational goal 3: Situational goal 4:

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Situational goal 5: Situational goal 6:

Supermarket scenario:

Bought products:

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Appendix C. Materials used in the empirical study.

Applicable to all scales: from left to right: Helemaal mee oneens-Helemaal mee eens so, 1= helemaal mee oneens, 7=helemaal mee eens Informed Consent

Beste deelnemer, Heel erg bedankt dat je wilt deelnemen aan dit onderzoek! Het invullen van de vragen zal ongeveer 10-15 minuten duren. Deze vragenlijst is ontworpen om verschillende lay-outs van supermarkten te onderzoeken. Er zijn hierbij geen goede of foute antwoorden. Ik ben geïnteresseerd in jouw mening en keuzes. Dit onderzoek is een onderdeel van mijn afstudeerscriptie en is dus gekoppeld aan de Wageningen Universiteit. De resultaten worden enkel gebruikt voor dit onderzoek en zullen op geen enkele manier naar jou herleid kunnen worden. Voor vragen kun je mailen naar iris.kempers@wur.nl Als beloning voor je deelname maak je kans op een traktatie pakket. Als je wilt deelnemen aan de loting kun je aan het einde van de vragenlijst je e-mailadres achter laten. Deelname aan de loting voor het traktatie pakket is natuurlijk niet verplicht. Onderaan elke pagina bevindt zich een "volgende logo" (>>). Klik hierop als je de vragen beantwoord of de tekst gelezen hebt en je door wilt naar de volgende pagina. Door op 'ja' te klikken geef je aan dat je bovenstaande gelezen hebt en hiermee instemt.

Ja, ik doe mee met dit onderzoek.

Peanut allergy

Ben je allergisch voor pinda's?

Helaas, je kunt niet deelnemen aan het onderzoek. Ik wil je wel erg bedanken voor je bereidheid om

deel te nemen. Dat doet me goed! Fijne dag vandaag en dankjewel voor je tijd.

Instruction

Dit onderzoek bestaat uit twee delen. In het eerste deel word je gevraagd om jezelf voor te stellen

dat je in de supermarkt bent om boodschappen te doen. Dit wordt verder uitgelegd op de volgende

pagina. Het tweede deel van het onderzoek bestaat uit het invullen van een aantal vragen.

Beeld je in dat je je in de volgende situatie bevindt:

Je merkt dat je een aantal producten nodig hebt en je besluit naar een supermarkt te gaan. De thee,

koekjes en wc papier zijn op. Ook heb je nog pasta en tomatensaus nodig. Dit brengt je tot het

onderstaande boodschappen lijstje.

Shopping list

- thee

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- koekjes - wc papier - pasta - tomatensaus Dit zijn de producten die je minimaal wilt kopen, maar je mag zeker ook meer producten (dan op het lijstje aangegeven) kopen.

Presence situational goal

Je hebt voor vanavond drie goede vrienden bij je thuis uitgenodigd. Jullie zullen vanavond in de

woonkamer zijn. Je bent van plan om vanavond met je vrienden TV te gaan kijken. Je weet nog niet

of dat jullie favoriete serie, een film of een TV programma is. Wel weet je dat je op de bank gaat

zitten met je vrienden en tijdens het TV kijken lekker wil snacken.

Je gaat naar de supermarkt om de boodschappen te doen en loopt rond in de winkel. Tijdens het

rondlopen zie je meerdere schappen die in de volgende schermen voorbij zullen komen. Als je een

product wilt kopen, kun je per schap met je muis (cursor) op een product op de afbeelding klikken. Er

verschijnt dan een rode cirkel op dat product. Je geeft dus per schap aan wat en óf je iets wilt kopen.

Je kunt per schap ook meerdere producten kopen. Als je niets wilt kopen klik je niet op een product.

Klik hierna op >>.

Absence situational goal

Je gaat naar de supermarkt om de boodschappen te doen en loopt rond in de winkel. Tijdens het

rondlopen zie je meerdere schappen die in de volgende schermen voorbij zullen komen. Als je een

product wilt kopen, kun je per schap met je muis (cursor) op een product op de afbeelding klikken. Er

verschijnt dan een rode cirkel op dat product. Je geeft dus per schap aan wat en óf je iets wilt kopen.

Je kunt per schap ook meerdere producten kopen. Als je niets wilt kopen klik je niet op een product.

Klik hierna op >>.

Impulse buying

Measure 1

Pictures of shelves

Je komt langs een schap met melk. Als je iets wilt kopen geef je dit aan door met je muis (cursor) op

het gebied te klikken. Klik als je klaar bent op >>.

->Adapted for each shelf

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http://www.levensmiddelenkrant.nl/nieuws/fabrikanten/fonterra-topman-melkprijs-blijft-dalen

https://www.linkedin.com/pulse/vbat-develops-shop-good-food-constanze-fluhme/

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http://maakhetglutenvrij.nl/glutenvrij-in-italie/

http://www.levensmiddelenkrant.nl/nieuws/algemeen/bewuste-levensstijl-versplintert-

theelandschap

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http://moniquevandervloed.nl/grootste-meuk-onzin-top-10/

http://www.distrifood.nl/formules/nieuws/2015/2/ex-leverancier-wc-papier-eist-geld-van-ah-10132371

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https://www.eigenwijsblij.nl/gadgets-shoppen/vegansuper-groningen-eerste-veganistische-supermarkt-noord-nederland

https://www.quavita.nl/zelf-sappen-maken-met-vitaal-water

64

https://nl.pinterest.com/pin/398990848208314658/ Deze foto kan gebruikt worden om manipulatie branded/non-branded product in te bouwen. manipulation branded product

Manipulation non-branded product

65

http://www.dixiechikcooks.com/michelada/

http://www.stichtingmerelswereld.nl/blog/keuzestress/

66

http://fitnesschicks.nl/food-haul-mijn-aankopen-bij-de-marokkaanse-supermarkt/ Measure 2: Adjusted version of the Consumer Impulsiveness Scale (CIS)

To what extent do the following words describe your action to buy products?

1. Impulsive 2. Careless 3. Self-controlled (R) 4. Extravagant 5. Farsighted (R) 6. Responsible (R) 7. Restrained (R) 8. Easily tempered* 9. Rational (R) 10. Methodical (R) 11. Enjoyment of spending 12. Planned (R) Accompanied by a seven-point likert scale ranging from "Helemaal niet" (Not applicable at all) to

"Helemaal" (Really applicable).

In hoeverre beschrijven de volgende woorden jouw actie van zojuist om producten te kopen? 1. Impulsief 2. Zorgeloos 3. Beheerst (R) 4. Overdreven 5. Met een vooruitziende blik (R) 6. Verantwoordelijk (R) 7. Terughoudend(R) 9. Rationeel (gebaseerd op logica, niet op gevoelens en emoties) (R) 10. Methodisch (op een vaste manier waarover je hebt nagedacht) (R) 11. Genieten van uitgeven 12. Gepland (R)

67

Item 8 was deleted in this study, since there exists no accurate translation in Dutch. The assumption is that the scale remains reliable, since it still has 11 items and only two subscales. Measure of dominant categorisation Indicate department

Reminder branded product

In de supermarkt heb je M&M's gezien.

Source: Mars NL

Reminder non-branded product

In de supermarkt heb je chocopinda's gezien.

Source: https://www.hemashop.com/gb/shop/cooking-dining/food-drinks/chocolate-

sweets/chocolate-peanuts-(10380019)

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Deze supermarkt maakt gebruik van een nieuw concept met ervaringseilanden in combinatie met

"normale" schappen. Beeld je in dat je M&M's/chocopinda's wilt kopen. Beeld je ook in dat je in de

supermarkt met onderstaande plattegrond aan het winkelen bent. Wat is de EERSTE plek in de

winkel waar je naar toe zou gaan om de M&M's/chocopinda's te vinden?

Geef de plek in de supermarkt aan waar je naar toe zou gaan aan door met je muis (cursor) op de

desbetreffende plek te klikken. Het geselecteerde gebied krijgt een kleur. Klik hierna op >>.

Indicate Reason

Waarom zou je naar die plek in de supermarkt gaan? Kies alsjeblieft één van onderstaande

antwoorden

- Ik ben op zoek naar chocolade - Ik ben op zoek naar koekjes - Ik ben op zoek naar een snack voor vanavond op de bank met vrienden - Ik ben op zoek naar snacks - Ik ben op zoek naar een snack voor na het sporten - Ik ben op zoek naar een snack om mee te nemen voor onderweg Appropriateness of categories

Geef aan in welke mate je M&M's/chocopinda's in onderstaande categorieën in de supermarkt

verwacht.

- Snoepgoed - Chocolade - Koekjes - Snacks

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- Een tv avond met vrienden - Producten voor na het sporten - Toetjes Accompanied by a seven-point Likert scale ranging from "Zeer onwaarschijnlijk" (not likely at all) to

"Zeer waarschijnlijk" (very likely).

Measure of taxonomic categorisation

Wat zijn volgens jou producten die vergelijkbaar zijn met M&M's/chocopinda's?

Typ in de onderstaande tekstvakken minimaal 5 producten die volgens jou vergelijkbaar zijn met

M&M's/chocopinda's. Denk hier niet te lang over na. Alle producten die bij jou opkomen zijn een

antwoord, het mogen ook specifieke producten zijn.

. Stel je voor dat de 5 producten die je net hebt genoemd samen een groep vormen. Welk product is

volgens jou het bekendste voorbeeld van deze groep? (Dit mag ook een product zijn dat je al

genoemd hebt). Vul je antwoord in in onderstaand tekstvak.

Instruction 2

Nu volgt het laatste deel van het onderzoek. Hierin word je gevraagd om een aantal algemene vragen

over je aankoopgedrag en eetgedrag te beantwoorden.

om een aantal vragen te beantwoorden.

Measure of habitualness (SRHI)

Behavior X is something . . .

1. I do frequently. 2. I do automatically. 3. I do without having to consciously remember. 4. that makes me feel weird if I do not do it. 5. I do without thinking. 6. that would require effort not to do it. 7. that belongs to my (daily, weekly, monthly) routine. 8. I start doing before I realize I'm doing it. 9. I would find hard not to do. 10. I have no need to think about doing. 11. that's typically "me." 12. I have been doing for a long time.

Snacken is iets

1. Dat ik regelmatig doe 2. Dat ik automatisch doe 3. Dat ik doe zonder dat ik mij herinner hoe 4. Dat vreemd zou voelen om niet te doen 5. Dat ik doe zonder na te denken 6. Dat mij inspanning vereist om niet te doen 7. Dat bij mijn (dagelijkse, wekelijkse, maandelijkse) routine hoort 8. Dat ik doe voordat ik het doorheb

70

9. Dat ik moeilijk zou vinden om niet te doen 10. Waar ik niet over na hoef te denken 11.Dat typisch is voor mij 12 .Dat ik al lange tijd doe Accompanied by a disagree/agree seven-point likert scale.

Snacking is defined as eating little portions of food in between meals.

Snacken wordt hier gezien als het eten van kleine hoeveelheden voedsel tussen de hoofdmaaltijden door. Snacken kan daarom zowel het eten van bijvoorbeeld een banaan als het eten van chips zijn.

Frequency of snacking

Hoe vaak snack je?

Snacken wordt hier gezien als het eten van kleine hoeveelheden voedsel tussen de hoofdmaaltijden door. Snacken kan daarom zowel het eten van bijvoorbeeld een banaan als het eten van chips zijn.

Multiple choice question including: rarely/never, once every week, once every day, several times a

day.

Measure impulsiveness as personality treat (ABIS)

Geef aan hoe vaak onderstaande stellingen van toepassing zijn op jouw manier van handelen en

denken.

1. Ik plan taken zorgvuldig (R) 2. Ik doe dingen zonder na te denken 3. Ik houd mijn aandacht er niet bij 4. Ik plan uitjes ruim van te voren (R) 5. Ik heb mezelf onder controle (R) 6. Ik kan mij gemakkelijk concentreren(R) 7. Ik denk zorgvuldig na (R)

71

8. Ik zorg dat ik een baan behoud (R) 9. Ik zeg dingen zonder eerst na te denken 10. Ik handel impulsief 11. Ik doe dingen in een opwelling 12. Ik ben een consequente denker (R) 13. Ik plan voor de toekomst (R) Conform the order of the BIS-11 (Patton & Stanford, 1995). Based on Dutch translation of the BIS-11 by Lijffijt en Barratt (2005). Accompanied by a 4-point response scale including: rarely/never (zelden/nooit), occasionally (soms), often (vaak), almost always/always ((bijna) altijd). Liking of chocolate and bitesizes

Hoe graag eet je onderstaande producten?

-Chocolade in het algemeen -Witte chocolade -Melk chocolade -Pure chocolade -Chocolade met noten -Borrelnootjes -Chips - Popcorn Accompanied by a seven-point likert scale ranging from "Helemaal niet graag" (I don't like this at all) until "Heel erg graag" ( I really like this). Brand familiarity

1. This brand is very familiar to me. 2. I'm very knowledgeable about this brand. 3. I have seen many advertisements about this brand in the mass media. Accompanied by a disagree/agree seven-point likert scale , based on the scale of Zhou, Yang and Hui

(2010).

Geef aan in hoeverre je het eens bent met de volgende stellingen met betrekking tot het merk

M&M's.

1. Dit merk is erg vertrouwd/bekend voor mij. 2. Ik ben zeer goed geïnformeerd over dit merk/ Ik weet veel over dit merk. 3. Ik heb veel advertenties over dit merk in de massamedia gezien. Frequency of shopping Hoe vaak doe je boodschappen? - Minder dan één keer per week - 1-2 keer per week - 3-5 keer per week - (bijna) Iedere dag

72

Multiple choice question with one response possibility. Disposable income Welke beschrijving is het meest van toepassing op jouw bestedingsgedrag? Als ik boodschappen doe: Accompanied by a seven-point likert scale ranging from "moet ik op de kleintjes letten" until "kan ik mij luxe veroorloven". Manipulation check: situational goal

Welke bedoeling gaven we je mee tijdens het winkelen in de supermarkt? Je kunt meerdere

antwoorden selecteren.

- De boodschappen doen - Iets kopen voor na het sporten - Zoveel mogelijk producten kopen - Iets kopen voor een TV avond op de bank met vrienden - Iets kopen voor een verjaardag A multiple choice question with multiple answers possible. Demographic variables (gender, age, level of education)

Wat is je geslacht? -man -vrouw

Wat is je leeftijd in jaren?-> open vraag

Wat is je hoogst voltooide opleiding ?- Basisonderwijs, VMBO

- HAVO, VWO, MBO - HBO, WO bachelor - WO master, PhD Debriefing

Dankjewel voor je deelname aan het onderzoek! Je hebt me enorm geholpen! Ik wil je vragen om

het niet met andere (mogelijke) deelnemers te hebben over je ervaringen met dit onderzoek. Dit kan

namelijk de resultaten van het onderzoek beïnvloeden.

Wil je meer informatie en precies weten wat er onderzocht is? Vul dan in het eerste tekstvak je e-

mail adres in. Wanneer het onderzoek is afgerond, zul je dan verdere informatie krijgen.

Wil je deelnemen aan de loting voor de traktatie pakketten? Vul dan in het tweede tekstvak je e-mail

adres in. Je kunt zelf kiezen of je in één van beide tekstvakken, beide tekstvakken of geen van de

tekstvakken je e-mail adres invult.'

Klik op >> om het onderzoek te voltooien.

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Pre-test

Instruction:

Beste deelnemer,

Heel fijn dat je wilt deelnemen aan een test voor mijn master thesis. Deze test zal ik gebruiken om

mijn onderzoek op te zetten en is dus gekoppeld aan de Wageningen Universiteit. Je blijft als

deelnemer aan deze test volledig anoniem. De resultaten worden enkel gebruikt voor mijn

onderzoek.

Tijdens deze test wordt er een aantal situaties voorgelegd. Er wordt je gevraagd om jezelf in te

beelden in de situatie en daarnaar een aantal vragen te beantwoorden. Er zijn hierbij geen goede of

foute antwoorden, ik ben geïnteresseerd in jouw mening en keuzes. De test zal ongeveer 5 minuten

duren.

Heel erg bedankt dat je deelneemt aan mijn test, je helpt me enorm!

Situational goal 1:

Stel jezelf de volgende situatie voor:

Je hebt voor vanavond een aantal goede vrienden bij je thuis uitgenodigd. Jullie zullen vanavond in

de woonkamer zijn. Je bent van plan om vanavond met je vrienden TV te gaan kijken. Je weet nog

niet of dat jullie favoriete serie, een film of een TV programma is. Wel weet je dat je op de bank gaat

zitten met je vrienden en tijdens het TV kijken lekker wil snacken.

Situational goal 2:

Stel jezelf de volgende situatie voor:

Volgend weekend ga je met een aantal goede vrienden naar Parijs. Jullie gaan naar Parijs om een

weekend te winkelen en vooral mooie kleding in te slaan. Het staat nog niet vast of jullie met de auto

of de trein naar Parijs gaan. Tijdens dit weekend wil je met je vrienden lekker gaan snacken.

Situational goal 3:

Stel jezelf de volgende situatie voor:

Vanavond ga je sporten bij jou in de buurt. Je gaat je favoriete sport uitoefenen. Na het sporten ben

je moe. Je wilt naar huis, maar je hebt ook honger gekregen. Om deze honger, die je na het sporten

hebt gekregen, te stillen wil je lekker snacken.

Situational goal 4:

Stel jezelf de volgende situatie voor:

Morgen heb je een lange dag voor de boeg want het is helaas nog geen weekend. Je bent daarom

morgen druk met je studie/ op het werk (beeld je in wat voor jou van toepassing is). Tijdens zo'n

drukke dag krijg je soms trek. Daarom wil je lekker gaan snacken tijdens je studie/werk.

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Situational goal 5:

Stel jezelf de volgende situatie voor:

Vanavond reis je met het openbaar vervoer naar huis. Deze reis zal een uur duren. Je gaat één keer

overstappen: van de trein naar de bus. Tijdens het reizen wil je lekker gaan snacken.

Situational goal 6:

Stel jezelf de volgende situatie voor:

Vanavond heb je een feestje bij jou thuis op de planning staan. Je hebt hiervoor een aantal vrienden

uitgenodigd. Om het feestje geslaagd te maken en gezellig te kunnen bijkletsen met vrienden wil je

lekker gaan snacken.

Supermarket scenario setting:

Beeld je in dat je je bevindt in de volgende situatie. Je merkt dat je een aantal producten nodig hebt

en je besluit naar een supermarkt te gaan. De thee, koekjes en wc papier zijn op. Ook heb je nog

pasta en tomatensaus nodig. Dit brengt je tot het onderstaande boodschappen lijstje.

Boodschappenlijstje

- thee - koekjes - wc papier - spaghetti - tomatensaus

Je gaat naar de supermarkt om de boodschappen te doen en loopt rond in de winkel. Tijdens het

rondlopen zie je een aantal schappen die in de volgende schermen voorbij zullen komen.

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Je hebt nu door de supermarkt gelopen en de schappen gezien. Welke producten zou je willen

kopen? Typ de producten alsjeblieft afzonderlijk in de onderstaande tekstvakken.

Items: Ik vind deze situatie realistisch. Ik vind deze situatie geloofwaardig. Ik kan mij deze situatie goed voorstellen. Ik bevind mijzelf regelmatig in deze situatie. Accompanied by a disagree/agree seven-point likert scale.

Pilot

Dit onderzoek bevindt zich in de testfase, jouw feedback wordt daarom erg gewaardeerd. Geef

alsjeblieft aan of en waar je fouten of gekke overgangen tegenkomt. Ik zou graag feedback van je

ontvangen over de leesbaarheid en duidelijkheid van de tekst en vragen. Ik blijf bij je in de buurt om

vragen te beantwoorden.

Bij iedere vraag aandacht besteden aan:

- Is de vraag duidelijk voor je? Waarom niet? -Kun je de tekst en vraag gemakkelijk lezen? - Begrijp je het scenario van boodschappen doen in de supermarkt? Vind je dit realistisch? Waarom wel/niet? -Ben je technische problemen/fouten in de survey tegen gekomen? -Hoe lang was je bezig met het onderzoek?

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Appendix D. Linear regressions third measure of categorisation.

Outcomes of the linear regressions of the effect of branded product, situational goal and their

interaction effect on dominant categorisation controlled for age and gender measured by

appropriateness of categories. There were no significant effects regarding the analyses below.