Department of Business Administration
Master's Program in Marketing
Master’s Thesis, 15 Credits, Spring 2020
Supervisor: Jan Abrahamsson
Consumers’ choice of grocery store in Umeå
A quantitative study on how healthy food
and nudging can affect consumers’ choice of grocery store
Augustine Iranyongeye & Laura-Maria Toivanen
i
[This page is intentionally left blank]
ii
Acknowledgements
We would like to start by saying thank you to our supervisor Jan Abrahamsson for
supporting and guiding us through the thesis writing process and providing valuable
insights and feedback. We would also like to thank the people who participated in our
survey and therefore made this research possible to conduct. We are also grateful for
our friends and family for their support and understanding during this process. Lastly,
we would like to thank each other for the great collaboration and flexibility during these
months.
Thank you!
Umeå, May 22th, 2020
Augustine Iranyongeye Laura-Maria Toivanen
iii
[This page is intentionally left blank]
iv
Abstract
Nowadays, consumers are being exposed to a large selection of food alternatives with an
aim of helping with health matters. For that reason, the consumption of healthy food has
been increasing among people, but at the same time, the consumption of unhealthy food
has expanded. Due to the advanced technology, there is more information available about
health, which makes the consumers’ knowledge about diseases caused by their way of
living to grow. Simultaneously, there has been studies proving that consumers’ choices
do not often resemble their attitudes.
Since consuming healthy food is more popular nowadays, this study had the aim of
examining if consumers will choose a grocery store based on different attributes. The
study is based on several theories that are the starting point for the study’s research
questions which are; Does the selection of healthy food affect consumers’ choice of a
grocery store? Does nudging of healthy food affect consumers’ choice of a grocery store?
The theories that are used in this study are nudge theory, libertarian paternalism theory,
behavioral economics, theory of reasoned action, theory of planned behavior, social
marketing theory, choice architecture, cognitive architecture and status quo.
The data was collected through a questionnaire, where different questions had the aim to
measure what affects consumers when choosing a grocery store. In total, the study
gathered a sample of 136 responses whereas 8 of them were removed from the study as
outliers. The outcome of this study is based on two independent variables; healthy food
and nudging and one dependent variable; choice of grocery store. These variables are
composite variables created from a range of other variables. The composite variable
healthy food is created from variables checklist, avoidance of unhealthy/unnecessary
food, people’s affection, healthy thinking, food habits, attitude of healthy eating, past
purchasing behavior, intention and behavior, same groceries and new groceries. The
composite variable nudging is created from variables product placement, memory,
product placement affection on consumers’ purchasing behavior and visible healthy food.
The dependent variable choice of grocery stores was created from the variables; number
of healthy food alternatives, price of healthy food, marketing of healthy food and place
of grocery store.
This study was analyzed in the data program STATA where a multiple linear regression
was used to test the hypotheses. According to the result from the regression analysis, there
is a significant level between healthy food and consumers' choice of grocery stores. In
addition to that, the study shows that there is a significant level between nudging and
consumers' choice of grocery stores. Thus, the null hypothesis of this study was rejected.
v
[This page is intentionally left blank]
vi
Table of Contents
1 Introduction .................................................................................................................. 1
1.1 Problem Background ........................................................................................... 1
1.1.1 Healthy food consumption nowadays.............................................................. 1
1.1.2 Healthy food as a concept ................................................................................ 1
1.1.3 What is nudging? ............................................................................................. 2
1.2 Problem discussion ............................................................................................... 3
1.2.1 Nudging in grocery stores................................................................................ 3
1.2.2 Consumer decision making process in grocery stores – habit vs choice ......... 4
1.2.3 Consumer free choices of grocery ................................................................... 5
1.3 Research gap ......................................................................................................... 6
1.4 Purpose .................................................................................................................. 6
1.5 Research questions: .............................................................................................. 6
1.6 Research Contribution ......................................................................................... 7
1.7 Limitations ............................................................................................................ 7
1.8 Delimitations ......................................................................................................... 7
2 Scientific method .......................................................................................................... 8
2.1 Philosophical considerations ................................................................................ 8
2.1.1 Ontology .......................................................................................................... 8
2.1.2 Epistemology & research paradigm ................................................................ 8
2.1.3 Axiology .......................................................................................................... 9
2.2 Research approach ............................................................................................... 9
2.3 Research strategy ................................................................................................ 10
2.4 Time horizon ....................................................................................................... 10
2.5 Literature search ................................................................................................ 10
2.6 Source criticism................................................................................................... 10
2.7 Preconceptions & choice of subject ................................................................... 12
2.8 Truth criteria ...................................................................................................... 12
2.8.1 Reliability ...................................................................................................... 12
2.8.2 Validity .......................................................................................................... 13
2.8.3 Generalizability ............................................................................................. 13
2.9 Summary of the scientific methodology............................................................ 14
3 Theoretical Framework .............................................................................................. 15
3.1 Behavioral economics ......................................................................................... 15
3.2 Nudge theory ....................................................................................................... 16
3.3 Choice Architecture ............................................................................................ 17
3.4 Libertarian Paternalism..................................................................................... 18
3.5 Theory of Reasoned Action ................................................................................ 19
3.6 Theory of Planned Behavior .............................................................................. 19
vii
3.7 Social Marketing Theory ................................................................................... 21
3.8 Cognitive Architecture ....................................................................................... 22
3.9 Status Quo ........................................................................................................... 22
3.10 Summary of the theoretical framework ......................................................... 23
3.11 Hypotheses ......................................................................................................... 24
4 Practical method and data .......................................................................................... 26
4.1 Choice of method ................................................................................................ 26
4.2 Research Design .................................................................................................. 26
4.3 Sample.................................................................................................................. 27
4.4 Data collection strategy ...................................................................................... 28
4.4.1 Questionnaire ................................................................................................. 28
4.4.2 Types of questionnaires ................................................................................. 29
4.5 Data collection process ....................................................................................... 29
4.6 Different variables .............................................................................................. 32
4.7 Composite variables ........................................................................................... 32
4.8 Dependent variable – Choice of grocery store ................................................. 33
4.8.1 Variables included in Choice of grocery stores ............................................. 33
4.9 Independent variables ........................................................................................ 34
4.9.1 Independent variables as composite variables ............................................... 35
4.9.2 Independent variable – Healthy food............................................................. 35
4.9.3 Moderating variable - Nudging ..................................................................... 36
4.10 Ethical aspects ................................................................................................... 37
5 Results ......................................................................................................................... 38
5.1 General results .................................................................................................... 38
5.2 Descriptive statistics for independent variables .............................................. 40
5.3 Descriptive statistics for dependent variable ................................................... 42
5.4 Correlation .......................................................................................................... 42
5.4.1 Correlation for the variables .......................................................................... 42
5.5 Outliers ................................................................................................................ 43
5.6 Heteroscedasticity ............................................................................................... 44
5.7 Multiple linear regression .................................................................................. 44
5.7.1 Multicollinearity ............................................................................................ 45
5.7.2 Linear regression with Robust ....................................................................... 46
5.7.3 Linear regression without Robust .................................................................. 47
5.7.4 R-squared value ............................................................................................. 47
5.8 Answering to the hypotheses ............................................................................. 47
6 Analysis ....................................................................................................................... 49
6.1 Healthy food, nudging and choice of grocery stores........................................ 49
viii
6.2 Limitations for the analysis ............................................................................... 50
7 Conclusion .................................................................................................................. 52
7.1 General conclusion ............................................................................................. 52
7.2 Implications ......................................................................................................... 53
7.2.1 Societal .......................................................................................................... 53
7.2.2 Practical ......................................................................................................... 53
7.2.3 Theoretical ..................................................................................................... 54
7.3 Future research recommendations ................................................................... 54
REFERENCE LIST ...................................................................................................... 56
APPENDIXES ............................................................................................................... 61
Appendix 1: Cover letter for the survey in Swedish.............................................. 61
Appendix 2: Cover letter for the survey in English ............................................... 61
Appendix 3: Questionnaire in Swedish ................................................................... 61
Appendix 4: Questionnaire in English .................................................................... 64
List of Figures Figure 1. Scientific methodology. .................................................................................. 14 Figure 2. Theories. .......................................................................................................... 15 Figure 3. Illustration of the theories used in connection to the subject. ........................ 23 Figure 4. Gender. ............................................................................................................ 38 Figure 5. Age. ................................................................................................................. 39 Figure 6. Occupation. ..................................................................................................... 39 Figure 7. Household status. ............................................................................................ 40 Figure 8. Weekly shopping. ............................................................................................ 40
List of Tables Table 1 - Keywords for literature search ........................................................................ 11 Table 2. Descriptive statistics for independent variables. ............................................. 41 Table 3. Descriptive statistics for dependent variable. ................................................... 42 Table 4. Correlation for independent variables. ............................................................. 43 Table 5. Gender outliers. ................................................................................................ 43 Table 6. Age outliers. ..................................................................................................... 43 Table 7. Occupation outliers. .......................................................................................... 44 Table 8. Variance inflation factor. .................................................................................. 46 Table 9. Linear regression with Robust. ......................................................................... 46 Table 10. Linear regression without Robust. .................................................................. 47 Table 11. Hypotheses. .................................................................................................... 48
1
1 Introduction In this chapter the background and the concepts for the research are being presented, to
increase the understanding for the chosen subject and the field of study. Therefore, the
important terms and standpoints are being introduced to better illustrate the problem at
hand.
1.1 Problem Background
1.1.1 Healthy food consumption nowadays Nowadays, consumers are facing an expanding number of food alternatives aimed for
helping with health matters while also showing growing consideration when it comes to
choosing healthy food (Anisimova 2016). For instance, the market for organic food in
Europe has grown from €10.8 billion to €21.5 billion between 2004 and 2011 (Willer et
al., 2013). During the years 1990-2010, the use of healthier foods has been increasing
among people, yet at the same time, the consumption of unhealthy foods had grown
(Imamura et al., 2015, p. e135).
As there is increased information available about health, grows the consumer knowledge
about diseases connected to a way of living (Kearney, 2010, p. 2804). However, it has
been noticed that consumers’ choices do not often resemble their attitudes, for example,
in organic products retail, there is identified an attitude-behavior gap, meaning that
consumers’ attitudes are not linked to their actual purchase behavior (Hwang, 2015). It
has also been noticed that both men and women tend to eat larger amounts of unhealthy
food than they consider being healthy for themselves (Wang & Worsley, 2014, p. 597).
At the same time, the level of consumption for healthier food alternatives, such as fruits,
is lower than they acknowledge to be sufficient.
Regarding what we eat, it can be seen as a personal behavior and due to that, people may
see it as unnecessary for public policy to influence their food choices. However, over a
lifespan, poor food alternatives can cost both individuals and society. For instance, proper
nutrition among children is recommended in order to support cognitive and physical
development. For adults, having an inadequate diet quality can cause the risk of numerous
chronic diseases, such as heart disease, stroke and high blood pressure (Guthrie et al.,
2015, p. 501). Therefore, public consumer education can help consumers to make
sufficient food choices which may have the benefit of nudging by providing nutrition
information to consumers (Guthrie et al., 2015, p. 502).
1.1.2 Healthy food as a concept It can be difficult to determine what the concept “healthy food” actually means. The
concept definition can also vary based on which viewpoint you take. For many, the
distinction between healthy and unhealthy food could be possibly measured by looking
at the amount of sugar or fat in the food whereas some people might consider organic and
ecological products as healthier. On the other hand, some could define the difference
between healthy and unhealthy food based on the level of processing for instance,
choosing a salad instead of a ready-meal. However, eating healthy is not about staying
idealistically thin or depriving yourself from food you love. It is more about feeling great,
having more energy and improving your health. For every diet expert who gives you
information about a certain food that is good for you, you will find another saying the
opposite which can be slightly confusing. For that reason, the foundation of a healthy
2
eating should be to replace administered food with real food anytime. Choosing food that
is closer to the way nature made it can have a positive effect on the way you think, look
and feel (Robinson et al., 2019).
To take a more scientific viewpoint; in a research by Imamura et al. (2015, p. e133) the
researchers divided foods between healthy and unhealthy category for their study: one
consisting of fruits, vegetables, beans, nuts, seeds, whole grains, milk, total
polyunsaturated fatty acids, fish, plant omega-3s, and dietary fiber. For the other group
the authors selected unprocessed red meats, processed meats, sugar sweetened beverages,
saturated fat, trans fat, dietary cholesterol and sodium). Fruits and vegetables are found
to be playing an important role in a healthy diet and should be preferred over sugary or
fatty foods (Krebs-Smith & Kantor, 2001, 497-498S). They are also a great source of
dietary fiber (Kearney, 2010, p. 2797). It has also been detected that large fiber intake in
a diet has an decreasing effect on some medical conditions such as heart disease, high
blood pressure, obesity and several cancers (Anderson et al., cited in Darian & Tucci,
2011, p. 421).
1.1.3 What is nudging? “A nudge is any aspect of the choice architecture that alters people’s behaviour in a
predictable way without forbidding any options or significantly changing their economic
consequences. To count as a mere nudge, the intervention must be easy and cheap to
avoid. Nudges are not mandates. Putting fruit at eye level [to attract attention and hence
increase likelihood of getting chosen] counts as a nudge. Banning junk food does not”
(Thaler & Sunstein cited in Ly et al., 2013, p. 5).
The idea behind nudging is to influence behavior by modifying the way choices are
presented in the environment. Changes in the environment can affect the behavior without
influencing financial incentives or limit the freedom of choice. However, a significant
change in economic effect may not be seen as a nudge, a nudge may contribute to
highlight an economic incentive (Ly et al., 2013, p. 5).
Taking a closer look at nudging in daily life, one can say that a GPS is an example of a
nudge as well as an app that counts peoples’ calories per day. Nudging can also be an
alarm clock or an automatic enrollment in a pension plan. It can also be a system for
automatic payment of credit card bills and mortgages (Sunstein, 2014, p. 583). When
speaking about nudging, it is important to see that the aim of many nudges is to make life
easier for people to navigate. For instance, when officials decrease or eradicate paperwork
requirements and instead promote simplicity and transparency, they are contributing to
reducing peoples’ burdens. Moreover, many nudges have the purpose to make sure that
people do not struggle when they seek to cooperate with the government or when they
want to achieve their goals (Sunstein, 2014, p. 584). Moreover, some nudges can be
described as “soft paternalism” (Sunstein, 2014, p. 584), because they navigate people
towards certain directions. However, nudges are designed to maintain a full freedom of
choice.
When speaking about official nudging, it should be more transparent and open rather than
hidden and covert. For instance, if a series of private stores decide to make healthy food
more visible for the consumers, the actions taken should not be hidden or covert. Nudges
should never be manipulative or tricky. This means that the public should be able to
review and scrutinize a nudge. Nudging can come in different ways, therefore Sunstein,
3
(2014, p. 585), has presented some important nudges in his article. Default rules, which
are seen as the most effective nudges, because automatic membership in health care plans
to improve health can have major effects. Simplification, this nudge can be little
problematic since it has a tendency of causing confusion. Use of social norms, this type
of nudge is to advise people that most others are involved in a certain behavior. Increases
in ease and convenience, this nudge focuses on making low-cost options or making
healthy foods more visible.
1.1.4 Need for nudging and purpose behind it In the past years, both private and public sectors have shown an increasing interest in
nudging because they mostly cost little and have the ability to promote economic goals
and other goals such as public health (Sunstein, 2014, p. 584). Moreover, all over the
world, even countries have become increasingly interested in nudges. For instance, the
UK has formed a behavioral insights team to which they call the “Nudge Unit” (Sunstein,
2014, p. 585), and the USA has formed a white house social and behavioral sciences team.
The mounting interest in nudges has its roots in the fact that they normally enforce low
or no costs at al. In the context of consumer behavior, nudging has shown the ability to
protect and save consumers against serious economic harm (Sunstein, 2014, p. 585).
Nudging has been used especially on measuring how the positioning of food affects
consumers’ decisions, and it has connected to healthier food consumption habits. It has
been argued that by arranging the groceries differently on the shelves, it has an effect on
how consumers choose their goods (Szaszi et al., 2018, p. 356). In a comparison
conducted, 16 out of 18 studies presented a positive effect on the groceries chosen,
illustrating the effectiveness of a nudge (Bucher et al, 2016, p. 2254).
Looking at nudging throughout the world, people have failed to make healthier life
choices in their own interest, because most citizens prefer to live unhealthfully or endure
from disability and disease. For this reason, nudging has been viewed as a natural
candidate in public health. However, although it is right that when easy nudging is about
advocating certain choices by making them easy, this idea is aimed in the sense of
developing evidence based on making target choices cognitively easy or intuitive (Hansen
et al., 2016, p. 241).
1.2 Problem discussion
1.2.1 Nudging in grocery stores It has been argued that supermarkets around the world are working in an important
position when it comes to forming dietary actions and yet snack foods are exceptionally
common in supermarkets globally (Thornton et al., 2013, p. 7). The existence of a large
amount of snack food in grocery stores has been found to be nearly unavoidable for
consumers to see during their visits in the store (Thornton et al., 2012, p. 7; Thornton et
al., 2013, p. 7). It was found out that 89,5% of the food products displayed to kids in
grocery stores were unhealthy (Horsley et al., 2014, p. 2456).
It has been argued that checkout policies in food stores were connected to decreased
bring-home purchases of sugary and salty snacks, the amount of these purchases also
showed out to be lower in those food stores that had implemented food policies (Ejlerskov
et al., 2018, p.17). These kind of voluntary store undertakings can be thus connected to
effect on the products purchased, decreasing the amount of sales of unhealthy products
4
and that way contribute to the health of the consumers by encouraging the consumers to
buy healthier products (Ejlerskov et al., 2018, p. 16-17).
Nudging efforts in grocery stores seem to influence positively on people and are
considered being helpful for the shoppers, especially for those with families. It was
perceived important that the actions for replacing unhealthy foods with healthier options
were taken, as there was detected irritation from the consumers’ side when it comes to a
large selection of unhealthy foods in grocery stores. However, at the same time, the sales
of sugary goods stayed on the normal level (Winkler et al., 2016, p. 7-8).
Nudging may not only affect the consumers positively, but it could help with grocery
stores’ branding activities: according to the study by Winkler et al. (2016, p. 10) placing
healthy food alternatives on the checkout messages the stores’ eagerness to implement
actions that the customers appreciate. In addition, this can help the stores to promote the
responsible actions they are doing and thus improve the customer loyalty (Winkler et al.,
2016, p. 10).
According to Hagman et al. (2015, p. 446) the average percentage for supporting nudge
policies in Sweden was high, nearly 73% (72,2%) when at the same time the percentage
in the United States was 66,1%. However, at the same time, many considered nudge
procedures to be interfering to freedom of choice, on average approximately 56% (in
Sweden). Sweden’s higher nudge supporting number could be explained for example with
the collective welfare state model and solutions that include everyone (Hagman et al.,
2015, p. 449). It was also found out, that people that are individualistic, found it harder
to accept nudges, whereas analytical people were less likely to think that nudges limit
freedom of choice highlighting the fact that nudges affect differently on different people
(Hagman et al., 2015, p. 451-452).
1.2.2 Consumer decision making process in grocery stores – habit vs choice The individualized behavior change is unproductive unless it converts into a habit. This
in turn requires support and empowerment through structural or environmental change,
in order to make sure that the new behavior is sustained. When it comes to dietary habits
and food choices, one can see them as a result of decisions and actions that are centered
on routines. This requires less effort in decision making as well as in thoughtful decision
making, where choice alternatives are cautiously considered (Bucher et al., 2016, p. 2252-
2253).
Looking at the consumer decision making process in grocery stores, consumers in many
parts of today’s society are fortunate with a range of choice when buying food products.
The first step in purchase occurs when a consumer scrutinizes the food and requires more
information. This means that an effective brand might be a key for quality, which may
lead to a purchase (Abdul et al., 2009, p. 40).
Regarding consumer choices and preferences, it is not given in advance but formed as a
result of the choice perspective. When it comes to decision making, consumers tend to
use stimuli and hints given in the moment of grocery shopping. For that reason, the
structure and framing in the choice perspective can influence how consumers process
information about relevant features and thereby consumers’ final choice of products to
purchase (Clement et al., 2013, p. 188).
5
Clement et al. (2013), did a study focusing on consumers’ in-store visual tactics and
decision-making. There have been several arguments saying that consumers buy
groceries by routine or by easy rules when they purchase their everyday groceries. There
have also been some arguments saying that consumers make most of their decisions in
the grocery shop, which is affected by the visual stimuli in the store. The paper written
by Clement et al. (2013) had the aim to investigate the visual saliency from two elements,
in-store signage and placement of products. The result shows that consumers tend to stare
longer at the target products when a signage is put in front of the shelf. The result also
shows that placement of products has a positive affection on volume sales (Clement et
al., 2013, p. 191-192).
According to a study, factors that can have a hindering effect on healthy food choices can
be categorized into two. The first category was named “a lack of self-efficacy in choosing,
preparing and cooking healthful foods'' (Hollywood et al., 2013, p. 124). In this category,
consumers found it more expensive and time-consuming to choose healthy foods during
their shopping tour. They also tended to choose more unhealthy alternatives due to habit
or because they found them faster and easier to cook. In addition to this, some consumers
felt that they lack knowledge when it comes to choosing the healthier alternative and
found it hard to rely on the label information (Hollywood et al., 2013, p. 121-122).
The study also found out that decisions between healthier or unhealthier alternatives can
be affected by family members’ opinions: consumers chose foods that they know
everyone in their family is eating, and thus avoiding cooking multiple different meals.
The study showed that the shoppers’ decisions in the grocery store were steered by
cravings and longings, meaning, surprising a family member with something they like, or
buying something to reward themselves (Hollywood et al., 2013, p. 122-123). This
behavior was categorized under “conflicting needs when satisfying self and others”
(Hollywood et al., 2013, p. 124).
1.2.3 Consumer free choices of grocery When it comes to store choice it can be a challenging decision for consumers to decide
where and when to shop. The first challenge includes the traditional store location choice
problem. The second challenge involves a shopping trip that includes information about
choosing the same store on subsequent shopping trips (Leszczyc et al., 2000, p. 324).
Regarding grocery shopping, it consists of a routine type of consumer behavior. Often
when consumers do their grocery shopping, the aim is to satisfy goals that must be
achieved through the process of purchasing groceries. This process includes a complex
range of in-store stimuli such as products, brands and purchase information. These
situations in turn create a perspective in which purchase intentions and outcomes are
variable, depending on the situational factors (Park et al., 1989).
Competition in the retailing industry is increasing drastically and retailers are competing
against new retailers, which they did not compete with in the past. These developments
can be analyzed further in the grocery industry for instance. As a result of these changes,
consumers face an environment where they have to make a choice to either stay loyal to
one grocery store or to try out new grocery stores. To make an impact on consumers'
choice of grocery store, retailers need to know about consumers’ choice of store and their
switching behavior in order to develop appropriate strategies (Leszczyc et al., 2000, p.
324).
6
1.3 Research gap In the search of the research gap, the authors of this study found out that there has not
been conducted a study about nudging in grocery store context in smaller cities of
Sweden. Since both authors live in Umeå, the idea came up to focus the study here. When
searching for previous research, the authors found out that there have been studies
focusing on nudging, but these studies have focused on the national and international
level (such as Hagman et al, 2015; Winkler et al, 2016; Ejlerskov et al, 2018) and thus
the gap for city-level research was acquired. Therefore, with this thesis, Umeå will be the
main focus.
Umeå is the biggest city in Norrland county, without forgetting the vivid student life with
almost 35 000 students (Umea.se, n.d.). Another reason behind the choice of the research
gap is the fact that Umeå is known for its vegan trend and students who are active and
strive for a healthy life and thus it forms a suitable foundation for conducting a study
there. Therefore, Umeå as a city is an interesting subject for the study, as it is fascinating
to observe if these preconceptions are achieving support from this study and strengthening
the image of healthy lifestyle habits. It is also of interest to see how the attitudes toward
healthy food are formed among Umeå inhabitants. Furthermore, these results could be
compared to future studies conducted in other Swedish cities.
1.4 Purpose The purpose of this study is to understand the attitudes of citizens in Umeå toward how
the selection of healthy foods affects their choice of a grocery store. The purpose is also
to understand, if the nudging activities could have an effect in the decisions made and
that way contribute to healthier eating habits.
According to the World Health Organization (WHO) one cause for noncommunicable
diseases (NCDs) such as diabetes or cardiovascular diseases, is due to eating unhealthily
(WHO, 2020). These diseases affect largely on the economy, as they cause large expenses
for the health care systems, as well as decrease the available workforce due to people
suffering from these diseases (Hunter & Reddy, 2013, p. 1337). As mentioned, unhealthy
diet is playing a role as a risk factor in noncommunicable diseases, and therefore obesity
is one of the factors that often appears in connection to noncommunicable diseases
(Hunter & Reddy, 2013, p. 1337). Between the years 1988 and 2012, the percentual rates
of obese people in Sweden were increasing, from 6% to 12% for men, and from 5% to
12% for women, between ages 20 and 64 (SCB, 2014, p.398).
This field of research is important, as it can provide new insights on how the offerings of
healthy food alternatives are considered in Umeå and if nudging of healthier food would
be beneficial for the grocery stores. As the nudging policies in food stores has been
connected to positive contribution of healthy food purchases (Ejlerskov et al., 2018, p.
17), it would be beneficial to research the subject more on a local level.
1.5 Research questions: Using the background as a foundation for this study, this thesis will focus on the following
research questions:
RQ1: Does the selection of healthy food affect consumers’ choice of a grocery store?
7
RQ2: Does nudging of healthy food affect consumers’ choice of a grocery store?
1.6 Research Contribution This study will contribute to the field of study and the existing literature by providing
new data and understanding for the area of healthy food, consumer decision-making,
choice of grocery store and nudging. The results from this study can be used to strengthen
the existing literature and theories as well as provide a new research that is focusing on
the city of Umeå, where a study like this has not been conducted before. Moreover, the
results could be beneficial for other Swedish cities also and provide guidelines that can
be of use both in the governmental level when it comes to the health care sector, as well
as in local grocery stores. The findings can therefore help to understand how to fight
against unhealthy diet and eating habits as well as how to attract consumers to pick a
specific grocery store for their shoppings.
1.7 Limitations A limitation concerning this study is the time frame, which is approximately eight weeks.
Due to this, the time available is limited, which plays part on how broad the study can be
and how much time there is available to use for each different chapter of the thesis. This
study will be based on data collected through a survey and as mentioned earlier, due to
the limited time, it can affect the size of the sample and how long the survey can be out
for the public. It is possible that the time frame limits the number of answers acquired
during the study time and this can be seen as a limitation of this study. The time planned
for the survey to be out is one week and with that, the authors hope to gather as much
information as possible, because the aim is to have a large sample that can be generalized
on the whole population.
The biggest impact for our thesis during the writing process is formed by Covid-19, or in
other words, corona virus, which has forced the university to close its facilities and limited
the possibilities regarding library usage. As social distancing is recommended, the level
of physical working together has been forced to limit to bare minimum, leading to some
challenges, that are, luckily, rather easy to overcome by using video calls.
1.8 Delimitations The concept of healthy food can be understood in multiple different ways. The viewpoint
taken in this study has been chosen in order to be able to limit the study broadness and to
help when defining the product differences in nudging concept. Therefore, studies
conducted with different healthy food characterization could give a different result.
Another delimitation is that this study will focus on nudging in grocery stores, which
means that if clothing stores want to apply the knowledge from this study it would not be
of relevance. For that reason, another study on how to nudge consumers towards possibly
buying environmentally friendly clothes would have to be conducted. This study does not
either define the size of the grocery store when conducting the research, which could
imply that if this kind of differentiation were made, it could possibly affect the results
being varied based on the size of the grocery store and the people who shop there.
8
2 Scientific method In this section, the study’s scientific principles will be presented. The part of scientific
method lies in the basis for the research that will later be conducted and therefore is of
importance to present before the empirical research.
2.1 Philosophical considerations It is extremely important for the ones conducting a research, that the philosophical
considerations have been thought through before deciding the strategy for data gathering
(Wright et al., 2016, p. 97).
2.1.1 Ontology Ontology takes a viewpoint to reality’s nature (Collis & Hussey, 2014, p. 47; Saunders et
al., 2009, p. 110) and focuses on the nature of social objects or “entities”, as Bryman &
Bell (2011, p. 20) state. Ontology focuses on a question “what can we know?” (Wright et
al., 2016, p. 97). Ontology consists of two different viewpoints, namely, objectivism
respectively constructionism. The first one, objectivism, is focusing on a question of can
these social objects be classified as objective, so that they have an exterior reality to social
effects. Constructivist viewpoint is focusing on the investigation of if the social objects
are created by social actors through attitudes and activities, making them to be understood
as social constructions (Bryman & Bell, 2011, p. 20).
Objectivist viewpoint assumes that “social phenomena and their meanings have an
existence that is independent of social actors”, meaning, that social phenomena are
something external, that cannot be affected (Bryman & Bell, 2011, p. 21). A given
example is an organization, where everything is regulated and standardized, and where
the workers have not a possibility to influence their job tasks. As this thesis aims to
analyze the effect of healthy food to the grocery store choice as well as the effect on
nudging to healthy food choice using quantitative and statistical methods, the objectivist
view is applicable in this study, to ensure that the results are scientifically trustworthy.
Therefore, the social phenomena studied in this thesis are assumed to have an existence
that is external.
2.1.2 Epistemology & research paradigm Epistemological approach is reviewing the question of what can be identified as
acceptable knowledge and is measured through the connection between the one doing the
research and the research subject (Collis & Hussey, 2014, p. 47). Epistemology focuses
on finding out how we can acquire knowledge that is considered valid (MacIntosh &
O’Gorman, 2015, p. 58). One of the main questions in this approach is if the same
foundation, methods and assumptions should be used for studying the social environment
as when studying natural science (Bryman & Bell, 2011, p. 15). In epistemology, there
are two paradigms used, namely, positivism and interpretivism, which will be defined and
explained next.
A research paradigm is a philosophical framework that lies in the background for the
research. This framework is constructed with ideas, thoughts and knowledge. Looking
deeper into the paradigms, one paradigm that can be adopted is positivism. This paradigm
has its roots in realism. From a positivist viewpoint, the research is based on science and
empirical research that normally include observations or experiments (Collis & Hussey,
2014, p.44). Moreover, the framework of positivism is often used by researchers in
9
scientific studies and also to a large extent in social science studies. Furthermore, the
paradigm is manufactured upon objectivity, precision and logic. From a positivist
viewpoint, researchers believe that social reality, or phenomenon can be measured and
thus this paradigm is associated with quantitative methods that are based on statistical
analysis (Collis & Hussey, 2014, p.44).
Another paradigm that can be adopted in the research paradigm is interpretivism. This
paradigm is the opposite of positivism and believes that social reality is not objective, but
instead subjective. Researchers who adopt an interpretivist viewpoint see reality as being
created from the preconceived sentences (Collis & Hussey, 2014, p.45). Compared to
positivism, interpretivism sees the complexity that lies in the social phenomenon through
interpretations. For that reason, it is therefore appropriate to use methods that try to
describe or translate meaning in the social environment, as qualitative studies do (Collis
& Hussey, 2014, p.45).
The empirical study of this thesis will be conducted through a positivist viewpoint. This
is because the study will be based on surveys that will be analyzed through statistical
methods to avoid impact on the results and to increase the validity of the study. For that
reason, objectivity and generalizability is sought.
2.1.3 Axiology Axiology is a philosophical context that is defined by the researchers’ values in
connection to the study conducted, thus, it studies “judgements about value” (Saunders
et al, 2009, p. 114). According to MacIntosh & O’Gorman (2015, p. 69) axiology as a
term describes the philosophical research of value. In a study that has taken a positivist
approach, the research is assumed to be free of values, meaning, that the ones conducting
the research are external from the research project and understand the research
phenomena objectively (Collis & Hussey, 2014, p. 48).
As this study will use quantitative methods in data collection and analysis, it can be seen
external from the phenomena studied. The authors will not be interacting with the data
collection participants, and thus cannot affect their opinions while answering to the
survey. This has also been taken into consideration when planning the survey, so that the
questions are not misleading. Thus, the positivist viewpoint is supported in this thesis
from the axiological perspective.
2.2 Research approach Research approach is the relationship between theory and practice (Bryman, 2016, p. 21).
Considering research approaches, there are two approaches that can be adopted. And
these are deductive and inductive approaches. Deductive approach is more used in
scientific methods (Bryman, 2016, p. 21) and for conducting statistical analyses
(MacIntosh & O’Gorman 2015, p. 51). Looking deeper into the deductive approach, it
designs a theoretical frame of reference which is then analyzed by using empirical
observation. The opposite of deductive approach is inductive approach. Inductive
approach is based on observations. These observations are later investigated until a theory
has been developed (Collis & Hussey, 2014, p. 7).
In this thesis, a theoretical framework will be developed to be able to test hypotheses that
have been designed. For that reason, the study will adopt a deductive approach to connect
theory to practice.
10
2.3 Research strategy As mentioned before, this study will adopt a positivist approach. According to Collis &
Hussey (2014, p.49), large samples are more likely to be used in studies where researchers
adopt a positivist approach. The data of this study will be collected through surveys and
the goal is to have a minimum of 100 surveys in order to match the principles of a big
sample. Thus, the data collected for the empirical study will be primary data, and the
analysis of the result will be conducted through a quantitative research method.
The empirical study will be analyzed through a multiple linear regression. Since the data
will include a large sample, regression analysis is more relevant for the analysis. The
study will include one dependent variable and several independent variables that are
further converted into composite variables. This will be discussed more in-depth in the
practical method section.
2.4 Time horizon This study will take a short-term time horizon, also called to be cross-sectional. Cross-
sectional time horizon is used in studies that are focusing on a specific phenomenon at a
specific time (Saunders et al., 2014, p. 155). As this study is focusing on healthy food,
consumers’ grocery store choice and nudging, it describes a specific phenomenon that is
not related to a particular time frame. According to Collis & Hussey (2014, p. 63) a cross-
sectional study is often chosen when the time or assets are delimited. Therefore, the time
frame for the thesis course also supports the decision to have a cross-sectional study, as
it is limited. Thus, cross-sectional study is the right alternative for this thesis.
2.5 Literature search When searching for different scientific articles, the goal was to find as new and accurate
articles as possible, because the time frame for this study is 2020. However, finding recent
articles was not always possible. For instance, when searching for articles related to
consumer free choices of grocery, the authors were unable to find recent articles. For that
reason, articles from an old decade were chosen. However, even though these old articles
were used, the authors chose to use these articles because the information was still
applicable in today’s situation.
During the literature search, attention was paid to find those articles that had been peer-
reviewed, in order to use relevant and actual information regarding the subject. According
to Winchester & Salji (2016, p. 309), it is important to use peer-reviewed articles when
planning the literature review for the research. In addition to this, the articles and books
used were limited to be written in the authors’ native language or English, in order to
make sure that there would not be a risk of misunderstandings due to translations.
2.6 Source criticism When it comes to scrutinization of resources, according to Umeå University (u.å), there
are some questions that should be considered. For instance, it can be of relevance to ask
yourself who is the contact person behind the information you find. If it is an expert or an
authority and if there is any further contact information to that person. Moreover, one
should ask herself if the text in the source is objective and who the target group is. One
should also check when the material is published and if the material is still relevant for
the research.
11
Source criticism is of importance in scientific study in order to ensure that the study is
reliable. When searching for resources, one can find both primary and secondary sources.
It is better to use primary sources since the secondary sources are revised (Collis &
Hussey, 2014, p. 76). In this thesis, secondary sources have been used to cite earlier
studies and theories when the original source was not accessible. However, these sources
have been scientifically scrutinized and are therefore considered as reliable. The data that
will be used in this study will be collected through a questionnaire which makes this
information primary.
The sources used in this study have been found through databases at Umeå University
Library, Google Scholar and Business Source Premier (see table 1). These databases have
provided access to a large number of scientific articles, books and previous studies that
have been of use in this thesis. This way, it has been possible to acquire information to
introduce the background for the study, as well as strengthen the arguments stated in this
study.
The table below presents the main keywords used when searching for the literature,
including the search engine and the number of hits. In addition to this, more articles were
found through reading reference lists for relevant articles and that way finding more
information about the subject.
Table 1 - Keywords for literature search
Keyword Number of hits Search engine
Nudging 41 585
Umeå University Library
What is nudging 46 Business Source Premier
Consumer decision making 88 700 Business Source Premier
Nudge Theory 70 000 Google scholar
Social Marketing Theory 50 Business Source Premier
Libertarian Paternalism 56 Google Scholar
Choice Architecture + Healthy food 22 089 Umeå University Library
Theory of Reasoned Action + Nudging 2349 Umeå University Library
Theory of Planned Behavior + Nudging 8155 Umeå University Library
The new policies regarding the library are having an impact on the thesis work, as it is
not possible to study in the library or make book reservations. Due to this, some of the
theoretical material that could have been of use in this study, was not able to be acquired,
12
as those were already loaned out to other students, with loan renewals until further notice.
Therefore, some of the sources used in this thesis have been taken from the secondary
source article, to be able to make sure that all the needed information can be gathered,
however, this was tried to be avoided to the largest matter.
The aim was that the information used in this thesis would be as recent and relevant as
possible, and therefore sources with older publishing dates were tried to be avoided.
However, when it comes to the theories, it is not completely possible to always find the
most recent article, as the aim was still to find the original source, which often was written
many years ago.
2.7 Preconceptions & choice of subject The authors of this thesis have experience from thesis writing in the form of Degree
Project from Civilekonom program, which they graduated from in the summer 2019.
Therefore, this project is going to be the second thesis that the authors will write. This
will provide some advantages, as the authors still have the last year’s project in their
memory and thus the writing project is not something that is completely new.
Before the start of this thesis course, both of the authors had taken D-level courses on
marketing, including courses such as Marketing Strategy, Consumer Behavior, Consumer
and Market Analysis and Strategic Marketing Planning. During these courses the interest
in consumer behavior was raised, and when deciding the subject, the choice was obvious.
Even though the authors had taken the course about consumer behavior, they did not have
any previous experience concerning research about consumer behavior, and thus earlier
research about the subject was rather new. Before the thesis course started, the authors
spent time reading about nudging as a concept, in order to be able to define a more specific
research area that was of interest. During the first meeting as research partners the idea
for implementing healthy food as the main concept was raised and thus the idea for the
thesis research was defined.
2.8 Truth criteria Reliability, validity and generalizability are three concepts that are very important and
should be taken into account since they are important for the credibility of the study. In
this study, transparency is therefore of importance and for that reason the methodology
part will be presented in a clear manner. In order to present how the study will be
conducted and what the study will investigate. In the next section the three truth criteria
will be presented and explained how the study will be conducted to fulfill these concepts.
2.8.1 Reliability “Reliability is defined as “the accuracy and precision of the measurement and the
absence of differences if the research were repeated” (Collis & Hussey, 2014, p. 52).
Therefore, it represents one way to measure the credibility of the study. For a study to be
reliable, it should provide similar conclusions, if the study would be conducted again.
According to Collis & Hussey (2014, p. 53) replication is significantly important for a
study with a positivist approach. Reliability is of big importance in studies that adopt a
quantitative research approach. However, studies that adopt a qualitative research
approach do not have to be as reliable (Collis & Hussey, 2014, p. 53). This study will
adopt a quantitative research method; therefore, it is important to describe in a clear
13
manner how the study will be conducted. As mentioned earlier, the data of the study will
be collected through surveys and the variables that will be used in this study will be
explained clearly. This to make it clear what it is the study wants to investigate.
The term reliability is related to the term replication. The term replication means that
other researchers can choose to repeat a previous study. The reason is to minimize errors
and increase the validity of the study (Bryman & Bell, 2015, p. 50). In order for the result
to be replicable, it is important that the researcher clearly describes how the study was
conducted. Thus, if the researcher does not clearly describe how the study was conducted
in detail, the study is no longer replicable (Bryman & Bell, 2015, p. 50). Moreover, if the
study is not replicable, other researchers may doubt the validity of the study.
To guarantee that the study is reliable, the data collection will be carefully planned in
order to ensure that the right questions will be asked and that they are interpreted
correctly, while also following the recommendations for a quantitative study. The study
conducted is also tried to describe and explain as carefully as possible, so that the possible
researchers who would like to replicate the study understand what has been done.
2.8.2 Validity Another factor that impacts on the credibility of the study results is validity (Collis &
Hussey, 2014, p. 52). Validity is defined as “the extent to which a test measures what the
researcher wants it to measure and the results reflect the phenomena under study” (Collis
& Hussey, 2014, p. 53). In other words, validity implies the extent to which the findings
present what they actually are supposed to present (Saunders et al., 2009, p. 155). Factors
that impact to validity could be for instance errors in the research, such as bad sampling
or imprecise measurements or failed methods. Validity can be estimated through different
concepts, and two concepts that are often used are face validity and construct validity.
The first mentioned focuses on determining that factors that are used to explain the
phenomena studied, are suitable for that, whereas the latter one is meant for making sure
that hypothetical constructs are implemented in order to explain phenomena studied from
the viewpoint that is not precisely observable (Collis & Hussey, 2014, p. 53).
To conserve high validity in this study, the attempt is to strictly focus on the research
subject, and thus avoid ending up into side tracks. This is also done in order to keep the
research concept clear, and not expand it too broad. A risk for validity loss can appear
when collecting the data, if not enough answers are acquired due to the tight time frame.
When analyzing the results, the appropriate methods will be studied carefully to be able
to present reliable results.
2.8.3 Generalizability Generalizability refers, as the word implies, to the level the study and its results are
generalizable in other research environments (Saunders et al., 2009, p. 158). As the
sample will be gathered in Umeå, and the location is therefore not rather specific
compared to other Swedish cities, it is believed that this does not create an obstacle for
the study to be generalizable.
Regarding quantitative research, one of the main questions that normally appears among
researchers is if the empirical results can be applicable on a whole population (Bryman
& Bell, 2015, p. 174). Thus, in research that adopts a positivist approach, the result is
based on a sample that later can represent a whole population (Collis & Hussey, 2014, p.
14
54). There are different ways one can generalize the result on a whole population, and
one of them is to utilize a statistical test. Moreover, in qualitative research, it is often
important to think about generalizability, due to the fact that the sample is usually smaller
than the sample in a quantitative research (Bryman & Bell, 2015, p. 174).
As mentioned earlier, this study will be based on a quantitative research method and
therefore the sample that will be used in this study should be able to generalize on a whole
population. In this study, the sample will be collected through a questionnaire that will be
shared online to people in Umeå. However, the authors believe that all of Umeå’s
population would not be able to have access to respond to the questionnaire and thus the
sample might not be the most accurate representation of the whole population. Anyhow,
the aim is that the sample would be as generalizable as possible by acquiring respondents
from different ages and different genders. Even though the study will be based in Umeå,
it is still hoped to be generalizable in other cities.
2.9 Summary of the scientific methodology
Figure 1. Scientific methodology.
Philosophical assumptions
Research Approach
Ontology: ObjectivismEpistemology: PositivismAxiology: Positivism
Deductive approach
Time Horizon Cross-sectional
Scientific methodology
15
3 Theoretical Framework In this section, a presentation of earlier studies and theories that are relevant for this
thesis will be presented. The theories will then be used as a framework for the empirical
study. Furthermore, theories will be examined in order to give the reader a deeper
understanding and knowledge about nudging and its elements.
This research bases its foundation on behavioral economics and is affected by several
theories in that field. Nudge theory acts as the red thread through this thesis and the other
theories are providing support and examples regarding nudge policies and actions.
Moreover, this thesis focuses on consumer behavior and uses some of the well-known
theories as a foundation, in order to understand the concept and what impacts on the
decision-making processes. The figure below illustrates the theoretical framework and is
further explained in this chapter.
Figure 2. Theories.
3.1 Behavioral economics Behavioral economics is defined as a mix between psychology and economics, and due
to the behavioral aspect, and it can be used to create economic behavior models together
with other social sciences (Thaler, 2016, p. 1577) such as sociology, philosophy or
anthropology (Diacon, 2014, p. 172). The neoclassical economic approach presumes
individuals to be rational and thus aim for the highest possible utility and the traditional
economic idea about human behavior has its foundation on the following characteristics:
rationality, egocentricity and indefinite will (Diacon, 2014, p. 177). That is why the aim
of behavioral economics in the beginning was to develop and understand illogical
consumer decisions better, and thus deforming the classical definition of a rational
consumer in economic context (Reed et al., 2013, p. 35).
“When people make choices, they do so based on a set of expectations about the
consequences of their choices and the many exogenous factors that can determine how
the future will evolve” (Thaler, 2016, p. 1593).
According to Reed et al (2013, p. 35) irrational decision making is a typical assumption,
meaning that people are affected by enticements and are making bad decisions even if
they know that deciding otherwise could be more beneficial. An example of this kind of
behavior is a situation, where a kid chooses an unhealthy dessert, such as a brownie, over
an apple, without thinking of the longstanding effects caused by the decision (Reed et al.,
2013, p. 36).
Diacon (2014, p. 177) defined behavioral economics as a collection of different economic
approaches that are challenging the traditional viewpoints and researches about the
decision-making processes in economics. These traditional viewpoints are aimed to be
Behavioral Economics
Nudge Theory
Choice Architecture
Libertarian Paternalism
Theory of Reasoned
Action
Theory of Planned Behavior
Social Marketing
Theory
Cognitive Architecture
Status Quo
16
expanded and enhanced with psychological models concerning decision-making.
Behavioral economics also leaves out some approaches, such as the economic rationality.
Behavioral economics can be seen as a piece of the increasing significance for empirical
work in the economics context, including framing, self-discipline and fairness. These
elements can make us understand our surroundings more effectively as well as strengthen
our behavioral understanding (Thaler, 2016, p. 1597).
Behavioral economics provides a solid foundation for this study by providing the
background for the irrational decision-making and acknowledging the fact that people do
not always make good decisions (Reed et al., 2013, p. 35), which is why policies like
nudges can be beneficial for people.
3.2 Nudge theory The book Nudge by Richard H Thaler, has its foundation in two main concepts: choice
architecture and libertarian paternalism (Thaler, 2018, p. 1283). As described earlier in
the thesis, “a nudge is any aspect of the choice architecture that alters people’s behavior
in a predictable way without forbidding any options or significantly changing their
economic incentives.” (Abdukadirov, 2016, p.21). One can also see nudge as changes to
the choice architecture around alternatives that motivate people toward choices that better
fulfill their interests. Choices are not influenced and in that way nudge works more as a
libertarian. Because people are free to make the same choices as they would have made
without the nudge (Abdukadirov, 2016, p. 21).
Analyzing the nudge theory deeper, Thaler and Sunstein, who are the main authors behind
the theory, give several examples of nudges in their academic work. One of them is an
experience conducted in a cafeteria, where the manager restructured the food items. To
be able to promote healthy eating among people who worked at the cafeteria without
taking away their free choice, the manager decided to put healthier options at the front of
the shelf and in the light. With this example, while customers are free to take from
whichever choice they want in the cafeteria, the manager takes advantage of their
behavior to steer them toward healthier choices (Abdukadirov, 2016, p. 21).
Regarding the example given by Thaler and Sunstein, one can see that it becomes obvious
that nudges can be implemented by a variety of actors and it can come in different forms
and strive for achieving a wide range of outcomes. For one, it seems like anyone can
nudge. For instance, the government can nudge to lower teenage pregnancy, business can
nudge to improve consumers’ health outcomes. Individuals can also nudge themselves.
For instance, they can nudge themselves to quit smoking (Kosters & Heijden, 2015, p.
279).
Thaler and Sunstein’s definition of a nudge has faced some criticism of nudging as a
concept. Moreover, nudging can be one of two things. First, it can be a governance
involvement that seeks to guide individuals to make choices that are in their own best
interest, which refers to as “type 1 nudges” (Kosters & Heijden, 2015, p. 279). Second,
nudge can be a governance involvement that wants to stimulate individuals’ behavior to
achieve a preferred collective end such as reducing crime and encouraging
environmentally friendly rituals (Kosters & Heijden, 2015, p. 280). A study by Hagman
et al (2015, p. 439, 441) has found out similar data: pro-self nudges are described to be
focusing on an individual’s well-being, such as a decision between a healthy or unhealthy
snack whereas a pro-social nudge is connected to the collective well-being, such as a
17
decision between recycling or not recycling. It was found out that pro-self nudges tend to
be less accepted by people, and that they are more connected to the limitation of freedom
of choice (Hagman et al., 2015, p. 451). Hagman et al. (2015, p. 452) also state that pro-
social nudges cannot be connected to libertarian paternalism the same way as pro-self
nudges, as they cannot be seen to support private well-being due to the aim for common
good.
Nudges do not always come without any concerns and for that reason, concerns about
nudges can be split into three categories: epistemic, ethical and practical. The epistemic
issues are the ones that are the leading factors to the ethical and practical problems. The
epistemic problem with nudges occurs when policymakers do not know the true interests
of the people that are being nudged. Taking for instance the scenario of promoting healthy
eating in the cafeteria, policymakers do not know if these nudges stimulate the true
benefits of any given individual. Health and wealth can be of interests to all individuals,
but each person understands them and combines them with other interests in different
ways, which policymakers have no knowledge about (Abdukadirov, 2016, p. 22).
All this vagueness does not help policymakers to gain a better knowledge of when and
when, where and why nudging may result in desired outcomes. Moreover, it will not help
policymakers to know if nudging results in more optimal effects than other governance
interventions. With that being said, nudging as defined by Thaler and Sunstein is difficult,
close to impossible to evaluate due to the seemingly all included understanding of the
governance involvement they seek to capture (Kosters & Heijden, 2015, p. 280).
As described earlier, there are different types of nudges and one of them is increases in
ease and convenience which focuses on making low-cost options or making healthy foods
more visible (Sunstein, 2014, p. 586). People often make choices that are easy for that
reason, if the goal is to promote a certain behavior, decreasing certain barriers is helpful
(Sunstein, 2014, p. 586). Since this thesis will be focusing on analyzing how the selection
of healthy foods affect consumers’ choices of grocery stores in Umeå and if nudging can
affect that behavior, the increases in ease convenience nudge will be the focus of this
study. The nudge theory will be used to get a better understanding on how nudging can
affect customers towards choice of a grocery store.
3.3 Choice Architecture As a term, choice architecture is described as: “the environment in which people make
decisions. Anyone who constructs that environment is a choice architect” (Thaler, 2018,
p. 1283). Another description given is the following: “the fact that there are many ways
to present a choice to the decision-maker, and that what is chosen often depends upon
how the choice is presented” (Thaler & Sunstein, as cited in Johnson et al., 2012, p. 488).
With choice architecture it is possible to affect, for example, the arrangement of different
choice opinions, to their order elements as well as the range of defaults. It could be
thought that when arranging choices, the result would be unbiased, but this is not true.
The order of the choices arranged will always have an effect on the decisions made.
(Johnson et al., 2012, p. 488)
Choice architects are facing the question about the appropriate number of choice
alternatives suitable to present for the ones deciding (Johnson et al., 2012, p. 488). To be
able to decide this, two different conditions are needed: firstly, the more alternatives there
are available, the easier it is to satisfy the decision makers’ needs. Secondly, the more
alternatives there are available, the more consuming it is for the decider. To find a suitable
18
solution for this, the willingness to engage in decision making, the contentment towards
the choice process as well as the process in general will be taken into consideration
(Johnson et al., 2012, p. 490).
A study by Thorndike et al (2014, p. 146) found out that by implementing a change in the
food setting can have a large effect on public health procedures, for example in the fight
against obesity. Their study also showed that the consumer behavior is possible to change
to pick healthier alternatives by labelling foods and by making interventions to the food
setting (Thorndike et al., 2014, p. 148), in other words, using choice architecture. They
used a method called “traffic light labeling”, where each food in the cafeteria got either
green, yellow or red labels on them based on the healthiness of the food. After this the
items were organized by setting all the green labelled foods to the eye level (Thorndike
et al., 2014, p. 144). According to the study, the food industry can contribute significantly
to the problems with obesity while still being successful and profitable.
Choice architecture is a useful concept in this study, as it allows a better understanding
when it comes to grocery store decisions and the healthy food selection there, as the order
of the choices will have an effect on the decisions (Johnson et al., 2012, p. 488).
3.4 Libertarian Paternalism The term paternalism according to Thaler (2018, p. 1283) means “choosing actions that
are intended to make the affected parties better off as defined by themselves”. In other
words, the aim is to help decision makers to end up making choices that they would do
with sufficient information available. With the word libertarian Thaler means to explain
the word paternalism even more, meaning, that nobody is forced to any actions. Thaler
gives a good example of libertarian paternalism, namely, GPS maps. Here the people have
the whole power to decide themselves, which route is the best alternative for them to get
to the wanted location, without any preliminary settings for choices (Thaler, 2018, p.
1283).
According to Thaler & Sunstein (2003, p. 175) it is unavoidable to make decisions in
organizations, and therefore paternalism will always exist there. This is the easiest to
notice when default rules are being set, for example, when a cafeteria worker is arranging
the food served, and chooses to put fruits before the desserts. A one step stronger action
would be to have the desserts placed on another table, further away, so that the ones eating
would have to especially go and get the dessert. As the placement of the dessert is still in
the cafeteria, it is easily accessible and voluntarily chosen, it can be classified as
libertarian (Thaler & Sunstein, 2003, p. 177).
How are the choices made then? Thaler and Sunstein (2003, p. 178-179) propose there to
be two different methods to use. First, if possible, a cost-benefit analysis should be
conducted, to compare the different choices, however, sometimes there may be a lack of
information and thus this comparison cannot be made. Another method to use can be
divided into three different viewpoint alternatives: 1) choosing the tactic “that the
majority would choose if explicit choices were required and revealed” 2) choosing the
tactic “that would force people to make their choices explicit”, so force the people into
making a decision, or 3) choosing the tactic “that minimizes the number of opt-outs”,
referring to automatic enrollment of people. The aim should be, that no random,
haphazard or damaging effects should be experienced, and the outcome would be
beneficial for the prosperity of the people.
19
Libertarian paternalism contributes to this thesis by strengthening the foundation for the
theoretical framework. As Thaler & Sunstein (2003, p. 175) stated, it is unavoidable to
make decisions in organizations, and therefore it is of interest to see if the choices made
in different grocery stores have an effect on how people decide in which grocery store
they want to shop at.
3.5 Theory of Reasoned Action The theory of reasoned action (TRA) includes two assumptions, namely, behavioral belief
and normative belief. The first one is described as “people are assumed to hold multiple
behavioral beliefs each of which links performance of the behavior to a different
outcome” and the latter as “person’s subjective probability that a particular normative
referent wants the person to perform a given behavior”. The mentioned referents can be
for instance family members or work colleagues (Ajzen, 2012, p. 440-441).
By linking the beliefs and outcomes together, a person creates either a positive or negative
stance to the behavior (Ajzen, 2012, p. 441). According to the model, a person’s attitudes
and behavior are connected to each other by their action, goal, setting and time, which is
called the principle of compatibility. Therefore, the theory of reasoned action provides a
possibility to reflect a person’s behavior through his or her attitudes. TRA also concerns
the social norms that are connected to people’s behavior; thus, a willingness towards a
specific behavior is a mix between the person’s attitude and a subjective norm which
work as a measurement towards the performed action (Ajzen, 2012, p. 444-445).
A study by Petrovici & Paliwoda (2008 p. 263) found out that attitudes, consumptions
habits and past behavior have an impact on the behavior intention when buying food.
From these three factors, habits were found to be the most significant factor affecting the
eagerness to consume whereas the past behavior had the smallest impact on consumption,
especially on fruits (Petrovici & Paliwoda, 2008, p. 263-264).
Childhood obesity has been increased the past years around the world. Due to that, the
theory of reasoned action and the theory of planned behavior (TBP) have been used to
plan and calculate different ways to involve different dietary behaviors. A study written
by Hackman & Knowlden (2014), has the aim to review and integrate theory of reasoned
action and theory of planned action based dietary behavior. The theory of planned
behavior will be explained deeper later in this study. The target group for this study was
adolescents and young adults. Hackman & Knowlden (2014) conducted eleven different
studies and nine of them gave a result in dietary behavior change that was featured in the
treatment of TRA and TPB-based dietary behavior. Moreover, ten of eleven studies
showed that there was a change in one concept of TRA or TPB based dietary behavior.
By understanding better the roles of attitudes and habits to food consumption from a
theoretical perspective, the theory of reasoned action can be useful when planning the
data collection for this study and also when comparing the results from this study to
previous literature.
3.6 Theory of Planned Behavior Theory of planned behavior (TPB) can be seen as one of the reasoned action theory
models and focuses mostly on goal-oriented behaviors that are affected by self-regulatory
manners (Ajzen, 2012, p. 450-451). As in theory of reasoned action, the theory of planned
20
behavior suggests that people are affected by behavioral beliefs, meaning the existing
beliefs towards possible outcomes of a behavior. People are also affected by normative
beliefs, referring to beliefs towards normative expectancies and actions by referents
(Ajzen, 2012, p. 448).
TPB is adding one more function to these behavioral intents, namely, perceived
behavioral control or control beliefs. This reflects on the importance of aligning attitudes
and subjective norms as well as the confidentiality of a person’s will towards a specific
behavior when defining the level of behavioral intentions. This affects the same way vice
versa, meaning, that if a person is less confident toward a specific behavior, they are less
likely to intent to act so. Henceforth, this third function can act as a stimulus in behavior
through the positive or negative effect on the performance (Ajzen, 2012, p. 447-448).
Therefore, the first function, behavioral beliefs, forms the attitude for a behavior, while
the second function, normative beliefs, describes the experienced social pressure. Lastly,
the third function, control beliefs, work as a strengthening factor for behavioral control.
According to the theory, if the attitude, social pressure and control are perceived strong,
will this lead to more powerful performance of the behavior at hand (Ajzen, 2012, p. 448).
According to a study by Weijzen et al. (2009, p. 114) when comparing people’s intention-
behavior consistency regarding snack choice habits, the ones with a healthier intention-
behavior consistency had better attitude towards health, they were more used to choosing
healthy snacks and they did not find it as negative to choose a healthier version. They also
found healthy snacks more appealing whereas unhealthy snacks less appealing and were
more likely to be educated women.
The study found out that approximately every fourth person who first was planning to
choose a healthy snack ended up choosing the unhealthy one, illustrating the gap between
desired and actual behavior. However, the study also showed that those who had an intent
to choose a healthy alternative, were actually likely to stay in their choice, and choose the
healthy snack. It appeared that factors that can play a part in intention behavior
consistency are for instance gender, education, snacking habits and controlled diet
(Weijzen et al., 2009, p. 117).
A study by Chan et al focused on adolescents and found a connection between the intent
to eat healthily and subjective norm from media, self-efficacy, attitudes and perceived
behavioral control (Chan et al., 2016, p. 22) and acknowledges the negative impacts of
unhealthy food consumption, both physically and psychologically as well as the social
and economic consequences (Chan et al, 2016, p.25). It was also found out that females’
attitudes for healthy food were connected to their behavior intents, whereas the same
connection was not found from males. Furthermore, males and their behavior intent were
connected to subjective norms, when at the same time females were not (Chan et al., 2016,
p.22).
By understanding the theory of planned behavior and especially the intention-behavior
consistency it could be easier to understand the consumers and their choices when it
comes to choosing a grocery store and when examining, if nudging would have an effect
to that. The previous studies also provide useful examples regarding which measurement
factors to use when conducting the study.
21
3.7 Social Marketing Theory “Social marketing is the systematic application of marketing alongside other concepts
and techniques, to achieve specific behavioral goals for a social good.” (Velma et al.,
2018, p. 237). Social marketing is a method that interprets the insights of the researchers,
into the focus audience to a mix of strategies. These strategies can be categorized under
the 4 P’s which are product, place, price and promotion. The categorization is done
according to the target they affect and match with nudging strategies (Velma et al., 2018,
p. 237). Traditionally, marketing worked as a strategy that helped business firms to assure
potential customers to purchase or use their products. One can say that it was a strategy
that seeks to connect potential buyers to a firm’s products or services (Chriss, 2015, p.
56).
Looking at nudging through a social marketing perspective, one can see that many studies
have its focus on how the environment can be improved by encouraging healthier eating
behavior among consumers. Strategies taken to encourage healthier eating are not often
examined in real life settings such as worksite cafeterias or grocery stores (Velma et al.,
2018 p. 236). A study conducted by Velma et al. (2018) has the aim to investigate the
effects of a healthy worksite cafeteria. The result of the study shows that the way worksite
cafeterias offer their products to consumers affect their purchase behavior. The result also
shows that located nudging and social marketing-based strategies are efficient in
promoting healthier alternatives and it is also objective to remain effective overtime.
Testing social marketing-based strategies in a worksite cafeteria is of relevance because
the worksite cafeteria is a particular setting where people have freedom of choice. In the
cafeteria, there is no set up menu, but the products offered blended with impulsive human
food choice behavior, are influencing what customers’ choices. Moreover, many people
visit the cafeteria often during their working life. This means that even small
improvements will affect people’s diets positively. For instance, a 40-year-old person
who switches from eating white bread to whole-wheat bread can lower risk of getting a
stroke and high blood pressure (Velma et al., 2018, p. 236).
Regarding the society goals, they are predicted on a voluntary agreement of the citizenry
who believe that their actions in the private and public domains develop an estimate of
the good for the society. However, the process of achieving a good society seems to
involve a group of experts who are less concerned about sentiment or opinion. This means
that these experts sometimes go behind citizens back in order to move them toward a
better life. But this can lead to overt resistance and for that reason, governments can use
social marketing to nudge citizens toward valued ends (Chriss, 2015, p. 54).
The social marketing theory will be used in this study in order to find out which social
marketing techniques grocery stores in Umeå use in order to stimulate buying healthy
groceries among consumers and how that affects the choice of grocery store. The study
written by Velma et al. (2018) shows that a social marketing-based strategies can promote
healthier alternatives, this theory will be used in this study to see if there are any
correlation between social marketing strategies and choice of a grocery store.
22
3.8 Cognitive Architecture Cognitive architecture includes an outline of cognitive load theory, which is a theory that
has been designed “to provide guidelines intended to assist in the presentation of
information in a manner that encourages learner activities that optimize intellectual
performance” (Sweller et al., 1998, p. 251). Cognitive architecture includes features of a
cognitive agent that includes short-term and long-term memories. However, research on
cognitive architecture is essential because it helps the goal of cognitive science (Langley
et al., 2009, p. 1).
One of the main challenges in creating human-level agents is to define the structure of
the store and process knowledge. The architecture includes design of the memories, the
administering and controlling tools. Cognitive architecture has memories and
representations of data. Furthermore, cognitive architecture can be found between the
physical level and the cognitive level, where it has the task of encouraging knowledge. In
theory, one can see that cognitive architecture can be implemented in hardware (brain
structures). Thus, a cognitive architecture provides the methods and memories which in
turn help to process knowledge about the environment where problem solving, and goal-
oriented behavior is current. This leads to the fact that architecture combined with
knowledge leads to behavior (Laird, 2012, p. 5-8).
All over the world, policymakers have started to acknowledge reasonable value of
insights from a psychology and behavioral economics perspective into how people make
their decisions. These intuitions can give information about the nonregulatory as well as
nonmonetary policy involvements. For that reason, the discussion of behavior approaches
has implemented nudges, in order to stimulate people in a particular direction at the same
time as their freedom of choice is still offered (Hertwig & Grune-Yanoff, 2017, p. 973).
As described, cognitive architecture includes memories and encouragement of
knowledge. In this thesis, cognitive architecture will be used to illustrate the importance
of using nudging in grocery stores to stimulate consumers toward healthier eating.
3.9 Status Quo The majority of the real decisions consist of status quo alternatives. This means that the
decision makers chose to do nothing or maintain current or previous decisions. The
question that has been interested in researchers in economics, political science,
psychology and sociology history is how individuals make decisions. When individuals
make decisions, they have a ranking of alternatives and use rational choice to select their
most preferred alternative in this ranking. For that reason, if policymakers know
individuals’ ranking, they can forecast their choice infallibly (Samuelson & Zechauser,
1998, p. 7).
The article written by Samuelson & Zechauser (1998), had the aim to test status quo
effects. The main results of the study are that decision makers demonstrate status quo
bias. When meeting new alternatives, most of the time, decision makers hold onto status
quo alternatives. For instance, following customary company policy or purchasing the
same product brands or to remain in the same business (Samuelson & Zechauser, 1998,
p. 8).
23
Status quo can be explained in terms of deficit aversion. Since the current situation shows
that a transformation of expected loss in some aspects can result in a gain in other aspects.
People are more loss averse than gain averse and due to that, the losses are weighed more
than the gains. Therefore, the possibility of people preferring an alternative in which the
expected gains are higher than expected losses is low. The loss aversion has been
considered to be the leading factor between selling price and buying price (Ritov & Baron,
1992, p. 49).
Analyzing status quo, a possible explanation of status quo bias is that transforming the
status quo needs an act, but maintaining the status quo requires only an omission which
is a collapse to act. However, just as the status quo is irrational, so is the bias toward
omissions. If the best way to achieve goals I through rationality, and if people's goals
affect the future outcomes of decisions, then the current ways of achieving outcomes are
irrelevant (Ritov & Baron, 1992, p. 50).
Most of the time when people go grocery shopping, there is a higher chance that they will
choose the same groceries that they are used to. As status quo described, decision makers
can choose to either change their decisions or to maintain their decisions. If a consumer
decides to buy the same products whenever he visits the store, then a status quo bias is of
relevance in his case. During this thesis, the status quo theory will be used to analyze the
situation where consumers have to make new decisions.
3.10 Summary of the theoretical framework
Figure 3. Illustration of the theories used in connection to the subject.
From the theoretical framework, one can say that the theory of behavioral economics is
one of the most important theories when it comes to decision making. As the theory
describes, “when people make choices they do so based on a set of expectations about the
consequences of their choices and many exogenous factors that can determine how the
future will evolve” (Thaler, 2016, p. 1593). For that reason, the theory will be used in this
thesis to examine how people make their choices in grocery stores. Furthermore, the
nudge theory can be seen as the second most important theory of this thesis. Once one
understands how people make their choices, one can utilize nudge theory to stimulate
people towards healthier choices without forbidding any options or changing their
economic consequences.
Behavioral Economics
Nudge Theory
Libertarian
Paternalism
Choice
Architecture
Does nudging of healthy food affect consumers’ choices of a grocery store?
Theory of Reasoned Action Theory of Planned Behavior
Does the selection of healthy food
affect consumers’ choices of a grocery
store?
Social Marketing Theory
Cognitive Architecture
Status Quo
RQ 1 RQ 2
24
Choice architecture theory can be used in order to stimulate decision makers’ choice. The
decision maker will choose an alternative depending on how that alternative is presented.
If one succeeds in making a good presentation of the alternatives, one can also steer
decision makers towards desired choices. When consumers have been successfully
nudged towards healthier choices, the process of choosing the healthier choices is not
over. For that reason, one can say that after nudge theory, libertarian paternalism can be
helpful in the process of nudging people towards the choice of a grocery store. After
giving consumers free choice to decide, libertarian paternalism can be used to help
decision makers to make choices that they would make with adequate information. As
Thaler (2018) describes, “libertarian paternalism means choosing actions that are
intended to make the affected parties better off as defined by themselves”.
The theories of reasoned action and planned behavior provide a good foundation for
understanding how the decision-making process is affected by different factors, namely,
behavioral beliefs, normative beliefs and control beliefs (Ajzen, 2012, p. 448). This is
helpful when studying the first research question, which is, trying to understand the
decision-making of people regarding grocery stores. With the help of these two theories,
it is possible to analyze the different factors affecting this decision-making and also thus
connect the second research question into the study; studying the effect of nudging in the
decision-making. That way it is possible to form a whole picture from the theoretical side,
both from the stores’ sides what comes to nudging, but also from the consumers’ side
regarding the decisions made.
Social marketing theory can be seen contributing to both of the research questions. As
mentioned earlier, social marketing refers to marketing combined with other approaches
aiming for behavioral results in social favors (Velma et al., 2018, p. 237). This concept
will be reviewed in this study as well, as the reasoning for visiting a specific grocery store
and nudging policies will be evaluated based on the research conducted.
Cognitive architecture as a theory supports the nudge theory, by providing additional
insights on the nudging concept through memories and knowledge encouragement and
thus helps in processing the knowledge about the environment (Laird, 2012, p. 5-8).
Lastly, status quo concept is beneficial for this study, as it can help to explain the decision-
making for individuals and how their ranking of the most preferred alternatives can be of
use (Samuelson & Zechauser, 1998, p. 7). As the theory describes, decision makers
choose to do nothing or maintain the previous decisions. Analyzing consumers' decision
making through the status quo biases can result in a better understanding behind the
reason for their final decisions.
3.11 Hypotheses Based on the theoretical framework, the following hypotheses were defined in order to
answer the research questions:
RQ1: Does the selection of healthy food affect consumers’ choice of a grocery store?
RQ2: Does nudging of healthy food affect consumers’ choice of a grocery store?
𝐻0: There is no positive connection between a store’s selection of healthy food and
consumers’ choice of grocery stores.
25
𝐻1: There is a positive connection between a store’s selection of healthy food and
consumers’ choice of grocery stores.
𝐻2: There is no positive connection between nudging of healthy food and consumers’
choice of grocery stores.
𝐻3: There is a positive connection between nudging of healthy food and consumers’
choice of grocery stores.
26
4 Practical method and data In this chapter the practical method including sampling and data collection strategy are
presented. In addition, the ethical aspects of data collection are considered, and
arguments provided to underline ethical standpoints for this thesis.
4.1 Choice of method There are two different main methods for conducting a study, namely qualitative study
and quantitative study (Bryman & Bell, 2011, p. 26). Typical for a qualitative study is
that it has its focus on the content and meaning in words, instead of gathering quantifiable
data. Qualitative research chooses an inductive approach, aiming for creating new
theories. Qualitative studies also acknowledge the social phenomena’s impact on social
entities (Bryman & Bell, 2011, p. 27).
This study uses quantitative methods when conducting the research. As the word
“quantitative” implies, this method has its focus on gathering and interpreting data that is
quantifiable. As mentioned before, a positivist perspective and deductive approach for
the study are typical for a quantitative study, and they are applied to this study as well
(Bryman & Bell, 2011, p. 27). In a quantitative study it is important to stay objective,
meaning that the researchers should not affect the data gathering process (Wright et al.,
2016, p. 98).
There are some factors that are describing the differences between a qualitative and
quantitative study; for instance, in quantitative study the researchers are more excluded
from the subjects studied whereas in qualitative study the researchers are often present
and near the studied subjects. In quantitative study the isolation is often preferred, as this
helps to keep the level of objectivity (Bryman & Bell, 2011, p. 410). Another factor
describing the difference between these studies is the level of structure; qualitative study
tends to be rather unstructured, to ensure that the data collected can provide all the
information needed, while quantitative study is more structured, in order to be able to
collect the relevant data. Quantitative studies also often aim for their results to be
generalizable, whereas qualitative studies focus more in the specific research setting
(Bryman & Bell, 2011, p. 411).
4.2 Research Design This study chooses an explanatory research design, which is convenient when
investigating relationships between different variables. Thus, researches that are focusing
on understanding causality, often take an explanatory approach (Saunders et al., 2009, p.
140).
Another possible research design would have been descriptive study, where the aim is to
understand and interpret phenomena as they are, and that way learn more about the factors
integrated to a specific dilemma (Collis & Hussey, 2014, p. 4). As can be understood from
the name of the design, the goal is to describe something particular (Collis & Hussey,
2014, p. 5). What is important in this research design, is that the researchers have to
understand the background for the problem coherently when starting the data gathering
(Saunders et al., 2009, p. 140).
An explanatory research design can be seen to be an extension to descriptive research
design and in this research design the aim is extended to understand why a specific
27
phenomenon is existing or how it works (Collis & Hussey, 2014, p. 5). As this study only
focuses on the causal effects, an explanatory study provides a better match with the
research purpose.
4.3 Sample A sample represents a part of a population and population is defined as “any precisely
defined body of people or objects under consideration for statistical purposes'' (Collis &
Hussey, 2014, p. 51). According to Collis & Hussey (2014, p. 197) if you cannot pick
the whole population for the study, you have to define a random sample that represents
the studied population. Considering the resources and time available, it is not possible to
make every Umeå citizen to answer the questionnaire, and thus a sample is needed.
Sampling can be categorized into two different sorts, namely, probability sampling and
non-probability sampling (Saunders et al., 2009, p. 213). Probability sample is connected
to the survey method, and it is useful when wanting to illustrate a specific population to
answer the research question using statistical methods (Saunders et al., 2009, p. 213-214).
Non-probability sampling represents the methods used that cannot be classified under
probability sampling (Bryman & Bell, 2011, p. 190) and is applicable when statistical
analysis is not used (Saunders et al., 2009, p. 213).
In probability sampling, a sampling frame is created. This frame consists of all the cases
included in the population that is being studied (Saunders et al., 2009, p. 214). The
population of Umeå in February 2020 was counted to be 128 901 inhabitants (Umeå
Kommun, 2020). As the population concerning this study consists of all the citizens in
Umeå, the authors did not have a possibility to create such a list. Saunders et al. (2009, p.
233) suggest therefore using another method for sampling. Concerning this, a suitable
sampling technique was found from the non-probability category.
In self-selection sampling the researchers let the potential people from the population
decide themselves, if they want to participate in the study. In this method, the need for
participants is informed for example in social media and thus collect data from the
voluntary participants (Saunders et al., 2009, p. 241). The authors published the
questionnaire in the social media platforms and expressed their need for participants to
respond to a survey. It was stated separately that the participants should be citizens of
Umeå as that is the sample.
Due to the limitations in conducting a probability sampling, some limitations can appear.
When the probability sampling allows the sample to be selected randomly, the non-
probability sampling is more defined through personal judgement (Saunders et al., 2009,
p. 232). Bryman & Bell (2011, p. 176) state that non-probability sampling can cause an
error, where some parts of the population studied are more represented than others. This
risk can appear in this study as well, since the questionnaire is shared in authors’ social
media platforms, which naturally consists mostly of students the authors have studied
together with. Therefore, there is a risk that students are overrepresented in the
questionnaire answers and thus skew the results. This can raise the risk for non-sampling
error, which is defined as the diversity between the sample and the actual population
studied (Bryman & Bell, 2011, p. 176). This is tried to be avoided in the largest matter by
keeping the survey open as long as possible, so that as many as possible have time to see
the survey and answer it. This is hoped to increase the diversity between the respondents.
28
Collis & Hussey (2014, p. 198) state that the bigger the sample selected, the better
possibilities it has to illustrate the population. However, they also argue that when writing
a master’s thesis, a certain level of ambiguity in the conclusions is allowed. Therefore,
the sample goal for this survey is 100 answers, but if possible, more. This has been
considered as a suitable number of answers keeping the time frame in mind. More than
100 answers are also desired, as there might appear some bias among the answers.
4.4 Data collection strategy When choosing a strategy for your study, the most important factor is that the strategy
works the designated study and allows conclusions to be drawn. Therefore, not one
research strategy is better than the others (Saunders et al., 2009, p. 141).
In this thesis study, a survey has been chosen as the strategic standpoint. Survey is a
suitable strategy for this study, as it is aimed for gathering an extensive amount of data
from a population. Therefore, survey is a great tool for gathering and analyzing
quantitative data and can even be used to analyze connections between factors, which
corresponds perfectly with the aim of this study (Saunders et al., 2009, p. 144). A survey
can be used to collect both primary and secondary data (Collis & Hussey, 2014, p. 62)
and in this thesis the data collected will be from primary sources.
According to Collis & Hussey (2014, p. 63) a survey can be either descriptive or
analytical. For this thesis, the analytical survey will be of use, as it can be used to
understand connections between different factors. A descriptive survey focuses on
illustrating a specific phenomenon at a specific time, which in fact, would not be wrong
in this study either, but it would not provide as in depth understanding for the subject
studied.
As the study’s time horizon is cross-sectional, it means that the data for the study is
gathered at one time, which is often rather short. This has also been called as snapshotting
the phenomenon studied (Collis & Hussey, 2014, p. 63).
4.4.1 Questionnaire One of the most common data collection techniques for survey strategy is to plan a
questionnaire, that can be used to standardize the data collected, and thus making it easily
comparable. Survey is also interpreted as non-complicated, which is beneficial regarding
the short time frame for the thesis writing (Saunders et al., 2009, p. 144). Collis & Hussey
(2014, p. 205) have defined the questionnaire to be “a list of carefully structured questions
which have been chosen after considerable testing with a view to eliciting reliable
responses from a particular group of people”.
To ensure that the survey meets the requirements for validity and reliability, it is important
that the questions are planned thoroughly and that the aim with the questionnaire is
explained. It is also important that the survey is not confusing for the participant
(Saunders et al., 2009, p. 362). The questions in the questionnaire were designed based
on the theoretical framework, and also the necessity of each question, meaning, that each
of them is contributing to answering the research question. An introduction for the survey
was written, so that the participants would have a better understanding regarding the
purpose and the aim of the questionnaire. The survey was designed in Google Forms,
which provides an easy and understandable way of designing a survey so that it is also
29
easy for the participants. The language in the questionnaire was chosen to be Swedish, as
the authors considered this to be improving the chances of acquiring more answers, so
that the respondents would be comfortable participating in the survey.
In addition to the previously mentioned, it is also important to pilot test the survey to see
that it works as it should (Saunders et al., 2009, p. 362). The authors were testing the
survey prior to publishing it, with the help of family members outside the sample and
noticed that some minor errors were detected, for instance a mistake on the age column.
This proved the importance of pilot testing the study and gave authors the possibility to
adjust the survey in order to gather reliable data. As the last factor, the handling of the
survey should be made in an organized manner (Saunders et al., 2009, p. 362).
Saunders et al. (2009, p. 362) have found that many researchers use questionnaires to
gather data without taking into consideration other methods such as secondary sources
such as observation and interviews. Gathering data through a questionnaire works best if
questions will be interpreted in the same way by all respondents. For that reason, the
authors behind this thesis sought to formulate the questionnaire in the way that will be
understandable for all respondents in the same way.
4.4.2 Types of questionnaires When it comes to designing a questionnaire, there are different types of them. These
questionnaires differ depending on how they are administered and specifically the amount
of contact you have with respondents. Self- administered questionnaires are normally
finalized by the respondents. These types of questionnaires are controlled electronically,
and in this thesis the chosen method is an internet-mediated questionnaire, which will be
filled in online. This was considered as the most appropriate method for this study as it
fits the time scale available as well as is considered as the best way to reach the sample
at the time, when social distancing should be embraced. Structured interviews known as
interview schedules. These types of questionnaires refer to the questionnaires where
interviewers meet respondents and ask questions face to face (Saunders et al., 2009, p.
363).
The question types used for the questionnaire were limited into two: category questions
and rating questions. The first mentioned, category questions, refers to a question type
where the one answering can only choose one answer option (Saunders et al., 2009, p.
376). The questions belonging to this category consisted of the demographic questions,
such as gender and occupation. In addition to category questions, rating questions were
used to understand the respondents’ opinions regarding nudging and their grocery store
behavior. In this questionnaire the implemented rating question style was similar to
Likert-style rating scale, where the answer is defined based on the level of agreement or
disagreement in a specific question (Saunders et al., 2009, p. 378). In this survey, a scale
from 1 to 6 was used, one representing low effect and 6 presenting strong effect. Both of
these question types were representing closed questions, as there was no possibility to
give a specified answer (Saunders et al., 2009, p. 375). Why six different alternatives
were chosen was because this way it was possible to avoid the middle scale neutral
answer, and thus the respondents were required to think about their opinions more.
4.5 Data collection process The data collection process started with a formulation of the questionnaire. First, the
gender of the respondent was asked, as the previous studies have shown differences
30
between genders when it comes to purchasing behavior (Chan et al, 2016, p.22). In the
survey, the age gap that was chosen was 15-24, 25-34, 35-44, 45-54, 55-64 and 64+. The
reason these age gaps were chosen is due to the importance of reaching a particular person
as respondent (Saunders et al., 2009, p. 363). The questionnaire should also be grouped
so, that the question alternatives do not overlap each other (Saunders et al., 2009, p. 378).
The people younger than 15 years old were excluded from the survey, as they cannot be
seen to be in charge of grocery shopping very often. In addition to this, the occupation of
the respondents were asked, in order to understand if the life situation plays a role in
grocery shopping behavior. The respondents were also asked to state their household
status, to see, if the groceries purchased are for a single person or for a family and their
average number of visits to grocery stores on a weekly basis.
The rest of the questions were defined based on the theoretical framework, to ensure the
linkage to the research problem. The questions were covering two different categories,
nudging activities and consumer behavior in grocery stores. However, this was not
mentioned specifically in the survey, but the questions were all grouped into one section.
All in all, there were 23 questions in the survey, and an approximate finishing time was
calculated to be around 3-5 minutes.
After the demographic questions, the survey continued with questions considering
different nudging policies and their effect on consumer choices. These questions included
the following: How big an impact does the number of healthy food alternatives have to
your decision of grocery store?, How big an impact does the price of healthy food have
to your decision of a grocery store?, How big an impact does marketing of healthy food
have to your decision of a grocery store? and How big an impact does the place have to
your choice of a grocery store?. These questions were designed based on the choice
architecture, social marketing theory and 4 P’s: product, price, place and promotion
(Velma et al., 2018, p. 237) to see if these nudging factors play a role in the purchase
behavior. In addition to this, a question about placement of groceries was added, to
measure the effect from a nudge policy: how much does the placing of items affect your
decisions - for example the placement on the shelf.
After stating the previously mentioned question, a direction was taken to move the focus
on the effects of nudging policies to the purchase behavior, including the following
questions: If the placement of items would be changed, how much would this affect your
memory of where you find the groceries? How big an impact would the changes in the
placement of groceries have to your purchase behavior? and If healthy food would be
placed visibly in comparison to less healthy food, how big is the probability that you
would choose the healthier alternative? These questions were related to cognitive
architecture, which takes the role of memory into the consideration (Laird, 2012, p. 5-8)
as well as to libertarian paternalism, where it is expressed that decisions are unavoidable
to make (Thaler & Sunstain, 2003, p. 175).
After these questions, the questionnaire took a step towards understanding the consumer
behavior regarding grocery shopping habits in general. The questions were based on
behavioral economics about understanding consumer decision-making better (Reed et al.,
2013, p. 35) and included the following questions: When you are doing grocery shopping,
what is the probability that you will do a checklist? If you do a checklist, how big is the
probability that you do it to avoid purchasing unhealthy/unnecessary things?, When you
are doing grocery shopping, how big is the probability that your choices of products are
31
affected by other people’s expectations?, How big is the probability that you are thinking
about your health when you are doing grocery shopping?
The theme continued further with more individual oriented questions covering the
theories of reasoned action and planned behavior. These questions measured the personal
behavior towards grocery shopping and how it affects it. In these theories, the attitudes,
social norms and control beliefs play a role in people’s behavioral intentions (Ajzen,
2012). Based on the theories, the following questions were defined: How much do your
food habits affect your purchase of food?, How much would you say that your attitude to
eat healthy affects your purchasing of food?, How big of an impact has your past behavior
have on your purchase behavior?, How big is the probability that your intention and
behavior meet when you do grocery shopping?
The last questions in the questionnaire were created based on the theory of status quo and
consisted of the following two questions: When you do grocery shopping, how big is the
probability that you stick with those groceries you are used to? and When you do your
groceries, how big is the probability that you will try new products? These questions were
illustrating the status quo ranking alternatives in people’s decision-making (Samuelson
& Zechauser, 1998, p. 7).
The survey was shared on both authors’ social media channels, by asking those who live
in Umeå, to participate in the survey. The survey was shared on Facebook, where the
authors had the biggest population of followers. The survey was also made public, so that
people living in Umeå, that did not belong to the authors’ friend list, could participate in
the survey. This way the spread was hoped to reach more people and ensure the sufficient
number of answers.
Regarding the methods of collecting data through questionnaires, it only offers one
chance to collect data. This is because it can be difficult to identify respondents or to
resend the questionnaire to collect additional information. With that being said, the time
you spend planning what data you need to collect and how you plan to analyze them is
important. Designing your questionnaire in a way that meets these requirements is
essential to be able to answer your research question(s) and meet your objectives
(Saunders et al., 2009, p. 366-367).
There are also other aspects to consider when choosing to conduct a survey as a data
collection method should be taken into consideration that can act as a hindrance. For
instance, when filling an online survey, the respondents do not have anyone to ask help
from, which highlights the importance of careful planning of the survey. In addition to
this, it is not possible to acquire more in-depth answers to specific questions, as the
questionnaire is filled in by the respondents themselves. However, the questionnaire in
this thesis is planned so that no additional information should be needed in order to answer
the research questions. A questionnaire that is completed without an interviewer being
present, also creates a risk for not wanted persons to answer for the survey. This is
impossible to avoid, as the researchers cannot control who is answering the survey, and
thus there is a possibility for biased results (Bryman & Bell, 2011, p. 233). A risk for
missing data has also been identified by Bryman & Bell (2011, p. 234). This can be caused
for example the reason, that not all the questions in the questionnaire have been answered.
This has been tried to avoid in the questionnaire by making each question in the survey
32
mandatory, which does not let the respondents to skip questions if they want to finish the
survey.
4.6 Different variables In this study, different variables that can affect consumers’ choices of a grocery store will
be investigated. Moreover, this study will investigate if healthy food nudging has a
positive connection to consumers’ choice grocery store. The variables this study chose to
take into consideration were taken from theories and earlier study. The study written by
Vecchio & Cavallo (2019) studied the art on nudging interferences designed to increase
healthy food choice.
According to Vecchio & Cavallo (2019), food marketing strategies use different methods
such as trendy messages, colorful floor decals and store arrangements to increase
consumers’ choice of healthy food. Moreover, the study examined different variables to
answer the research question. One of the variables was product placement. According to
Vecchio & Cavallo (2019), behavior and attention goes hand in hand, because behavior
is affected by where a person put his attention. At the same time, the time and effort
involved in selecting an option plays an important role in deciding which of multiple
possibilities people choose. Furthermore, the importance of product placement relies on
three behavioral economic beliefs which are; cognitive overload, cues and salience. These
concepts can be described as the accessibility of necessary information at the time of
decision (Vecchio & Cavallo, 2019, p. 4). In this study, product placement is one factor
that will be examined. The reason why product placement will be examined is to know
how big of importance product placement plays on consumers’ choice of healthy food.
4.7 Composite variables A composite variable is a variable that is made up by two or more variables that are highly
related to each other. The variables that are combined to make a composite variable may
be scales or categorical variables. The method of utilizing composite variables is common
in scientific studies to determine error rate, for instance, when a sample is not adequate
to test several comparisons. However, there are disadvantages that come with the creation
of composite variables. Creating composite variables can result in loss of information,
and challenges in understanding the composite variable in relationships with outside
variables (Song et al., 2017).
In order to ensure that creating the composite variables would not affect the results
wrongly, the independent composite variables were divided into two separate groups
where healthy food represents the independent variable affecting the choice of grocery
stores and nudging the moderating independent variable that affects the relationship
between healthy food and choice of grocery stores. To calculate the composite variable
for healthy food, the independent variables checklist, avoidance of unhealthy/unnecessary
food, people’s affection, healthy thinking, food habits, attitude of healthy eating, past
purchasing behavior, intention and behavior, same groceries and new groceries were
combined to calculate the average of the variables. The composite variable for nudging
moderating variables were calculated from the average value of the independent variables
product placement, memory, product placement affection on consumers’ purchasing
behavior and visible healthy food. For the moderate variable for the dependent variable,
the average from the independent variables number of healthy food alternatives, price of
healthy food, marketing of healthy food and place of grocery store was calculated to
estimate the dependent variable choice of grocery store. Thus, the result from this study
33
will be based on two independent variables: healthy food and nudging and one dependent
variable: choice of grocery store.
4.8 Dependent variable – Choice of grocery store A dependent variable is a variable where its value is affected by one or more independent
variables (Collis & Hussey, 2014, p. 204). This study will be based on one dependent
variable which is the choice of grocery stores.
The aim of this study is to examine if there is a positive connection between a store’s
selection of healthy food and consumers’ choices of grocery stores and if nudging plays
a part in that. To be able to control this connection the questions that were posed in the
questionnaire was; How much influence does the amount of available healthy food
alternatives have on your choice of grocery store? How much influence does the price of
healthy food have on your choice of grocery store? How much influence does marketing
of healthy food have on your choice of grocery store? And how much influence does the
location have on your choice of grocery store? (See Appendix 4).
As the dependent variable was created to be a composite variable, the above-mentioned
questions were combined together and will be explained more in detail down below.
4.8.1 Variables included in Choice of grocery stores
Number of healthy food alternatives This attribute variable was chosen to measure how a grocery store with multiple options
of healthy alternatives can affect consumers’ choice grocery store. If a store is offering
different healthy options, it may stimulate consumers to choose that specific store due to
the larger selection of products. However, this study cannot determine how this attribute
can affect consumers’ choice of healthy alternative yet.
Price of healthy food When buying groceries, it is a big possibility that people may choose groceries with lower
price. Especially if you are a student and cannot afford luxury groceries. For that reason,
the question if the price of healthy food can affect consumers’ choice of healthy groceries
and thus the grocery store were asked.
Marketing of healthy food To see marketing about healthy food on electronic devices and in their living environment
may have an impact on how consumers choose their grocery store. Thus, the question if
marketing of healthy food affects consumers’ choice of grocery store was asked in the
questionnaire.
Place of grocery store The authors of this thesis believe that the place of grocery stores can have an impact on
consumers’ choice of grocery store. For instance, if you live near ICA, there is a big
possibility that you will choose ICA instead of Coop. For that reason, the question if place
can have an impact on consumers’ choice of grocery store was asked in the questionnaire.
34
4.9 Independent variables An independent variable is a variable where its value causes changes in a dependent
variable. Therefore, it is important to provide an alternative explanation to why certain
independent variables are chosen in a research approach (Saunders et al., 2009, p. 367).
However, the relationship between dependent and independent variables are prone to be
tested through statistical analysis from the data collected from the questionnaire. For that
reason, it is important for the researcher to be clear about which detail they will be
measured at the design stage (Saunders et al., 2009, p. 368). In this study, the relationship
between dependent and independent variables will be examined to find out if the selection
of healthy food affects consumers’ choices of a grocery store in Umeå, and if nudging
can affect that.
According to Dillman (as cited in Saunders et al., 2009, p. 368), there are three types of
variables when collecting data through questionnaire. Opinion, behavior and attribute. It
is important for the researcher to know the difference between them as they have a big
impact on how the questions are formulated. Opinion variables show how respondents
feel about something or what they believe is true or false. Behavioral variables consist of
data on what people or organizations did in the past or what they will do in the future.
Attributes variables consist of data about respondents’ characteristics. These variables are
used to measure how opinions and behavior can differentiate between respondents.
Attributed variables contain features such as age, gender, marital status, education,
occupation and income (Saunders et al., 2009, p. 368).
In this study, the independent variables that were chosen for the empirical model are
categorized under the attribute variables. Because, as Dillman (as cited in Saunders et al.,
2009) describes, the attributes variables consist of age, gender occupation and household
status. These variables are included in the questionnaire that was formulated and the
authors believe that they have a greater impact on how people respond to the rest of the
questions in the questionnaire. For instance, if a person is living alone, his answer on how
often he visits a grocery store per week will be different from a person who is married
and has children.
Gender One of the independent variables, classified as attributes variables that this study
highlighted is gender. The authors believe that gender can have an affection on people’s
choice of grocery store as well as their choice of healthy food. Since women are known
for being the ones taking care of groceries in a household, they may be more attracted to
buy more healthy food than men do. However, no conclusion can be drawn directly.
Age Age is also one variable that can affect the dependent variable of this thesis. The authors
believe that people who are younger may not be so conscious about their health when
buying groceries, compared to people who are older. Since younger people may think that
they still have more time to live or lack of knowledge.
Occupation Another independent variable that was taken into consideration is occupation. Depending
on your occupation, it may have an affection on your choice of grocery store and your
choice of healthy food. For instance, if you are a student, you may choose a grocery store
35
with a cheaper price and if you work full-time, you may choose a grocery store with
higher price because you can afford that.
Household status The significance of household status was of interest in this study as it may affect the
purchasing behavior depending on if the person only buys food for themselves or to their
family. Thus, different habits and attitudes might appear when deciding what to buy.
4.9.1 Independent variables as composite variables In addition to the demographic variables, there are additional independent variables. In
this thesis the additional independent variables were reformed to create two composite
variables, one for healthy food and one for nudging to work. As previously mentioned,
the first one represents an independent variable affecting the choice of grocery stores and
the other one works as a moderating variable affecting the relationship between the
independent variable and the dependent variable.
4.9.2 Independent variable – Healthy food In this study, healthy food is categorized as the independent variable. Because, the aim of
this study is to examine if there is a positive connection between nudging and consumers’
choice of healthy food in the choice of grocery stores.
The composite variable for healthy food was formed based on the following questions in
the survey: When you are doing grocery shopping, what is the probability that you will
do a checklist? If you do a checklist, how big is the probability that you do it to avoid
purchasing unhealthy/unnecessary things?, When you are doing grocery shopping, how
big is the probability that your choices of products are affected by other people’s
expectations?, How big is the probability that you are thinking about your health when
you are doing grocery shopping? How much do your food habits affect your purchase of
food?, How much would you say that your attitude to eat healthy affects your purchasing
of food?, How big of an impact has your past behavior have on your purchase behavior?,
How big is the probability that your intention and behavior meet when you do grocery
shopping? When you do grocery shopping, how big is the probability that you stick with
those groceries you are used to? and When you do your groceries, how big is the
probability that you will try new products? (see Appendix 4).
Next, these variables are presented more in detail below.
Checklist This attribute was chosen to look into the fact that checklists may decrease consumers’
unnecessary purchases. For that reason, the question was combined with the question if
consumers do the checklist to avoid buying unhealthy or unnecessary things.
Affection When we buy food, some of our purchasing behavior can unconsciously be affected by
people surrounding us. For that reason, the study wanted to understand if respondents
purchasing behavior is affected by other peoples’ expectations of them.
36
Healthy thinking Moreover, consumers may choose to purchase healthy food because they take their health
into consideration. Thus, the question if consumers think about their health when
purchasing groceries were included in the questionnaire.
Food habits When we purchase groceries, we tend to use our food habits as an excuse for what we
buy. In order to have a better understanding of what drives respondents to purchase certain
products, one question was asked in the questionnaire. Which is, how big consumers’
purchase of food is affected by their eating habits. The attribute of food habits was
combined with the attribute of attitude to eat healthy and the affection of past purchase
behavior.
Intention and behavior We all recognize that at some point we have said to ourselves that we only visit a grocery
store to buy a packet of milk for example. However, it does not always end as we planned.
For that reason, the question, if respondents’ intention and behavior meets when
purchasing groceries. Moreover, this variable was combined with the variables about how
consumers are willing to try out some new products or if they are more willing to stick to
the same product they are used to.
4.9.3 Moderating variable - Nudging The moderating variable affecting the relationship between healthy food and choice of
grocery stores was selected to be nudging, as the previous studies have shown the
connection. Similarly as in other variables, a composite variable was created based on the
survey questions focusing on nudging activities: how much does the placing of items
affect your decisions - for example the placement on the shelf, If the placement of items
would be changed, how much would this affect your memory of where you find the
groceries? How big an impact would the changes in the placement of groceries have to
your purchase behavior?, and If healthy food would be placed visibly in comparison to
less healthy food, how big is the probability that you would choose the healthier
alternative? (see Appendix 4). Below, the product placement variable is explained more
in-depth.
Product placement As mentioned earlier, the study written by Vecchio & Cavallo (2019) looked into factors
that can increase consumers’ choice of healthy food, and product placement was one of
the factors. Thus, this study chose to examine how this attribute can affect consumers’
choice of healthy food. In order to strengthen the product placement variable, it was
combined with other questions such as how consumers' memory would be affected if the
grocery store changed their product placement. And how the change in product placement
can affect consumers’ purchasing behavior. Lastly, product placement attribute was
combined with the question about how likely consumers are to choose the healthy
alternative if placed visibly.
37
4.10 Ethical aspects It is important to acknowledge the ethical dilemmas in business research (Bryman & Bell,
2011, p. 128). According to Saunders et al (2009, p. 183) research ethics are present
throughout the whole research project, from research planning to results. They also define
research ethics as suitability of the researchers’ acts towards the research subjects. The
ethical consideration factors can be divided into four categories; “harm to participants,
lack of informed consent, invasion of privacy and deception” (Diener & Crandall, as cited
in Bryman & Bell, 2011, p. 128).
Starting with the first one, harm to participants, also called as non-maleficence, focuses
on factors such as confidentiality and data collection. Here, all kinds of harm, for instance
stress or anxiety should be avoided during the research project (Saunders et al., 2009, p.
186). During this thesis project the harm for participants was decreased to minimum by
letting the people answer to the survey on their own, without any hurry or time
constraints. The questionnaire was also conducted in Swedish, which was hoped to
increase the comfort level in respondents and avoid confusion. Problems with anonymity
can be seen to be larger when conducting a qualitative research (Bryman & Bell, 2011, p.
130). As this research is conducted following quantitative methods, a direct contact with
participants is not formed. The authors are not able to know who has filled in the survey,
which provides full anonymity for the respondents. The online survey was also a good
alternative considering the anonymity of the respondents, as it was available online, and
not sent specifically to participants. As the questionnaire did not require any log-in, the
respondents answering could stay anonymous and thus the confidentiality level was kept
high.
The ethical aspect about the lack of informed consent is focusing on the dilemma, if the
participants in the study are receiving all the needed information concerning the research
in order to make a valid decision of taking part in the study (Bryman & Bell, 2011, p.
133). When the questionnaire was published online, the authors were explaining the
purpose for the study in the introductory part prior to the survey questions. Here it was
also mentioned, that the study is anonymous and therefore the respondents cannot be
identified. As the questionnaire was published from the authors’ personal pages, it also
provided the opportunity for contacting the authors if additional questions would have
appeared.
The last of the most common ethical considerations, deception, can happen if the study is
claimed to be something else than it actually is (Bryman & Bell, 2011, p. 136). Deception
is connected for behavior where the real purpose with the study is tried to be hidden from
the participants to ensure that the data stays as neutral as possible (Bryman & Bell, 2011,
p. 137). In this research, the authors have been completely open about the purpose for the
study and nudging as a term was defined in the questionnaire introduction in order to
make sure that the participants would understand why the study is conducted. The
participants have not been misled when conducting the study in order to acquire better
answers.
In addition to the previously mentioned ethical considerations, the guidelines from USBE
Thesis Manual have been followed in order to write a thesis that is transparent,
trustworthy and reliable as well as scientifically acceptable.
38
5 Results In this chapter, the general result from the survey will be presented to give the reader an
idea how respondents answered the survey. In addition to that, statistical tests will be
conducted to measure the connection between dependent and independent variables, and
the correlation between independent variables. Lastly the hypothesis will be answered
based on a multiple linear regression.
5.1 General results In total, the survey gathered 136 answers, which of 69.1% was female, 30.2% male and
0.7% did not want to define their gender (see Figure 4). As mentioned earlier, the goal
for the number of responses to the survey was 100, so gathering more than that was a
positive surprise. The time the survey was out for the public was 10 days. Measuring the
responses age-wise, the majority of the respondents were classified to the age group of
15-24 with a percentage of 59,6% and the second biggest group consisted of respondents
in the ages between 25-34 with a percentage of 32,4%. In addition to this, 5,2% of the
respondents belonged to the group of 35-44 year olds, 2,2% to the group of 65+ year olds,
and 0,7% to the group of 45-53 year olds. No responses were acquired from people in the
group of 55-64 year olds (see Figure 5).
Figure 4. Gender.
Women Men Other
0
10
20
30
40
50
60
70
80
Gender
39
Figure 5. Age. Majority of the respondents were students from their occupation, more specifically 59,6%
of all the respondents. The second largest representation was in the group of “working
full time”, with a percentage of 25,7%. 11% of the respondents were working part-time,
while 2,2% were unemployed and 1,5% were retired (see Figure 6). The large number of
young adults answering the survey could also be noticed when looking at the household
status, as 65,4% of the respondents were living alone. In addition to this, 22,1% was living
with someone or was married and 12,5% was living together with someone and also had
kids (see Figure 7).
Figure 6. Occupation.
15-24 25-34 35-44 45-54 55-64 65+
0
10
20
30
40
50
60
70
Age
0
10
20
30
40
50
60
70
Student Working full-time
Working part-time
Unemployed Retired
Occupation
40
Figure 7. Household status. Over half of the respondents, 55,1% were visiting grocery stores only once or twice per
week, while 38,2% were visiting grocery stores 3 to 4 times per week. 6,6% of all the
respondents stated that they visit grocery stores 5-7 times a week (see Figure 8 below).
Figure 8. Weekly shopping. 5.2 Descriptive statistics for independent variables The descriptive statistics are commonly used in quantitative study and are used to describe
simple attributes of the data in a study. Their aim is to provide simple summaries about
the different attributes of the study. Moreover, descriptive statistics describe what the data
is or what the data shows. Descriptive statistics are also used to introduce quantitative
descriptions in a controllable form. It is common that in a research study, you may have
to measure a larger number of people or any measure. Descriptive statistics is a tool that
helps us to simplify a greater amount of data in a reasonable way (Trochim, 2020).
0
10
20
30
40
50
60
70
Single Living withsomeone/married
Living withsomeone/married with
kids
Household status
0
10
20
30
40
50
60
1-2 times 3-4 times 5-7 times
Weekly shopping
41
Descriptive statistics contains many elements but, in this study, the elements that will be
looked into in details are mean, standard deviation, minimum and maximum. When
measuring location for the data, mean is considered to be the most important measure.
Mean provides information about the central location of data (Anderson et al, 2011, p.
87). The data that the standard deviation provides is the positive square root of the
variance (Anderson et al., 2011, p. 99).
In table 2, the descriptive statistics for the independent variables are presented. In the
table, one can see that the variables number of healthy food, visible healthy food, healthy
thinking, food habits, attitude of healthy eating, intention and behavior, same groceries,
price of healthy food and place of grocery store have the mean of over 4. This indicates
that these variables have a higher affection on consumers when it comes to choosing
grocery stores. Regarding the variable number of healthy food alternatives with a mean
of 4.10, one can see that the majority of respondents would choose a grocery store that
has a variation of healthy food. Moreover, when it comes to the variable visible food, the
descriptive statistics indicate that consumers are more likely to choose a grocery store
where healthy food is placed visibly. Furthermore, people have shown to be more and
more concerned about their health when purchasing groceries. This can be one of the
leading factors why people take their health into consideration when choosing a grocery
store. This can be seen through the variable healthy thinking, with a mean of 4.42. The
variables food habits and attitude of healthy eating seem to have an impact on consumers
when it comes to choosing grocery stores. However, these variables do not have a higher
affection compared to the price of healthy food, with a mean of 4.60.
Table 2. Descriptive statistics for independent variables.
Variables Mean Standard Deviation
Number of healthy food alternatives 4,10 1,20
Product placement 3,02 1,51
Memory 3,86 1,40
Product placement affection on consumers’ purchasing behavior
3,37 1,36
Visible healthy food 4,40 1,42
Checklist 3,98 1,77
Avoidance of unhealthy/unnecessary food 3,18 1,78
Peoples’ affection 2,58 1,40
Healthy thinking 4,42 1,10
Food habits 4,45 1,22
Attitude of healthy eating 4,45 1,29
42
Past purchasing behavior 3,92 1,37
Intention and behavior 4,45 1,23
Same groceries 4,63 1,10
New groceries 3,73 1,26
Price of healthy food 4,60 1,26
Marketing of healthy food 3,41 1,60
Place of grocery store 4.32 1.54
5.3 Descriptive statistics for dependent variable When analyzing the descriptive statistics for the dependent variable, one can see that it
has a mean of 4.11 which indicates that the chosen independent variables have a high
affection on consumers’ choice of grocery store. However, one can only predict that there
is a strong connection between the chosen independent variables and the dependent
variable. But that connection will further be tested in the result section.
Table 3. Descriptive statistics for dependent variable.
Dependent variable Mean Standard Deviation Min Max
Choice of grocery store 4.11 0.85 2 6
5.4 Correlation A correlation coefficient is used to measure the strength of the linear relationship between
two variables that can be ranked or numerical. The value for this can be anywhere
between -1 and +1, where the value +1 means a perfect positive correlation. A positive
correlation is a connection between two variables, for instance, if variable 1 is growing,
so does variable 2. Perfect negative correlation is represented by -1, meaning that when
variable 1 is growing, variable 2 is decreasing. When there is no correlation and the values
are independent from each other, a value 0 is obtained (Saunders, 2009, p. 459). If the
correlation value is plus 1, it indicates that there is a strong connection between the
variables and that the variables move in the same direction. However, if the value is minus
1, it also indicates that there is a strong connection between variables but that they move
in opposite directions. If the value is 0, it means that there is a weak connection between
variables (Moore et al., 2011, s. 93).
5.4.1 Correlation for the variables Correlation comparison between the independent variables and the dependent variable.
As the value of correlation for the variables is 0,42 respectively 0,38 there is no significant
positive correlation between the variables and therefore the correlation is weak (see Table
4 below).
43
Table 4. Correlation for independent variables.
Independent variable Dependent variable
Healthy food 0,42
Nudging 0,38
5.5 Outliers Data can occasionally include observations that have atypically small or large value
compared to the average. These values are called outliers. Outliers can appear for instance
due to an error in the recording or by an unsuitable observation in the data set (Anderson
et al, 2011, p. 106).
To exclude outliers from the data, the program STATA was used to encode the categorical
variables into numerical ones: gender, age and occupation. The program also allowed to
see the diversity between the answers in each category which was useful when detecting
the outliers in the data.
The three tables below represent the frequency and percentage of each alternative
category when asking gender, age and occupation. For instance, it can be noticed that
when asking about gender, only one person did not want to define their gender and is thus
creating an outlier (see Table 5). In table 6, it can be seen that only one person answered
from a group of 45-54 and three people from group +65 year olds. Lastly, when asking
about occupation three respondents were unemployed and two respondents retired, and
therefore being outliers (see Table 7).
Table 5. Gender outliers.
Gender Frequency Percentage
Other 1 0.74
Woman 94 69.12
Man 41 30.15
Total 136 100
Table 6. Age outliers.
Age Frequency Percent
15-24 81 59.56
25-34 44 32.35
35-44 7 5.15
44
45-54 1 0.74
65+ 3 2.21
Total 136 100
Table 7. Occupation outliers.
Occupation Frequency Percent
Unemployed 3 2.21
Work part-time 15 11.03
Work permanent 35 25.74
Retired 2 1.47
Student 81 59.56
Total 136 100
In total 8 outliers were removed from the data including people in ages 45-54 and 65+,
people who did not want to define their gender, and people with occupations as
unemployed or retired. This was expected, as both authors have a limited contact of
people over 45 years in their social media, it was difficult to reach that category. Thus,
people within that age category constituted a small sample. It is also worth acknowledging
that some of the outliers were landing into two categories such as 65+ and retired, and
thus were removed from the data only once.
5.6 Heteroscedasticity When conducting a linear regression, there are some approaches that one can take into
consideration and one of them is homoscedasticity. The opposite to that is
heteroscedasticity, which means models where the error terms have different variance.
Test of heteroscedasticity is often common in statistical tests where there is a big gap
between the smallest and largest variables (Newbold et al, 2013, p. 558). In order to test
if there is heteroscedasticity, a Breusch-Pagan test was conducted in the statistical
program STATA. The test demonstrated a p-value of 0.2319 (23.19 %), which is higher
above 1 %. This indicates that the null hypothesis cannot be rejected and thus, there is no
heteroscedasticity. However, this was expected since there is no big gap between the
smallest and largest variables in the collected data material.
5.7 Multiple linear regression A multiple linear regression is a statistical model that is used when there is more than one
independent variable that affects the dependent variable (Moore et al., 2001, p. 573).
Regarding multiple linear regression analysis, it makes several assumptions. First, the
regression assumes that there must be a linear relationship between the dependent variable
and the independent variables. In order to control that relationship one can use scatter
plots, which shows whether there is a linear or a curvilinear relationship (Statistics
45
solutions, n.d.). Moreover, multiple linear regression assumes that the residuals are
normally distributed. It also assumes that there is no multicollinearity. Which means that
there is no high correlation between the independent variables (Statistics solutions, n.d.).
Multiple regression model is described with an equation that is the following:
𝑦 = 𝛽0 + 𝛽1𝑥1 + 𝛽2𝑥2 + ⋯ + 𝛽𝑝𝑥𝑝 + 𝜖
In the equation y is the dependent variable and 𝑥1, 𝑥2,..., 𝑥𝑝 represent the independent
variables. As the equation describes multiple regression, 𝛽0, 𝛽1, 𝛽2,... 𝛽𝑝 describe the
parameters and is the random variable (Anderson et al., 2011, p. 644).
In this thesis there are only two independent variables, and thus the equation is formed to
look like the following:
𝑦 = 𝛽0 + 𝛽1𝑥1 + 𝛽2𝑥2 + 𝜖
5.7.1 Multicollinearity In statistical terms, when conducting a regression analysis, the term independent variable
is used to relate to any variable that is being used to predict or explain the value of the
dependent variable. However, that does not mean that the independent variables are
independent in any statistical sense. In a multiple regression, most independent variables
are somehow correlated with each other (Anderson et al., 2011, p. 662). For that reason,
there are statistical tests that have the aim to predict the correlation among the
independent variables. Multicollinearity reveals the correlation between independent
variables. Moreover, these tests have the aim to determine whether multicollinearity is
high enough to cause problems. To the extent possible, one should avoid including
independent variables that are highly correlated to each other. (Anderson et al., 2011, p.
662). Generally, multicollinearity does not have a substantial effect on how the regression
analysis is conducted or how the result from a study is interpreted. Yet, when
multicollinearity is high, for instance, when two or more independent variables are highly
correlated with one another, it can cause difficulty in interpreting the results of T tests on
the individual factors (Anderson et al., 2011, p. 663).
In order to test for multicollinearity, a variance inflation factor (VIF) test was conducted
in the statistical program STATA. Variance inflation factor has the aim to expose
multicollinearity in regression analysis. The VIF estimates the degree to which variance
of a regression coefficient is inflated due to multicollinearity in the regression model. The
variance inflation factor is scale from 1 upwards. The VIF number tells us what
percentage the variance (standard error square) is inflated for each coefficient. For
instance, a VIF of 1.9 indicates that the variance of a specific coefficient is 90 % bigger
than what to expect if there was no multicollinearity. To be able to interpret the result
from the VIF test, a rule of thumb should be taken into consideration. Which says if the
VIF value is equal to 1, no multicollinearity. If the VIF value is between 1 and 5,
moderately multicollinearity. If the VIF value is greater than 5, then there is high
multicollinearity between the independent variables (Glen, 2015). The table 8
demonstrates the result from the VIF test. As one can see from the table, the VIF value is
on a scale of 1.10 for both independent variables. This indicates that there is no
multicollinearity between the independent variables.
46
Table 8. Variance inflation factor.
Variable VIF 1/VIF
Healthy food 1.10 0.91
Nudging 1.10 0.91
Mean VIF 1.10
5.7.2 Linear regression with Robust After conducting a VIF test, a linear regression test with robustness was in turn conducted
in the statistical program STATA. Robust regression is often used in data that might have
outliers as an alternative to minimize squares regression. Robust regression can also be
used to discover leading observations (UCLA, n.d)
Multiple regression analysis has the aim to see if there is a statistically significant
relationship between the variables (Glen, 2015). To test the significant relationship, the
study used 5 % significance level. The critical value at the 5 % significance level is 1.96.
In testing for significance, one can take a F-test, which is a test related to multiple
regression analysis. The significance tests used in the multiple linear regression are T-test
and F-test where both tests have different purposes. The F-test is used to verify if there is
a significant relationship between the dependent variable and the set of all independent
variables. The F-test is referred to as a test for overall significance. The T-test is used to
determine if each of the independent variables is significant. The T-test is referred to as a
test for individual significance (Anderson et al., 2011, p. 658).
The F-test shows a value of 23.11 and a p-value of 0.000. Since the p-value is less than
the significance level (5 %), one can conclude that the F-test shows that there is a
significant relationship between the dependent variables and the independent variables.
However, to control the significance level for each variable, the T-test was conducted.
Table 9 demonstrates the result from the T-test. As one can read from the table, the T-
value for the independent variable healthy food is 3.58, which means is above the critical
value 1.96. that indicates that there is a significant level between healthy food and
consumers’ choice of grocery store. Moreover, to strengthen the significance level, the P-
value is 0.000 which is less than the significance level 5 %. Thus, the null hypothesis can
be rejected. Regarding the independent variable nudging, one can also see that the T-
value is higher than the critical value: 3.9 > 1.96. Which also means that there is a strong
connection between nudging and choice of grocery store. The T-test confirms that the
result from F-test, that has the aim to check the overall significance, is trustworthy.
Table 9. Linear regression with Robust.
Choice of grocery store Coefficient Standard error T-value P-value
Healthy food 0.42 0.12 3.58 0.000
Nudging 0.26 0.08 3.09 0.002
47
Constant 1.51 0.42 3.58 0.000
5.7.3 Linear regression without Robust A linear regression analysis without robustness was also conducted, and one can see that
the result that this regression shows in table 10 does not differ from the previous result.
The T-value for the independent variables healthy food and nudging are both above the
critical value 1.96 which indicates that there is a significant level between each of the
independent variables and the dependent variable. The P-value for both independent
variables is under 5 %, which signifies that the null hypothesis can be rejected as well.
Comparing the result from the regression analysis with robustness and regression analysis
without robustness, one can conclude that robust effect does not have a major impact on
the result of the collected data.
Table 10. Linear regression without Robust.
Choice of grocery store Coefficient Standard error T-value P-value
Healthy food 0.42 0.10 4.11 0.000
Nudging 0.26 0.07 3.45 0.001
Constant 1.51 0.42 3.59 0.000
5.7.4 R-squared value R-squared or 𝑅2, also called as the coefficient of determination. The value of 𝑅2 can vary
between 0 and 1 and the larger the value the better the regression is (Newbold et al, 2013,
p. 414).
When conducting the multiple regression analysis, the results indicated the 𝑅2 values to
be rather low. In the regression analysis with Robust, the 𝑅2 value was 0.2468 whereas
in the analysis without Robust the 𝑅2 value was 0.2468 and Adjusted 𝑅2 0.2347.
However, it has been argued that the high 𝑅2 values are not always required and for
example in research where the data has its foundation on population suchs as countries or
companies the average 𝑅2 values lay between 0.40 and 0.60 and when the data focuses
on individuals can the 𝑅2 value be between 0.10 and 0.20 (Newbold et al, 2013, p. 415).
Therefore, as this study is based on a smaller sample that is especially focusing on
opinions of individuals and their behavior, can the lower 𝑅2 values acquired in the
multiple regression tests still be considered acceptable.
5.8 Answering to the hypotheses Based on the regression analysis conducted, it is now possible to answer the hypotheses
created for this study. As mentioned before, the statistics show that the null hypothesis
can be rejected and therefore it means that the H1is supported indicating that there is a
positive connection between a store’s selection of healthy food and consumers’ choices
of grocery stores. Further on, the statistics showed that H3 is also supported, indicating
that there is a positive connection between nudging of healthy food and consumers’
choice of grocery stores. Moreover, this means that the H2 is then rejected. (See table 11).
48
Table 11. Hypotheses.
Hypothesis Description Result
𝐻0 There is no positive connection between a store’s selection of healthy food and consumers’ choice of grocery stores
Rejected
𝐻1 There is a positive connection between a store’s selection of healthy food and consumers’ choice of grocery stores
Supported
𝐻2 There is no positive connection between nudging of healthy food and consumers’ choice of grocery stores
Rejected
𝐻3 There is a positive connection between nudging of healthy food and consumers’ choice of grocery stores
Supported
49
6 Analysis In this chapter the results are being analyzed and compared to the previous research
conducted, in order to see if the theories and previous findings can be strengthened with
the findings from this study.
As the results showed there is support for the hypotheses claiming the positive connection
between a store’s selection of healthy food and consumers’ choices of grocery stores and
between nudging of healthy food and consumers’ choices of grocery stores. Therefore,
the studies can now be compared to the previous researches and theories to find the
similarities and differences.
6.1 Healthy food, nudging and choice of grocery stores The first research question in this thesis was focusing on the selection of healthy food in
grocery stores and how it affects the choice of grocery stores.
In a study by Winkler et al (2016, p. 7-6) efforts regarding healthy food in grocery stores
seem to influence positively on people and are considered helpful for the shoppers. The
customers perceived as important the actions for replacing unhealthy foods with healthier
options as there was detected irritation from the consumers’ side when it comes to a large
selection of unhealthy foods in grocery stores.
The findings from previous studies indicate support for the results found in this thesis as
the hypothesis for positive effect between selection of healthy food and choice of grocery
stores was supported. When asking the respondents how big an impact does the number
of healthy food alternatives have to your decision of grocery store, 75% of the respondents
chose an answer category between alternatives 4 and 6, illustrating the impact being
strong.
As mentioned in the beginning of this thesis, there has been proof that nudging activities
can make an impact on the choice of grocery store as a moderating variable. In the study
by Szaszi et al. (2018, p. 356) it was stated that by arranging the groceries differently on
the shelves, it has an effect on how consumers choose their goods. Another study found
out the usefulness of checkout policies in food stores and the impact on bring-home
purchases of sugary and salty snacks (Ejlerskov et al., 2018, p. 17).
These studies promote the positive impacts on healthy food decisions caused by
implemented nudging policies and the findings from this study show similar results. For
instance, when asking the respondents would they more like to choose a healthy food
alternative if it would be placed more visibly the majority (29,4%) answered the highest
alternative 6 indicating very high probability. In addition to this 46,3% of the respondents
answered alternative 5 or 4, indicating high probability for this behavior. Therefore, it
seems that this study provides further support for the benefit of using nudging policies in
a healthy food context.
What comes to the second research question if nudging can affect the choice of grocery
store, this study shows support for the statement. In a study by Winkler et al. (2016, p.
10) placing healthy food alternatives on the checkout messages the stores’ eagerness to
implement actions that the customers appreciate. In addition, this can help the stores to
promote the responsible actions and thus improve the loyalty of the customers for the
50
store. Therefore, this study indicates that nudging can act as a moderating factor affecting
the store’s brand image and customers’ opinions and thus lead them to choose the store
when they do groceries.
However, as described earlier in the theoretical framework, nudging can have some
disadvantages such as epistemic issues. Which are the problems that occur when
policymakers do not know the true interests of people that are being nudged
(Abdukadirov, 2016, p. 22). For that reason, even if the result from this study
demonstrates that there is a connection between nudging and consumers’ choice of
grocery store, one has to be critical and analyze the true interests of people that are being
nudged. This because, if the interests are unknown, it can lead to the fact that consumers
constantly change their choice of grocery store.
Comparing the result that this study generated with behavioral economics theory, one can
say that people's choice of grocery store is based on a variation of affection such as
product placement in the store and product placement affection on consumers' purchasing
behavior. With that being stated, the theory of behavioral economics has an impact on the
outcome of this study. Because the theory states that “when people make choices they do
so based on a set of expectations about the consequences of their choices and many
exogenous factors that can determine how the future will evolve” (Thaler, 2016, p. 1593).
Choice architecture theory and libertarian paternalism have also an impact on the outcome
of this study. According to the choice architecture theory, the decision maker will choose
an alternative depending on how that alternative is presented. Which indicates that, for
consumers to choose a grocery store, how marketing of healthy food for that particular
grocery store has an impact on consumers’ final decision, as well as the place of the
grocery store. With libertarian paternalism, one can state that the outcome of this study is
strengthened by the definition of this theory, which is that nobody is forced to any actions
(Thaler, 208, p. 1283).
One can state that the theories of reasoned action and planned behavior had an affection
on the outcome of this study. Since the theories provide a good foundation for
understanding how decision-making process is affected by different factors. Thus, the
result from this study shows that healthy food and nudging moderating variables have an
affection on consumers’ choice of grocery store.
Regarding the social marketing theory, one can state that this theory did not have much
of an impact on the result of the study, since the theory refers to marketing combined with
other approaches. And looking at the question on how big of an impact marketing has on
consumers, choice of grocery store, only 14 % of the respondents found marketing to
have a big impact on their decision. Unlike social marketing theory, status quo showed to
have a bigger impact on the outcome of the study. The theory states that decision makers
choose to do nothing or maintain the previous decisions. Thus, on the question of how
likely consumers choose the same groceries they are used to, 37.5 % of the respondents
would choose the same groceries, whereas 10.3 % would choose new groceries.
6.2 Limitations for the analysis As the demographic data acquired from respondents was skewed towards women being
the majority of all respondents, it may not provide accurate results if comparing the
genders and therefore it was excluded from the thesis. Same applied for age, occupation
and household status as the majority of the respondents were students and thus the other
groups were not as sufficiently represented. Therefore, the results are compared to other
51
studies as a one group, containing both males and females. This leads the results to not
be as specific as planned in the beginning, but this is hoped to give a more accurate and
reliable result in general.
52
7 Conclusion In this last chapter the results from the study are being concluded, as well as presented
the societal, practical and theoretical contributions this thesis takes. Lastly, future
recommendations for the study field are being given.
7.1 General conclusion The aim of this study was to investigate the relationship between healthy food, nudging
activities and their effect on consumers’ choice of grocery store. The purpose of this study
was to understand the attitudes of people living in Umeå toward how the selection of
healthy foods affects their choice of a grocery store. The purpose was also to understand,
if the nudging activities could have an effect in the decisions made.
The goal was that the study could contribute to the field of study and the existing literature
by providing new data and understanding for the area of healthy food, consumer decision-
making, choice of grocery store and nudging. By doing this, the results of this study could
be of use when trying to understand how to fight against unhealthy diet and eating habits
as well as how to attract consumers to pick a specific grocery store.
As the results showed, the null hypothesis could be rejected, and thus the study got
support for hypotheses 1 and 3, indicating that there is a positive connection between a
store’s selection of healthy food and consumers’ choice of grocery store and between
nudging of healthy food and consumers’ choice of grocery store. This allows now the
possibility for answering the research questions.
The research questions chosen for the study were the following:
RQ1: Does the selection of healthy food affect consumers’ choice of a grocery store?
RQ2: Does nudging of healthy food affect consumers’ choice of a grocery store?
Starting with the research question 1, the results from this study give support for the
statement that the selection of healthy food does affect the consumers’ choices of a
grocery store. Similarly, the results also give support for the second research question,
and thus it can be stated that nudging of healthy food does affect consumers’ choices of
a grocery store.
However, looking on data gathered, one can see that the majority of respondents were
students. This can have had a big impact on the final result of this study. If, for instance,
the majority of respondents were people between the age of 35 to 44 and 45 to 54, the
result could have been different. The result could have shown a significant level between
choice of grocery store and healthy food, but not a significant level between choice of
grocery store and nudging. However, one cannot say with certainty that the results of this
study would have changed if the circumstances were different.
Based on these results, the purpose with this thesis can be seen to succeed by bringing
new information about the field of study, which can be of use in the actions preventing
unhealthy eating habits. The results can also be of use for the grocery store managers
when creating strategies for nudging and attracting consumers to shop at their grocery
store. However, these results should be read with critical mind remembering the
53
surrounding conditions. As mentioned in the analysis of the findings chapter, the true
interests of the consumers may not always be known which makes it more difficult to
analyze the effects from nudging and choices regarding grocery stores. Therefore, it is
recommended to keep this in mind when reading this thesis and if planning to use the
gathered information.
7.2 Implications
7.2.1 Societal As mentioned previously, the World Health Organization (WHO) mentions one reason
for noncommunicable diseases (NCDs) such as diabetes or cardiovascular diseases, being
caused by eating unhealthily (WHO, 2020). These diseases impact largely on the
economy, as they cause large expenses for the health care systems, as well as decrease
the available workforce (Hunter & Reddy, 2013, p. 1337).
It has been stated that supermarkets around the world are acting in an important position
when it comes to forming dietary actions (Thornton et al., 2013, p. 7). For adults, having
an inadequate diet quality can cause the risk of numerous chronic diseases, such as heart
disease, stroke and high blood pressure (Guthrie et al., 2015, p. 501).
The results from this thesis can be contributing to the actions related to fighting against
unhealthy eating habits and obesity and chronic diseases. By providing new and relevant
data about the perceptions regarding healthy food offerings and nudging policies in
grocery stores it can help to better understand consumers’ decision-making processes
when choosing the grocery stores. In addition to this, understanding people’s attitudes
toward healthy food actions in grocery stores and how they are perceived can help to
understand what kind of actions are needed when planning a strategy for promoting
healthier eating habits.
If right actions are taken, promoting healthy food could in the long run lead to a decreased
number of people who need help due to diseases and conditions caused by unhealthy diet.
As the results show, a strong connection between the younger population and the
measured activities was found, which can be considered useful in the long run, as these
same people will be the ones doing groceries even after decades. This can be useful when
it comes to planning governmental actions, since the actions can be aimed towards the
younger part of the population, and thus can be planned to be more long-term. Further on,
these actions could lead to more healthy eating habits in general that are moved forward
to the next generations. This would save resources in the health care sector and the free
resources acquired could be led to other important actions.
7.2.2 Practical This thesis can contribute to understanding better how the selection of healthy food
impacts on the decisions when choosing a grocery store. This can be of use to store
managers by providing new insights on the decision-making process and how big the
effect of healthy food selection is in this process and help to build a competitive
advantage.
This study can also help grocery stores to have a better understanding about how they can
make use of nudging in order to influence consumers’ choice of healthy food. It can help
54
employees in the grocery stores to navigate better where different groceries should be
placed in order to attract customers.
Moreover, this study will help the managers of grocery stores in Umeå to know how to
nudge consumers toward buying healthier food, without taking away consumers’ free
choice. This study will give managers some tips on how to manage consumers’ choice
with a nudge. When managers have applied the knowledge of nudging, the authors believe
that it will improve their ways of architecting the placement of groceries.
Since there has not been a study about nudging and grocery stores in Umeå, this study
will provide new acquired knowledge which can be beneficial for other similar cities as
well, and the authors believe that whoever reads this study will have a good use of it in
life. The results can also be of use for the grocery stores when planning a business strategy
and how to attract consumers to choose their grocery store.
Furthermore, extended to other environments, the results can be applicable to other
locations than only grocery stores, such as cafeterias or restaurants as the information
acquired from this study can also be applicable in other locations, such as the
effectiveness of nudging.
7.2.3 Theoretical This study contributes to the existing research literature by adding a more location
specific view on the subject, focusing on consumers from different backgrounds. It
provides additional and up-to-date knowledge about the attitudes towards nudging and
can be beneficial for the future studies conducted, especially in the context of Sweden but
also for instance in other Nordic countries.
The study will also contribute to the existing research about nudging both nationally and
internationally by providing new and modern insights on the subject as well as providing
support for previously conducted studies in the field of nudging and consumer purchase
behavior. Therefore, this study provides an additional viewpoint to the previous research
conducted and thus expands the number of studies conducted in this field.
More specifically, this study provides new information from the perspective of younger
generations, namely people between ages 15 to 34. This information could be useful for
other studies focusing especially on this age group and health related questions and it can
contribute to the literature about students’ eating and shopping habits.
7.3 Future research recommendations This study was focusing on researching the choice of grocery stores and how the selection
of healthy food and its nudging activities can affect that.
For future research a similar research in other cities in Sweden could be conducted to
understand if there are differences between the decisions on healthy food and choices of
grocery stores. Thus, more credible results could be gained and the stated arguments in
this thesis could be further strengthened. As this study acquired answers mostly from
students and people placed in younger age groups, a study focusing on older age groups
with different backgrounds could be beneficial to see if there are differences in how the
decision between different grocery stores is made, or how the nudging activities are
55
perceived. The results from this study could also be strengthened by replicating the study
with a longer time-span, so that more diverse answers could be gained.
To make the findings more applicable for wider context, similar studies could be
conducted in different environments, such as in cafeterias or lunch restaurants. Thus, the
purchasing behavior and decision-making processes could be further studied to
understand if there are differences in these behaviors depending on the place of purchase.
Another possible future research could focus on specifically measuring the nudging
activities in grocery stores to see how they are perceived by the consumers and if they
have an effect on the purchasing behavior. Similarly, it could be studied more specifically
in a chosen grocery store, if the healthy food promoting activities have an effect on how
the consumers select the grocery store to shop at.
56
REFERENCE LIST
Abdukadirov, S. (2016). Nudge theory in action: Behavioral design in policy and
markets. Arlington, Virginia: Mercatus center at George Mason University. E-book.
Abdul, M., Ismail, H., Hashim, H., & Johari, J. (2009). Consumer decision making
process in shopping for halal food in Malaysia. China-USA Business Review, 8 (75), 40-
48.
Ajzen, I. (2012). The Theory of Planned Behavior. In: P.A.M. Van Lange, A.W.
Kruglanski., & E.T. Higgins, eds. Handbook of Theories of Social Psychology Volume 1.
1st edition. London: SAGE Publications Ltd. pp. 438-459.
Anderson, D.R., Sweeney, D.J., & Williams, T.A. (2011). Statistics for Business and
Economics. Mason: South-Western Cengage Learning. E-book.
Anisimova, T. (2016). Integrating Multiple Factors Affecting Consumer Behavior
Toward Organic Foods: The Role of Healthism, Hedonism, and Trust in Consumer
Purchase Intentions of Organic Foods. Journal of Food Products Marketing, 22 (7), 809-
823.
Bucher, T., Colling, C., Rollo, M. E., McCaffrey, T. A., De Vlieger, N., & Van der Bendl,
D. (2016). Nudging consumers towards healthier choices: a systematic review of
positional influences on food choice. British Journal of Nutrition, 115, 2252–2263.
Bryman, A., & Bell, E. (2015). Business research methods. 4th edition. United Kingdom.
Bryman, A. (2016). Social and research methods. United Kingdom: Oxford University
Press. E-book.
Bryman, A., & Bell, E. (2011). Business Research Methods. New York: Oxford
University Press Inc. E-book.
Chan, K., Prendergast, G., & Ng, Yu-Leung. (2016). Using an expanded Theory of
Planned Behavior to predict adolescents’ intention to engage in healthy eating. Journal
of International Consumer Marketing, 28 (1), 16-27.
Chriss, J.J. (2015). Nudging and social marketing. Social science and public policy, 52,
54-61
Clement, J., Aastrup, J., & Forsberg, S.C. (2015). Decisive visual saliency and consumer’
in-store decisions. Journal of retailing and consumer services, 22, 187-194.
Collis, J., & Hussey. R. (2014). Business research. 4th edition. London: macmillan
education.
Darian, T., & Tucci, L. (2011). Perceived health benefits and food purchasing decisions.
Journal of Consumer Marketing, 28 (6), 421–428.
Diacon, P-L. (2014). From economic behaviour to behavioural economics. Acta
Universitatis Danubius. OEconomica, 10 (1), 171-180.
57
Ejlerskov, K., Sharp, S.J., Stead, M., Adamson, A.J., White, M., & Adams, J. (2018).
Supermarket policies on less-healthy food at checkouts: Natural experimental evaluation
using interrupted time series analyses of purchases. PLoS Med, 15 (12), 1-21.
Glen, S. (2015). What is a variance inflation factor? Statistics how to.
https://www.statisticshowto.com/variance-inflation-factor/. [Retrieved 2020-05-07].
Guthrie, J., Mancino, L., & Lin, C-T J. (2015). Nudging consumers towards better food
choices: Policy approaches to changing food consumption behaviors. Psychology &
marketing, 32 (5), 501-511.
Hackman, C.L., & Knowlden, A.P. (2014). Theory of reasoned action and theory of
planned behavior-based dietary interventions in adolescents and young adults: a
systematic review. Adolescent health, medicine and therapeutics, 5, 101-114.
Hagman, W., Andersson, D., Västfjäll, D., & Tinghög, G. (2015). Public Views on
Policies Involving Nudges. Review of Philosophy and Psychology, 6 (3), 439-453.
Hansen, P.G., Skov, L.R., & Skov, K.L. (2016). Making healthy choices easier:
Regulation versus nudging. Annual reviews of public health, 37, 237-251.
Hertwig, R., & Grune-Yanoff, T. (2017). Nudging and boosting: Steering or empowering
good decisions. Association for psychological science, 12 (6), 973-986.
Hollywood, L.E., Cuskelly, G.J., O’brien, M., Mcconnon, A., Barnett, J., Raats, M.M., et
al. (2013). Healthful grocery shopping. Perceptions and barriers. Appetite, 70, 119-126.
Horsley, J.A., Absalom, K.AR., Akiens, E.M., Dunk, R.J., Ferguson, A.M. (2014). The
proportion of unhealthy foodstuffs children are exposed to at the checkout of convenience
supermarkets. Public Health Nutrition, 17 (11), 2453-2458.
Hunter, D.J., & Reddy, K.S. (2013). Noncommunicable Diseases. The New England
Journal of Medicine, 369 (14), 1336-1343.
Hwang, J. (2015). Organic food as self-presentation: The role of psychological motivation
in older consumers' purchase intention of organic food. Journal of Retailing and
Consumer Services, 28, 281-287.
Imamura, F., Micha, R., Khatibzadeh, S., Fahimi, S., Shi, P., Powles, J., et al. (2015).
Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic
assessment. The Lancet Global Health, 3(3), e132-e142.
Johnson, E.J., Shu, S.B., Dellaert, B.G.C., Fox, G., Goldstein, D.G., Häubl, G., et al.,
(2012). Beyond nudges: Tools of a choice architecture. Marketing Letters, 23 (2), 487-
504.
Kearney, J. (2010). Food consumption trends and drivers. Philosophical Transactions of
the Royal Society, 365 (1554), 2793-2807.
58
Kosters, M., & Heijden, J.V.D. (2015). From mechanism to virtue: Evaluating nudge
theory. Sage journals, 21 (3), 276-291.
Krebs-Smith, S.M., & Kantor, L.S. (2001). Choose a Variety of Fruits and Vegetables
Daily: Understanding the Complexities. The Journal of Nutrition, 131 (2S-1), 487S-501S.
Laird, J.E. (2012). The soar cognitive architecture. London: Cambridge Massachusetts.
E-book.
Langley, P., Laird, J.E., & Rogers, S. (2009). Cognitive architectures: research issues and
challenges. Cognitive systems research, 1-37.
Leszczyc, P.T.L.P., Sinha, A., & Timmermans, H.J.p. (2000). Consumer store choice
dynamics: An analysis of the competitive market structure for grocery stores. Journal of
retailing, 76 (3), 323-345
Ly, K., Mazar, N., Zhao, M., & Soman, D. (2013). A practitioner’s guide to nudging.
[PDF]. Rotman school of management.
MacIntosh, R., & O’Gorman, K.D. (2015). Research Methods for Business &
Management: A guide to writing your dissertation. 2nd edition. Oxford: Goodfellow
Publishers Limited.
Moore, D.S., McCabe, G.P., Alwan, L.C & Craig, B.A. (2011). The practice of statistics
for business and economics. 3rd edition. New York: W.H. Freeman and Company.
Newbold, P., Carlson, W.L., & Thorne, B.M. (2013). Statistics for Business and
Economics. 8th edition. New Jersey: Pearson. E-book.
Park, C.W., Iyer, E.S., & Smith, D.C. (1989). The effects of situational factors on in-store
grocery shopping behavior: The role of store environment and time available for
shopping. Journal of consumer research, 15 (29), 422-433.
Petrovici, D.A., & Paliwoda, S.J. (2008). Reasoned Action and Food Choice in a
Transitional Economy. Journal of East-West Business, 14 (3-4), 249-270.
Reed, D.D., Niileksela, C.R., & Kaplan, B. A. (2013). Behavioral Economics: A Tutorial
for Behavior Analysts in Practice. Behavior Analysis in Practice, 6 (1), 34–54.
Ritov, I., & Baron, J. (1992). Status-quo and omission biases. Journal of risk and
uncertainty, 5, 49-61.
Robinson, L., Segal, J., & Segal, R. (2019). Healthy eating. Help guide.
https://www.helpguide.org/articles/healthy-eating/healthy-eating.htm. [Retrieved 2020-
04-02].
Samuelson, W., & Zeckhauser, R. (1988). Status Quo Bias in Decision Making. Journal
of Risk and Uncertainty, 1 (1), 7–59.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students.
Harlow: Pearson Education Limited. E-book.
59
SCB. (2014). Statistical Yearbook of Sweden 2014. [PDF]. Stockholm: Statistics
Sweden. http://share.scb.se/ov9993/data/historisk%20statistik//SOS%201911-
/Statistisk%20%C3%A5rsbok%20(SOS)%201914-2014/Statistisk-arsbok-for-Sverige-
2014.pdf. [Retrieved 2020-04-03].
Song, M.K., Lin, F.G., Ward, S.E., & Fine, J.P. (2017). Composite variables. HHS
public access, 62 (1), 45-49.
Statistics solutions. (n.d.). Assumptions of multiple linear regression. Statistics
solutions. https://www.statisticssolutions.com/assumptions-of-multiple-linear-
regression/. [Retrieved 2020-04-21].
Sunstein, C.R. (2014). Nudging: A very short guide. J Consum Policy, 37, 583-588.
DOI 10.1007/s10603-014-9273-1.
Sweller, J., Merrienboer, J.J.G.V., & Paas, F.G.W.C. (1998). Cognitive architecture and
instructional design. Educational psychology review, 10 (3), 251-296.
Szaszi, B., Palinkas, A., Palfi, B., Szollosi, A., & Aczel, B. (2018). A Systematic
Scoping Review of the Choice Architecture Movement: Toward Understanding When
and Why Nudges Work. Journal of Behavioral Decision Making, 31 (3), 355-366.
Thaler, R. (2016). Behavioral Economics: Past, Present, and Future. The American
Economic Review, 106 (7), 1577-1600.
Thaler, R.H. (2018). From Cashews to Nudges: The Evolution of Behavioral
Economics. American Economic Review, 108 (6), p. 1265-1287.
Thaler, R.H., & Sunstein, C.R. (2003). Libertarian paternalism. American Economic
Review, 93 (2), 175-179.
Thorndike, A.N., Riis, J., Sonnenberg, L.M., & Levy, D.E. (2014). Traffic-Light Labels
and Choice Architecture. American Journal of Preventive Medicine, 46 (2), 143-149.
Thornton, L., Cameron, A., McNaughton, S., Waterlander, W., Sodergren, M.,
Svastisalee, C., et al. (2013). Does the availability of snack foods in super markets vary
internationally? International Journal of Behavioral Nutrition and Physical Activity, 10
(1), 1-9.
Thornton, L. E., Cameron, A.J., McNaughton, S.A., Worsley, A., & Crawford, D.A.
(2012). The availability of snack food displays that may trigger impulse purchases in
Melbourne supermarkets. BMC Public Health, 12 (194), 1-8.
Trochim, W.M.K. (2020). Descriptive statistics. Research methods knowledge base.
https://conjointly.com/kb/descriptive-statistics/. [Retrieved 2020-04-27].
UCLA (n.d.) Robust regression in data analysis examples. UCLA.
https://stats.idre.ucla.edu/r/dae/robust-regression/. [Retrieved 2020-05-09].
60
Umeå Kommun (2020, February 2). Kommunfakta. Umeå Kommun.
https://www.umea.se/umeakommun/kommunochpolitik/kommunfakta.4.bbd1b101a585
d704800061691.html. [Retrieved 2020-04-21].
Umeå universitetsbibliotek. (n.d). Källkritik. Källkritik.
https://www.ub.umu.se/skriva/kallkritik. [Retrieved 2020-04-16].
Umeå.se (n.d.) Umeå. Vill Mer. Umeå.se
https://www.umea.se/mer/faktaochsiffror.4.b68a4ef11c312891ac800015457.html.
[Retrieved 2020-05-19].
Vecchio, R., & Cavallo, C. (2019). Increasing healthy food choices through nudges: A
systematic review. Food quality and preference, 78, 1-11.
Velma, E., Vyth, E.L., Hoekstra, T., & Steenhuis, I.H.M. (2018). Nudging and social
marketing techniques encourage employees to make healthier food choices: a
randomized controlled trial in 30 worksite cafeterias in the Netherlands. The American
journal of clinical nutrition, 107 (2), 236-246.
Wang, W.C., & Worsley, A. (2014). Healthy eating norms and food consumption.
European Journal of Clinical Nutrition, 68 (5), 592-601.
Weijzen, P.L.G., de Graaf, C., & Dijksterhuis, G.B. (2009). Predictors of the consistency
between healthy snack choice intentions and actual behaviour. Food Quality and
Preference, 20, 110–119.
Willer, H., Lernoud, J., & Schaack, D. (2013). The European market for organic food
2011. [PDF]. Bonn: Research Institute of Organic Agriculture.
http://orgprints.org/22345/19/willer-2013-session-european-market.pdf. [Retrieved
2020-04-05].
Winchester, C.L., & Salji, M. (2016). Writing a literature review. Journal of Clinical
Urology, 9 (5), 308-312.
Winkler, L., Christensen, U., Glümer, C., Bloch, P, Mikkelsen, B.E., Wansink, B., et al.
(2016). Substituting sugar confectionery with fruit and healthy snacks at checkout – a
win-win strategy for consumers and food stores? a study on consumer attitudes and sales
effects of a healthy supermarket intervention. BMC Public Health, 16 (1), 1-12.
World Health Organisation. (2020). Global Action Plan for the Prevention and Control
of NCDs 2013-2020. World Health Organisation.
https://www.who.int/nmh/events/ncd_action_plan/en/ [Retrieved 2020-04-03].
Wright, S.C., O’Brien, B., Nimmon, L., Law, M., & Mylopoulos, M. (2016). Research
Design Considerations. Journal of graduate medical education, 8 (2), 97-98.
61
APPENDIXES
Appendix 1: Cover letter for the survey in Swedish Hej! Vi är två tjejer som skriver sin Masteruppsats i marknadsföring vid Umeå
Universitet. Idén med vår uppsats är att kontrollera om valet av hälsosamma livsmedel
påverkar konsumenternas val av mataffär i Umeå och om nudging (puffning) kan påverka
det beteendet. Nudging innebär att man underlättar för individer att fatta beslut som
gynnar deras välfärd utan att begränsa eller ta bort deras handlingsfrihet.
För att kunna genomföra vår studie skulle vi vara jättetacksamma om ni tog eran tid och
svarade på denna enkät. Enkäten tar ca 3 minuter att svara på. Svaren är anonyma.
Appendix 2: Cover letter for the survey in English Hello! We are two girls writing our Master’s Thesis in marketing in Umeå University.
The idea with our thesis is to control if the choice of healthy food affects consumers’
choices of grocery stores in Umeå and if nudging can affect that behavior. The purpose
with nudging is to make it easier for individuals to make decisions concerning their health
without limiting or taking away their freedom of choice.
To be able to conduct this study we would be very grateful if you could take your time
and answer to this survey. The survey takes approximately 3 minutes to answer. Answers
are anonymous.
Appendix 3: Questionnaire in Swedish
Grundläggande information
Vem är du
· Man
· Kvinna
· Annat
Ålder
· 15-24
· 25-34
· 35-44
· 45-54
· 55--64
· 65+
Hushållsstatus
· Ensamboende
· Sambo/gift
· Sambo/gift med barn
Vad är din sysselsättning?
· Student
· Jobbar deltid
62
· Jobbar fulltid
· Arbetslös
· Pensionär
Hur ofta besöker du mataffären i veckan?
· 1-2 ggr
· 3-5 ggr
· 5-7 ggr
Besvara frågorna nedan genom att kryssa in rätt alternativ.
1= låg 6=hög
Hur stor påverkan har mängden tillgängliga alternativ av hälsosamt livsmedel ditt
beslut av livsmedelsbutik?
1 2 3 4 5 6
Hur stor påverkan har priset på hälsosamma livsmedel ditt val av livsmedelsbutik?
1 2 3 4 5 6
Hur stor påverkan har marknadsföringen av hälsosamt livsmedel ditt val av
livsmedelsbutik?
1 2 3 4 5 6
Hur stor påverkan har platsen på ditt val av livsmedelsbutik?
1 2 3 4 5 6
Hur stor påverkas dina beslut av placering av varor? Till exempel placering på
hyllan.
1 2 3 4 5 6
Hur stor skulle ditt minne angående vart du hittar varor påverkas om placering av
varor skulle förändras?
1 2 3 4 5 6
Hur stor påverkan skulle omplacering av varor göra på ditt köpbeteende?
1 2 3 4 5 6
Om hälsosam mat skulle placeras synligt jämfört med mindre hälsosam mat, hur
stor är sannolikheten att du skulle välja det hälsosamma alternativet?
1 2 3 4 5 6
När du handlar mat, vad hur stor är sannolikheten att du gör en checklista?
1 2 3 4 5 6
63
Om du gör en checklista, hur stor är sannolikheten att du gör en för att undvika
handla ohälsosamt/ onödiga saker?
1 2 3 4 5 6
När du handlar mat, hur stor är sannolikheten att dina val av produkter påverkas
av andra människors förväntningar på dig?
1 2 3 4 5 6
Hur stor är sannolikheten att du tänker på din hälsa när du handlar matvaror?
1 2 3 4 5 6
Hur stor påverkas ditt köp av livsmedel av dina matvanor?
1 2 3 4 5 6
Hur stor skulle du säga att din attityd att äta nyttigt påverkar ditt köp av livsmedel?
1 2 3 4 5 6
Hur stor påverkan har ditt förflutna inköpsbeteende på ditt köp av livsmedel?
1 2 3 4 5 6
Hur stor är sannolikheten att din avsikt och beteende möts när du handlar
matvaror? Till exempel: Avsikt att köpa ett hälsosamt mellanmål leder till att köpa
ett hälsosamt mellanmål.
1 2 3 4 5 6
När du handlar dina varor, hur stor är sannolikheten att du håller dig till samma
varor?
1 2 3 4 5 6
När du handlar dina varor, hur stor är sannolikheten att du provar nya produkter?
1 2 3 4 5 6
64
Appendix 4: Questionnaire in English
Basic information
Who are you?
· Man
· Woman
· Other
Age
· 15-24
· 25-34
· 35-44
· 45-54
· 55--64
· 65+
Household status
· Living alone
· Living with someone/married
· Living with someone/married with kids
What is your occupation?
· Student
· Working full-time
· Working part-time
· Unemployed
· Retired
How many times per week do you shop groceries?
· 1-2
· 3-5
· 5-7
Answer the questions below by choosing the right alternative
1= low 6=high
How big an impact does the number of healthy food alternatives have to your
decision of grocery store?
1 2 3 4 5 6
How big an impact does the price of healthy food have to your decision of a grocery
store?
1 2 3 4 5 6
How big an impact does marketing of healthy food have to your decision of a grocery
store?
1 2 3 4 5 6
65
How big an impact does the place have to your choice of a grocery store?
1 2 3 4 5 6
How much does the placing of items affect your decisions? For example the
placement on the shelf.
1 2 3 4 5 6
If the placement of items would be changed, how much would this affect your
memory of where you find the groceries?
1 2 3 4 5 6
How big an impact would the changes in the placement of groceries have to your
purchase behavior?
1 2 3 4 5 6
If healthy food would be placed visibly in comparison to less healthy food, how big
is the probability that you would choose the healthier alternative?
1 2 3 4 5 6
When you are doing grocery shopping, what is the probability that you will do a
checklist?
1 2 3 4 5 6
If you do a checklist, how big is the probability that you do it to avoid purchasing
unhealthy/unnecessary things?
1 2 3 4 5 6
When you are doing grocery shopping, how big is the probability that your choices
of products are affected by other people’s expectations?
1 2 3 4 5 6
How big is the probability that you are thinking about your health when you are
doing grocery shopping?
1 2 3 4 5 6
How much do your food habits affect your purchase of food?
1 2 3 4 5 6
How much would you say that your attitude to eat healthy affects your purchasing
of food?
66
1 2 3 4 5 6
How big of an impact has your past behavior have on your purchase behavior?
1 2 3 4 5 6
How big is the probability that your intention and behavior meet when you do
grocery shopping? For example: Intention to buy a healthy snack will lead to buying
a healthy snack.
1 2 3 4 5 6
When you do grocery shopping, how big is the probability that you stick with those
groceries you are used to?
1 2 3 4 5 6
When you do your groceries, how big is the probability that you will try new
products?
1 2 3 4 5 6
Business Administration SE-901 87 Umeå www.usbe.umu.se