gamification of online grocery shopping ......gamification is defined as “a process of enhancing a...
TRANSCRIPT
GAMIFICATION OF ONLINE GROCERY
SHOPPING EXPERIENCE: THE EFFECT
OF BADGES ON THE PURCHASE OF
HEALTHY PRODUCTS
Word count: <13.941>
Bregje Liessens Student number : 000140476511
Supervisor: Prof. Dr. Maggie Geuens
Master’s Dissertation submitted to obtain the degree of:
Master in Business Economics: Marketing
Academic year: 2018-2019
i
Confidentiality agreement
I declare that the content of this Master’s Dissertation may be consulted and/or reproduced,
provided that the source is referenced.
Name student: Bregje Liessens
ii
Abstract
This paper explores the role of gamification and online (grocery) shopping in addressing
suboptimal diets and obesity. This research aims to investigate whether the introduction of
badges leads consumers to buy more healthy products. Participants (N = 207) were exposed
to an online experiment and survey. They were asked to do grocery shopping for three days,
for one person. The treatment group received badges according to their shopping behaviour.
Independent t-tests and Kolmogorov-Smirnov tests were executed to measure whether the
treatment group made healthier purchases than the control group. The results show that those
who received badges (M = 4.30, SD = 0.38) made healthier choices than those who did not
receive badges (M = 4.19, SD = 0.36). This study demonstrates that gamification can steer
customers towards purchasing healthier products, but did not find evidence of secondary
effects of gamification.
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Preface
Writing this master’s dissertation as closure for my degree of Business Economics: Marketing,
was a perfect summary of my career at the University of Ghent: though and challenging, but
at the same time educational and rewarding. It was not possible to bring this to a successful
conclusion on my own. Therefore I would like to take the time to thank a few people.
To my family: a big thank you for your continuous support. Your encouragements and
expressions of belief helped me through the easy and hard times. To my parents especially, I
also want to express my appreciation for giving me the opportunity to obtain a degree.
To my friends and fellow students: thank you for the fun times and for lifting me to a higher
level in many different areas.
To sir Ziad Choueiki: thank you for your comprehensive feedback and quick answers to my
questions during the whole year. I also owe you my gratitude for making me feel more at ease
from the start.
To professor dr. Geuens: thank you for giving me the opportunity to work on this fascinating
and highly relevant subject. My interest in consumer behaviour and passion for marketing
research grew even more during the writing of this thesis.
To Gerrit, Heleen and Jos: thank you for being my critical readers and giving me relevant
feedback.
To everyone who filled in my survey and shared it with their network: thank you, it would have
been difficult to make discoveries without your help.
To the reader of this paper: I hope you enjoy reading this and learn something new, like I did.
Bregje Liessens,
May 2019
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Table of contents
Confidentiality agreement ........................................................................................................ i
Abstract .................................................................................................................................. ii
Preface .................................................................................................................................. iii
Table of contents ................................................................................................................... iv
List of abbreviations .............................................................................................................. vi
List of tables ......................................................................................................................... vii
List of figures ....................................................................................................................... viii
Introduction ........................................................................................................................... 1
1. Gamification ...................................................................................................................... 3
1.1 Definition ...................................................................................................................... 3
1.2 Usability ....................................................................................................................... 3
1.3 Current applications ..................................................................................................... 4
1.3.1 Applications in grocery shopping ............................................................................ 5
1.4 Badges ......................................................................................................................... 6
1.5 Key elements ............................................................................................................... 6
2. Online shopping ................................................................................................................ 8
2.1 Current landscape ........................................................................................................ 8
2.2 Advantages .................................................................................................................. 8
2.3 Characteristics ............................................................................................................. 9
2.4 Online grocery shopping ..............................................................................................10
2.4.1 Influencing buying behaviour .................................................................................11
3. Obesity .............................................................................................................................13
3.1 Situation ......................................................................................................................13
3.2 Causes ........................................................................................................................14
3.3 Consequences ............................................................................................................15
3.4 Solutions .....................................................................................................................15
3.5 Labelling ......................................................................................................................17
3.5.1 Nutri-Score ............................................................................................................18
4. Motivating consumers .......................................................................................................20
4.1 Self-determination theory ............................................................................................20
4.2 Utilitarian versus hedonic motivations ..........................................................................21
4.3 Theory of reasoned action & theory of planned behaviour ...........................................22
4.4 Goal-gradient hypothesis .............................................................................................23
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5. Hypotheses ......................................................................................................................25
6. Methodology .....................................................................................................................28
6.1 Experiment ..................................................................................................................28
6.2 Sample ........................................................................................................................29
7. Results .............................................................................................................................30
8. Discussion and limitations ................................................................................................34
9. Suggestions for further research and implications ............................................................37
10. Conclusion......................................................................................................................39
Reference list ........................................................................................................................ ix
Addendum 1: The calculation of the Nutri-score label (Julia, & Hercberg, 2017) ................... xx
Addendum 2: Survey ........................................................................................................... xxi
2.1 Introduction ................................................................................................................ xxi
2.2 Treatment ................................................................................................................... xxi
2.3 Control ..................................................................................................................... xxix
2.4 Helaas (Did not read the instructions correctly) ...................................................... xxxvii
2.5 Treatment Outcome Badges .................................................................................. xxxvii
2.6 General questions ........................................................................................................ xl
Addendum 3: SPSS output ................................................................................................. xlvi
3.1 Frequencies .............................................................................................................. xlvi
3.2 Internal consistency tests .......................................................................................... xlvii
3.2.1 Enjoyment ........................................................................................................... xlvii
3.2.2 Goal commitment ................................................................................................ xlix
3.2.3 Competence ............................................................................................................. l
3.2.4 Perceived autonomy ............................................................................................... li
3.2.5 Engagement .......................................................................................................... liii
3.3 Independent samples t-tests hypotheses .................................................................... lvi
3.4 Tests of Normality ....................................................................................................... lix
3.5 Mann-Whitney tests ...................................................................................................... lx
3.6 Additional independent samples t-tests ....................................................................... lxi
3.6.1 Low versus high education .................................................................................... lxi
3.7 One-way ANOVA ....................................................................................................... lxiii
vi
List of abbreviations
NPS Net Promotor Score
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List of tables
Table 1: Raw versus fried fries .............................................................................................19
Table 2: Net promotor score .................................................................................................25
Table 3: User engagement scale short form .........................................................................26
Table 4: Goal commitment scale ..........................................................................................26
Table 5: Enjoyment scale .....................................................................................................27
Table 6: Perceived competence scale ..................................................................................27
Table 7: Perceived autonomy scale ......................................................................................27
Table 8: Results independent t-tests ....................................................................................33
Table 9: Age categories ........................................................................................................36
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List of figures
Figure 1: Duolingo badges .................................................................................................... 5
Figure 2: Obesity rates Europe .............................................................................................13
Figure 3: Neutral label ..........................................................................................................17
Figure 4: Positive label .........................................................................................................17
Figure 5: Label with colour coding ........................................................................................17
Figure 6: Nutri-score label ....................................................................................................18
Figure 7: Utilitarian versus hedonic needs (Kolenda Group LLC, 2019) ................................21
Figure 8: Theory of planned behaviour (AfricanBioServices, 2019) ......................................23
Figure 9: First badge ............................................................................................................28
Figure 10: Expert badge .......................................................................................................28
Figure 11: Advanced badge..................................................................................................28
Figure 12: Starter badge .......................................................................................................28
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Introduction
Recent theoretical developments have revealed that gamification, adding game elements to a
non-gaming environment, has a lot of positive effects. It has been applied in many fields and,
if done with consideration, it continuously shows higher intrinsic motivation, user engagement,
goal commitment and in general better behavioural outcomes that extend to all demographic
groups. In grocery shopping it is often implemented to increase customer loyalty.
A popular type of gamification are badges. They have multiple advantages, such as making
clear goals, making it possible for the users to follow their progress, and offering users the
possibility to compare their progress with others.
An interesting field to apply gamification to, might be the battle against obesity. The increasing
obesity rate is, after all, a challenging problem. Not only obesity has a lot of negative
consequences, suboptimal diets in general have a negative effect on one’s health. Next to
heavy marketing, the influence of genes and peoples lifestyle, the way people consume food
(which foods, how much, how often) is an important element in this development. As far as we
know, no previous research has investigated the influence of gamification on the purchase of
healthy products. Therefore, the objective of this paper is to research a solution for suboptimal
diets by investigating whether the introduction of gamification, more specifically badges,
positively influences what type of groceries consumers purchase. It is of interest to know
whether the positive effects of gamification still hold true in an online grocery store
environment, when the goal is not tangible. This will be researched with a survey in a (1x2)
between subjects design.
This paper starts with an elaborate literature review. The first section discusses gamification.
The section begins with defining the concept. This is followed by researching in which context
it can be used successfully. Next, we look into current applications of the concept, including
the existing applications in grocery shopping. After that, the usability of badges is discussed.
The section concludes with researching the important elements that are needed to be taken
into account when implementing gamification into a service.
The second section of this paper reports on online shopping. It starts with a presentation of the
current landscape of this growing sector. Subsequently, advantages in comparison with
physical stores are discussed, followed with specific characteristics. Lastly, online grocery
shopping is examined.
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The third subject discussed extensively, is obesity. For this we examine the current situation,
the causes, consequences and possible solutions. We also take a closer look at how important
labels are to inform consumers.
The fourth and last part of the literature review researches how consumers can be motivated
while grocery shopping. Four relevant theories are explained. Firstly, the self-determination
theory. Secondly, the difference between hedonic and utilitarian motives. Thirdly, the theory of
reasoned action, and by extension the theory of planned behaviour. Fourthly, the goal-gradient
hypothesis is touched upon.
Next the hypotheses for this research are introduced. The key research question is whether
the introduction of badges leads to consumers purchasing healthier products. In addition to
this, a few secondary effects of gamification will be investigated. This part is followed by the
methodology section, which explains the research design. After that, the results are reported
and discussed. To end this paper, the limitations of the study are elucidated and suggestions
for further research are given.
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1. Gamification
In this part gamification will be discussed. Firstly, the term will be defined. Secondly, literature
will be examined to determine whether it is a technique that works for everyone. This will be
followed by a review of the current applications in grocery shopping. After that, badges as a
form of gamification will be elucidated. To finish, the important elements for successful
gamification will be reported.
1.1 Definition
Gamification is defined as “a process of enhancing a service with affordances for gameful
experiences in order to support user's overall value creation” (Huotari, & Hamari, 2012, p. 19)
or “the application of lessons from the gaming domain in order to change stakeholder
behaviours and outcomes in non-game situations” (Robson, Plangger, Kietzmann, McCarthy,
& Pitt, 2014, p. 352). This means adding game-elements into a non-gaming environment to
influence the actions of people in that environment. The popularity of the concept both in
research and business is shown in the estimated growth of the gamification industry from USD
2.17 billion in 2017 to USD 19.93 billion in 2023 (Xi, & Hamari, 2019).
1.2 Usability
It is generally accepted that gamification works because it encourages user engagement and
strengthens positive patterns in the use of the service, which leads to positive intrinsic
motivation. Other good effects contributed to gamification are increased goal commitment and
overall better behavioural outcomes, which lead to increased service profitability (Hamari,
2017). However, the effectiveness is dependent on the context in which it is used and the
abilities of the user. For services oriented towards rational behaviour, including e-commerce,
it could be challenging to implement because customers might be focused on economic gains
(Hamari, Koivisto, & Sarsa, 2014).
Gaming is popular among all demographic groups (Williams, Yee, & Caplan, 2008). The main
difference between gaming and gamification is that gamification has goals outside the game
(Koivisto, & Hamari, 2014). Due to this small difference, it is an interesting field to research
whether gamification also works among all demographic groups. However, the number of
research papers regarding this subject, is limited.
One research found four interesting conclusions. Firstly, age does not have an influence on
most benefits of gamification, only the ease of use diminishes with aging and older users find
the existence of a network more important than younger users. When a service would like older
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people to join, it should provoke mental and physical activity, increase the possibility of social
engagement and offer feedback and support while increasing the user’s perceived self-
efficacy. Secondly, on the differences between genders, it is suggested that women are more
stimulated by the social factors and that they recognize the social benefits more than men.
Next to that, women value ease of use more. Thirdly, to keep users utilising your service, using
social features is beneficial. Therefore it is also a good idea to integrate new users in a
community of users of the service from the start. Nevertheless, as users get more familiar with
the service, they might rely more on their own opinions rather than on those of the community.
Finally, it is also important to note that there are novelty effects. The longer one uses the
service, the lower the perceived usefulness, enjoyment and playfulness. This effect tends to
be greater with younger users, because they get uninterested more easily (Koivisto, et al,
2014). On the contrary, research on persuasive technology (which includes gamification)
suggested that males are more influenced by rewards and competition, which are social
aspects, than females. They also imply that younger people are more easily influenced than
older people (Oyibo, Orji, & Vassileva, 2017).
1.3 Current applications
Gamification has been applied in many different environments and has been proven to have a
positive influence in most cases. Researchers examined the influence of gamification in the
online banking sector (Rodrigues, Costa, Oliveira, 2014), in education (Škuta, & Kostolányová,
2016), in food waste prevention (Fadhil, 2018), in health behaviours, such as exercising (King,
Greaves, Exeter, & Darzi, 2013), dietary decision making in schools (Jones, Madden,
Wengreen, Aguilar, & Desjardins, 2014; Jones, Madden, & Wengreen, 2014) and food tracking
(Ball, Mouchacca, & Jackson, 2014; Lowe, Fraser, & Souza‐Monteiro, 2015; Luhanga,
Hippocrate, Suwa, Arakawa, & Yasumoto, 2016; Spitz, Queiroz, Pereira, Leite, Ferranti, &
Dam, 2018). For lifestyle changes in general it has been looked into by many as well: Hu, Fico,
Cencela, & Arredondo (2014) introduced a technology-based solution to teach children to have
good life-style habits; Wortley (2014) studied how gamification can be applied to rectify public
health by focussing on increasing lifestyle related problems, such as dementia; Wortley (2015)
researched the health and well-being outcomes of lifestyle tracking and health monitoring
equipment; González, et al (2016) designed a training program based on motor games, in
which the school, the family and the child were targeted, in order to combat child obesity.
Gamification is often incorporated in applications. One example is the HAPPY ME app,
developed to fight obesity by children. There are nine quests in the game, six of which are
available from the beginning, the other three can be unlocked by earning experience points.
The quests handle subjects such as healthy food, physical activity, socio-emotional support
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and obesity-related information. Points and badges can be won when the user completes a
quest. Next to that, there is a real-time score board that gives the users the chance to compare
their results with friends (Kim, et al, 2015).
A second example is Duolingo. This
service offers the opportunity to learn
a new language. There are different
levels and the user can unlock new
levels by completing previous ones.
Next to points to win by completing
levels, the user also receives badges
(figure 1) for completing certain
tasks, or ‘lingots’ when completing
lessons multiple days in a row. Lingot
is the in-game currency and can be
used to ‘buy’ extra lessons. Like the
HAPPY ME app, Duolingo also works with leader boards. There are also some other
gamification elements, such as the possibility to personalize the avatar and to make friends
(Škuta, et al, 2016).
1.3.1 Applications in grocery shopping In shopping, both in online and physical stores, gamification has also been applied. It is most
often used in the form of loyalty programs. Consumers can collect points or stamps that can
later be exchanged for a discount or a present. This is done because retention costs are often
much lower than the acquisition costs for new customers. Research shows that it is effective,
but not as effective as one likes to believe, since people who get the most benefit out of it,
often are already loyal customers (Leenheer, Van Heerde, Bijmolt, & Smidts, 2007). This is
called self-selection bias. People often participate in things that already spark their interest,
which wrongly positively influences measurements of effectiveness (Lavrakas, 2008). Next to
that, most people are not exclusively loyal to one shop (Leenheer, et al, 2007). Other research
confirms that many consumers take part in different loyalty programs. This diminishes the
switching costs, thus making the loyalty program less effective. The research results also
showed that a loyalty program should have two aspects to be successful: promotions for the
price sensitive cherry picker and an extra service that adds value for the full-basket, less price
sensitive shopper (Lal, & Bell, 2003). Loyalty programs also have a motivating aspect. This will
be discussed in section 4.4.
Figure 1: Duolingo badges
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1.4 Badges
Badges are a popular way of gamifying services. A digital badge is “a representation of an
accomplishment, interest or affiliation that is visual, available online, and contains metadata
including links that help explain the context, meaning, process and result of an activity.”
(Gibson, Ostashewski, Flintoff, Grant, & Knight, 2015, p. 404). StackOverflow (a platform
where one can post questions and answers about programming (Rajeeva, 2017)) grants
badges to developers who reach a certain amount of contributions. Big websites, such as
Amazon and Y! Answers, also use badges to encourage users to contribute to the website.
They introduce it in a competitive setting, meaning that the users are in competition to receive
the most badges (Easley, & Ghosh, 2016).
A badge offers immediate feedback, which engages users, and facilitates low-cost information
transfer (Xi, et al, 2019). It also gives the opportunity to compete with others and oneself.
Additionally, it gives an indication on how close the user is to accomplishing a goal, which is
accompanied by a certain reputation. That way a badge is a representation of one’s knowledge
and ability to do something. This results in badges being able to motivate, increasing brand
loyalty and customer retention (Gibson, et al, 2015). When translating to the self-determination
theory (as will be discussed later), badges fulfil the three components. Perceived autonomy is
satisfied when users are able to choose which goal they want to achieve. The feeling of
competence is fulfilled by the challenges the user overcomes. Therefore, it is important that
the goals are challenging yet achievable. The third component, relatedness, is met when users
can see each other’s progress and achievements (Snell, 2019).
1.5 Key elements
In order to conduct the experiment, aspects that are important to successfully implement
gamification are reviewed. Richards, Thompson, & Graham (2014) dedicated their study to the
important elements making gamification an effective motivator. The first aspect they mention
is that the design of the game should be interdisciplinary. Therefore, the game should be built
by people from different disciplines. The second aspect is that the developers should leave
room for adaptations. The users are the most important, so they should be able to make
changes to the game based on user feedback. Thirdly, it is important to always keep your
target group in mind. Do they have certain limitations? Are there cultural differences within the
group? etc. King, et al (2013) also underlined the importance of input of clinical and behavioural
scientists in health applications. When the goal is to really change behaviour, it is essential to
have effective interventions. The researchers fear that a game developer will not have enough
knowledge of the theoretical framework in order to be effective.
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For a self-tracking application, it was discovered that negative feedback leads to people to stop
using the app because it makes them feel guilty. In a particular application, users’ step count
was measured and contributed to the growth of a virtual pet. However, when participants did
not reach their daily goal, the pet showed a sad face. This pet functioned as a motivator, but
participants that saw a sad pet several times, reported they no longer looked at the pet. They
were disheartened by the negative state (Lin, Mamykina, Lindtner, Delajoux, & Strub, 2006).
A better way is to give constructive criticism. Next to that, virtual rewards are motivating, but
only when the user knows what he or she can do with them. Competition also helps to make
people like it more. Additionally, to create a habit with the user to use it, the application should
work with notifications (Luhanga, et al, 2016). Furthermore, the service should have the basic
game characteristics incorporated, such as objectives, defined rules, systems of feedback and
participation on a voluntary basis (Souza-Júnior, Queiroz, Correia-Neto, & Vilar, 2016).
Butgereit, & Martinus (2016) argued that the combination of tracking food consumption with
real life rewards, works.
Elements that can influence whether a gamification design works are the context and the
manner in which it is applied, or the discrepancy between the used techniques and the target
audience (Johnson, Deterding, Kuhn, Staneva, Stoyanov, & Hides, 2016). Next to that, not all
gamification works equally well with everybody. That is why personalization, based upon
clustering consumers on common beliefs and behavioural tendencies, is advocated (Lounis,
Neratzouli, & Pramatari, 2013). As previously mentioned, research repeatedly confirms that a
leader board, or any other way users can follow the performance of others, motivates users
(Spitz, et al, 2018).
Gamification, when implemented correctly, may improve intrinsic motivation by satisfying the
needs for autonomy, competence and relatedness; important elements that are also
mentioned in section 4 of this master’s dissertation. However, over-using gaming elements
may diminish the intrinsic motivation (Mekler, Brühlmann, Tuch, & Opwis, 2017).
To conclude, gamification is already widely used and is proven to be successful in changing
consumers’ behaviour when applied with consideration of the elements discussed above.
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2. Online shopping
This section elaborates on the online retailing sector. It starts with a picture of the current
landscape, followed by an analysis of the positive aspects of online shops. After that, research
about what an online shop should look like, how consumers navigate through it and how the
design can influence what consumers buy, is reviewed. Lastly, we take a closer look at why
online grocery shopping stays behind.
2.1 Current landscape
Online shopping is a trending topic of great interest to researchers and managers. As stated
in the Ecommerce Report Belgium 2018 from The Ecommerce Foundation, the sector will
reach a worth of around €11.84 billion in 2018 while in 2015 this was €8.24 billion. When
defining an online shopper as “an individual who regularly bought or ordered goods or services
through the internet” (p. 41), 60% of the Belgian population were online shoppers in 2017. It is
expected that the number of online shoppers will increase from a little over 6 million in 2017 to
a little over 7 million in 2018, but the budget they spend will decrease slightly. According to the
report, in 2017 the biggest online product categories in Belgium were sports and leisure
products (15%), home furnishing (13%) and toys (11%) (Lone, Khelladi, & Packiarajah, 2018a).
Others found, based on self-reports of the people surveyed, that Belgians reported the
following categories as most often bought online: flights and hotels (21%), clothing (17%) and
electrical goods (10%) (Becommerce, 2017).
2.2 Advantages
Morganosky and Cude (2000) found that online grocery shops are mainly used by people who
have above average opportunity costs. Opportunity costs are “the benefits an individual,
investor or business misses out on when choosing one alternative over another” (Investopedia,
2019). In this case it is about people for whom the benefits of online shops are much higher
than for others. For example, people with a disability would lose the benefit of not having to
ask someone else to do their groceries. Morganosky, et al (2000) also identified reasons such
as time constraints, crowding and waiting in line in physical stores as drivers to purchase
online. Next to that, consumers find it convenient that they can fill their basket over several
days and can refer to cupboards or recipes. Other aspects that consumers value are ease of
navigation, convenience and the opportunity of examining the products. Alongside this,
broader selections (Gillenson, & Sherrell, 2002) and competitive pricing (Keeney, 1999) are
also associated with online shopping. Another advantage for customers, is that they are more
empowered due to the high availability of information (Bhattacherjee, 2001).
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For retailers, the internet provides the opportunity to make a loaded shopping environment,
meaning that there are many possibilities to make it entertaining and interactive (Childers,
Carr, Peck, & Carson, 2001).
2.3 Characteristics
Multiple studies have been conducted on what an online shop should look like to be pleasant
to use and how consumers use online shops. Consumers’ attitudes, expectations and
preferences for online and interactive shopping may alter from those in the physical store, even
for comparable products (Childers, et al, 2001). Hansen, Jensen, & Solgaard (2004)
demonstrated that the products that are bought most online, are products that are selected
based on search attributes because you do not need to experience them. Furthermore,
Desrocher, Léger, Sénécal, Pagé & Mirhoseini (2015) did a case study on online grocery
shopping. They reported that consumers use the product pictures more when browsing for
experience goods as opposed to for search goods. Experience goods are difficult to judge on
features or quality and therefore need to be experienced before one can make a judgement
(e.g. a haircut), search goods can easily be evaluated before one buys it (e.g. a computer).
The pictures may be a complementary source of information and may be more indicative than
text description.
The importance of brands has also been pointed out. It is important that a website has an easy
to use search option, that way the customers can easily find their preferred brands. When not
specifically looking for a brand, but for a product category as a whole, it is important for brands
to have a place on the first page, since consumers often look at few pages. Next to that, visual
recognition is important. When consumers see a brand they know or use, they will very likely
buy it (Anesbury, Nenycz‐Thiel, Dawes, & Kennedy, 2016). The research of Danaher, Wilson
& Davis (2003) confirms these findings. They added that better-known brands have greater
loyalty online than offline. A possible explanation is that better known brands have a lower
perceived risk and that online customers are able to select from a list of previously bought
products, thus increasing the loyalty. Additionally, in-store price promotions result in less brand
loyalty than online promotions. However, the more information about products is available, the
less important brands become (Degeratu, Rangaswamy, & Wu, 2000). The importance of
brands in the context of trying to make customers purchase more healthy products, is mainly
for unhealthy products because healthy products are often not branded (e.g. fruits and
vegetables). Brands can be important for unhealthy products for which the most famous brand
is not necessarily the best option. For example: chocolate spread. The most famous brand is
Nutella, which has a Nutri-score label E, which is lower than the less famous brand Canderel,
10
with a Nutri-score label C (Colruyt Group, 2018). The meaning of this Nutri-label will be
discussed in section 3.5.1.
Furthermore, Shankar, Rangaswamy & Pusateri (1999) looked into the effect of the online
medium on the price sensitivity. They found that, when in the perception of the consumer, the
website offers sufficient and searchable information, price sensitivity decreases.
Lastly, the quality of a company’s website, the product quality and the service quality are
positively related to a consumer’s intentions to come back in the future to that specific online
grocery retailer (Boyer & Hult, 2005).
2.4 Online grocery shopping
As stated in the beginning of this section, online retailing is growing every year. However,
notwithstanding the booming sector, online grocery shopping is lagging behind. In spite of food
related purchases increasing with 135% in 2016, only 1.1% of this category was bought online
(Becommerce, 2017). In 2017, only 14% of online shoppers in Europe bought food/groceries
online (Lone, Khelladi, & Packiarajah, 2018b). Comeos vzw (2018) conducted an online survey
about the online purchase experience of consumers in the last 12 months. They found that
consumers are still very hesitant to buy food online. The category ‘food’ consisted of groceries,
as well as prepared food (such as take-away and catering) and meal packs. 25% of the survey
participants selected ‘food’ as answer to the question “Which of the following products/services
would you never (again) purchase online?”. The three main reasons given (also selected from
a list) were “Because physical shops clearly offer advantages, e.g. wider range, immediately
available...”, “Because I want to see or try it first” and “Out of habit”.
Many researchers tried to find answers to the question why online grocery shopping is not
taking off equally well, as compared to online shopping in general. To begin with, grocery
shopping on the web is seen as a complement rather than a substitute to grocery shopping in
a physical store. People mainly buy their groceries online due to situational factors rather than
by elaborate decision making. They often start buying online because of circumstances, such
as illness or a baby, that make it more difficult to physically go to a shop. Customers also often
stop using the service at the end of such life event (Hand, Dall'Olmo Riley, Harris, Singh, &
Rettie, 2009). Secondly, most products that are sold online are products that are decided upon
based on searchable attributes (e.g. colour). That is why groceries are difficult to buy online
(Hansen, 2008). Thirdly, most groceries are perishable products. Which means that those
products should not be on the road for too long and, most importantly, should be delivered
when someone is at home to store it in the refrigerator immediately (Ghazali, Mutum, &
Mahbob, 2006). Fourthly, whether a consumer has a positive attitude towards e-shopping or
11
not, is also influenced by personal values. Since food is culture-bound, it is intrinsically part of
a system of meanings and values (Hansen, 2008). Next, social norms also have an influence
on whether consumers consider online grocery shopping. Potential consumers that are
uninformed on the matter, highly value the guidance they get from friends and family. Another
aspect that stands in the way of the growth of online grocery shopping, is that people simply
like to roam around the shop (Hansen, et al, 2004).
Furthermore, researchers looked closer at the influence of delivery charges, time availability,
travel time to the shop and the purpose of the trip on the choice of shopping channel. The
results showed that they all have an influence on why consumers are hesitant to do grocery
shopping online. The most remarkable finding is that an extra fifteen minutes travel time had a
bigger impact on the preference to shop online than the £5 delivery fee (Huang, & Oppewal,
2006). Marganosky, et al (2000) pointed out the importance of not bringing in-store stressors,
such as stock-outs, to the online environment. Other research confirmed this and added that
since we are talking food, people have different preferences. For example, whether they like
their bananas ripe or still slightly green. Additionally, the study mentioned that online shops
are not price-competitive with the physical stores due to the high operational costs and the
small amount of customers (Anckar, Walden, & Jelassi, 2002). Alongside this, other barriers
for doing online grocery shopping are transactions obstacles, ease of use and security
concerns. Clarity regarding information and the ordering process are also important. Lastly,
consumers do not want to change their existing buying habits (Hansen, 2005).
2.4.1 Influencing buying behaviour The aspects of online shops that have an effect on what consumers buy are also widely
investigated. Milkman, Rogers, & Bazerman (2010) found two contrasting effects in online
grocery shopping. On the one hand, when the time between the order and the delivery
increases, consumers spend less money, order a higher portion of should items (e.g. fruit) and
a lower portion of want items (e.g. chocolate). It showed that consumers are less impulsive
when the outcomes are less immediate. On the other hand, when buying for a moment closer
in time, consumers buy for more specifically planned meals. When ordering for planned meals,
they go more likely for should items than for want items. Other research showed that training
consumers in episodic future thinking (future-oriented thoughts) results in consistently better
resistance to immediate rewards, resulting in consumers being more focussed at good
outcomes further in the future (Hollis-Hansen, Seidman, O'Donnell, & Epstein, 2018).
Additionally, a good layout design and a pleasant atmosphere of the shop have a mediating
effect on the consumer’s emotional arousal and attitude towards the shop (Wu, Lee, Fu, &
Wang, 2013). Next to that, focus groups regarding packaging established that visual packaging
12
and label information play an important role in buying decisions. Visual packaging, mainly
graphics and colour, had a big influence when consumers try to quickly make a decision, while
labels are important for the consumers that are more involved. However, the participants
mentioned that they wished that the label information was easier to understand (Silayoi, &
Speece, 2004). More about labels will be discussed in section 3.5.
Another study argued that online grocery shopping results in less unhealthy products bought,
because of the product presentation. Symbolic presentation decreases the products’ vividness
(Huyghe, Verstraeten, Geuens, & Van Kerckhove, 2017).
In the context of altering consumer decisions, nudging is a concept that is gaining increasing
attention in research. A nudge is “any aspect of choice architecture that alters behavior in a
predictable way without forbidding alternatives or significantly changing economic incentives.
To count as a mere nudge, the intervention must be easy and cheap to avoid.” (Sunstein, &
Thaler, 2008, p. 6). Nudging has been applied in different fields, among which trying to make
people eat more healthily. For example, it has been found that shelf arrangements and choice
set compositions have a significant impact on whether consumers buy healthy or unhealthy
products (Van Kleef, Otten, & van Trijp, 2012; Kroese, Marchiori, de Ridder, 2015). Also,
rearranging one out of two lines in a cafeteria to a convenience line with only healthier foods
and flavoured milk, increases sales of healthier foods by 18% (Hanks, Just, Smith & Wansink,
2012). Adding gaming elements to shopping is an application of nudging since it gives
incentives to choose one thing, but the consumer is still able to choose something else.
In short, online shopping is a sector that cannot be ignored due to its growth and it offers many
new possibilities. Remarkably, online grocery shopping stays behind.
13
3. Obesity
The following part discusses the current obesity health crisis. After a brief outline of the
situation, this paper discusses the causes, followed by the consequences and possible
solutions. To end this section, labelling of products is reviewed as a prelude to the experiment,
because labels play an important role in consumer decision making.
3.1 Situation
There is no doubt that obesity and being overweight are a worldwide problem. The GBD 2015
Obesity Collaborators (2017) analysed data from 68.5 million people in 195 countries over 25
years and concluded that in 2015, 711.4 million children and adults worldwide were obese. In
Figure 2: Obesity rates Europe
14
more than 70 countries the obesity rate has doubled since 1980 and in almost every other
country it also increased. Figure 2 portrays the European situation in 2018 (Jacobs, 2018).
Research shows that in 2017 there was a suboptimal intake of nearly all healthy foods and
nutrients. The biggest problems were found in the underconsumption of nuts and seeds, milk
and whole grains. Contrary, the consumption of sugar-sweetened beverages, processed meat
and sodium transcended the optimal intake (GBD 2017 Diet Collaborators, 2019).
3.2 Causes
There has been quite a bit of research regarding risk factors for obesity. When searching
“causes obesity” on Google Scholar, there are 228 000 results of publications since 2015.
An 8-year long follow up study of 41 580 women found that total fat intake was not strongly
related to weight gain, but increasing energy intakes from animals’, saturated and trans fats
were (Field, Willett, Lissner, & Colditz, 2007). Another study that followed women for 12 years,
found that those who had a higher refined grain intake consistently gained more weight than
those eating more whole grains (Liu, Willett, Manson, Hu, Rosner, & Colditz, 2003). Also,
people who ate more nuts (Jiang, Manson, Stampfer, Liu, Willett, & Hu, 2002), drank light to
moderate amounts of alcohol (Wannamethee, Field, Colditz, & Rimm, 2004), increased their
water, coffee or diet beverages intake (Pan, Malik, Hao, Willett, Mozaffarian, & Hu, 2013) and
increased their intake of vegetables, fruits or yogurt (Schulze, Fung, Manson, Willett, & Hu,
2006) all experienced less weight gain. On the other hand, increasing the intake of sugar-
sweetened beverages or fruit juices (Schulze, et al, 2004), potato chips, potatoes, sweets or
desserts, red meat and fried foods (Mozaffarian, Hao, Rimm, Willett, & Hu, 2011) is associated
with weight gain. Other research confirms that a high intake of sodium, low intake of fruits and
low intake of whole grains are the main alimentary risk factors for disability-adjusted life-years
and death. It affects consumers regardless of age, sex, and their sociodemographic
development (GBD 2017 Diet Collaborators, 2019). A different study that followed men for 16
years, discovered that men who passed up on breakfast had 21% higher risk of type two
diabetes. Also, men who snacked additionally to the three main meals of the day, had an
increased risk (Mekary, Giovannucci, Willett, van Dam, & Hu, 2012).
Next to food, there were also studies regarding physical activity. Higher activity levels were
related to prevention of weight gain and to weight maintenance in the long term. Jogging,
running, brisk walking and cycling were seen as the best options (Mekary, Feskanich,
Malspeis, Hu, Willett, & Field, 2009). Also, too little sleep was associated with obesity (Patel,
& Hu, 2008), as well as the environment one lives in. Women living in higher density countries
had a lower BMI (James, et al, 2013).
15
Alongside personal choices of the consumer, literature has emerged that blames the food
industry itself. The accusation is made that the industry makes highly processed foods in order
to be able to ask higher prices. It is also believed that they produce every product that they are
able to sell, regardless of the nutritional value. For consumers it is difficult to avoid these
products because they get so heavily marketed (Nestle, 2013). These accusations of bad
intentions from the retailers and producers have gained fresh prominence by the introduction
of the Nutri-score label. More about labels will be discussed later in section 3.5.
In addition to this, proof has been found of the existence of genes that play an important part
in the development of early forms of obesity (Bell, Walley, & Froguel, 2005).
3.3 Consequences
Weight gain has many possible consequences. On a physical level there are higher chances
of diseases such as diabetes, cardiovascular diseases, cancers, asthma, cataract, psoriasis,
etc. Next to that, there are also higher risks of gallstones, infertility and mortality. Also on a
mental level there are possible effects, such as depression (Hruby, et al, 2016).
A poor diet not only results in higher risks of obesity, but also higher risks of high blood
pressure, high cholesterol levels and osteoporosis (Infoteur, 2019). The GBD 2017 Diet
Collaborators (2019) estimated that worldwide 11 million deaths and 255 million disability-
adjusted life-years were due to deficient diets.
3.4 Solutions
Seeing the severity of this issue, many have tried to find solutions. Improvement of diet could
possibly prevent one in five deaths globally (GBD 2017 Diet Collaborators, 2019). According
to Wyatt, Winters & Dubbert (2006), medical and surgical interventions have not lived up to
their expectations as being a solution. Most surgeries have some serious possible risks and
are only for the morbidly obese people with a BMI higher than 40 (UZ Leuven, 2018). It is also
argued that although behavioural interventions are part of the treatment, they should be
supplemented with care of psychological factors, such as permanent habits that have been
given by family and society (Wyatt, et al, 2006). One study, based on official medical records,
argues that roughly one third of people who underwent a gastric bypass, have a relapse of
type two diabetes within five years (Arterburn, et al, 2013).
Even small changes can increase weight loss (Hruby, et al, 2016). To reduce child obesity, it
is a smart idea to target the parents. Try to coach them in a way that they do no longer reward
with unhealthy foods, but also try to motivate them to be healthier since children are prone to
16
copying their parents (Epstein, Gordy, Raynor, Beddome, Kilanowski, & Paluch, 2001).
Research done in Cuba confirms the role of the parents. The food consumption and the socio-
economic status of the parents have a big influence. Furthermore, when the parents struggle
with overweight, they are less likely to notice it in their child. The researchers also found that
next to the parents, teachers also have an important role, since nutritional education and
promoting physical activity proves to be successful. It is also believed that kids are highly
influenced by media. Therefore it is important that the whole environment of the child gets dealt
with (González, et al, 2016). Also, the availability of sweet and savoury snacks and sugar
sweetened beverages at home, might result in overconsumption of high-calorie foods (Hollis-
Hansen, et al, 2018).
Eating habits of college students have also been the subject of research. There are several
factors that could influence what students eat: internal cues, such as hunger and taste, external
cues, such as friends and media, and other cues, such as budget, time-efficiency and
convenience. Factors that motivate students to eat healthily are wanting a healthy appearance,
providing positive feelings and preventing disease. Determinants of poor eating habits are
higher perceptions of stress, low self-esteem and a low level of nutrition knowledge. The best
way to make college students eat healthier, is to inform them (Deshpande, Basil & Basil, 2009).
Providing information as a way to influence habits, is an aspect validated in multiple studies
(Ball, et al, 2014; Lowe, et al, 2015).
Another aspect that is looked at, is the influence of intentions. When one plans in detail to eat
healthily, one eats more healthily. However, intentions are not able to break the negative
influence of unhealthy habits (Verplanken, & Faes, 1999).
Other research found that the best way to reduce the intake of energy-dense and nutrient-poor
foods is by promoting fruits and vegetables. Food choices were also a result of food-purchasing
habits. When a consumer does not buy healthy foods, it will not be available for consumption
at home (Moreira, Moreira, & Fiates, 2015). Recently, the grocery store Delhaize announced
a pilot-project in which they increase consumers’ purchasing power for healthy products.
Products with a Nutri-score A or B (infra) get a 20% discount on top of the regular actions (The
New Pub, 2019).
An interesting fact that was found in various studies is that consumers are aware of the link
between a poor diet and health problems. However, this is often not reflected in behaviour.
Making healthy decisions when shopping requires effort. Reasons reported for buying
convenient, less healthy options were constraints set by money or time, as well as temptations
in the shop. It is suggested that the best way to improve dietary choices is facilitation, reducing
the perception of effort (O’Brien, et al, 2015). Lynch, Holmes, Keim, & Koneman (2012)
17
confirmed that most people can indicate which foods are healthier than others, without knowing
why. Consumers determine the healthfulness by its nutrient content or the effect of the
consumption of the food on the body. However, in the evaluation important nutrients are often
forgotten and consumers often lack knowledge about the connection of foods with nutrients
and health effects. Next to that, consumers often belief that their diet is already healthy. It also
shows to be difficult to resist the temptation of unhealthy food choices when shopping (Moreira,
et al, 2015). A possible solution to make it easier for the consumer, is suggesting healthier
options. When consumers get a suggestion for a product that contains less salt, even when it
is not from the same category, the salt volume of their shopping basket lowers with 9% (Riches,
Aveyard, Piernas, Rayner, & Jebb, 2019).
The report of the GBD 2017 Diet Collaborators (2019) summarizes the problem well with the
statement “suboptimal diet is responsible for more deaths than any other risks globally,
including tobacco smoking, highlighting the urgent need for improving human diet across
nations” (p. 10). They also emphasize the importance of integrated measures that target food
production as well as food processing and distribution, to improve food consumption.
3.5 Labelling
Previously, it was mentioned that informing the consumer is important to change behaviours.
As a way of informing consumers, labels are used. Labels also play an important role in buying
decisions (Silayoi, et al, 2004).
In Europe there are three types of nutrition labels. The neutral labels give objective information
on the nutritional values of the product. Positive labels are added to products that are a healthy
choice within a product category. Labels with colour coding give each product a colour, varying
from red to green (e.g. the traffic lights label or the Nutri-score label), according to how healthy
the product is (Vlaams Instituut Gezond Leven, 2019a).
Consumers need less effort to interpret labels and pick healthier products when there are
nutrient-specific labels that consist of both text and symbolic colour rather than labels that only
give numeric information about the nutritional value (Hersey, Wohlgenant, Arsenault, Kosa &
Figure 3: Neutral label Figure 4: Positive label Figure 5: Label with colour coding
18
Muth, 2013). Other research confirms that the presence of labels results in a significant
increase in the customers’ capability to classify the products correctly. It is found that for some
product categories (sweet biscuits and sometimes cheeses and sweet spreads), nutrition
labels lead to smaller portion sizes than when there is no label on the products (Egnell, et al,
2018).
3.5.1 Nutri-Score Recently, the use of the Nutri-score label has been on
the rise. To inform consumers, distributors and even
some producers, such as Danone, are starting to
introduce this label. It rates the products within a
product category on a scale from A to E, with A being
the healthiest, and from dark green to red, with dark
green being the best option. The labels are put on
products in the shops, thus making it easier for consumers to quickly see which option is the
healthiest (Vlaams Instituut Gezond Leven, 2019b).
The label rates a product based on the energy (kJ) and the levels of sugar, saturated fats,
sodium, fibre and protein. This results in a rating between -15 and 40. The three steps to
calculate which label a product receives, are explained in addendum 1 (Julia, & Hercberg,
2017).
A pitfall to this label is that it rates products based on what is in the packaging. Consequently,
freezer fries have the rating A, because the content of such bag is merely potato. However,
most people fry those fries, which would result in a C-rating (see table 1). This could give
consumers a wrong impression about the level of healthiness of products and can also be
slightly contra-intuitive since consumers do tend to associate fries with being unhealthy.
Figure 6: Nutri-score label
19
Freezer fries Fried fries from freezer
Per 100g (Iglo,
2018) Points
Per 100g
(Eenvoudig
afvallen, 2019)
Points
Energy (kJ) 537 1 1333 3
Sugar (g) 0.33 0 0.06882 0
Saturated fats (g) 1.7 1 4.0182 4
Sodium (mg) 50 0 193.4064 2
Fibre (g) 2.4 3 3.4188 4
Protein (g) 2.6 1 3.7518 2
Total
1+0+1+0-(3+1) =
-2
3+0+4+2-(4+2)=
3
Rating A C
Table 1: Raw versus fried fries
This concern of confusion has been confirmed with recent uproar in the media. Specialists had
to emphasize that the Nutri-label does not take into account the preparation of food (vrtnws,
2019).
In addition to this confusion and in accordance with the accusations towards producers, it has
been shown that not all producers are equally keen on the labels. Multi-national companies
(e.g. Mars and Coca Cola) are even introducing their own label (Julia, Charpak, Rusch,
Lecomte, Lombrail, & Hercberg, 2018).
20
4. Motivating consumers
As stated before, consumers know what is healthy and unhealthy and also know the possible
health effects of a poor diet but often do not translate it into actual behaviour. Therefore, it is
important to know how consumers can be motivated to buy healthily. This section talks about
theories that try to explain how consumers are motivated to purchase certain products. There
are many such theories, but below the ones believed to be relevant for this study on grocery
shopping are briefly explained. First the self-determination theory is discussed, followed by
utilitarian versus hedonic motivations; subsequently, the theory of reasoned action and the
theory of planned behaviour. Lastly, the goal-gradient hypothesis is shortly looked into.
4.1 Self-determination theory
The self-determination theory starts from the idea that there are two types of motivation,
intrinsic and extrinsic. When someone is intrinsically motivated, that person does something
because he or she finds it inherently interesting or enjoyable. Someone is extrinsically
motivated because of external pressures or rewards. It has been proven that intrinsic
motivation is the best motivation if one wants to learn something. However, knowing that
learning something is not always inherently interesting or fun, it is also important to make use
of the more active and voluntary forms of extrinsic motivation (Ryan, & Deci, 2000a). People
who do something based upon extrinsic motivation, will stop doing it when the external
pressures or rewards subside.
There are 3 components of motivation. Firstly, autonomy. When one is autonomous he or she
can make his or her own decisions. Secondly, perceived competence. When someone feels
competent, he or she feels like he or she is capable of doing the task at hand. Thirdly,
belongingness (sometimes called relatedness). This means that one feels he or she belongs
to, or can relate to, a group. Depending on the level of these components, there are different
stages ranging from amotivation to intrinsic motivation. When all the factors are low, the person
is in a state of amotivation. This means that he or she has no intention to act. The second
stage is external regulation. One does something because he or she gets a reward or wants
to avoid punishment (extrinsic motivation). The third stage is introjected regulation. One does
something to improve one’s ego. The fourth stage is identified regulation. This is when one
does not like doing a task, but he or she understands the importance of it. The fifth stage is
integrated regulation. The motivation has been integrated with one's own values and needs.
The final stage is intrinsic motivation. One does something because he or she likes to do it
(Ryan, & Deci, 2000b).
21
Another study states that the leading factor to behavioural change is individual motivation and
that there are indeed two types of motivation, intrinsic and extrinsic. This study confirms that
intrinsic motivation works better (Johnson, et al, 2016). Luhanga, et al (2016) also endorse that
intrinsic motivations are more important and that those motivations subside when extrinsic
motivations are added.
This theory has also been proven true in a gaming environment. When players have a higher
perceived in-game autonomy and competence, they enjoy and prefer the game more and it is
even related to positive pre- and post-play feelings (Ryan, Rigby, & Przybylski, 2006).
This thesis looks at the possibility to promote buying healthy by keeping autonomy,
competence and belongingness high, meaning that the consumer is intrinsically motivated.
This will be attempted by introducing gamification, and more specifically badges. As stated in
section 1.4, badges fulfil the three prerequisites. One obstacle is that people get motivated by
different things, though are consistent on what motivates them. One study that related gaming
with food consumption, showed that people who get motivated within games by different things,
are also motivated by different things to eat certain types of food (Luomala, et al, 2017).
4.2 Utilitarian versus hedonic motivations
The second theory states that there are two types of motivations for buying a product: utilitarian
and hedonic
motivations. Utilitarian
motivations are for
products that are
functional, while
hedonic motivations are
based on pleasure.
Sometimes a third type,
social motivations, is
added. This means that
people are social creatures who want to relate to others, so they buy products to fulfil this need
(Hamari, & Koivisto, 2015).
Labbe, Ferrage, Rytz, Pace, & Martin (2015) found that when consuming coffee for the
caffeine, an utilitarian motivation, the consumers found the process less pleasant than those
who drank coffee for the enjoyment. Aspects that influence utilitarian motivation are
convenience, cost saving, product range and information availability. Hedonic motivations are
influenced by authority, status and adventure (To, Liao, & Lin, 2007). Other research states
Figure 7: Utilitarian versus hedonic needs (Kolenda Group LLC, 2019)
22
that the use of utilitarian systems is motivated by perceived usefulness, while the use of
hedonic systems is driven by perceived enjoyment. Gamification is somewhere in between and
therefore driven by both. That is why ease of use and enjoyment are determinants of why
people keep using a gamification service and usefulness influences the positive attitude
towards the service. Additionally, social and utilitarian aspects are more likely to act as a
mediator for the attitude towards the service, while hedonic, less cognitive aspects have a
positive influence on the behaviour (Hamari, et al, 2015).
Related to the current paper, if one buys healthy products because he or she likes the taste,
they have hedonic motivations to buy. If one buys healthy products because of the health
benefits, they are utilitarianly motivated. However, when they like the taste, they would
probably just buy it. Therefore, it is assumed that the consumers who have to be motivated,
will buy most healthy products because of utilitarian motives.
4.3 Theory of reasoned action & theory of planned behaviour
Hansen, et al (2004) stated that online grocery buying intention can be explained by both the
theory of reasoned action and the theory of planned behaviour. The fact that they found that it
can be explained by both theories, should not be surprising since both theories are developed
by Fishbein and Ajzen and actually build on one another. They are a result of continued
development.
The theory of reasoned action argues that in order to make a decision on what product to buy,
a consumer takes two things into consideration: his own attitude towards the product, and
social norms. Social norms are what the consumer beliefs that others think about the product,
weighed with the importance of their opinion according to that consumer. The theory of planned
behaviour adds an extra factor to the mix, namely perceived behavioural control. This means
what the consumer feels he or she can accomplish (De Pelsmacker, Geuens, & Van den
Bergh, 2007).
23
When working with this theory, there are a few aspects online grocery shops can play with.
Previously in this paper, we learned that online grocery shops are not as popular as other
online shops. When one knows what a consumer values in online shops, these aspects can
be put in the spotlight when promoting the online grocery shop. Which will positively influence
the consumers attitude and, according to the theory of planned behaviour, will improve his or
her attitude towards online grocery shopping. Additionally, when a consumer believes he or
she is not capable of doing online grocery shopping, it is very unlikely he/she will try it.
Therefore, to promote online grocery shopping, the ease of use should be underlined. Finally,
the more people who are convinced to use online grocery shops, the more favourable social
norms will be.
4.4 Goal-gradient hypothesis
The goal-gradient hypothesis states that there is a positive acceleration in the motivation to
reach a goal, the closer one is to that goal (Hull, 1932, 1934).
This is a finding that can also be seen regarding loyalty programs (section 1.3.1). Consumers
tend to buy more different products, more frequently and bigger quantities the closer they are
to their goal, which in these settings is the present or discount when reaching a certain amount
of points. This is because goal striving is intrinsically motivating, reinforcing the extrinsic reward
(Kivetz, Urminsky, & Zheng, 2006).
It has been shown that this effect exists even when the progress is artificial. With artificial
progress being for example having a saving card that requires 12 stamps to be completed, but
two are already given upon receiving the card. Consumers are also more inclined to join the
program, find the program more attractive and are more likely to complete the program,
Attitude
Social norms
Perceived
behavioural
control
Intentions Behaviour
Figure 8: Theory of planned behaviour (AfricanBioServices, 2019)
24
meaning continuing until the goal is reached, when they are given artificial progress (Nunes,
& Dreze, 2006).
Bonezzi, Brendl, & De Angelis (2011) argue that this theory only applies in some cases. They
say that one’s motivation depends on what is used as reference point. If a person uses the
end state as reference point, getting closer to the goal will be motivating. However, if a person
uses the starting point for monitoring progress, motivation will decrease as they get further.
The authors also indicate a third type, where a person shifts his or her reference point in the
middle of the task, which results in a motivation dip in the middle towards the goal.
As stated before, there are multiple other theories that try to explain how consumers are
motivated to buy. However, these are not all relevant for (online) grocery shopping. Therefore,
they will not be discussed in this paper. If the reader is interested in those other theories, it is
recommended to take a closer look into literature about consumer behaviour, such as
“Consumer behaviour models: an overview” by Jisana (2014).
25
5. Hypotheses
As discussed in the literature review, obesity is a big problem and a considerable cause of this
problem is the way people consume food: which foods, how much food, how often. Therefore
it is important that people start consuming foods with a better nutritional value more often.
Several methods (expanding food literacy, altering environments, …) have been used to try to
make consumers adopt a healthier lifestyle. Gamification has been used in many situations,
including the grocery shopping environment in an attempt to make consumers more loyal, and
in the healthier lifestyle business in an effort to make them more active. However, gamification
has not been used to guide consumers towards healthier products during the grocery shopping
experience. This paper looks into the possibility to use gamification to motivate consumers into
buying healthier. It would make it more fun and consumers would be more committed towards
this goal.
The main research question of this paper is to find out what the effects of gamification are on
consumers’ purchases of healthy foods.
H1: When in a gamified shopping experience customers receive a badge according to the
healthiness of their shopping basket, the customer will purchase a healthier shopping
basket.
In the ‘Obesity’ section, we learned that to promote the use of food services to consumers, it
should be promoted as that it adds excitement to life. To get a feel of how excited the participant
is about the shopping experience, his or her intent to return and intents of word-of-mouth
promotion are measured. It is expected that consumers will be more excited when there are
game elements included.
H2: Consumers are more excited to shop when they receive badges during the shopping
process in an online grocery shop.
This will be measured by the net promotor score (NPS), a tool used to measure loyalty
(Satmetrix Systems, Inc, 2017).
How likely is it that you would recommend [brand] to a friend or colleague?
Table 2: Net promotor score
Next to that, the effectiveness of the gamification is assessed, based on three hypotheses.
H3a: Consumers are more engaged when they receive badges during the shopping
process in an online grocery shop.
26
Engagement will be assessed with the ‘User engagement scale short form’ developed by
O’Brien, Cairns, & Hall (2018).
1. I lost myself in this shopping experience.
2. The time I spent shopping just slipped away.
3. I was absorbed in my shopping task.
4. I felt frustrated while visiting this shopping website.
5. I found this shopping website confusing to use.
6. Using this shopping website was taxing.
7. This shopping website is attractive.
8. This shopping website was aesthetically appealing.
9. This shopping website appealed to my senses.
10. Shopping on this website was worthwhile.
11. My shopping experience was rewarding.
12. I felt interested in my shopping task.
Table 3: User engagement scale short form
H3b: Consumers are more committed to their goal when they receive badges during the
shopping process in an online grocery shop.
Goal commitment is measured by the scale developed by Klein, Wesson, Hollenbeck, Wright,
& DeShon (2001).
1. It’s hard to take this goal seriously.
2. Quite frankly, I don’t care if I achieve this goal or not.
3. I am strongly committed to pursuing this goal.
4. It wouldn’t take much to make me abandon this goal.
5. I think this is a good goal to shoot for.
Table 4: Goal commitment scale
H3c: Consumers enjoy shopping more when they receive badges during the shopping
process in an online grocery shop.
Enjoyment is measured with a part of the scale of the Intrinsic Motivation Inventory
(selfdeterminationtheory.org, 2019).
27
1. I enjoyed doing this activity very much.
2. This activity was fun to do.
3. I thought this was a boring activity.
4. This activity did not hold my attention at all.
5. I would describe this activity as very interesting.
6. I thought this activity was quite enjoyable.
7. While I was doing this activity, I was thinking about how much I enjoyed it.
Table 5: Enjoyment scale
In the ‘Motivating consumers’ part, the strength of intrinsic motivation was discussed. It is the
most effective and most sustainable way of motivation. Therefore it is interesting to know
whether the consumer is significantly more intrinsically motivated in this gamified environment.
H4: Consumers are more intrinsically motivated when they receive badges during the
shopping process in an online grocery shop.
For this, two scales are used, one for perceived competence, and one for perceived autonomy.
Both are retrieved from the Intrinsic Motivation Inventory (selfdeterminationtheory.org, 2019).
In section 4.1 it was discussed that motivation consists of three components: perceived
competence, perceived autonomy and relatedness. However, in this experiment there is no
social aspect added to the shopping experience, therefore relatedness is not measured.
1. I think I was pretty good at this activity.
2. I think I did pretty well at this activity, compared to other students.
3. After working at this activity for awhile, I felt pretty competent.
4. I am satisfied with my performance at this task.
5. I was pretty skilled at this activity.
6. This was an activity that I couldn’t do very well.
Table 6: Perceived competence scale
1. I believe I had some choice about doing this activity.
2. I felt like it was not my own choice to do this task.
3. I didn’t really have a choice about doing this task.
4. I felt like I had to do this.
5. I did this activity because I had no choice.
6. I did this activity because I wanted to.
7. I did this activity because I had to.
Table 7: Perceived autonomy scale
28
6. Methodology
6.1 Experiment
This research is conducted in two parts: an experiment followed by a survey. Participants are
randomly assigned to either the treatment or control group.
In the experiment, both groups are asked to shop for themselves for
3 days, with a maximum budget of €50, in a mock-up online shop.
Pictures are used to provide complementary information and in an
attempt to make the experience more enjoyable. The treatment group
is motivated to buy more healthy products by adding gamification
elements. The decision was made to use badges as gamification
element, because it is something that gives immediate feedback, an
element which is linked to a successful gamification design. It is also
a visual reward, which works motivationally. During their shopping experience, the treatment
group receives a badge on two occasions. The first badge (figure 9) is shown when they enter
the shop, together with the message that there is a possibility to upgrade the badge by
shopping in the shop three more times in a healthy way. Participants receive a second badge
at the end of their shopping trip. The second badge differs according to how healthy they shop.
If the average product in their shopping basket has an A- or B-score, they receive the ‘expert’
badge (figure 10), they are experts in buying healthily. If the average product has a C-rating,
they are ‘gevorderd’ (advanced) in buying healthily (figure 11). If the average product has a D-
or E-rating, they are ‘beginners’ (starters) (figure 12). The badges are used in conjunction with
constructive criticism.
Figure 10: Expert badge
Figure 11: Advanced badge
Figure 12: Starter badge
Previously, it was mentioned that many consumers lack the information on what is healthy and
what is less healthy. In this study, the Nutri-score label (shown in figure 6) is added to each
product in the shop to inform the consumer. Which label belongs to which product, is retrieved
from the Colruyt Group website (2018).
Figure 9: First badge
29
To measure the mere influence of the gamification, both the treatment and the control group
see the Nutri-score label, but only the treatment group sees the badges. The literature study
showed that brands and price sensitivity might be of influence in an online grocery shopping
environment. That is why no brands are used and both groups see the same prices.
The survey is identical for both groups. Considering the participants earn the most important
badge at the end of their shopping trip, the impact of gamification is best measured by a scale
that measures intention to buy again. Therefore, the first question uses the net promotor score
(table 2). User engagement is measured with the ‘User engagement scale short form’ (table
3). The five-item scale developed by Klein, et al (2001) is used to measure goal commitment
(table 4). Enjoyment and intrinsic motivation are measured with parts of the scale of the
Intrinsic Motivation Inventory (tables 5-7). All statements were translated to Dutch, and if
necessary, slightly adapted to fit the situation. Lastly, socio-demographic questions are asked.
The survey as seen by the respondents can be found in addendum 2.
6.2 Sample
Over the period of April 1st to April 13th 2019, the survey was distributed via e-mail and social
media. A €20 gift coupon for a grocery store was raffled among the participants who reached
the end of the survey. 345 people started the survey, 330 completed it. Of the latter, several
were omitted. 93 were eliminated due to not choosing any products and 14 due to transcending
the €50 budget. An additional 16 respondents were deleted from the sample because they
answered the control question incorrectly. This resulted in a usable sample of 207
respondents.
Of those 207, 62.8% were female and the average age was 41.16 years (SD = 20.02, range
16 to 82). 75.3% had a bachelor’s degree or higher. Of the sample, 39.1% were students and
36.7% were in paid employment. 87.9% had a varied diet, 5.3% a vegetarian diet and 6.8%
followed another diet (of which none were vegans).
The research was a 1x2 (gamification vs. no gamification) between subjects design, with
respondents being randomly assigned to either the treatment or control group. There were 107
respondents in the treatment group and 100 in the control group.
30
7. Results
Since every hypothesis is a (one-tailed) comparison of two means, independent t-tests were
conducted. This is a widely used test in marketing research. Statistically speaking, t-tests are
only allowed when the variables have a normal distribution. After conducting the Kolmogorov-
Smirnov test with the Lilliefors correction, only the variables ‘autonomy’ and ‘average score’
prove to have a normal distribution, but this only in the treatment group. Because of this, next
to the t-test, an independent samples Mann-Whitney test was conducted for all variables, as
control test.
The average score, which is the total score (sum of scores of all chosen products) divided by
the number of products chosen, for every respondent was calculated. The independent t-test
shows that the mean of the treatment group that was subjected to gamification (M = 4.30, SD
= 0.38) is significantly higher than the mean of the control group (M = 4.19, SD = 0.36) (t(205)
= 2.19, p = 0.029). The Mann-Whitney test also demonstrates that the average score was
significantly higher for the treatment group (Mdn = 4.36) than for the control group (Mdn = 4.20)
(U = 4339.00, p = 0.019). The results show that when in an gamified shopping experience
consumers receive a badge according to the healthiness of their shopping basket, the
customer will purchase a healthier shopping basket, thus confirming H1.
The net promotor score was used to calculate respondents’ excitement about the shop. The
independent t-test shows that the mean of the treatment group (M = 5.75, SD = 2.49) is not
significantly higher than the mean of the control group (M = 5.23, SD = 2.62) (t(205) = 1.46, p
= 0.146). The Mann-Whitney test also indicated that the excitement was not significantly
greater for the treatment group (Mdn = 6.00) than for the control group (Mdn = 6.00) (U =
4701.50, p = 0.129). This result shows that the introduction of badges does not make
consumers more excited about the online grocery shop, which consequently does not support
H2.
The consumer engagement was measured by the 12-item ‘User engagement scale short form’
on a 7-point Likert scale. The scores of the items “Ik voelde me gefrustreerd tijdens het
winkelen.”1, “Ik vond de online winkel verwarrend om te gebruiken.”2 and “Het gebruik van deze
online winkel was lastig.”3 were reversed. After determining the internal consistency (α =
0.886), the mean of the items was calculated. The independent t-test shows that the mean of
the treatment group (M = 4.50, SD = 0.90) is not significantly higher than the mean of the
control group (M = 4.34, SD = 0.96) (t(205) = 1.18, p = 0.240). The Mann-Whitney test also
1 I felt frustrated while visiting this shopping website. 2 I found this shopping website confusing to use. 3 Using this shopping website was taxing.
31
proved that the user engagement was not significantly greater for the treatment group (Mdn =
4.58) than for the control group (Mdn = 4.46) (U = 4958.50, p = 0.363). This result shows that
the introduction of badges does not make consumers more engaged during shopping in the
online grocery shop, which does not confirm H3a.
Goal commitment was measured by means of a five-item seven-point Likert scale. After
reversing the scores of the items “Het is moeilijk om ‘gezond te kopen’ serieus te nemen.”4,
“Om eerlijk te zijn kan het me niet schelen of ik al dan niet gezond koop.”5 and “Het zou niet
veel vergen om me ‘gezonde voeding kopen’ te laten opgeven.”6, the internal consistency was
determined (α = 0.744) and the mean of the items was calculated. The independent t-test
shows that the mean of the treatment group (M = 5.34, SD = 0.89) is not significantly higher
than the mean of the control group (M = 5.26, SD = 1.00) (t(205) = 0.58, p = 0.564). The Mann-
Whitney test also indicated that the goal commitment was not significantly higher for the
treatment group (Mdn = 5.60) than for the control group (Mdn = 5.30) (U = 5146.50, p = 0.641).
This result shows that the introduction of badges does not make consumers more committed
to their goal during shopping in the online grocery shop, thus not supporting H3b.
Enjoyment was measured by means of a seven-item seven-point Likert scale. The scores of
the items “Ik vond dit een saaie activiteit.”7 and “Deze activiteit hield mijn aandacht helemaal
niet.”8 were reversed. After determining the internal consistency (α = 0.913), the mean of the
items was calculated. The independent t-test shows that the mean of the treatment group (M
= 4.57, SD = 1.17) is not significantly higher than the mean of the control group (M = 4.35, SD
= 1.21) (t(205) = 1.32, p = 0.188). The Mann-Whitney test also indicated that the enjoyment
was not significantly greater for the treatment group (Mdn = 4.71) than for the control group
(Mdn = 4.57) (U = 4816.50, p = 0.215). This result shows that the introduction of badges does
not make consumers enjoy themselves more during their online grocery shopping, which does
not confirm H3c.
To measure consumers’ intrinsic motivation, perceived autonomy and competence were
assessed. A seven-item seven-point Likert scale was used to measure perceived autonomy.
“Ik had het gevoel dat het niet mijn eigen keuze was om deze taak te doen.”9, Ik had niet echt
een keuze over deze activiteit.”10, “Ik had het gevoel dat ik dit moest doen.”11, “Ik heb deze
4 It’s hard to take ‘eating healthily’ seriously. 5 Quite frankly, I don’t care if I buy healthily or not. 6 It wouldn’t take much to make me abandon ‘buying healthy foods’. 7 I thought this was a boring activity. 8 This activity did not hold my attention at all. 9 I felt like it was not my own choice to do this task. 10 I didn’t really have a choice about doing this task. 11 I felt like I had to do this.
32
activiteit gedaan omdat ik geen keuze had.”12 and “Ik heb deze activiteit gedaan omdat ik dit
moest.”13 were reversed. After determining the internal consistency (α = 0.856), the mean of
the items was calculated. The independent t-test shows that the mean of the treatment group
(M = 5.33, SD = 0.88) is not significantly higher than the mean of the control group (M = 5.14,
SD = 1.05) (t(205) = 1.40, p = 0.162). The Mann-Whitney test also showed that the perceived
autonomy was not significantly greater for the treatment group (Mdn = 5.29) than for the control
group (Mdn = 5.14) (U = 4945.00, p = 0.346). A six-item seven-point Likert scale, with reversed
item “Deze activiteit kon ik niet goed.”14, (α = 0.857) measured competence. The independent
t-test shows that the mean of the treatment group (M = 4.99, SD = 0.87) is not significantly
higher than the mean of the control group (M = 4.91, SD = 0.81) (t(205) = 0.69, p = 0.490). The
Mann-Whitney test also indicated that the competence was not significantly greater for the
treatment group (Mdn = 5.17) than for the control group (Mdn = 5.00) (U = 4975.00, p = 0.383).
These findings show that consumers are not intrinsically more motivated to buy healthily in an
online grocery shop by the introduction of badges, hence H4 is not confirmed.
The results are summarized in table 8.
12 I did this activity because I had no choice. 13 I did this activity because I had to. 14 This was an activity I couldn’t do very well.
33
Variable Hypothesis Mean SD t(df) p Confirmed by Mann-
Whitney test?
Average score H1* Mtreatment = 4.30
Mcontrol = 4.19
0.38
0.36 t(205) = 2.19 0.029 Yes
Excitement H2** Mtreatment = 5.75
Mcontrol = 5.23
2.49
2.62 t(205) = 1.46 0.146 Yes
User engagement H3a** Mtreatment = 4.50
Mcontrol = 4.34
0.90
0.96 t(205) = 1.18 0.240 Yes
Goal commitment H3b** Mtreatment = 5.34
Mcontrol = 5.26
0.89
1.00 t(205) = 0.58 0.564 Yes
Enjoyment H3c** Mtreatment = 4.57
Mcontrol = 4.35
1.17
1.21 t(205) = 1.32 0.188 Yes
Perceived autonomy H4** Mtreatment = 5.33
Mcontrol = 5.14
0.88
1.05 t(205) = 1.40 0.162 Yes
Competence H4** Mtreatment = 4.99
Mcontrol = 4.91
0.87
0.81 t(205) = 0.69 0.490 Yes
* Hypothesis confirmed ** Hypothesis not confirmed
Table 8: Results independent t-tests
34
8. Discussion and limitations
The present experimental study confirms that the introduction of badges steers consumers
towards buying healthier products. However, even though there is a statistically significant
difference, the relevance of this difference is limited. In this study, the groceries were rated on
a scale of one to five, based on their Nutri-score. When extending this reasoning, both 4.30
and 4.19 (the average score of respectively the treatment and control group) would be
considered as a B-rating. For this there are multiple plausible explanations.
First of all, out of the 68 products that were offered in the primitive online grocery store, 32 had
an A-rating, thus there was a predominance of healthy products. Even though an effort was
made to compose the shop in a varied way, it was hard to have more or less the same number
of products for every rating while still being realistic. One reason is that ‘vegetables’ was a
whole section consisting of eight products and all of these have an A-rating. Also, as discussed
in section 3.5.1, products that are rather unhealthy after preparation might have a rather
positive Nutri-score (e.g. fries).
Secondly, 75.4% of the respondents (74.8% in the treatment group, 76.0% in the control group)
had a higher education and as has been previously reported in the literature, higher education
results in making better choices regarding ones diet (Li, & Powdthavee, 2015). However, in
this study the hypothesis that higher educated people buy healthier food cannot be confirmed.
The average score of the less educated people (M = 4.18, SD = 0.37) is not significantly lower
than the average score of the high educated people (M = 4.26, SD = 0.38) (t(205) = -1.32, p =
0.188).
A third clarification could be, that the addition of the Nutri-score made respondents highly
aware of what they were buying and its health rating. Therefore making them more prone to
buy products with an A- or B-rating, both in the control and treatment group.
Another explanation could be that working with a five-point scale is not distinguishing enough.
Meaning there is not enough difference to differentiate oneself. In order to address this issue,
the possibility to work with points (in addition to the Nutri-score) from 1-10 based on the Nutri-
score, in combination with the food triangle, was considered. However, this could have been
confusing for respondents, therefore the decision was made to not work with it during this
experiment.
This analysis did not find evidence of the existence of the secondary effects of gamification
that were mentioned in the literature review. In this study, respondents did not feel more
intrinsically motivated, more excited about their shopping experience, more engaged, more
35
goal committed, nor enjoyed shopping more when they received badges. Gamification not
significantly influencing intrinsic motivation does appear in other studies (Mekler, et al, 2017).
Another study also suggests that not everyone is equally motivated by badges (Denny, 2013).
That users are not more engaged when gamification is introduced, is contrasting with many
previous research papers (Gustafsson, Katzeff, & Bang, 2009; Dong, Dontcheva, Joseph,
Karahalios, Newman, & Ackerman, 2012; Li, Grossman, & Fitzmaurice, 2012). Users usually
also enjoy the task at hand more when it is gamified (Flatla, Gutwin, Nacke, Bateman, &
Mandryk, 2011). As stated in the literature review, the effectiveness of gamification is
dependent on the context, and e-commerce could be challenging.
Nevertheless, I speculate that lack of secondary effects in the current study might be due to
the fact that the gamification element was limited. Many services use multiple aspects, whilst
here only badges were used. Due to limitations of the survey software, the introduction of a
leader board, something that has been shown to be an excellent form of gamification and
would add an aspect of relatedness, which might make the consumer more intrinsically
motivated, was not feasible. Also, during the shopping process, there was no interaction
between the user and the system possible and therefore no personalization either.
As mentioned before, the amount of products with an A-score was disproportionally high, which
results in the fact that the goal to buy healthily is not that challenging. Next to that, since the
study was not longitudinal, the incentive of ‘shop three more times with us in a healthy way,
and the badge will be upgraded’ had no real outcome.
It is important to remember that even this limited amount of gamification had a positive effect
on the purchase of healthy products, therefore suggesting that an increase of the gamification
elements would result in an even greater effect.
The low NPS can be contributed to the primitiveness of the shop. Several respondents
separately indicated that the absence of an indication on how much they spent thus far was
an impediment. There was also no possibility to navigate through the products by a search
bar. Both are limitations of the software used. An unattractive website, as explained in the
literature review, gives a high possibility of consumers not returning to the shop, thus also not
recommending it to others and contributing to a low NPS.
In the literature review it was discussed how all age groups appreciate gamification equally,
only ease of use diminishes with age and effects tend to diminish quicker for younger users.
The latter could not be researched, since this was not a longitudinal study. A one-way ANOVA-
analysis was conducted to research whether the former can be confirmed with the data of this
study. Based on the literature, it is expected that all variables measured in the survey are equal
36
for all ages. However, it is important to note that these conclusions should be interpreted with
caution. Considering that only the treatment group can be used for this analysis, the three age
categories that were constructed are small and therefore not necessarily representative of the
population. The categories are shown in table 9.
Category N
Young (age ≤ 25) 48
Middle-age (25 < age < 60) 28
Old (age ≥ 60) 31
Table 9: Age categories
For the variable competence, there was a statistically significant difference between groups as
determined by one-way ANOVA (F(2) = 3.84, p = 0.025). A Tamhanes T2 (equal variances not
assumed, p = 0.026) post hoc-test revealed that the perceived competence of the old category
(4.63 ± 0.85) was statistically significantly lower than the young category (5.13 ± 0.65) (p =
0.021). There was no statistically significant difference between the young and middle-age (p
= 1.00) and middle-age and old (p = 0.168) categories. For all other variables, the null
hypothesis (the mean of all groups are equal) could not be rejected.
A possible explanation for the lower perceived competence could be that elderly people feel
more insecure about using a computer. However, the survey was completed by respondents
who have a computer at home and made the decision to participate without obligations, which
could indicate that all of them feel rather confident in using their computer, even for something
they never did before.
Other limitations of this study include the fact that respondent not really receive what they buy,
possibly leading to not choosing what they would really buy, or even consume. Additionally,
the survey was distributed in my personal network, thus implying that most people who filled
in the survey, have comparable feelings towards health and food consumption.
37
9. Suggestions for further research and implications
Going forward, further studies could prove quite beneficial to the literature. Future research
should continue to explore the effects of gamification on healthier consumption. First of all, the
gamification should be expanded to multiple elements throughout the shopping experience.
Next to badges, a leader board would be a great addition as it adds competition and a social
aspect. Other factors, such as one’s own avatar, could also be used for personalisation. Next
to that, there should be more interaction between the system and the user. The use of pop-
ups may be beneficial. For example, when choosing something healthy, the user could get a
pop-up to encourage him or her. This interplay would alert consumers during the entire
process. However, it is important that these pop-ups do not happen too often, since it could
make the shopping process cluttered. Another idea could be to work with a scale next to the
shopping basket, which indicates the healthiness of the current basket content and its effect
on the current level or place on the leader board.
In future work, investigating in a longitudinal way might prove important. That way consumers
can invest in a durable way in their health. Promises as ‘the badge will be upgraded when you
come back three more times and shop in a healthy way’ will become more realistic. It would
give insights in whether it motivates in the long-run, whether these are not mainly effects of
newness. Also, the shopping environment should be made more realistic. Both of these can
be achieved by collaborating with a real grocery store. Furthermore, working with a real shop
would eliminate the problem of a population consisting of only similar people and also gives a
realistic view of the distribution of A-labels in comparison to B- to E-labels. It further gives a
higher probability that consumers buy what they will really use, since they actually receive what
they choose and they pay real money for it.
In addition, investigating if gamification works for people that would benefit from it, might prove
an important area for future research. This means to research whether consumers that usually
buy unhealthily are reached with such measures. In this study we see a trend to buy healthier,
but we see that the control group also buys rather healthily. Therefore it could be interesting
to investigate whether consumers who usually buy unhealthily are (greatly) influenced by
gamification. In accordance with this, it can be examined whether consumers eat healthier
when they buy healthier and if it results in them being healthier. Additionally, it can be
researched if consumers are more motivated when they receive an ‘expert’ badge in
comparison with the ‘beginner’ badge. The latter could not be researched in this study, since
the consumer received his or her badge at the end without prior knowledge of which badge
they might earn.
38
Research discussed in section 1.3.1 showed that in loyalty programs, consumers buy more
when closer to their goal. Therefore, in the future it can be investigated whether consumers
are also incentivised to buy something extra, or things in bigger quantities, in order to reach a
certain badge or level, when that badge or level is not related to the amount bought.
Furthermore, research can clarify whether adding gamification to online grocery stores, makes
consumers like them more, which could result in more consumers using online grocery shops
instead of the brick-and-mortar versions.
In the future, scientists can also research the usability of hedonic and utilitarian motivations, in
order to influence consumers into buying healthier. In this master’s dissertation it was found
difficult to implement, since one person likes tomatoes, and would therefore buy it for hedonic
reasons, but not like carrots, and would therefore buy those for utilitarian reasons. And this
would also differ from one person to another.
An implication of this study is that consumers really tend to buy healthier. Therefore parties
that want to encourage their consumers, can implement gamification. The government can
also make use of gamification to make the public buy healthier.
The current study also indicated some downsides to the Nutri-score. This provides a good
starting point for discussion and further research. It can be an indication that there should be
an adaptation to this Nutri-score or that consumers should be better informed on what the label
indicates and certainly also on what it does not indicate.
39
10. Conclusion
In conclusion, this paper argued that adding gamification could make consumers buy more
healthily in an online grocery store. This proposition was based on a thorough literature review
on gamification, online (grocery) shopping, obesity and motivation. In this literature review we
learned that gamification is a growing trend among businesses. Adding gaming elements to
non-gaming environments motivates people within all demographic groups to reach certain
goals, when the gaming elements are added with consideration. The literature review also
discussed that online shopping is increasing in turnover every year and that there are multiple
possible advantages that can be attributed to online versus offline shops. Unfortunately, online
grocery shopping is lagging behind because consumers see it as an add-on rather than a
substitute. Additionally, ways in which consumers can be influenced in what they buy were
explored.
Next, the problem of obesity was analysed. An important risk factor for this, is the way the
population currently consumes food. Many initiatives have been taken to reduce obesity rates,
but none have proven to be the break-through. Nutrition labels as a possible solution, has been
discussed elaborately, including demurs regarding the relatively new Nutri-score label. The
“motivating consumers” section discussed four theories that explain how consumers are
motivated to buy certain products during grocery shopping.
After conducting an experiment, it proved to be true that consumers buy more healthily when
gamification elements, more specifically badges, are added. However, there was no proof
found of the secondary effects that are often attributed to gamification. For this there were
multiple possible explanations discussed.
The main limitations of this study were due to the software with which the shop was installed,
which could be solved by conducting this experiment in a real online grocery store, and the
time constraints.
ix
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Addendum 1: The calculation of the Nutri-score label (Julia, &
Hercberg, 2017)
xxi
Addendum 2: Survey
2.1 Introduction
Bedankt om deel te nemen aan dit experiment voor mijn masterproef. De enquête neemt een
kleine 15 minuten in beslag om volledig in te vullen.
Al uw antwoorden worden anoniem verwerkt.
Indien u de volledige enquête invult, kan u meedoen om een bon t.w.v. €20, voor een
grootwarenhuis naar keuze te winnen.
Bregje Liessens
Master student Business Economics: Marketing
2.2 Treatment
Op de volgende pagina betreedt u een online grootwarenhuis. Elk product is voorzien van een
nutri-score.
Een score A betekent dat het product erg goed scoort op de aan-/afwezigheid van
verschillende voedingsstoffen.
Daarnaast werkt het grootwarenhuis met een badgesysteem. In ruil voor het aankopen van
gezonde voeding (een score A of B), krijgt u een betere badge, dan als u hoofdzakelijk minder
gezonde voeding koopt.
Buiten specerijen heeft u niets meer in huis, dus u moet zich bevoorraden. Doe inkopen voor
1 persoon, voor 3 dagen, met een maximumbudget van €50. U mag zoveel of zo weinig
producten per categorie kiezen, als u zelf wilt. U koopt de hoeveelheid die bij het product
aangegeven staat.
In het kader van dit onderzoek is het belangrijk dat u het maximumbudget niet overschrijdt en
minimum 1 product koopt. Indien u dit niet doet, zal u opnieuw moeten beginnen.
xxii
Gefeliciteerd! Dankzij het kiezen voor onze winkel, hebt u uw eerste badge verdiend.
Shop nog 3 keer bij ons, op een gezonde manier, om deze badge te upgraden.
Drank
Fruitsap - € 3,60/liter Alcoholische dranken - € 8,65/liter Melk - € 0,99/liter
xxiii
Frisdrank - € 1,03/liter Water - € 0,60/liter Frisdrank light/zero - € 0,80/liter
Vlees
Kalkoen - € 1,59/200g Chipolata - € 1,60/200g Gehakt - € 1,48/200g Lamskoteletten - € 2,79/200g
Biefstuk - € 2,73/200g Kalfsburger - € 1,99/200g Varkensvlees - € 1,99/200g Kipfilet - € 1,36/200g
xxiv
Vis
Kabeljauw - € 3,63/200g Pangasiusfilet - € 1,99/200g Haring - € 2,18/200g
Zalm - € 5,39/200g Forel - € 2,68/200g
Veggie/vegan
Groentenburger - € 1,86/200g Quorn burger - € 3,65/200g Tofu - € 2,06/200g Notenburger - € 3,98/200g
xxv
Koolhydraten
Couscous - € 2,19/kg Kroketten - € 1,89/kg Aardappelen - € 1,19/kg
Frieten - € 0,88/kg Rijst - € 2,90/kg Pasta - € 3,50/kg
Bereide gerechten
Aardappelpuree - € 0,80/200g Lasagne - € 2,24/400g Soep - € 1,19/460ml
xxvi
Appelmoes - € 0,65/200g Bolognese saus - € 2,19/700g
Zuivelproducten
Eieren - € 1,79/6stk Kaas - € 2,98/200g Yoghurt - € 1,46/kg
Groenten
Sla - € 0,60/500g Tomaten - € 1,25/500g Brocolli - € 1,35/500g Bloemkool - € 0,98/500g
xxvii
Soepgroenten - € 2,69/kg Wortelen - € 0,43/500g Courgette - € 1,00/500g Paprika - € 1,13/500g
Diepvries maaltijden
Macaroni kaas - € 2,15/500g Kaaskroketten - € 1,20/6stk Pizza - € 2,43 Loempia - € 3,07/4stk
Broodbeleg
Ham - € 3,76/200g Chocoladepasta - € 1,48/200g Pindakaas - € 1,17/200g
xxviii
Salami - € 2,19/200g Confituur - € 1,10/200g
Ontbijtproducten
Koffiekoeken - € 1,38/6stk Brood - € 2,49/stk Toast - € 0,79/500g
Muesli - € 2,29/500g Havermout - € 0,87/500g Ontbijtgranen - € 3,55/500g
xxix
Desserts / tussendoortjes
Noten - € 1,99/200g Chips - € 0,54/200g Pudding - € 3,20/kg Koekjes - € 1,33/200g
Snoep - € 1,12/200g Fruit - € 1,00/500g Chocolade - € 0,87/200g Schepijs - € 1,89/liter
2.3 Control
Op de volgende pagina betreedt u een online grootwarenhuis. Elk product is voorzien van
een nutri-score.
Een score A betekent dat het product erg goed scoort op de aan-/afwezigheid van
verschillende voedingsstoffen.
xxx
Buiten specerijen heeft u niets meer in huis, dus u moet zich bevoorraden. Doe inkopen voor
1 persoon, voor 3 dagen, met een maximumbudget van €50. U mag zoveel of zo weinig
producten per categorie kiezen, als u zelf wilt. U koopt de hoeveelheid die bij het product
aangegeven staat.
In het kader van dit onderzoek is het belangrijk dat u het maximumbudget niet overschrijdt en
minimum 1 product koopt. Indien u dit niet doet, zal u opnieuw moeten beginnen.
Drank
Fruitsap - € 3,60/liter Alcoholische dranken - € 8,65/liter Melk - € 0,99/liter
Frisdrank - € 1,03/liter Water - € 0,60/liter Frisdrank light/zero - € 0,80/liter
xxxi
Vlees
Kalkoen - € 1,59/200g Chipolata - € 1,60/200g Gehakt - € 1,48/200g Lamskoteletten - € 2,79/200g
Biefstuk - € 2,73/200g Kalfsburger - € 1,99/200g Varkensvlees - € 1,99/200g Kipfilet - € 1,36/200g
Vis
Kabeljauw - € 3,63/200g Pangasiusfilet - € 1,99/200g Haring - € 2,18/200g
xxxii
Zalm - € 5,39/200g Forel - € 2,68/200g
Veggie/vegan
Groentenburger - € 1,86/200g Quorn burger - € 3,65/200g Tofu - € 2,06/200g Notenburger - € 3,98/200g
Koolhydraten
Couscous - € 2,19/kg Kroketten - € 1,89/kg Aardappelen - € 1,19/kg
xxxiii
Frieten - € 0,88/kg Rijst - € 2,90/kg Pasta - € 3,50/kg
Bereide gerechten
Aardappelpuree - € 0,80/200g Lasagne - € 2,24/400g Soep - € 1,19/460ml
Appelmoes - € 0,65/200g Bolognese saus - € 2,19/700g
xxxiv
Zuivelproducten
Eieren - € 1,79/6stk Kaas - € 2,98/200g Yoghurt - € 1,46/kg
Groenten
Sla - € 0,60/500g Tomaten - € 1,25/500g Brocolli - € 1,35/500g Bloemkool - € 0,98/500g
Soepgroenten - € 2,69/kg Wortelen - € 0,43/500g Courgette - € 1,00/500g Paprika - € 1,13/500g
xxxv
Diepvries maaltijden
Macaroni kaas - € 2,15/500g Kaaskroketten - € 1,20/6stk Pizza - € 2,43 Loempia - € 3,07/4stk
Broodbeleg
Ham - € 3,76/200g Chocoladepasta - € 1,48/200g Pindakaas - € 1,17/200g
Salami - € 2,19/200g Confituur - € 1,10/200g
xxxvi
Ontbijtproducten
Koffiekoeken - € 1,38/6stk Brood - € 2,49/stk Toast - € 0,79/500g
Muesli - € 2,29/500g Havermout - € 0,87/500g Ontbijtgranen - € 3,55/500g
Desserts / tussendoortjes
Noten - € 1,99/200g Chips - € 0,54/200g Pudding - € 3,20/kg Koekjes - € 1,33/200g
xxxvii
Snoep - € 1,12/200g Fruit - € 1,00/500g Chocolade - € 0,87/200g Schepijs - € 1,89/liter
Hartelijk dank om bij ons te winkelen!
Klik op het pijltje om verder te gaan.
2.4 Helaas (Did not read the instructions correctly)
Oeps, het lijkt erop dat u helemaal niks hebt gekocht. Begin opnieuw.
Oeps, u hebt het maximumbudget van €50 overschreden. Begin opnieuw.
2.5 Treatment Outcome Badges
Gefeliciteerd, dankzij de producten die u gekozen heeft, hebt u deze badge verdiend.
xxxviii
De producten die u kocht, hadden gemiddeld een A- of B-score. U bent erg gezond bezig, doe
zo verder!
Hartelijk dank om bij ons te winkelen! Klik op het pijltje om verder te gaan.
Gefeliciteerd, dankzij de producten die u gekozen hebt, hebt u deze badge verdiend.
xxxix
De producten die u kocht hadden gemiddeld een C-score. U bent op de goede weg! Hartelijk
dank om bij ons te winkelen!
Klik op het pijltje om verder te gaan.
Gefeliciteerd, dankzij de producten die u gekozen hebt, hebt u deze badge verdient.
xl
De producten die u kocht hadden gemiddeld een D- of E-score. Wist u dat we ook gezondere
alternatieven in ons assortiment hebben? U kan ze herkennen aan de A- of B-score.
Hartelijk dank om bij ons te winkelen! Klik op het pijltje om verder te gaan.
2.6 General questions
Hoe waarschijnlijk is het dat u deze online shop (moest hij echt bestaan), aan een vriend of
collega zou aanraden?
Helemaal niet waarschijnlijk Heel waarschijnlijk
0 1 2 3 4 5 6 7 8 9 10
Duid aan wat het beste bij u past. Alle uitspraken hebben betrekking tot het online shoppen
waar u zojuist aan deelnam.
xli
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Terwijl ik deze activiteit aan het doen
was, dacht ik hoeveel ik er van genoot.
Ik vond deze activiteit vrij aangenaam.
Ik zou deze activiteit als ‘erg interessant’
beschrijven.
Ik vond dit een saaie activiteit.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik genoot heel erg van deze activiteit.
Deze activiteit hield mijn aandacht
helemaal niet.
Deze activiteit was leuk om te doen.
Duid aan wat het beste bij u past. Alle uitspraken hebben betrekking tot het online shoppen
waar u zojuist aan deelnam.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Om eerlijk te zijn, kan het me niet
schelen of ik al dan niet gezond koop.
Het zou niet veel vergen om me ‘gezonde
voeding kopen’ te laten opgeven.
Duid het middelste bolletje aan.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Het is moeilijk om ‘gezond te kopen’
serieus te nemen.
xlii
Ik denk dat ‘het kopen van gezonde
voeding’ een goed doel is om naar te
streven
Ik ben erg toegewijd aan het kopen van
gezonde voeding.
Duid aan wat het beste bij u past. Alle uitspraken hebben betrekking tot het online shoppen
waar u zojuist aan deelnaam.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik was bekwaam in deze activiteit.
Ik denk dat ik in vergelijking met anderen,
deze activiteit goed heb gedaan.
Na enige tijd met deze activiteit bezig te
zijn, voelde ik me bekwaam.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik ben tevreden van mijn prestaties bij
deze activiteit.
Ik denk dat ik deze activiteit goed kan.
Deze activiteit kon ik niet goed.
Duid aan wat het beste bij u past. Alle uitspraken hebben betrekking tot het online shoppen
waar u zojuist aan deelnam.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik geloof dat ik enige keuze had over
deze activiteit.
Ik had het gevoel dat ik dit moest doen.
Ik heb deze activiteit gedaan omdat ik dit
moest.
xliii
Ik had het gevoel dat het niet mijn eigen
keuze was om deze taak te doen.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik heb deze activiteit gedaan omdat ik dat
wou.
Ik heb deze activiteit gedaan omdat ik
geen keuze had.
Ik had niet echt een keuze over deze
activiteit.
Duid aan wat het beste bij u past. Alle uitspraken hebben betrekking tot het online shoppen
waar u zojuist aan deelnam.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik was verdiept in mijn winkelervaring.
Ik verloor mezelf in deze winkelervaring.
Deze online winkel is aantrekkelijk.
Ik vond de online winkel verwarrend om
te gebruiken.
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Mijn winkelervaring was lonend.
De tijd die ik aan het winkelen
spendeerde, gleed weg.
Winkelen op deze website was de moeite
waard.
Deze online winkel sprak mijn zintuigen
aan.
xliv
Helemaal
niet
akkoord
Niet
akkoord
Eerder
niet
akkoord
Noch
akkoord,
noch niet
akkoord
Eerder
akkoord Akkoord
Helemaal
akkoord
Ik voelde me geïnteresseerd in mijn
winkeltaak.
Het gebruik van deze online winkel was
lastig.
Ik voelde me gefrustreerd tijdens het
winkelen.
Deze online winkel was esthetisch
aangenaam.
Om af te sluiten, vraag ik u nog deze algemene vragen in te vullen.
Wat is uw geslacht?
Vrouw
Man
Ander
Wat is uw geboortejaar (YYYY)?
Wat is uw hoogst behaalde diploma?
Basisonderwijs
Secundair onderwijs
Bachelor diploma
Master diploma
Doctoraat
Wat is uw dagelijkse bezigheid?
Student
Gepensioneerde
Bediende/arbeider/zelfstandige
xlv
Werkloos
Ander
Wat is uw dieet?
Gevarieerd
Vegetarisch
Veganistisch
Ander
Hartelijk dank voor uw deelname. U bracht mij een stap dichter bij mijn diploma :-) U kan de
enquête afronden door op het pijltje te klikken.
Indien u kans wil maken op een bon t.w.v. €20 voor een grootwarenhuis naar keuze, vul dan
de volgende schiftingsvraag in: Hoeveel personen zullen deze enquête invullen voor 14 april
2019?
Vul hier uw e-mailadres in, zodat ik u kan contacteren als u gewonnen hebt. Dit wordt op geen
enkele manier gelinkt aan uw antwoorden gegeven in de enquête.
xlvi
Addendum 3: SPSS output
3.1 Frequencies
Condition
Frequency Percent Valid Percent
Cumulative
Percent
Valid Treatment 107 51,7 51,7 51,7
Control 100 48,3 48,3 100,0
Total 207 100,0 100,0
Statistics
age
N Valid 207
Missing 0
Mean 41,1594
Std. Deviation 20,02398
Variance 400,960
Minimum 16,00
Maximum 82,00
Wat is uw geslacht?
Frequency Percent Valid Percent
Cumulative
Percent
Valid Man 76 36,7 36,7 36,7
Vrouw 130 62,8 62,8 99,5
Ander 1 ,5 ,5 100,0
Total 207 100,0 100,0
Wat is uw hoogste behaalde diploma?
Frequency Percent Valid Percent
Cumulative
Percent
Valid Basisonderwijs 3 1,4 1,4 1,4
Secundair onderwijs 48 23,2 23,2 24,6
Bachelor diploma 88 42,5 42,5 67,1
Master diploma 65 31,4 31,4 98,6
Doctoraat 3 1,4 1,4 100,0
Total 207 100,0 100,0
xlvii
Wat is uw dagelijkse bezigheid?
Frequency Percent Valid Percent
Cumulative
Percent
Valid Student 81 39,1 39,1 39,1
Bediende/arbeider/zelfstandig
e
76 36,7 36,7 75,8
Gepensioneerd 44 21,3 21,3 97,1
Ander 6 2,9 2,9 100,0
Total 207 100,0 100,0
Wat is uw dieet?
Frequency Percent Valid Percent
Cumulative
Percent
Valid Gevarieerd 182 87,9 87,9 87,9
Vegetarisch 11 5,3 5,3 93,2
Ander 14 6,8 6,8 100,0
Total 207 100,0 100,0
3.2 Internal consistency tests
3.2.1 Enjoyment
Case Processing Summary
N %
Cases Valid 207 100,0
Excludeda 0 ,0
Total 207 100,0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha N of Items
,913 7
xlviii
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total
Correlation
Cronbach's
Alpha if Item
Deleted
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik genoot
heel erg van deze activiteit.
27,04 49,901 ,836 ,888
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Deze
activiteit was leuk om te doen.
26,42 51,370 ,835 ,890
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik vond dit
een saaie activiteit.
26,25 52,034 ,754 ,897
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Deze
activiteit hield mijn aandacht
helemaal niet.
26,19 56,030 ,522 ,921
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik zou deze
activiteit als 'erg interessant'
beschrijven.
27,12 50,990 ,757 ,897
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik vond deze
activiteit vrij aangenaam.
26,48 50,785 ,854 ,887
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Terwijl ik
deze activiteit aan het doen was,
dacht ik hoeveel ik er van genoot.
27,89 52,332 ,622 ,913
xlix
3.2.2 Goal commitment
Case Processing Summary
N %
Cases Valid 207 100,0
Excludeda 0 ,0
Total 207 100,0
a. Listwise deletion based on all variables in the
procedure.
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total
Correlation
Cronbach's
Alpha if Item
Deleted
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Het is
moeilijk om 'gezond te kopen' serieus te
nemen.
21,39 15,481 ,455 ,719
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik denk
dat 'het kopen van gezonde voeding' een goed
doel is om naar te streven.
20,53 17,736 ,470 ,720
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Het zou
niet veel vergen om me 'gezonde voeding
kopen' te laten opgeven.
21,76 14,883 ,403 ,750
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik ben
erg toegewijd aan het kopen van gezonde
voeding.
21,57 14,082 ,640 ,648
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Om
eerlijk te zijn, kan het me niet schelen of ik al
dan niet gezond koop.
20,83 14,038 ,634 ,650
Reliability Statistics
Cronbach's Alpha N of Items
,744 5
l
3.2.3 Competence
Case Processing Summary
N %
Cases Valid 207 100,0
Excludeda 0 ,0
Total 207 100,0
a. Listwise deletion based on all variables in the
procedure.
Item-Total Statistics
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik denk dat
ik deze activiteit goed kan.
24,62 17,149 ,788 ,806
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik denk dat
ik in vergelijking met anderen,
deze activiteit goed heb gedaan.
25,20 19,480 ,558 ,848
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Na enige
tijd met deze activiteit bezig te
zijn, voelde ik me bekwaam.
25,03 18,562 ,548 ,852
Reliability Statistics
Cronbach's Alpha N of Items
,857 6
li
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik ben
tevreden van mijn prestaties bij
deze activiteit.
24,57 18,780 ,642 ,834
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Ik was
bekwaam in deze activiteit.
24,64 17,134 ,757 ,811
Duid aan wat het beste bij u past.
Alle uitspraken hebben betrekking
tot het online shoppen waar u
zojuist aan deelnam. - Deze
activiteit kon ik niet goed.
24,34 18,188 ,598 ,842
3.2.4 Perceived autonomy
Case Processing Summary
N %
Cases Valid 207 100,0
Excludeda 0 ,0
Total 207 100,0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha N of Items
,856 7
lii
Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if Item
Deleted
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik geloof dat ik enige keuze had over deze
activiteit.
31,39 36,102 ,602 ,839
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik had het gevoel dat het niet mijn eigen keuze
was om deze taak te doen.
31,47 33,095 ,668 ,829
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik had niet echt een keuze over deze activiteit.
31,46 33,026 ,688 ,826
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik had het gevoel dat ik dit moest doen.
31,91 33,977 ,538 ,851
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik heb deze activiteit gedaan omdat ik geen
keuze had.
31,16 34,591 ,652 ,832
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik heb deze activiteit gedaan omdat ik dat
wou.
31,21 35,896 ,625 ,836
liii
Duid aan wat het beste bij u past. Alle uitspraken hebben
betrekking tot het online shoppen waar u zojuist aan
deelnam. - Ik heb deze activiteit gedaan omdat ik dit
moest.
31,43 34,373 ,601 ,839
3.2.5 Engagement
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Cronbach's
Alpha if Item
Deleted
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik
verloor mezelf in deze winkelervaring.
50,25 116,322 ,263 ,893
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - De
tijd dat ik aan het winkelen spendeerde,
gleed weg.
49,08 111,755 ,385 ,888
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik
was verdiept in mijn winkelervaring.
48,75 102,898 ,675 ,872
Case Processing Summary
N %
Cases Valid 207 100,0
Excludeda 0 ,0
Total 207 100,0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha N of Items
,886 12
liv
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik
voelde me gefrustreerd tijdens het
winkelen.
47,68 111,686 ,421 ,886
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik
vond de online winkel verwarrend om te
gebruiken.
47,78 107,986 ,511 ,882
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Het
gebruik van deze online winkel was lastig.
47,73 109,021 ,496 ,882
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. -
Deze online winkel is aantrekkelijk.
48,90 99,451 ,783 ,865
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. -
Deze online winkel was esthetisch
aangenaam.
48,78 103,210 ,675 ,872
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. -
Deze online winkel sprak mijn zintuigen
aan.
49,02 103,839 ,651 ,873
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. -
Winkelen op deze website was de moeite
waard.
48,74 102,211 ,772 ,867
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. -
Mijn winkelervaring was lonend.
48,65 105,618 ,687 ,872
lv
Duid aan wat het beste bij u past. Alle
uitspraken hebben betrekking tot het online
shoppen waar u zojuist aan deelnam. - Ik
voelde me geïnteresseerd in mijn
winkeltaak.
48,38 101,285 ,737 ,868
lvi
3.3 Independent samples t-tests hypotheses
Group Statistics Condition N Mean Std. Deviation Std. Error Mean
avgpoints Treatment 107 4,2995 ,38087 ,03682
Control 100 4,1858 ,36397 ,03640
Hoe waarschijnlijk is het dat u
deze online shop (moest hij
echt bestaan), aan een vriend
of collega zou aanraden?
Treatment 107 5,75 2,492 ,241
Control 100 5,23 2,616 ,262
Enjoyment Treatment 107 4,5674 1,17073 ,11318
Control 100 4,3486 1,21054 ,12105
Goalcomm Treatment 107 5,3402 ,89114 ,08615
Control 100 5,2640 1,00499 ,10050
Competence Treatment 107 4,9860 ,87329 ,08442
Control 100 4,9050 ,80864 ,08086
Autonomy Treatment 107 5,3298 ,87787 ,08487
Control 100 5,1414 1,04890 ,10489
Engagement Treatment 107 4,4961 ,90425 ,08742
Control 100 4,3433 ,95979 ,09598
lvii
Independent Samples Test
Levene's Test for
Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of the Difference
Lower Upper
avgpoints Equal variances
assumed
,410 ,523 2,194 205 ,029 ,11374 ,05185 ,01151 ,21598
Equal variances
not assumed
2,197 204,895 ,029 ,11374 ,05177 ,01167 ,21582
Hoe waarschijnlijk is
het dat u deze online
shop (moest hij echt
bestaan), aan een
vriend of collega zou
aanraden?
Equal variances
assumed
,492 ,484 1,458 205 ,146 ,518 ,355 -,182 1,218
Equal variances
not assumed
1,456 202,249 ,147 ,518 ,356 -,184 1,219
Enjoyment Equal variances
assumed
1,338 ,249 1,322 205 ,188 ,21885 ,16553 -,10751 ,54522
Equal variances
not assumed
1,321 202,915 ,188 ,21885 ,16572 -,10790 ,54561
lviii
Goalcomm Equal variances
assumed
,517 ,473 ,578 205 ,564 ,07619 ,13183 -,18373 ,33611
Equal variances
not assumed
,576 198,066 ,566 ,07619 ,13237 -,18485 ,33722
Competence Equal variances
assumed
1,963 ,163 ,691 205 ,490 ,08098 ,11721 -,15011 ,31207
Equal variances
not assumed
,693 204,984 ,489 ,08098 ,11690 -,14951 ,31147
Autonomy Equal variances
assumed
3,718 ,055 1,404 205 ,162 ,18834 ,13412 -,07608 ,45277
Equal variances
not assumed
1,396 193,570 ,164 ,18834 ,13492 -,07776 ,45445
Engagement Equal variances
assumed
,246 ,621 1,179 205 ,240 ,15277 ,12956 -,10267 ,40821
Equal variances
not assumed
1,177 201,726 ,241 ,15277 ,12982 -,10321 ,40875
lix
3.4 Tests of Normality
Tests of Normality
Condition
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
avgpoints Treatment ,081 107 ,083 ,978 107 ,078
Control ,103 100 ,011 ,987 100 ,406
Hoe waarschijnlijk is het dat u
deze online shop (moest hij
echt bestaan), aan een vriend
of collega zou aanraden?
Treatment ,169 107 ,000 ,921 107 ,000
Control ,166 100 ,000 ,938 100 ,000
Enjoyment Treatment ,106 107 ,005 ,970 107 ,015
Control ,105 100 ,009 ,976 100 ,067
Goalcomm Treatment ,129 107 ,000 ,968 107 ,012
Control ,115 100 ,002 ,962 100 ,006
Competence Treatment ,087 107 ,047 ,975 107 ,040
Control ,118 100 ,002 ,959 100 ,003
Autonomy Treatment ,064 107 ,200* ,983 107 ,185
Control ,113 100 ,003 ,970 100 ,022
Engagement Treatment ,086 107 ,049 ,977 107 ,064
Control ,101 100 ,013 ,956 100 ,002
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
lx
3.5 Mann-Whitney tests
Test Statisticsa
avgpoints
Hoe waarschijnlijk is
het dat u deze
online shop (moest
hij echt bestaan),
aan een vriend of
collega zou
aanraden? Enjoyment Goalcomm Competence Autonomy Engagement
Mann-Whitney U 4339,000 4701,500 4816,500 5149,500 4975,000 4945,000 4958,500
Wilcoxon W 9389,000 9751,500 9866,500 10199,500 10025,000 9995,000 10008,500
Z -2,348 -1,520 -1,240 -,467 -,873 -,942 -,910
Asymp. Sig. (2-tailed) ,019 ,129 ,215 ,641 ,383 ,346 ,363
a. Grouping Variable: Condition
lxi
3.6 Additional independent samples t-tests
3.6.1 Low versus high education
education
Condition Frequency Percent Valid Percent
Cumulative
Percent
Treatment Valid low educated 27 25,2 25,2 25,2
high educated 80 74,8 74,8 100,0
Total 107 100,0 100,0
Control Valid low educated 24 24,0 24,0 24,0
high educated 76 76,0 76,0 100,0
Total 100 100,0 100,0
Group Statistics education N Mean Std. Deviation Std. Error Mean
avgpoints low educated 51 4,1842 ,37008 ,05182
high educated 156 4,2643 ,37730 ,03021
lxii
Independent Samples Test
Levene's Test for
Equality of Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of the
Difference
Lower Upper
avgpoints Equal variances
assumed
,369 ,544 -1,322 205 ,188 -,08008 ,06058 -,19952 ,03935
Equal variances
not assumed
-1,335 86,531 ,185 -,08008 ,05998 -,19932 ,03915
lxiii
3.7 One-way ANOVA
Descriptives
N Mean Std. Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
avgpoints young 48 4,2236 ,35499 ,05124 4,1206 4,3267 3,46 5,00
middle-age 28 4,3314 ,37685 ,07122 4,1853 4,4776 3,33 5,00
old 31 4,3882 ,41112 ,07384 4,2374 4,5390 3,25 5,00
Total 107 4,2995 ,38087 ,03682 4,2265 4,3725 3,25 5,00
Enjoyment young 48 4,6429 ,81561 ,11772 4,4060 4,8797 2,57 6,43
middle-age 28 4,2194 1,53787 ,29063 3,6231 4,8157 1,00 6,57
old 31 4,7650 1,22865 ,22067 4,3143 5,2157 1,71 7,00
Total 107 4,5674 1,17073 ,11318 4,3430 4,7918 1,00 7,00
Goalcomm young 48 5,2458 ,83767 ,12091 5,0026 5,4891 3,40 6,80
middle-age 28 5,5571 ,96049 ,18152 5,1847 5,9296 3,00 6,80
old 31 5,2903 ,90309 ,16220 4,9591 5,6216 2,40 7,00
Total 107 5,3402 ,89114 ,08615 5,1694 5,5110 2,40 7,00
Competence young 48 5,1319 ,65320 ,09428 4,9423 5,3216 3,83 6,50
middle-age 28 5,1310 1,11698 ,21109 4,6978 5,5641 2,00 6,83
old 31 4,6290 ,84734 ,15219 4,3182 4,9398 3,17 6,33
Total 107 4,9860 ,87329 ,08442 4,8186 5,1534 2,00 6,83
Autonomy young 48 5,2024 ,70838 ,10225 4,9967 5,4081 3,71 6,71
middle-age 28 5,4694 1,05828 ,20000 5,0590 5,8797 3,00 7,00
old 31 5,4009 ,93781 ,16844 5,0569 5,7449 3,71 7,00
Total 107 5,3298 ,87787 ,08487 5,1615 5,4980 3,00 7,00
Engagement young 48 4,5729 ,71368 ,10301 4,3657 4,7801 3,08 6,58
lxiv
middle-age 28 4,2649 1,10183 ,20823 3,8376 4,6921 1,33 5,75
old 31 4,5860 ,96477 ,17328 4,2321 4,9399 2,25 7,00
Total 107 4,4961 ,90425 ,08742 4,3228 4,6694 1,33 7,00
Test of Homogeneity of Variances
Levene Statistic df1 df2 Sig.
avgpoints ,091 2 104 ,913
Enjoyment 6,094 2 104 ,003
Goalcomm ,052 2 104 ,949
Competence 3,771 2 104 ,026
Autonomy 2,897 2 104 ,060
Engagement 2,176 2 104 ,119
ANOVA
Sum of Squares df Mean Square F Sig.
avgpoints Between Groups ,549 2 ,274 1,924 ,151
Within Groups 14,828 104 ,143
Total 15,377 106
Enjoyment Between Groups 4,875 2 2,437 1,805 ,170
Within Groups 140,409 104 1,350
Total 145,284 106
Goalcomm Between Groups 1,822 2 ,911 1,151 ,320
Within Groups 82,355 104 ,792
Total 84,177 106
Competence Between Groups 5,561 2 2,780 3,841 ,025
Within Groups 75,279 104 ,724
lxv
Total 80,840 106
Autonomy Between Groups 1,482 2 ,741 ,961 ,386
Within Groups 80,209 104 ,771
Total 81,690 106
Engagement Between Groups 2,031 2 1,015 1,248 ,291
Within Groups 84,641 104 ,814
Total 86,672 106
Multiple Comparisons
Dependent Variable: Competence
(I) agecategory (J) agecategory
Mean Difference
(I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
Bonferroni young middle-age ,00099 ,20231 1,000 -,4913 ,4933
old ,50291* ,19603 ,035 ,0259 ,9799
middle-age young -,00099 ,20231 1,000 -,4933 ,4913
old ,50192 ,22181 ,077 -,0378 1,0417
old young -,50291* ,19603 ,035 -,9799 -,0259
middle-age -,50192 ,22181 ,077 -1,0417 ,0378
Tamhane young middle-age ,00099 ,23119 1,000 -,5764 ,5784
old ,50291* ,17902 ,021 ,0614 ,9444
middle-age young -,00099 ,23119 1,000 -,5784 ,5764
old ,50192 ,26023 ,168 -,1409 1,1447
old young -,50291* ,17902 ,021 -,9444 -,0614
middle-age -,50192 ,26023 ,168 -1,1447 ,1409
*. The mean difference is significant at the 0.05 level.
