how does intrinsic motivation moderate the effect of...
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How Does Intrinsic Motivation Moderate The Effect of Gamification on
The Sustained Use of Wearable Fitness Technology?
A Quantitative Study
-MASTER THESIS-
Jonas Kose
931015
Rasmus Eriksson
920110
Antonio Tacke
911208
Supervisor: Urban Ljungquvist
Examinator: Prof. Anders Pehrsson
Date: 25th May 2017
Course: 4FE15E-Business
Administration with Specialization in Marketing, Degree Project
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I Abstract
Purpose: The purpose of this study is to adress the influence of individual’s intrinsic motivation on
the impact of gamification on the sustained use of WFT.
Hypotheses:
H1: The higher the intrinsic motivation is, the lower is the impact of gamification aspects on
attitudes, motivation and hence sustained use of WFT.
Theories: The Influence of Attitudes and Motivation on Sustained WFT Use, Intrinsic Motivation,
Gamification, Gamification & WFT.
Methodology: Deductive, Quantitative & Correlational-Sectional Survey Research.
Findings: The results pointed out that intrinsic motivation negatively moderates the effect of
gamification aspects on attitudes, motivation and finally the sustained use of WFT devices. Hence,
the effect of gamification becomes lower as intrinsic motivation increases. Therefore, it can be
concluded that gamification aspects can be seen as useful method to prevent attrition of WFT
devices and facilitate sustained use for individuals that have a low intrinsic motivation to engage in
sports or physical activity. In order to prevent attrition and further a sustained usage of WFT for
high intrinsic motivation individuals, the use of gamification is not an effective way.
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II Table of Content
1. Introduction 5
1.1 Background 5
1.2 Problem Discussion 6
1.3 Purpose 8
2. Literature Review 9
2.1 The Influence of Attitude and Motivation on Sustained WFT Use 9
2.2 The Tri-Component Attitude Model 10
2.2.1 Affect 10
2.2.2 Cognition 10
2.2.3. Conation 11
2.3 Intrinsic Motivation 11
2.4 Gamification 12
2.5 Gamification in WFT 13
3. Conceptual Framework 15
4. Methodology 18
4.1 Research Approach, Research Design & Data Source 18
4.2 Data Gathering 19
4.3 Sampling 19
4.3.1 Sampling Method 19
4.3.2 Sample Size 19
4.4 Data Collection Method 20
4.4.1 Questionnaire Design 20
4.4.2 Operationalisation21 4.4.3 Pre-test 24 4.4.4 Data Gathering Process 24 4.5 Data Analysis Method 24
4.5.1 Linear Regression Analysis 24
4.6 Data Coding 26
4.7 Quality Criteria 26
5. Results 28
5.1 Descriptives 28
5.1.1 Demographics 28
5.1.2 Intrinsic Motivation 29
5.2 Hypothesis Testing 31
5.2.1 Simple Linear Regression Analysis 31
5.2.2 Multiple Linear Regression Analysis 33
5.3 Validity 36
5.3.1 Intrinsic Motivation 36
5.3.2 Attitude 37
5.4 Reliability 37
5.4.1 Intrinsic Motivation 38
5.4.2 Attitude 38
6. Discussion 39
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7. Conclusion 42
8. Implications, Limitations, & Future Research 43 8.1 Theoretical Implications 43 8.2 Managerial Implications 44 8.3 Limitations 45
8.4 Future Research 45
III References 47
IV Appendix 56
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1. Introduction
This introductory chapter briefly outlines the topic of wearable fitness technology (WFT) and the
Internet of Things (IoT). Further, the problem of attrition and the concept of gamification to further
sustained use are discussed, leading to the problem formulation and the statement of purpose.
1.1 Background
Wearable health and fitness technology (WFT) has been defined as lightweight devices that
transmit information about a variety of internal (e.g. heart rate) and external variables (e.g. running
distance). These devices can be worn either close to skin or directly on the skin (Düking et al.,
2016). Past year (2016), wearable technology in general was a $6-billion industry and is projected
to grow to a $25-billion industry by the year of 2019 (Halson et al., 2016). It has been argued that
the greatest advantages of using wearable technology lies within the healthcare and fitness sector
(Chan et al., 2012). Gao et al. (2015) have argued that in general there are two different types of
wearables within the field of healthcare, namely medical wearable devices and fitness wearable
devices. While the former refers to devices used to manage serious diseases, such as diabetes, the
latter refers to devices monitoring individuals’ daily activity in terms of steps taken, calories, sleep
etc. (Gao et al., 2015). Recently, WFT devices have reached a high popularity due to their ability to
constantly monitor and analyse an individual's health condition (Spil et al., 2017; Asimakopoulos et
al., 2017).
Moreover, it was found that WFT accounted for a majority (61%) of the wearable technology
market in 2014 (ABI Research, 2013). Zhou and Piramuthu (2014) have argued that the new
generation of WFT recently launched to the market is different from those of the past since these
devices are continuously connected to the internet and can communicate as well as synchronise with
other device. As such, these devices facilitate a digitalisation of everyday activities. This
phenomenon is referred to as the Internet of Things (IoT), which in detail has been defined as the
interconnectivity of electronic devices, allowing a digitalisation of everyday “things” (Ray, 2014;
Zhou & Piramuthu, 2014).
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Already in 2010, it has been mentioned that smartphones as well as wearable technologies are the
main drivers of the quick development of the IoT. Further, it has been estimated that there will be
around 16 billion interconnected devices by 2020 (Sundmaeker et al., 2010). Vermesan et al. (2017)
argue that the interaction between the real and the digital world is enabled by sensors and actuators
integrated into several devices used for everyday activities. This can be connected to the earlier
research of Zhou and Piramuthu (2014) who support that WFT devices are part of the IoT since
they are continuously interconnected.
1.2 Problem Discussion
Recent statistics have highlighted that even though WFTs have reached a new level of popularity,
there is a significant attrition problem which means that users quit using their devices relatively
quick (Fritz et al., 2014; Shih et al., 2015; Coorevits & Coenen, 2016; Ledger & McCaffrey, 2016;
Xu & Wang, 2016). While Shih et al. (2015) found that 75% of WFT users quit using their devices
after 1 month only, Xu & Wang (2016) argue that approximately one third of all users quit using
their WTFs within six months. Also, Ledger and McCaffrey (2016), who analysed data for
Endeavour Partners, support that there is a problem of attrition even though that their findings
indicate that the majority of users completely quit using their devices after 18 months. Spil et al. (2017) have argued that the wide range of wearables and their multitude of functions/
designs raise confusion among consumers with regards to their wants. Canhoto and Arp (2017)
claim that there is a theoretical relevance for marketing research, and in detail to the field of
consumer behaviour, to highlight how a continuous and sustained use of WFTs can be ensured.
While Coorevits and Coenen (2016) argue that users need more triggers and reminders to prevent
wearable attrition, other studies on WFT have addressed both the adoption process and the attrition
problem by investigating how attitudes and the motivation or behavioural intention to continuously
use such a technology are related (Zaremohzzabieh et al., 2015; Lunney et al., 2016,
Asimakopoulos et al., 2017). The results suggested that if a positive attitude towards WFTs is
maintained among users of such technologies, motivation is also sustained as well as a sustained
usage is more likely to occur (Lunney et al., 2016; Asimakopoulos et al., 2017).
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These results point out that attitude has an impact on motivation, which was earlier suggested by
several studies stating that attitude and motivation are strongly related and interdependent (Peak &
Jones, 1955; Beebe et al., 1999; Bakar et al., 2010). Moreover, social aspects in form of subjective norms, social support, social comparison have been
found to be positively related to motivation and therefore sustained usage of WFT (Chang et al.,
2016; Coorevits & Coenen, 2016; Lunney et al., 2016). One way to trigger motivation and hence
also sustained WFT usage, is through elements of gamification, which is defined as the application
of engaging and enjoyable mechanisms of games within a non-game setting (e.g. real world
scenarios) to create motivation and engagement for individuals. As such gamification principles can
have an engaging, rewarding as well as motivating function for individuals (Lister et al., 2014;
Miller et al., 2014; Alturki & Gay, 2016; Schwartz et al., 2016; Zhao et al., 2016). Similarly,
Lunney et al. (2016) mention that motivation can be activated by the perceived social pressure
involved with the gamified setting. These findings are consistent with the very recent study by
Asimakopoulos et al. (2017), arguing that the motivation of WFT users can be influenced by the
implementation of gamification, which they point out as a heuristic to maintain user motivation and
hence a sustained use of the devices. On the contrary, Vaughan (2016) found that gamification does
not contribute to the market success of wearable technology which shows that there is a degree of
discordance within this area of research.
Sultan (2015) as well as Lunney et al. (2016) have argued that research within the field of wearable
technology is still in its initial phases. Moreover, a considerable amount of research within the field
of wearable technology has been attributed to the establishment of accuracy and reliability of WFT
devices (Mahar et al., 2014; Takacs et al., 2014; Diaz et al., 2015; El-Amrawy, Pharm & Nounou,
2015; Huang et., 2016; Leininger et al., 2016; Pobiruchin et al., 2016) while, as Robson et al.
(2015) have argued, past research on the understanding of gamification as well as the mental
motivations changing individuals’ behaviours and habits has been rather scarce. This goes in line
with the statements of Spil et al. (2017) who suggest that there is a lack of knowledge on how to
integrate gamification as well as its effects on the industry of wearable technology. Further,
Asimakopoulos et al. (2017) suggest that future research on post-adoption behaviour is necessary in
order to comprehend how WFT user motivation can be successfully influenced in order to ensure a
sustained use of the devices.
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Also, it has been argued for more research on the effectiveness of gamification aspects when it
comes to the augmentation of long-term WFT user motivation (Asimakopoulos et al., 2017). As
Chang et al. (2016) have argued, enhancement of motivation is an essential element in order to
overcome the attrition issue. Canhoto and Arp (2017) even state that the usage of WFT devices is
depending on the personal goals of the user.
As it has been pointed out vide supra, there is need for a better understanding of the mental
motivations changing the behaviours and habits of individuals in the context of gamification
(Robson et al., 2015). When it comes to a successful and positive sporting experience, intrinsic
motivation1 has been identified as the most influential mental motivation (Duda, 2007; Vallerand,
2007). It has been commonly found that athletes with a high intrinsic motivation are more likely to
continue in their sporting experience because they perform an activity as a result of pleasure and
satisfaction (Sarrazin et al., 2002; Ntoumanis, 2005; Vallerand, 2007). Yet, it appears that none of
the recent studies that addressed the use of gamification aspects in a WFT context has paid attention
to the users’ intrinsic motivation to engage in sports or physical activity, even though that intrinsic
motivation has an essential impact on a positive sporting experience.
1.3 Purpose
The purpose of this study is to adress the influence of individual’s intrinsic motivation on the
impact of gamification on the sustained use of WFT.
1 Intrinsic motivation is described as a type of motivation which comes from the individual’s inner reason (e.g.
interest) (Ryan & Deci, 2000).
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2. Literature Review
The following chapter provides a review of prior research conducted within the area of attitudes,
motivation and sustained WFT use, the Tri-Component Attitude Model, intrinsic motivation,
gamification as well as gamification in the context of WFT.
2.1 The Influence of Attitude and Motivation on Sustained WFT Use
According to Peak and Jones (1995) attitude and motivation are two interdependent concepts, which
goes in line with the findings of Wang (2017). It means that these two concepts are firmly
correlated with each other. This is further consistent with Beebe et al. (1999) arguing that attitudes
are psychological compositions that build up motivation to perform a certain behaviour. Also,
Westen (1999) has stated that behaviour is considerably impacted by attitude as well as motivation.
Bakar et al. (2010) conducted a study investigating the relationship between achievement
motivation and attitude of students. The results support the interdependence of attitude and
motivation as a significant correlation was found (Bakar et al., 2010).
All these results highlight that there is a positive relationship between attitude and motivation (Peak
& Jones, 1955; Beebe et al., 1999; Bakar et al., 2010). Also, within the WFT literature results have
shown that there exists an interdependence between attitude and motivation. Several prior studies
on WFT have investigated how attitudes, motivation, and the behavioural intention to use such a
technology are related (Zaremohzzabieh et al., 2015; Lunney et al., 2016, Asimakopoulos et al.,
2017).
It has been commonly found that a positive attitude as well as motivation positively influence the
likelihood of sustained use of a WFT device (Fritz et al., 2014; Chang et al., 2016; Coorevits &
Coenen, 2016; Lunney et al., 2016; Asimakopoulos et al., 2017). The results of Asimakopoulos et
al. (2017), who researched how self-efficacy, motivation, and health technology factors impact
individuals’ attitudes towards WFT, supported this argumentation.
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Based on the results stated above it has been argued that attitudes towards WFT devices have a
positive impact on repeated and/or sustained use of WFT as well as they influence how engaging
the use of the WFT device feels for users. Simultaneously, it was pointed out that high motivation
has a positive influence on sustained use. This can be connected to Coorevits and Coenen (2016)
arguing that motivation created on the basis of social comparison can further the sustained use of a
WFT device. Also, Fritz et al. (2014) as well as more recently Chang et al. (2016) have argued that
increased motivation prevents attrition of the WFT since users have a higher willingness to achieve
their physical activity goals.
2.2 The Tri-Component Attitude Model
Lantos (2011) stated that three components, namely affect, cognition, and conation, build an
individual’s overall attitude towards an attitude object (AO). While the first component affect
regards individuals’ emotions towards the object, cognition relates to beliefs and thoughts one has
about the AO. Conation represents the behavioural intentions and actions in relation to the AO
(Lantos, 2011).
2.2.1 Affect
Affect relates to individuals’ general feeling or mood, which means the emotional appeals such as
like/dislike, love/hate towards an AO (Evans et al, 2009; Lantos, 2011, Chen & Cheng, 2012, Chih
et al., 2015). Chen & Cheng (2012) argued that affect regards to consumer evaluations that are
established upon how congruent the expectation of what the AO provides is with individuals’
perception of what actually is provided.
2.2.2 Cognition
Cognition refers to the descriptive beliefs and thoughts one has about an AO. Such beliefs usually
concern physical attributes the AO possesses as well as the cognitive value one can obtain from it
(Evans et al., 2009; Lantos, 2011).
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2.2.3. Conation
Conation has been referred to as predispositions relating to behavioural intentions and actions of
individuals with reference to an AO (Evans et al., 2009; Lantos, 2011, Chen & Cheng, 2012). Such
actions or behaviours are found on the affective as well as cognitive component (Lantos, 2011).
2.3 Intrinsic Motivation
Vallerand and Thill (1993) mention that motivation is affected by internal and/or external forces.
The two major types of motivation that have been researched are intrinsic and extrinsic motivation2
has been shown to be a key element for the success of athletes in sports (Gould, et al., 2002).
Furthermore, it has been described that the motivational process as a psychological construct
energises, directs and regulates the achievement behaviour (Vallerand, 2007). According to the Self-Determination Theory (SDT) human behaviour can be categorised into three
types of motivation. An individual can be either intrinsically motivated, extrinsic motivation, or
amotivated (Deci & Ryan, 1985; Ryan & Deci, 2000). This differentiation is based on distinct
reasons which humans have for an action or behaviour. The construct of intrinsic motivation was
first mentioned in an experimental study conducted by White (1959). Within the study, it was
discovered that many individuals engage in exploratory, playful, and curiosity-driven behaviour
even without any type of reinforcement or reward. Referring to humans, there are different types of
motivation, still intrinsic motivation is described as a pervasive and important one (Ryan & Deci,
2000). Furthermore, it has been stated that this natural motivational tendency is crucial regarding
cognitive, social, and physical development. Intrinsic motivation is described as a type of motivation which comes from the individual’s inner
reason, for instance interest. Within the SDT, intrinsic motivation has been argued to be the most
self-determined type of motivation (Duda, 2007; Vallerand, 2007).
2 Ryan and Deci (2000) describe extrinsic motivation as a construct that applies when an activity is done to achieve
a separable outcome, particularly instrumental values.
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A number of researchers have found specific behaviours and feelings which can be linked to being
intrinsically motivated. For instance, it appears to be the most influential component of a positive
and successful sporting experience (Duda, 2007; Vallerand, 2007). The research of Reinboth and
Duda (2006) shows that athletes who try to learn more about their field of sports and constantly try
to improve their performance can be linked to a high intrinsic motivation. Furthermore, individuals
who focus on their own performance as criterion for their accomplishment within sports have a
higher tendency to experience intrinsic motivation (Duda, Chi, Newton and Walling, 1995; Sit and
Linder, 2007). It has been commonly found that athletes with a high intrinsic motivation are more
likely to continue in their sporting experience because they perform an activity as a result of
pleasure and satisfaction (Ntoumanis, 2005; Sarrazin et al., 2002, Vallerand, 2007). Research has shown that the reason why athletes usually drop in motivation can be explained
through a shift towards extrinsic reasons. Introducing and withdrawing extrinsic rewards causes a
reduction and elimination of intrinsic motivation (Lepper, et al., 1973; Greene & Lepper, 1974;
Lepper & Greene, 1975).
2.4 Gamification
Vaughan (2016) states that gamification is the utilisation of the essential features of game playing
added to a specific product. Other researchers have explained gamification as the utilisation of
gaming characteristics aiming to change behaviours in non-game settings (Lister et al., 2014; Miller
et al., 2014; Alturki & Gay, 2016; Schwartz et al., 2016; Zhao et al., 2016). Swan (2009) explains
that companies employ a wide variety of persuasive methods as well social influence strategies in
order to stimulate user engagement. One of these strategies is gamification, where competitions and
challenges are common. Gamification also includes virtual rewards for activity related
achievements (Swan, 2009). Duhigg (2012) claims that the repetition of desired outcomes is the
very foundation of successful gamification. Following the motivational results of reinforcements
and emotions, these desired outcomes become a product of habit. Habits are created through the
provision of cues evoking behaviours that are subsequently rewarded. This, in turn, results into a
desired behaviour that is continuously reinforced (Duhigg, 2012). Robson et al. (2015) explain that
gamification can achieve behavioural change by rewarding desired customer behaviours, which in
turn gives rise to a more satisfying customer experience than the non-gamified alternative.
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Moreover, Robson et al. (2015) have, based on previous game design literature, developed a
framework aiming to explain how gamified experiences can be produced. This framework
summarises the interdependent relationship of three principles of gamification: mechanics,
dynamics, and emotions (MDE framework). Mechanics refer to the decisions that designers of a
gamified setting make to define goals, rules, setting, context, who the opponents are, as well as the
boundaries of the gamified setting. It has been argued that the mechanics are constant, in that they
do not change from one player to another, or from one game to another (Robson et al., 2015).
According to Carmerer (2003), the Dynamics of gamification relate to the development of various
types of behaviour as the players participate in the experience. Given the mechanics of a gamified
setting (the rules etc.), the dynamics represent how players adhere to these mechanics. Robson et al.
(2015) point out that the dynamics of gamification are coupled with a great amount of uncertainty,
as it is difficult to foresee how players will behave to the gamified mechanics. Dynamics include
behaviours as e.g. cooperation and cheating . Emotions of gamification have to do with the affective
states and reactions aroused inside the player when participating in the gamified experience. As
such, emotions are the consequence of how the players adhere to the mechanics, and in response to
these mechanics produce dynamics (Robson et al., 2015). Sweetser and Wyeth (2005) explain that it
is vital that emotions in gamified experiences are paired with the element of fun for the sake of
player engagement. Consequently, players will not continue to partake in a game if enjoyment on an
emotional level is absent. Robson et al. (2015) claim that the element of fun comes in a variety of
forms, e.g. excitement, amusement, astonishment, pride, etc.. However, players often times feel a
multitude of emotions, including negative feelings (Robson et al., 2015).
2.5 Gamification in WFT
Recent research has revealed that gamification has a positive impact on the motivation of WFT
users (Lunney et al., 2016; Zhao et al., 2016; Asimakopoulos et al., 2017). It has further been found
that the self-efficacy of WFT users (Asimakopoulos et al.,2017), usage among consumers who
already own a WFT device (Coorevits & Coenen, 2016), adoption of WFTs (Spil et al., 2017), and
engagement as well as satisfaction of WFT users (Zhao et al., 2016) are positively affected by
gamification. In contrast, the findings of Vaughan (2016) suggest that gamification is not a large
motivational influencer for many users.
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Henceforth, it is recommended that companies should pay less attention to gamification and direct
more focus towards increased data accuracy and goal oriented features (Vaughan, 2016). Similarly,
Canhoto and Arp (2017) argue that sustained use is more dependent on the accumulation of useful
and accurate data. Spil et al. (2017) go on to say that there is a considerable amount of uncertainty
among consumers, in that consumers do not specifically know what they are looking for in wearable
devices. The authors argue that this uncertainty may stem from the multitude of wearable devices
available today, where features and design vary remarkably.
Furthermore, current and potential consumers were found to have a positive attitude towards
gamified health apps. The authors suggest that this positive attitude stems from the fact that such
apps are in general perceived as useful and user-friendly. Lunney et al. (2016) specifically advice
WFT developers to look to how Fitbit has incorporated the element of gamification with their leader
board feature. The authors argue that the leader board is an effective way to motivate WFT users to
exercise. Canhoto and Arp (2017) argue that the belief that WFT devices will facilitate the user to
achieve more ordinary fitness goals, such as just being more active, are related to sustained use of
WFT devices. On the other hand, goals of a more specific nature were found to be related to loyalty,
although the patterns of use were unstable. Schwartz et al. (2016) argue that applying apps to WFTs
is one way to reduce the risks and barriers associated with wearables.
However, the vast majority of fitness apps (approximately 80 percent) are uninstalled after the first
time of usage. It is argued that this is caused by the lack of gamification elements in the
applications, as these applications rarely contain more than three elements of gamification. There
are a multitude of gamification elements (up to 26 possible elements have been proposed), where
leaderboards and social pressure are some examples. It is argued that these gamification elements
can increase the motivation of the users (Schwartz et al. 2016). Zhao et al. (2016) tested the
feasibility and possible advantages of applying gamification of health and fitness to WFTs. Their
findings suggest that player versus player and goal oriented games are suitable approaches to
gamify exercise and fitness in the context of wearable devices, as these approaches had a positive
effect on motivation, engagement, and satisfaction. However, goal oriented games had a more
positive effect on users’ engagement and motivation to exercise, while player versus player games
generated a higher overall satisfaction score (Zhao et al., 2016).
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3. Conceptual Framework
As the literature review vide supra has pointed out, the addition of essential game elements in non-
game contexts or settings, namely gamification, is an effective method to to increase an individual's’
attitude and motivation to engage in a specific behaviour (Lister et al., 2014; Miller et al., 2014;
Alturki & Gay, 2016; Schwartz et al., 2016; Vaughan, 2016; Zhao et al., 2016). Gamification does
not only stimulate individuals’ emotions, their enjoyment and engagement through its rewarding
mechanisms but furthermore, it can change behaviour by facilitating goal-setting. (Swan, 2009;
Robson et al., 2015). Since attrition, which means discontinuous behaviour, is the most essential
problem in the WFT industry (Fritz et al., 2014; Shih et al., 2015; Coorevits & Coenen, 2016;
Ledger & McCaffrey, 2016; Xu & Wang, 2016), gamification has recently been researched. The
results commonly showed that gamification had a positive influence both on user motivation as well
as their attitudes which, in turn, have the ability to influence sustained use of the WFT (Lunney et
al., 2016; Zhao et al., 2016; Asimakopoulos et al., 2017). As prior research has highlighted,
motivation and attitude are significantly correlated and interdependent (Peak & Jones, 1955; Beebe
et al., 1999; Bakar et al., 2010). The Tri-Component Attitude Model is a well established framework
incorporating affection, cognition, and conation. In other words these components represent feelings
(emotions), beliefs and behaviour. It has been determined that the third component conation
(behaviour) is a result of the other two components, as Lantos (2011) argues that actions or
behaviours are founded on the affective as well as cognitive component.
This can be connected to gamification since Robson et al. (2015) argue that emotions of a gamified
experience has to do with the affective states and reactions of players (users). It is further argued
that it is indispensable that the experience is coupled with the element of fun in order to facilitate
continued participation, thus sustained use. Fun can be; excitement, amusement, and astonishment
(Robson et al., 2015). In relation to beliefs Canhoto and Arp (2017) state the belief that WFT
devices will facilitate the user to achieve more ordinary fitness goals, (e.g. being more active) is
related to sustained use of WFT devices. Hence, the emotions and beliefs influenced by
gamification elements have an impact on the behavioural component. Hereof Robson et al. (2015)
have highlighted that gamification can achieve behavioural change by rewarding desired customer
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behaviours, which in turn gives rise to a more satisfying customer experience than the non-gamified
alternative.
Duhigg (2012) mentioned that following the motivational results of reinforcements and emotions,
these desired outcomes become a product of habit. Habits are created through the provision of cues
evoking behaviours that are subsequently rewarded. This, in turn, results into a desired behaviour
that is continuously reinforced (Duhigg, 2012).
Beside the motivation provoked by gamification, individuals have an intrinsic motivation to
perform a certain behaviour or action. These intrinsic motivations appear to be the most influential
component of a positive and successful sporting experience (Duda, 2007; Vallerand, 2007) and can
have different levels depending on the individual. Since gamification, as an external factor, has the
ability to change behaviour by making the user more motivated, one can assume that the natural
level of intrinsic motivation of the user can have an impact on the strength of the effect of
gamification. Reinboth and Duda (2006) have mentioned that athletes who are trying to learn more
about their field of sports and constantly trying to improve their performance can be linked to a high
intrinsic motivation. Furthermore, individuals who focus on their own performance as criterion for
their accomplishment within sports have a higher tendency to experience intrinsic motivation.
Hence, since gamification is usually applied in order to facilitate goal-setting and motivation it can
be assumed that the higher an individual’s intrinsic motivation is, the lower the impact of
gamification on attitudes, motivation and sustained use. This can be connected to several
researchers who have argued that athletes with a high intrinsic motivation are more likely to
continuously engage in sports because they perform an activity as a result of pleasure and
satisfaction (Ntoumanis, 2005; Sarrazin et al., 2002, Vallerand, 2007). Concludingly, the hypothesis (H1) vide infra are formulated:
H1: The higher the intrinsic motivation is, the lower is the impact of gamification aspects on
attitudes, motivation and hence sustained use of WFT.
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Figure 3 - Conceptual Model
The conceptual model reflects the theoretical framework resulting into the stated hypothesis above.
Existing theory has highlighted that gamification prevents attrition by impacting users’ attitude,
motivation and hence the sustained use of WFT. However, the level of intrinsic motivation one
naturally possesses can be different among individuals. The model hypothesizes that intrinsic
motivation is a moderator (H1). Based on existing theory, the authors hypothesize that when
intrinsic motivation increases, the effect gamification aspects have on sustained use will decrease
and vice versa (H2
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4. Methodology
The next chapter provides information about how the researchers plan to design the study, how
data is gathered and how the data is analyzed. Additionally, it explains how the gathered data is
coded into information and how the quality criteria is approached.
4.1 Research Approach, Research Design & Data Source
This research applies existing theories in order to formulate and test hypotheses. Since the
measurements and their relationship with other determinants are based on previous literature, a
deductive research approach is chosen for the present study (Giola et al., 2012).
The explanatory research conducted within the scope of this study aims to explain the effect
(moderation) that intrinsic motivation has on the effect of gamification on attitudes/motivation and
hence sustained use of WFT devices. The authors conduct a correlational research where the aim is
to investigate if intrinsic motivation, as a moderator, is correlated with the effect of gamification
aspects on attitudes, motivation and sustained use (Bryman & Bell, 2015). A correlational study can
have three different outcomes, namely positive correlation, negative correlation, or no correlation.
Typical features of a correlational study are that two or more variables are collected directly from
each respondent in the sample at a single point of time. Here, the predictor variable is commonly
collected before the criterion variable. Further, the data is treated as one group in the analysis. It is
important to note that a correlation does not necessarily include causation (Bryman & Bell, 2015).
Due to the limited amount of data found within the chosen field, primary data is collected through a
quantitative method, which helps the authors to get a generalisable result (Malhotra, 2010).
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4.2 Data Gathering
Primary data can be gathered through qualitative or quantitative research methods (Malhotra, 2010).
Since the purpose of this study is to identify how intrinsic motivation moderates the impact of
gamification aspects on sustained use of WFT, quantitative data gathering is the most suitable
method. This can be further explained due to the need to reach more conclusive and generalisable
findings.
4.3 Sampling
When data is collected from a sample, there are two essential parts researchers must consider
namely, sampling method and sample size (Bryman & Bell, 2015; Malhotra, 2010; Aaker et al.,
2016).
4.3.1 Sampling Method
Due to the limited amount of resources, this research uses a non-probability sample.
Using convenience sampling allows the authors to collect a large amount of respondents in a short
period of time. In comparison to other sampling processes this method is the least time intensive
sampling method (Malhotra, 2010). By using convenience sampling method, the researchers decide
on their own convenience who the participants in the research will be (Bryman & Bell, 2015).
Furthermore, this decision can be strengthened by the argument that no specific demographics or
other characteristics of respondents are required. The only criteria for the sample is that respondents
know what WFT is as well as the characteristics of WFT. However, convenience sampling is an
issue when it comes to the replicability of the study.
4.3.2 Sample Size
There are many different methods to determine the sample size (Aaker et al., 2016). A generally
accepted approach is the application of a rule of thumb. According to VanVoorhis and Morgan
(2007) the sample size should contain a minimum of 50 participants.
20
With the intention to reduce sampling error and to increase the generalizability of the results, the
authors aim to reach a larger sampling size than suggested.
4.4 Data Collection Method
For the present study, survey research in the form of a questionnaire is the most suitable approach to
gather primary data, considering that the study is of quantitative nature and the author's chose a
correlational survey research as research design (Bryman & Bell, 2015). According to Bryman and
Bell (2015) a questionnaire is considered as a time effective tool to collect data. Additionally, the
likelihood to manipulate any of the answers decreases.
The questionnaire is used in order to measure how individuals’ intrinsic motivation moderates the
impact of gamification aspects on sustained use of WFT. In order to be able to measure the
moderation, the questionnaire identifies respondents’ natural intrinsic motivation. Next, it presents a
description of a fictive WFT device which integrates gamification aspects (product description with
focus on gamification features). Finally, the authors measure the respondent's’ attitude by applying
the Tri-Component Attitude Model in order to explore how sustained use changes depending on a
change in intrinsic motivation (see vide infra).
4.4.1 Questionnaire Design
The questionnaire is designed with the help of Google forms and consists of two pages. When the
questionnaire is posted on social media the post includes a brief introduction discussing what
participants can expect, ensuring ethical data management as well as a presentation of the authors of
this paper. The authors were also including that a price can be won when participating in the
questionnaire in order to increase the willingness to participate (see Appendix). Further, the first
page of the questionnaire starts with questions/statements (measurement items) regarding the
respondents’ intrinsic motivation. These questions have been formulated based on previous research
results stating that athletes who want to learn more about their type of sports and who frequently try
to surpass themselves can be regarded as being intrinsically motivated towards their sport (Sarrazin
et al., 2002; Ntoumanis, 2005; Reinboth & Duda, 2006; Duda, 2007; Vallerand, 2007).
21
Hence, based on the answers on these questions, the authors will be able to measure the
respondents’ level of intrinsic motivation. The second page starts with a description of a gamified activity tracker (bracelet). In this description
the activity bracelet is called Actiboost X2 and the authors mention that it has all the features that
one would expect from a modern activity tracker in order to ensure that respondents’ answers on the
following statements are solely influenced by the gamification feature of the device. None of the
features is defined in order to ensure that answers are not biased by other features of the WFT than
gamification. In order to measure the effect of gamification aspects, the findings of Zhao et al.
(2016) are applied to create the description. As already mentioned, Zhao et al. (2016) suggest that
player versus player aswell as goal oriented games are suitable approaches to gamify exercise and
fitness in the context of wearable devices, since these approaches have a positive effect on users’
motivation, engagement, and satisfaction. In detail, goal oriented games had a more positive effect
on users’ engagement and motivation to exercise, while player versus player games generated a
higher overall satisfaction score (Zhao et al., 2016). Finally, statements (measurement items) to
measure respondents’ attitude and hence, motivation and sustained use are formulated with the help
of the Tri-Component Attitude Model. The statements are formulated for each component (affect,
cognition, conation) respectively. The specific statements can be seen in the operationalisation
below. Demographic control questions regarding the gender and age of the respondents were
included in the end of the questionnaire. The complete design of the questionnaire including the
description of the fictive activity bracelet can be found in Appendix.
4.4.2 Operationalisation
The following operationalisation is created in order to measure the moderation of intrinsic
motivation (moderator variable) on the effect of gamification (independent variable) on user
attitudes and hence their motivation and sustained use of WFT (dependent variable).
22
!
Theoretical Concept Justification of Measurement Measurement Items
Intrinsic Motivation Intrinsic motivation appears to 1. How much do you train per
Intrinsic motivation is a type of
be the most influential week?
component of a positive and (10-Point Likert Scale)
motivation which comes from successful sporting experience
2. I find it important to engage
the individual’s inner reason, (Duda, 2007; Vallerand, 2007).
for instance interest, and is It has been commonly found in physical activity.
based on pleasurement and that athletes with a high (5-Point Likert Scale)
satisfaction intrinsic motivation are more
3. In general, engaging in
(Sarrazin et al., 2002; likely to continue in their
Ntoumanis, 2005; Reinboth & sporting experience because physical activity is not
Duda, 2006; Duda, 2007; they perform an activity as a inconvenient for me.
Vallerand, 2007). result of pleasure and (5-Point Likert Scale)
satisfaction (Sarrazin et al.,
4. I receive satisfaction through
2002; Ntoumanis, 2005;
Vallerand, 2007). As such, the exercising.
amount one trains depends on (5-Point Likert Scale)
the pleasure and satisfaction
5. I inform myself about my
that is attained through
training, which depends on sport to learn more about it.
intrinsic motivation. (5-Point Likert Scale)
Reinboth and Duda (2006) 6. I try so increase my training
state that athletes trying to performance constantly.
learn more about their field of (5-Point Likert Scale)
sports and constantly trying to
surpass themselves can be
regarded as being intrinsically
motivated toward their sport.
Tre-Component Model of Affection (Feelings) 1. I feel positive about the
Attitude (ABC) (Evans et al, 2009; Lantos, fitness device.
This model argues that an
2011; Chen & Cheng, 2012; (5-Point Likert Scale)
Chih et al., 2015).
2. I feel excited about the
individual’s overall attitude
Robson et al. (2015) argue that
towards an attitude object is fitness device.
founded on three components, emotions of a gamified (5-Point Likert Scale)
namely affect, cognition and experience has to do with the
3. The fitness device feels
conation (Evans et al., 2009; affective states and reactions of
Lantos, 2011) players (users). It is further entertaining.
argued that it is absolutely vital (5-Point Likert Scale)
that the experience is coupled
with the element of fun in
order to facilitate continued
participation. Fun can be:
excitement, amusement,
astonishment (Robson et al.,
2015).
23
Cognition (Beliefs) The fitness device feels
(Evans et al., 2009; Lantos, entertaining.
2011) (5-Point Likert Scale)
Canhoto and Arp (2017) argue I believe that the fitness device
that the belief that WFT would help me to be more
devices will facilitate the user active.
to achieve more ordinary (5-Point Likert Scale)
fitness goals, such as just being
I believe that the fitness device
more active, are related to
sustained use of WFT devices. would help me to improve my
health condition.
(5-Point Likert Scale)
I believe that the fitness device
would help me to control my
weight and/or condition.
(5-Point Likert Scale)
Conation (Behaviour) I would be more motivated to
(Evans et al., 2009; Lantos, exercise if I used the device.
2011, Chen & Cheng) (5-Point Likert Scale)
According to Duhigg (2012) is I would develop new goals
the repetition of desired easier if I used the device.
outcomes the very foundation (5-Point Likert Scale)
of successful gamification.
I would have more fun
Following the motivational
results of reinforcements and exercising if I used the device.
emotions, these desired (5-Point Likert Scale)
outcomes become a product of
I would have a more satisfying
habit. Habits are created
through the provision of cues training experience if I used the
evoking behaviours that are device.
subsequently rewarded. This, (5-Point Likert Scale)
in turn, results into a desired
behaviour that is continuously
reinforced (Duhigg, 2012).
Robson et al. (2015) explain
that gamification can achieve
behavioural change by
rewarding desired customer
behaviours, which in turn gives
rise to a more satisfying
customer experience than the
non-gamified alternative.
Table 4.4.2 - Operationalisation
24
4.4.3 Pre-test
According to Bryman and Bell (2015) authors should pre-test the data collection instrument to
increase the ability to generalize the result. Furthermore, pre-testing helps to identify possible errors
within the questionnaire which could result into misjudgment (Malhotra, 2010). To receive
feedback regarding the formulation of questions/statements, the questionnaire is shown to six
marketing students at Linnaeus University in Växjö, Sweden. Within the phase of pre-testing the
questionnaire was improved (formulation of questions/statements) to optimise the data gathering
process.
4.4.4 Data Gathering Process
Due to the limited amount of time and monetary resources, the authors expect to receive a higher
number of respondents by distributing the questionnaire online through social media (Facebook).
The authors focus on Facebook groups with active athletes as well as students due to the
convenience sampling method of this study and the easy access to these online networks. By the
statement that this study only considers people who already know wearable technology and its
characteristics in the Facebook postings, the authors made sure that the participants fit to the sample
group and have enough knowledge to be able to answer the statements properly.
4.5 Data Analysis Method
All data analyses are conducted with the help of the IBM SPSS Statistics software.
4.5.1 Linear Regression Analysis
Since the relationship between the independent (Gamification) and dependent variable (Attitudes/
Motivation to Sustained Use of WFT) in this study is known (positive), the authors aim to
investigate the effect of the moderator variable (Intrinsic Motivation) on the effect the independent
variable has on the dependent.
25
Due to this setting a simple linear regression analysis is used to transform data into information
since there is only one independent variable. Malhotra (2010) state that a multiple regression
includes one dependent variables and at least two independent variables. When conducting a
multiple regression analysis, the focus is on strength of association, significance testing, and partial
regression coefficients as well as examination of residuals. A residual is the difference between the
predicted value by the regression model and the observed value. Furthermore, Malhotra (2010)
argue that the strength of association is measured by R2. Significance testing relates to testing the
significance of the entire regression equation. It also includes testing the significance of certain
partial regression coefficients (Malhotra, 2010). Aaker et al. (2016) describe that a linear regression analysis is a suitable method to describe, predict
and to control a relationship between a dependent and an independent variable (in this case
moderator variable). Moreover, it can display the strength of such a causal relationship (Malhotra,
2010; Aaker et al., 2016).
The Pearson correlation coefficient (R) measures the linear association between those two variables.
The value of R can range from -1, which represents a perfectly negative relationship, to +1, which
reflects a perfectly positive relationship, whereas a value of 0 shows that there exist no linear
relationship between the variables (Saunders et al., 2009). Furthermore, the coefficient of
determination R squared (R2) presents the degree to which data fits to the statistical model and will
provide an understanding of the goodness-of-fit of the actual data and its variation from the
regression line. A more precise value can be provided through R square adjusted, since it excludes
all alternative variable and only take the independent variable into account (Jianlong et al., 2015).
However, a correlation analyses only explains the strength of the relationship between the variables
and cannot explain the sort of relationship (Aaker et al., 2016). The unstandardized beta coefficient
reflects the change of the dependent variable when the independent variable changes by one unit
(Saunders et al., 2009). The authors used the independent variable of this study as a constant (description of a gamification
feature in WFT) that does not change and checked for moderation by entering the moderator
variable as the independent predicting variable in the regression analysis. Then the results show
how much the dependent variable will vary based on the variation in the moderator variable.
26
The three components of the dependent variable (Affect, Cognition, Conation) are summed up to
one average dependent variable, namely attitude.
4.6 Data Coding
Before the authors are able to analyse the data, it has to be coded (Saunders et al., 2009). The
measurement items (statements) of the questionnaire are measured with a 5-point Likert scale where
1 represented strongly disagree, 2 disagree, 3 neither agree nor disagree, 4 agree while 5 represented
strongly agree. Only for the first question to measure intrinsic motivation (How much do you train
per week?) a 10-point Likert Scale, instead of a 5-Point Likert Scale, is applied in order to provide
respondents the possibility to answer more detailed and to limit restrictions.
The demographic control question regarding gender was measured with a nominal scale and coded
1 for female and 2 for male in SPSS. For the age, a ratio scale was used.
In SPSS the results were coded as follows: respondents between 18-25 were coded 1, between 26-
30 as 2 and 31-35 as 3, 4 represented 36-40, 5 between 41-45, and 46-50 was coded as 6. The final
age group of 50+ was coded as 7.
4.7 Quality Criteria
For the authors it is crucial to achieve a high quality of the research and be able to generalise the
results. To be able to do so, one has to ensure that all measures are useful and accurate (Aaker et al.,
2016). Through measuring reliability and validity of the questionnaire, the authors can ensure a high
quality of the measurements (Bryman and Bell, 2015). Furthermore, they describe that reliability
measures if the results are consistent over time which can be measured by calculating a Cronbach’s
Alpha. A Cronbach’s Alpha of 0.8 or higher is generally accepted and ensures reliability (Bryman
and Bell, 2015). In order to assure reliability the exact replicability of the study is required.
27
Hence, the authors describe this methodology chapter in detail in order to facilitate the replicability
of the study (Asendorpf et al., 2013). However, as mentioned before, the non-probability sampling
method used in the present study is an issue when it comes to replicability.
The other core measurement is validity, which measures if the questions are measuring what they
intend to measure (Aaker et al., 2016). Through construct and face validity, the authors ensure that
the questions are valid. When conducting a Pearson correlation coefficient (R), a value between 0.3
and 0.9 assures construct validity (Dancey & Ridley, 2011). Face validity was ensured by sending
out the questionnaire design to two supervisors working at the marketing department of Linnaeus
University in Växjö, Sweden.
28
5. Results
The following chapter displays the results of the questionnaire and the simple linear regression
analysis which was conducted to test the hypotheses. Further, the results of the validity tests as well
as the reliability tests for both the measurement items of the moderator variable and the
measurement items of the dependent variable are presented.
5.1 Descriptives
5.1.1 Demographics
As Figure 5.1.1a shows, 47.2% of the participants were female and 52,8% were male. Hence, the
gender of participants was nearly equally distributed.
Figure 5.1.1a - Descriptives: Gender
As shown in Figure 5.1.1b, the majority of participants were between the age of 18 and 25 (73). 54
respondents were between 26 to 30 years, and 31 respondents between 31 and 35 years old. 23
respondents were within the range of 36 to 40 years. Further, both groups, 41 to 45, and 46 to 50
contain 6 participants each. Only two participants were older than 50 years.
29
Figure 5.1.1b - Descriptives: Age
5.1.2 Intrinsic Motivation
Table 5.1.2a shows the number of participants (n=195), the minimum average intrinsic motivation
score (1) as well as the maximum score (5,83). It can also be seen that the mean score (which is
somewhere around 4) is very close to the average score of 3,9761. Lastly, the table shows the
standard deviation (1,15482).
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Intrinsic 195 1,00 5,83 3,9761 1,15482
Motivation
Valid N 195
(listwise)
Table 5.1.2a - Descriptives: Intrinsic Motivation
30
The Table 5.1.2b shows how the different levels of intrinsic motivation are distributed among the
195 respondents. There are five different levels of intrinsic motivation: very low intrinsic
motivation (ranging from 1-1,83), low intrinsic motivation (ranging from 2-2,83), moderate
intrinsic motivation (ranging from 3-3,83), high intrinsic motivation (ranging from 4-4,83), and
very high intrinsic motivation (ranging from 5-5,83). The first column (Frequency) shows how
many respondents have an average intrinsic motivational score corresponding to the range of each
of the five levels. The next column (Percent) shows what percentage the average intrinsic
motivation scores correspond to, seen to the total amount of scores. The last column shows the
cumulative percentage. Here, it can be noted that the mean of average intrinsic motivation scores is
very close to the level of "High intrinsic motivation". Hence, there is no equal distribution of
respondents among the different levels and ranges.
Intrinsic Motivation
Frequency Percent Cumulative Percent
Very low intrinsic 2 1,0 1,0
motivation 1,0
1,17 1 0,5 1,5
1,33 3 1,5 3,1
1,50 2 1,0 4,1
1,67 1 0,5 4,6
1,83 1 0,5 5,1
Low intrinsic motivation 4 2,1 7,2
2,0
2,17 3 1,5 8,7
2,33 4 2,1 10,8
2,50 5 2,6 13,3
2,67 7 3,6 16,9
2,83 7 3,6 20,5
Moderate intrinsic 3 1,5 22,1
motivation 3,0
3,17 8 4,1 26,2
3,33 10 5,1 31,3
3,50 5 2,6 33,8
!30
31
3,67 12 6,2 40,0
3,83 8 4,1 44,1
High intrinsic motivation 10 5,1 49,2
4,0
4,17 9 4,6 53,8
4,33 7 3,6 57,4
4,50 7 3,6 61,0
4,67 12 6,2 67,2
4,83 13 6,7 73,8
Very high intrinsic 14 7,2 81,0
motivation 5,0
5,17 13 6,7 87,7
5,33 12 6,2 93,8
5,50 5 2,6 96,4
5,67 4 2,1 98,5
5,83 3 1,5 100,0
Total 195 100,0
Table 5.1.2b - Descriptives: Intrinsic Motivation
5.2 Hypothesis Testing
5.2.1 Simple Linear Regression Analysis
Model Summary
Model R R Square Adjusted R Square
1 ,300a 0,09 0,085
Table 5.2.1a - Model Summary
Table 5.2.1a above shows the model summary of the simple linear regression analysis. R is the
Pearson correlation coefficient and shows that there is a correlation (0.3). The R Square adjusted of
0.085 and the R Square of 0.09 show that only 9% of the total variation in the dependent variable
‘attitude’ can be explained by the linear regression model.
32
ANOVAa
Sum of Squares df Mean Square F Sig.
Regression 15,658 1 15,658 19,090 ,000b
Residual 158,305 193 0,820
Total 173,964 194
Note: a = Attitude/Motivation, b = Intrinsic Motivation
Table 5.2.1b - ANOVA
Table 5.2.1b presents the ANOVA of the simple linear regression analysis. It points out that the
variation in the dependent variable to the moderation of the effect of the independent variable is
statistically significant and a linear model exists. In other words, the variation in attitudes is
significant due to the different levels of intrinsic motivation which moderates the effect of the
independent variable, gamification, significantly. Thus, these results accept hypothesis 1 (H1).
Coefficientsa
Unstandardized Coefficients Standardized t Sig.
Coefficients
B Std. Error Beta
(Constant) 4,325 0,233 18,557 0,000
Intrinsic -0,246 0,056 -0,300 -4,369 0,000
Motivation
Note: a = Attitude/Motivation
Table 5.2.1c - Coefficients
Table 5.2.1c presents the coefficients from the simple linear regression analysis. The unstandardised
Beta coefficient intrinsic motivation shows how much the dependent variable (attitude) changes
when the intrinsic motivation increases by one unit. Thus, the change is -0.246, which means that
the average value of attitude decreases by a value of 0.246 when intrinsic motivation increases by
one unit. Hence, there is a negative moderating effect of intrinsic motivation on the effect that
gamification aspects have on attitudes and thus motivation and sustained use of WFT. Based on
these results it can be concluded that hypothesis 1 (H1) is accepted.
33
Also, the significance level in this table highlights again that the variation in attitude towards a
WFT device can be considered as statistically significant (0.0), which also supports hypothesis 1
(H1). The authors also conducted two split-file regression analyses in order to see if there are significant
differences between males and females as well as the different age groups. However, no significant
differences were found between the different demographic characteristics. Also, due to the low R Squared in the simple linear regression analysis, the authors decided to
conduct a multiple linear regression analysis in order to test if more of the variation in attitude/
motivation can be explained by gender or age. The results of the miltiple regression analysis can be
found vide infra.
5.2.2 Multiple Linear Regression Analysis
Three models were generated by the multiple regression analysis. Model 1 tested again Intrinsic
Motivation as predictor, while Model 2 took the factor Age into consideration. Model 3 considered
Intrinsic Motivation, Age, as well as Gender as three predictors of a change in attitude/motivation.
Model Summary
Model R R Square Adjusted R Square
1 ,300a 0,09 0,085
2 ,307b 0,094 0,085
3 ,307c 0,095 0,08
Note: a = Intrinsic Motivation, b = Intrinsic Motivation, Age, c = Intrinsic Motivation, Age,
Gender Table 5.2.2a - Model Summary
Table 5.2.2a above shows the model summary of the multiple linear regression analysis. R is the
Pearson correlation coefficient and shows that there are correlations. The R Square adjusted of
0.085 and the R Square of 0.09 show that only 9% of the total variation in the dependent variable
‘attitude’ can be explained by intrinsic motivation. Also, it shows that only 9.4% of the variation in
attitude can be explained by intrinsic motivation and age, which is higher than for intrinsic
motivation alone. Finally, in model 3 a R Squared of 9.5% is shown.
34
This means that intrinsic motivation, age, and gender together can predict only 9.5% of the variation
in the dependent variable. Hence, the R Squared value could not be increased by including age and
gender in the regression analysis.
ANOVAa
Model Sum of df Mean Square F Sig. Squares
1 Regression 15,658 1 15,658 19,090 ,000b
Residual 158,305 193 0,820
Total 173,964 194
2 Regression 16,431 2 8,216 10,013 ,000c
Residual 157, 532 192 0,820
Total 173,964 194
3 Regression 16,440 3 5,480 6,645 ,000d
Residual 157,523 191 0,825
Total 173,964 194
Note: a = Attitude/Motivation, b = Intrinsic Motivation, c = Intrinsic Motivation, Age, d = Intrinsic
Motivation, Age, Gender
Table 5.2.2b - ANOVA
Table 5.2.2b presents the ANOVA of the multiple linear regression analysis. It points out that the
variation in the dependent variable to the moderation of the effect of the independent variable is
statistically significant and a linear model exists. In other words, the variation in attitudes is
significant due to the different levels of intrinsic motivation, age, and gender which moderates the
effect of the independent variable, gamification, significantly.
35
Coefficientsa
Model Unstandardized Coefficients Standardized t Sig. Coefficients
B Std. Error Beta
1 (Constant) 4,325 0,233 18,557 0,000
Intrinsic -0,246 0,056 -0,300 -4,369 0,000
Motivation
2 (Constant) 4,413 0,250 17,662 0,000
Intrinsic -0,242 0,056 -0,295 -4,284 0,000
Motivation
Age -0,45 0,47 -0,67 -0,971 0,333
3 (Constant) 4,404 0,262 16,828 0,000
Intrinsic -0,242 0,057 -0,295 -4,272 0,000
Motivation
Age -0,045 0,047 -0,066 -0,962 0,337
Gender 0,014 0,130 0,007 0,106 0,916
Note: a = Attitude/Motivation
Table 5.2.2c - Coefficients
Table 5.2.2c presents the coefficients from the multiple linear regression analysis. The
unstandardised Beta coefficient intrinsic motivation shows how much the dependent variable
(attitude) changes when the intrinsic motivation increases by one unit. Thus, the change is -0.246,
which means that the average value of attitude decreases by a value of 0.246 when intrinsic
motivation increases by one unit. Hence, there is a negative moderating effect of intrinsic
motivation on the effect that gamification aspects have on attitudes and thus motivation and
sustained use of WFT, which the simple linear regression analysis already showed.
The table also shows that both age and gender do not cause a major change in attitude/motivation
due to the low beta coefficients presented above. Further, the values of the coefficients for age and
gender are insignificant.
36
5.3 Validity
5.3.1 Intrinsic Motivation
Correlations
Intrinsic Intrinsic Intrinsic Intrinsic Intrinsic Intrinsic Intrinsic Motivantio Motivation1 Motivation2 Motivation3 Motivation4 Motivation5 Motivation6
n Items
Intrinsic Pearson - ,564** ,522** ,522** ,544** ,661**
Motivation1 Correlation
Intrinsic Pearson ,564** - ,596** ,706** ,578** ,577**
Motivation2 Correlation
Intrinsic Pearson ,522** ,596** - ,502** ,481** ,499**
Motivation3 Correlation
Intrinsic Pearson ,522** ,706** ,502** - ,565** ,517**
Motivation4 Correlation
Intrinsic Pearson ,544** ,578** ,481** ,565** - ,517**
Motivation5 Correlation
Intrinsic Pearson ,661** ,577** ,499** ,517** ,643** -
Motivation6 Correlation
Notes: ** p < 0.01 (2-tailed)
Table 5.3.1 - Correlations: Intrinsic Motivation
Table 5.3.1 shows the correlation between the measurement items for intrinsic motivation. There
are three values displayed in the correlation analysis. The Pearson correlation coefficient shows the
direction and strength of the correlation. Firstly, all values are within the range of -1 and +1 which ensures that a correlation exists.. Further,
all values are positive which means that there is a positive correlation between all items used for the
moderator variable. The third part is the significance level (2-tailed). This level is below 0.05 for all
of the combinations between the items which reflects that these items are significantly correlated
with each other and in turn validates the moderator variable.
37
5.3.2 Attitude
Correlations
Attitude Affect Cognition Conation components
Affect Pearson Correlation - ,755** ,760**
Cognition Pearson Correlation ,755** - ,832**
Conation Pearson Correlation ,760** ,832** -
Notes: ** p < 0.01 (2-tailed)
Table 5.3.2 - Correlations: Attitude Components
Table 5.3.2 displays the correlation between the measurement components (affection, cognition,
conation) for the dependent variable attitude, which includes motivation and sustained use. The Pearson
correlation coefficient (R) shows the direction and strength of the correlation. Firstly, all value are
within the range of -1 and +1 which ensures that a correlation exists. Further, all values are positive
which means that there is a positive correlation between all three components used for the dependent
variable. The third part is the significance level (2-tailed). This level is below 0.05 for all of the
combinations between the items which points out that these components are significantly correlated with
each other and in turn validates the measurement of the dependent variable.
In order to make sure that the specific measurement items (statements) used to measure each
component of attitude are valid, too, the authors conducted correlation analyses on all items for each
of the three respectively. The results here were similar to what the correlation analysis of the
components reflects (significant and positive correlation).
5.4 Reliability
A reliability test was performed for each theoretical concept to assure that the items are equivalent
to the measured concepts. Bryman & Bell (2011) have argued that a Cronbach’s Alpha with a value
of 0.8 or higher is an appropriate indicator for exceptional internal consistency reliability.
38
5.4.1 Intrinsic Motivation
Reliability Statistics
Cronbach’s Alpha N of items
0,845 6
Table 5.4.1 - Cronbach’s Alpha: Intrinsic Motivation
Table 5.4.1 shows the Cronbach’s alpha for the moderator variable as well as the number of items
used to measure the variable. As the Table 5.4.1 shows is the Cronbach’s alpha above 0.8 (0.845)
which implies an exceptional internal consistency reliability. Thus, it is assured that all three
components measure the same concept, which is attitude.
5.4.2 Attitude
Reliability Statistics
Cronbach’s Alpha N of items
0,914 3
Table 5.4.2 - Cronbach’s Alpha: Attitude Components
Table 5.4.2 presents the Cronbach’s alpha for the dependent variable as well as the number of items
used to measure the variable which in this case means the components. As the Table 5.4.2 shows is
the Cronbach’s alpha above 0.8 (0.914) which implies an exceptional internal consistency
reliability. Hence, it is assured that all three components measure the same concept, which is
attitude. In order to make sure that the specific measurement items (statements) used to measure
each component of attitude are reliable as well, the authors conducted reliability analyses on all
items for each of the three components respectively. The results were similar to what the reliability
analysis of the components reflects (above 0.8).
39
6. Discussion
Attrition, which means discontinuous usage, has been described as the most significant issue within
the industry of WFT (Fritz et al., 2014; Shih et al., 2015; Coorevits & Coenen, 2016; Ledger &
McCaffrey, 2016; Xu & Wang, 2016). Recent research has shown that the addition of gamification
elements to WFT devices can positively influence the motivation and attitude towards these devices
(Lunney et al., 2016; Zhao et al.,2016; Asimakopoulos et al., 2017). In turn, an increase in
motivation and/or attitude is positively related to sustained use of WFT devices (Fritz, 2014; Chang
et al., 2016; Coorevits & Coenen, 2016; Lunney et al., 2016; Asimakopoulos et al., 2017). Hence,
gamification can be seen as a means to prevent attrition of WFT devices. These findings go in line
with Westen (1999), arguing that behaviour is considerably impacted by attitude as well as
motivation. In contrast to the vast majority of current research arguing for the effectiveness of
gamification with regards to changing the consumer's behaviour, Vaughan (2016) suggests that
gamification is not a large motivational influencer for many users. The findings of the current paper
provide interesting insights to this opposing finding. These findings reveal that the intrinsic
motivation one has to engage in sports moderates the relationship between gamification and
positive attitudes and increased motivation and hence, sustained use of WFT. In detail, the higher
the intrinsic motivation, the less effective is gamification on motivation and attitude towards WFT.
As such, the reason as to why gamification aspects fail to serve as a strong motivational influencer
for some WFT users may be attributed to the different levels of intrinsic motivation among users.
Moreover, intrinsic motivation has been found to be the most influential component of a positive
and successful sporting experience (Duda, 2007; Vallerand, 2007). It has been commonly found that
athletes with a high intrinsic motivation are more likely to continue in their sporting experience
because they perform an activity as a result of pleasure and satisfaction (Sarrazin et al., 2002;
Ntoumanis, 2005; Vallerand, 2007). Research has also shown that the reason as to why athletes
usually drop in motivation can be explained through a shift towards extrinsic reasons, which has to
do with rewards that come from outside of the individual (Lepper, et al., 1973; Greene & Lepper,
1974; Lepper & Greene, 1975). Hence, it can be assumed that highly intrinsically motivated athletes
are less affected by extrinsic rewards than less intrinsically motivated athletes. Gamification
includes virtual rewards for activity related achievements (Swan, 2009).
40
Robson et al. (2015) explain that gamification can achieve behavioural change by rewarding desired
customer behaviours, which in turn gives rise to a more satisfying customer experience than the
non-gamified alternative. This can be connected to the findings of the current paper. As
gamification builds upon rewarding a desired behaviour, the effectiveness of gamification on an
individual's attitude and motivation will depend on how the individual responds to these extrinsic
rewards, such as the virtual rewards provided by gamified apps connected to WFT. Hence,
gamification aspects in the context of WFT devices will arguably be less effective on changing the
behaviour of a highly intrinsically motivated individual, since this individual's motivation to engage
in physical activity does not rest on extrinsic rewards. In contrast, extrinsically motivated
individuals who are low in intrinsic motivation will likely be more affected by gamification in terms
of a change attitude/motivation, as their motivation to engage in fitness-related activities is
dependent on external influences (rewards). This can also be connected to the findings of Duda et
al. (1995) as well as Sit and Linder (2007), arguing that intrinsically motivated athletes focus on
their own performance as criterion for their accomplishment within sports. Therefore, the sense of
accomplishment is not relative the performance of others. Gamification of WFTs commonly
includes aspects of competitions and leaderboards (Swan, 2009). As such, the sense of
accomplishment is oftentimes relative to the performance of others when it comes to gamification
of WFT. Hence, the element of comparing the individual performance with the performance of
others within gamified WFT devices may not serve as a motivational influencer for intrinsically
motivated individuals, due to that the sense of accomplishment is reliant on one's own performance.
Consequently, the opposite should apply for extrinsically motivated individuals low in intrinsic
motivation. In this respect, a parallel can be drawn to the findings of Coorevits and Coenen (2016),
arguing that motivation created on the basis of social comparison can further the sustained use of a
WFT device.
Moreover, research has found specific behaviours and feelings which can be linked to intrinsic
motivation (Duda, 2007; Vallerand, 2007). E.g.,intrinsically motivated athletes are continuously
trying to enhance their performance (Reinboth & Duda, 2006). Drawing upon these findings, it
would appear that different levels of intrinsic motivation give rise to different training related goals.
41
Within the research field WFT, Canhoto and Arp (2017) have argued that the belief that WFT
devices will facilitate the user to achieve more ordinary fitness goals, such as just being more
active, is related to sustained use of WFT devices. As intrinsic motivation has been argued to be the
most influential component of a positive and successful sporting experience (Duda, 2007;
Vallerand, 2007) as well as long-lasting sporting engagement (Ntoumanis, 2005; Sarrazin et al.,
2002, Vallerand, 2007), it can be assumed that ordinary fitness goals, such as "just being more
active", corresponds to a lower degree of intrinsic motivation. Hence, an individual who possesses
such ordinary fitness goals, would likely be more responsive to extrinsic rewards, and therefore
more affected by gamification. In this sense, gamification would help the individual to continuously
engage in physical activity by rewarding this behaviour, ultimately making exercising a habit,
which in turn would lead to sustained WFT use. Duhigg (2012) explains that habits are created
through the provision of cues evoking behaviours that are subsequently rewarded. This, in turn,
results into a desired behaviour that is continuously reinforced (Duhigg, 2012). On the other hand,
goals of a more specific nature have been found to be related to unstable usage of WFT devices
(Canhoto & Arp, 2017). By applying the same way of reasoning, goals of a more specific nature
may be related to a higher degree of intrinsic motivation. As such, individuals with more specific
goals should likely be less impacted by gamification, giving rise to unstable usage of the WFT
devices. In summary, gamification of WFT devices will arguably not prevent attrition to the same
extent for highly intrinsically motivated individuals as for extrinsically motivated individuals
(individuals low in intrinsic motivation), due to that highly intrinsically motivated individuals do
not need such external influences to engage in physical activity. This goes in line with Canhoto and
Arp (2017) stating that the usage of WFT devices is depending on the personal goals of the user.
Once again, this reflects back on the findings of the current study, stating that gamification is less
effective on changing the motivation and attitude of intrinsically motivated individuals.
Finally, the results have pointed out that the effect of gamification on attitude/motivation to WFT is
not dependent on age or gender. It seems as the character of one’s personal fitness goals, either
specific or more general, is not a product of age nor gender. The findings of the present study could
point out that intrinsic motivation can partly explain the variation in attitudes towards gamified
WFT devices. However, it appears that there is some other major factor(s) influencing one’s
attitude/motivation even more, which also impacts the sustained use of WFT.
42
7. Conclusion
Based on the results of the statistical analysis and the discussion it can be concluded that intrinsic
motivation negatively moderates the effect of gamification aspects on attitudes towards WFT
devices, motivation and finally the sustained use of WFT devices. From this follows that the effect
of gamification decreases as intrinsic motivation increases. Hence, gamification aspects can be seen
as an useful method to prevent attrition of WFT and facilitate sustained use for individuals that have
a low intrinsic motivation to engage in sports or physical activity. The reason for this is that for
them extrinsic factors are necessary for a positive attitude, goal-setting and the creation of more
motivation which results into sustained usage of WFT devices. On the other hand, the results have
pointed out that individuals that have a high intrinsic motivation to engage in sports or physical
activity are less affected by gamification aspects. The reason here is that these individuals are
already highly motivated and have the ability to achieve their goals themselves. Hence, there is no
need to build up motivation with the help of external motivational factors like gamification aspects
of WFT. In order to prevent attrition and to further a sustained usage of WFT for highly intrinsically
motivated individuals, the use of gamification is not an effective way.
43
8. Implications, Limitations, & Future Research
8.1 Theoretical Implications
It has been argued that research within the field of wearable technology is still in its infancy (Sultan,
2015; Lunney et al., 2016). Although, within this research field, a considerable amount of attention
has been dedicated to the establishment of accuracy and reliability of WFT devices (Mahar et al.,
2014; Takacs et al., 2014; Diaz et al., 2015; El-Amrawy, Pharm & Nounou, 2015; Huang et., 2016;
Leininger et al., 2016; Pobiruchin et al., 2016). Nevertheless, the concept of gamification has lately
gained momentum within this field of research (Lunney et al., 2016;Vaughan, 2016; Zhao et al.,
2016; Asimakopoulos et al., 2017). However, it has been pointed out that there is a need for a better
understanding of the mental motivations changing the behaviours and habits of individuals in the
context of gamification (Robson et al., 2015). Intrinsic motivation has been identified as the most
influential component of a positive and successful sporting experience (Duda, 2007; Vallerand,
2007). Yet scholars appear to have overlooked how intrinsic motivation affects the individual’s
response to gamification in terms of attitude, motivation, and sustained use. Following the future
research recommendations of Robson et al. (2015), the current paper adds to the research body of
gamification and WFT, by presenting a much needed understanding of how the mental motivations,
more precisely intrinsic motivation, moderate the well-established relationship between positive
attitudes/motivation and gamification. The current paper is to the knowledge of the authors the first
paper to address this research gap. The theoretical contribution of the study can also be connected to
Asimakopoulos et al. (2017) who recently argued that more research on the effectiveness of
gamification principles when it comes to the augmentation of long-term WFT user motivation is
needed. In this respect, the current paper provides useful insights as to how the WFT user's attitude,
motivation and hence sustained behaviour is affected by gamification when the factor intrinsic
motivation is taken into consideration.
44
8.2 Managerial Implications
It has been argued that there is a need to establish how to successfully integrate gamification in a WFT
context (Spil et al., 2017). The findings of this paper provide helpful insights for managers and
marketers on how gamification can be integrated in a WFT context. Gamification is a means to prevent
attrition and to facilitate sustained use. Gamification can achieve this behaviour change by positively
influencing the attitude and motivation of WFT users (Fritz, 2014; Chang et al., 2016; Coorevits &
Coenen, 2016; Lunney et al., 2016; Asimakopoulos et al., 2017). However, the findings of the current
paper suggest that merely those who have low intrinsic motivation are positively affected by
gamification aspects in this matter. Consequently, gamification is not an effective method to ensure
sustained use among users who are highly intrinsically motivated to engage in sports or physical
activity. Arguably, gamification does not prevent attrition among individuals who are highly
intrinsically motivated. Rather, gamification could possibly even increase attrition among these
individuals. Based on past research it can be argued that highly intrinsically motivated individuals do
not need external influences (e.g. virtual rewards) in order to set goals and to engage in physical activity
(Lepper, et al., 1973; Greene & Lepper, 1974; Lepper & Greene, 1975). According to Reinboth and Duda (2006) are these individuals naturally engaged in trying to
increase their performance. Hence, they do not need additional motivational influences from outside
themselves (external).
Moreover, for these individuals the sense of accomplishment rests on their own performance (Duda,
Chi, Newton & Walling, 1995; Sit & Linder, 2007), while less intrinsically motivated individuals
with more ordinary fitness goals are more sensitive to social comparison. Individuals who are low
on intrinsic motivation benefit from extrinsic rewards in terms of developing goals and
continuously engaging in physical activity (Lepper, et al., 1973; Greene & Lepper, 1974; Lepper &
Greene, 1975). Hence, less intrinsically motivated individuals with more ordinary fitness ambitions
are reasonably more positively affected by gamification. As such, managers and marketers should
segment the WFT market accordingly. When trying to reach athletes with specific goals, such as
running a marathon, the functionality and accuracy of the device may be a suitable approach. Past
research has suggested that data accuracy (Vaughan, 2016; Canhoto & Arp, 2017) and data
usefulness (Canhoto & Arp, 2017) contribute to sustained use of WFT devices.
45
On the other hand, when trying to reach individuals with more ordinary activity goals, such as
walking a given set of steps per day, gamification is presumably a much more suitable feature to
integrate and promote since the intrinsic motivation of the more ordinary exerciser is relatively low.
The element of fun (Sweetser and Wyeth, 2005) as well as the aspect of social interaction and
comparison contribute to a more fulfilling training experience, and will ultimately increase
engagement, which in turn would prevent attrition (Chang et al., 2016; Coorevits & Coenen, 2016;
Lunney et al., 2016).
8.3 Limitations
The results and conclusion of this study need to be treated with caution especially when it comes to
generalisation or the transfer to another context than wearable technology. The low R Squared (as
well as the R Squared Adjusted) show that a relatively small amount of the variation in attitude can
be explained by the linear regression model conducted. The authors consucted a multiple regression
analysis additional to the simple linear regression analysis in order to test if age and/or gender have
an impact on the variation in attitude. However, as the results showed the R Squared did not
increase significantly. Hence, there are other factors influencing the outcome which were not
investigated within the scope of this study. One reason for the low R Squared value could be the
sample size. Even though that much more of the least recommended amount of respondents was
reached, a larger sample would by reason represent the population in a better way. Also, this study
only focussed on the characteristic intrinsic motivation and the demographic factors gender and age.
Occupation and culture were ignored. Hence, it is not clear that the results are similar among
different occupations or cultures. Also, the replicability of the study cannot be completely ensured.
Even though that the implementation of the study has been described in detail the convenience
sampling method makes it difficult to replicate the results exactly.
8.4 Future Research
Based on the limitations stated vide supra, the authors have several recommendations for future
research. First of all, this study should be replicated with a larger sample size in order to see if a
higher R Squared (as well as the R Squared Adjusted) can be reached. Also, future research should
46
focus on finding factors that can explain a majority of the variation in attitude, motivation, and
hence sustauned use of WFT (high R Squared) since the present study could not find this or these
particular factor(s).
Also, future research needs to investigate if there are differences among different demographic
characteristics for instance occupation, and culture which the present study did not regard. This is
necessary in order to assure a high external validity of the results and to make them more
generalisable.
Moreover, more research about the prevention of attrition and the facilitation of sustained use of
WFT device is necessary. The present study found that gamification is effective as long as intrinsic
motivation is low. Future research needs to clarify methods to prevent attrition and facilitate
sustained use of WFT for individuals with high intrinsic motivation in order to fill a theoretical
research gap and to provide advice for practitioners in the WFT industry. Finally, the authors
recommend to in detail investigate what role intrinsic and extrinsic motivation play when it comes
to the sustained use of WFT.
47
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IV Appendix
Facebook Post:
Hello!
We are three marketing students who are currently writing our master’s thesis (Jonas, Rasmus &
Antonio). The paper is about wearable fitness technology (WFT). We are now in the need of your
help. If you are familiar with wearable fitness trackers (you do not have to own one yourself), we
would highly appreciate if you would answer our questionnaire. Your answers will be completely
anonymous. They will also only be accessible for the authors. If you participate in the study, you
have the chance to win a wearable fitness tracker (MI Band 2 by Xiaomi).
If you have any questions or remarks, please do not hesitate to contact us at:
Thank you for your participation!
Questionnaire Design:
How much do you train per week?
1 2 3 4 5 6 7 8 9 10
Not at all O O O O O O O O O O Very often
much
I find it important to engage in physical activity.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
In general engaging in physical activity is not inconvenient for me.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
57
I receive satisfaction through exercising.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I inform myself about my sport to learn more about it.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I try to increase my performance constantly.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
________________________________________________________________________________
Actiboost X2 is a wearable fitness tracker equipped with all the features you would expect from a
modern activity bracelet. The bracelet does also come with a mobile application that can be synced
to the bracelet. The mobile application is designed to facilitate and develop your training goals. In
the application you and your friends can choose to follow each other's development and set up
internal competitions. The application also allows you to easily follow your own development. In a
game-like format, your development is illustrated graphically in the form of a flower that blooms
and grows as your training progresses. As the player achieves milestones in terms of distance,
distance per unit of time, calorie consumption, etc., the flower develops and new levels become
available. If the user's activity decreases, the flower will eventually wither and die. Each training
session is followed by a summary where data, e.g. calorie consumption and distance are reported.
58
I feel positive about the fitness device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I feel excited about the fitness device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
The fitness device feels entertaining.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I believe that the fitness device would help me to be more active.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I believe that the fitness device would help me to improve my health condition.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I believe that the fitness device would help me to control my weight and/or condition.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
59
I would be more motivated to exercise if I used the device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I would develop new goals easier if I used the device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I would have more fun exercising if I used the device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
I would have a more satisfying training experience if I used the device.
strongly 1 2 3 4 5 strongly
disagree O O O O O agree
What is your gender?
O Female
O Male
60
What is your age?
O 18 - 25
O 26 - 30
O 31 - 35
O 36 - 40
O 41 - 45
O 46 - 50
O 50+
By entering my mail/phone number, I would like to participate in the competition where the
winner gets a fitness tracker (MI Band 2 by Xiaomi).
________________________________________________________________________________