Consumer Attitudes toward Black Hats : An Exploratory Study of Motivational Designs in Gamification

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Consumer Attitudes toward Black Hats

An Exploratory Study of Motivational Designs in Gamification

Authors: Yuri Lazar & Adam Kvarforth Tutor: Mart Ots

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Abstract

In this exploratory study the attitudes of consumers toward Black Hat gamification are examined, as well as the reasons given for these attitudes. Eight participants were given three mobile applications (Wish, Duolingo and Forest) to experience Black Hat design and were subsequently interviewed on their attitudes. It was found that Black Hat design can at times cause negative affective experiences but that consumers can justify these experiences depending on their cognitive evaluations of the application’s purpose. In cases where the application was perceived as useful, consumers were more likely to accept being motivated by Black Hat motivators. Ethical considerations and the alignment of Black Hats with

consumer interests are discussed. Although issues of validity arise, these findings can provide a basis for further studies into motivational design in gamification.

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1. Introduction

1.1 Background

The significance of games in modern society can hardly be overstated. Over the past decade, games and video games have become more advanced and accessible which has in turn increased their popularity. For many, games are a hobby or even a lifestyle. More recently, games became interesting to other fields due to the possible application outside of fully-fledged game experiences (Deterding, 2012). The use of game elements outside of games was given the term gamification (Deterding, Dixon, Khaled, & Nacke, 2011) and became a hot topic among academics. This is because gamification tends to induce an increase of motivation and improved performance among its users when applied in the right contexts (Deterding, 2012). By combining the hedonic elements of games with utilitarian systems, gamification has the potential to make important yet dull tasks more engaging. Elements of gamification can be found in healthcare, education, crowdsourcing, and e-commerce, amongst many other sectors, all seeking to make use of the motivational qualities of gamification (Seaborn & Fels, 2015).

Moreover, gamification has been considered a sleeping giant in the field of marketing (Seaborn & Fels, 2015; Zichermann & Cunningham, 2011). Although research is largely absent on the relation between gamification and purchase intentions, an increase in the total use and the quality of use of a service have been shown (Hamari, Koivisto, & Sarsa, 2014). This is to be expected. As games are designed for entertainment, they can create positive experiences and motivate users to be engaged intensely in the game for an extended period of time (Deterding et al., 2011). It would benefit marketeers tremendously to effectively transfer elements of game design into their product/service in order to achieve such a state.

However, ever since the concept of gamification was defined, researchers and marketeers have had difficulties coming up with an adequate answer regarding when and how

gamification should be implemented. Although many examples exist of businesses that have successfully incorporated game elements into their value proposition – simple loyalty programs like Starbucks and more elaborate gamified systems such as Foursquare come to mind – there is not a single solution or framework that can reliably replicate these successes (Fitz-Walter, Johnson, Wyeth, Tjondronegoro, & Scott-Parker, 2017; Hamari et al., 2014;

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Nacke & Deterding, 2017). Several issues in creating such a framework exist, among them an absence of a commonly accepted taxonomy of game elements, despite several attempts at defining them (Deterding et al., 2011; Robinson & Bellotti, 2013). Despite this, the

gamification market is booming and projected to continue doing so for at least the next five years with a projected annual growth rate of 27.4% during this period (Markets and Markets, 2020).

An important reason for the growth of gamification is its uses in mobile applications. The advances in technological capabilities in modern societies have allowed for the digitalization of many everyday tasks, with mobile applications at the forefront of this process (Nacke & Deterding, 2017). Many popular mobile applications now use some type of points, badges and/or leaderboards system in addition to more sophisticated gamification designs.

Consumers are widely exposed to at least some level of gamification in their mobile applications. Given this fact, it would be in the best interest of the consumer and the industries to better understand how gamification can be applied.

1.2 Problem Statement

Many articles have aimed at examining the effectiveness of certain game elements in non-game contexts and found that these vary greatly depending on the context in which it is applied (Fitz-Walter et al., 2017; Nacke & Deterding, 2017). This makes it difficult to come to any definite conclusion regarding how effective any particular game element is, as game elements can occur in an infinite variety of contexts. Additionally, the lack of a commonly agreed upon framework of game elements increases difficulties in examining their

effectiveness. In light of this, this thesis takes a different approach and, instead of focusing on the effectiveness of any particular game element, seeks to understand the role of the

motivational drives any user might have that the game elements attempt to appeal to. Chou (2015) introduced a framework called Octalysis that describes the motivations that users of a game or gamified system have. Eight different types of motivations, called Core

Drives, were identified. These Core Drives are what motivate a player to undertake an action

within a game or gamified system. In order to motivate a player, game elements should be designed specifically to appeal to at least one of the Core Drives, since in the case that none

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of them are activated, player motivation to undertake action is zero (Chou, 2015). Successful gamification effectively designs for these Core Drives and thereby increases motivation among its users. It is therefore prudent to examine how consumers experience the attempts to motivate them through the gamifying of these Core Drives.

This thesis focuses on three particular Core Drives Chou names Black Hats. Black Hats are Core Drives that motivate by inducing feelings of obsession, addiction, and anxiousness. They include the drives of unpredictability, avoidance, and scarcity. A short introduction to these Core Drives follows below:

Avoidance: This is the Core Drive that motivates through the fear of losing something or having undesirable events transpire. It is the motivation to avoid something negative from happening (Chou, 2015, p. 309)

Unpredictability: Unpredictability refers to users not knowing what will happen next, therefore making it more engaging. This Core Drive is the main force behind our infatuation with experience that are uncertain or involve chance (Chou, 2015, p. 271).

Scarcity: This is the Core Drive of wanting something because it is exclusive, rare, or immediately impossible to attain, therefore making it more desirable. This is the drive that motivates us simply because we are either unable to have something immediately, or because there is great difficulty in obtaining it (Chou, 2015, p. 231).

These Core Drives are interesting because of the supposed negative effect they have on consumers. Assuming that Black Hats do in fact induce negative emotions in players, this would logically make the user experience worse. Despite this, they are heavily featured in many popular applications and services, among them the mobile applications used in this study. Research regarding the use of Black Hats in gamification is mostly absent, as is empirical research into Octalysis in general. This can be attributed to a lack of standard evaluation model for designers when implementing gamification techniques, even though a large number of models now exist (Tondello, Kappen, Mekler, Ganaba, & Nacke, 2016). Additionally, research tends to focus on individual elements rather than the motivational drives behind the elements. To our knowledge, Octalysis is the most comprehensive

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framework on motivation in gamification. Moreover, it is the only one that discusses the drives of scarcity and avoidance (Tondello et al., 2016).

By studying the types of motivation behind the elements and how these are perceived by the consumer, this thesis attempts to understand the forces at play behind the game elements rather than the elements in themselves. This knowledge can contribute to the existing body of work on gamification by providing a perspective that has generally been researched less than others, namely Black Hats.

1.3 Purpose

By examining consumer attitudes toward Black Hats, this thesis aims to contribute to gaining a better understanding of when and how to apply Black Hat gamification in marketing

contexts, both for the consumer and the marketeer.

Consumer attitudes toward Black Hat designs are valuable to obtain because they provide designers and marketeers with knowledge regarding when and how these techniques should be used, and perhaps more importantly when they produce negative experiences that are rejected by the consumers. This could contribute to more effective implementation of Black Hat gamification from the perspectives of both the consumer and the marketeer.

1.4 Research Question

Based on the purpose of this research, the following research question was developed:

RQ: What attitudes do consumers have regarding Black Hats in gamification and what are the reasons for these attitudes?

Attitudes are relevant to analyze because they are an important factor in determining behavior (Ajzen, 1991). Attitudes consist of two components, affect and cognition (Eagly & Chaiken, 1993). Affect primarily concerns feelings and emotions whereas cognition is about thoughts and beliefs.

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Examining the affective component captures how Black Hats are experienced by consumers in terms of feelings and emotions. According to Deterding et al. (2011), a positive experience within a game or gamified system tends to induce motivation for continued use. Additionally, a positive experience can be regarded as desirable for consumers whereas a negative

experience is undesirable.

Gaining a better understanding on consumers’ thoughts and beliefs on Black Hats may give answers regarding what contexts consumers believe is appropriate for Black Hat

gamification. Knowing this will provide insight for marketeers to determine when

gamification is perceived as ethical and desirable by consumers, and aid in deciding whether to gamify their service or not. Understanding the reasons for why consumers accept or reject these motivational designs can therefore be of value for both the consumer and marketeer.

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2. Theoretical Background

2.1 Definition of a game

Games are structured by including multiple necessary conditions. Games cannot consist of a single necessary condition but emerge once a set of those necessary conditions are combined (Deterding et al., 2011; Juul, 2003). Although pre-existing definitions of a game have

included various necessary conditions to ultimately be defined as a game, the common

feature is that these conditions can be divided into two components (Huotari & Hamari, 2012, 2017). A game has a systematic component, that describes the construction of the game, and an experiential component, that describes the human involvement with the game.

Furthermore, conditions for a game can be separated into three levels of abstraction. The first level of abstraction includes the systematic conditions of game-mechanisms and the

experiential condition that a game requires a player (Huotari & Hamari, 2017). The second level of abstraction includes the systematic conditions of game design elements, such as rules, goals, and uncertain outcomes (Huotari & Hamari, 2017). The experiential conditions at the second level of abstraction account for the players hedonic experiences and evaluation of uncertain outcomes (Huotari & Hamari, 2017). Conditions unique to games are at the third level of abstraction (Huotari & Hamari, 2017). However, previous literature on games has not been able to address conditions that are unique to games (Huotari & Hamari, 2017), which demonstrates the abundance of possibilities in game creation through endless combinations of conditions (Deterding et al., 2011; Juul, 2003). Researchers in the field are intrigued by the lack of unique experiential conditions at the third level of abstraction since there is no clear consensus as to which experiences can arise only from games and how the emergence of a game is recognized by players (Deterding et al., 2011; Huotari & Hamari, 2017; Juul, 2003).

2.2 Definition of gamification

There is no standard conceptualization of gamification (Seaborn & Fels, 2015). However, many sources agree that gamification refers to when services and systems through their design approach enhance the user experience to be more similar to that of a game (Deterding et al., 2011; Hamari, Huotari, & Tolvanen, 2015; Huotari & Hamari, 2012; Liu, Santhanam,

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& Webster, 2017). Even though “the use of game design elements in non-game contexts” (Deterding et al., 2011, p. 9) is accepted as a definition of gamification, the purpose of its use and its effects on humans affective and cognitive processes are disputed (Seaborn & Fels, 2015).

Gamification aims to motivate people to undertake desired actions (from a developer perspective) within the context in which the game elements are placed (Koivisto & Hamari, 2019), mainly through applying mechanics that are designed to satisfy intrinsic needs (Xi & Hamari, 2019). Research during the last decades have indicated that gamification can be used to leverage users’ engagement in a non-game context (Huotari & Hamari, 2017), including marketing (Huotari & Hamari, 2017), health care (Hamari & Koivisto, 2015; Sardi, Idri, & Fernández-Alemán, 2017; Schmidt-Kraepelin, Thiebes, Tran, & Sunyaev, 2018), education (Hanus & Fox, 2015; Muntean, 2011), and information systems (Liu et al., 2017). These examples indicate that there is a purpose in using gamification as a strategy to improve user experiences.

Gamification can also be used to recreate the positive experiences people are believed to obtain from engaging with games (Deterding et al., 2011). Gamification is successful when the positive experiences from the game-mechanics becomes associated with the environment they are placed in (Robson, Plangger, Kietzmann, McCarthy, & Pitt, 2015). Desired user experiences from the game-mechanics are the sense of autonomy, mastery, accomplishment, enjoyment, and flow, amongst others (Ryan, Rigby, & Przybylski, 2006). These feelings are recognized as intrinsically motivating and induce the user to “engage with the system simply for the sake of using it” (Robson et al., 2015, p. 413).

On the contrary, Zichermann (2011) argues that only catering to users’ intrinsic motivation may not be possible or necessary. Zichermann (2011) proposes that extrinsic motivators could strategically be altered into becoming internalized as intrinsic motivators, even though he acknowledges that there is a risk of decreasing motivation whilst increasing performance. The difference in what is considered successful gamification is one of the factors to why there is no universal theoretical foundation, and standards for practice in conceptualizing gamification (Seaborn & Fels, 2015).

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2.3 Intrinsic and Extrinsic motivations

Gamification is a useful tool for changing users’ behavior by attempting to tap into the motivational behavior of human beings (Robson et al., 2015). It can be accomplished by using reinforcements and emotions. Both positive and negative reinforcements encourage behaviors to be repeated, which has been described in psychology studies on operant conditioning (Skinner, 1938). Creation of motivation occurs because satisfactory outcomes from behaviors are also more likely to be repeated or motivate to further change the

behaviors (Skinner, 1938), which is regarded as a successful outcome within the field of gamification (Robson et al., 2015).

Motivations can also be grouped into either intrinsic- or extrinsic motivation (Skinner, 1938). Intrinsic motivation is a result of being motivated for the amusement of performing an action, while extrinsic motivation derives from external rewards, such as fame and money (Higgins, 2006). Both categories can serve as motivating factors for the recipient of the reinforcement (Higgins, 2006), as well as collaboratively create motivation (Harter & Jackson, 1992).

Extrinsic motivation poses an issue for consumers (Bittner & Shipper, 2014). Consumers already intrinsically enjoy games, and exposure to extrinsic incentives may diminish the intrinsic motivations present at the start of the consumer journey (Bittner & Shipper, 2014). Extrinsic motivational incentives such as points, leaderboards, badges, loyalty programs and rewards perform better when accompanied with intrinsic incentives such as storylines, avatars, and the sense of autonomy through choices because these elements may enhance enjoyment of participation in the game (Bittner & Shipper, 2014), and engage the consumers by promoting the intrinsic incentives (De-Marcos, Dominguez, Saenz-de-Navarrete, & Pagés, 2014).

2.4 Definition of Attitudes

Since this study attempts to examine consumer attitudes toward Black Hat gamification, one needs to define the construct of attitude. Eagly and Chaiken (1993) defined an attitude as “a psychological tendency that is expressed by evaluating a particular entity with some degree

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of favor or disfavor”. This definition functions as an umbrella term that posits three vital features, namely evaluation, attitude object and tendency.

Evaluation is explained by Eagly and Chaiken (1993) as referring to all types of evaluative

responding. This evaluative responding constitutes of all evaluative efforts, both conscious and unconscious. These evaluative efforts include the evaluating of some entity based on a person’s beliefs and thoughts, feelings and emotions, intentions, and overt behavior. Evaluation cannot occur without the existence of some entity that is evaluated. Eagly and Chaiken (1993) refer to this entity as the attitude object. The attitude object is the entity (or thing) toward which the evaluation is directed. Anything that can be evaluated on some level can therefore function as an attitude object. This can include concrete entities or things in addition to more abstract concepts.

Eagly and Chaiken’s (1993) pose that evaluation primarily consists of two components, the

affective and cognitive. The affective component refers to feelings and emotions regarding

the attitude object, in this case Black Hat gamification. The cognitive component captures the thoughts and beliefs about them. The combination of these two components together form the basis for an evaluation of the entity with some degree of favor or disfavor.

Differences in importance of affect and cognition in evaluating certain objects have been found. Kempf (1999) discovered that in hedonic products affect tends to be more important, whereas cognition is more important in utilitarian products. Since gamification combines both hedonic and utilitarian elements in one system, difficulties in evaluating may arise when affective and cognitive evaluation do not align. Moreover, Haddock and Zanna (1998) found that people that identified as “thinkers” tend to evaluate with their beliefs, whereas “feelers” evaluate through affect.

Lastly, an individual’s tendency to react positively or negatively toward an attitude object is grounded in the individual’s past experiences (Eagly & Chaiken, 1993). The term allows the researcher to consider previous experiences as a significant factor in determining attitude but leaves open the possibility of its smaller or absent role in the process.

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2.5 Octalysis

Octalysis is a framework within gamification designed by Chou (2015) that describes player motivation in gamified systems. Within Octalysis, there are eight Core Drives that motivate players to undertake actions. A Core Drive is a motivation that every person has to some extent, the strength of which varies between individuals as some people are affected more by certain Core Drives than others. Game elements attempt to appeal to particular Core Drives that function as motivators for players to make decisions and pursue certain actions. If none of the Core Drives are affected, the player is not motivated. All eight motivation types (displayed in figure 1) motivate players differently. Octalysis can be utilized as a tool to understand player motivation in games or gamified systems.

Figure 1. Octalysis Framework (Chou, 2015)

The eight Core Drives are displayed in an octagonal shape. The drives on the left side of the octagon tend to draw from extrinsic motivation whereas those on the right side are more intrinsically motivating (Chou, 2015).

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A short description of the first five Core Drives in Octalysis follows below, as given by Chou (2015). Core Drives 6-8 are Black Hats and will be covered more extensively in the next section given their importance to this study.

Core Drive 1: Meaning

Meaning refers to when users feel like they are doing something that is greater than

themselves, or that they were “chosen” to do something. Therefore, they spend a lot of their time creating, maintaining, and contributing to the game/project.

Core Drive 2: Accomplishment

This is a user’s drive for achievement, making progress and overcoming challenges.

Development and accomplishment often involve PBL (Points, Badges and Leaderboards) but are not limited to these.

Core Drive 3: Empowerment

The third Core Drive motivates users by engaging them in a creative process where they can continuously create new things or try different combinations. It simultaneously allows users to express their creative side while giving them feedback so they can see the results of their creativity.

Core Drive 4: Ownership

Ownership occurs when users are motivated because they own or control something. When someone feels ownership over something, they innately want to increase and improve what they own. This can refer to wealth, in-game currencies, projects, organizations, and

processes.

Core Drive 5: Social Influence

Includes all social elements that motivate people, such as: mentorship, social acceptance, social feedback, companionship, competition, and envy.

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Chou (2015) introduces the concepts of “White Hats” and “Black Hats”. White Hats can be found at the top of the octagon and are described as positive motivation elements that make users feel powerful, fulfilled, and satisfied. White Hats include Core Drives 1-3, meaning,

accomplishment and empowerment.

On the contrary, Black Hats are more negative motivation elements (Chou, 2015). These include Core Drives 6-8, scarcity, unpredictability, and avoidance. They can be found at the bottom of the Octalysis model. Black Hats are considered negative because although their motivational effect is evident, they tend to make players feel obsessed, anxious, and addicted. Black Hats are strong motivators because they create a sense of urgency among players. This is something that is lacking in White Hats. White Hat techniques are useful in creating a fun, rewarding experience for the players meaning they will enjoy their time and likely keep playing, but they do not create the necessary urgency that persuades a consumer into purchasing. A system that provides the user with meaning, accomplishment and

empowerment will give the user fulfillment but will not drive sales. This is why Black Hats are often utilized by companies, they trigger psychological effects that make the user stressed and forces a decision. Below follows an in-depth description of what Black Hats are and how they accomplish this.

Core Drive 6: Scarcity

This is the Core Drive of wanting something because it is exclusive, rare, or immediately impossible to attain, therefore making it more desirable (Chou, 2015). Many studies have been conducted regarding the effect of scarcity impacting a good or service’s desirability (Brock, 1968; M. Lynn, 1991). Studies have found that the value of an object is enhanced when it is scarce (Brock, 1968; Fromkin & Brock, 1971; W. M. Lynn, 1987). When an object is scarce or limited, people become more motivated toward obtaining it. This same theory can be applied to gamification practices. Hamari and Lehdonvirta (2010) explored how game mechanics create scarcity or an illusion of scarcity. By making certain items rarer than others, users often spend time trying to obtain them. This can be achieved by lowering the rate at which players are awarded certain items or rewards. Alternatively, when items are only made available once or at specific times in a particular time period it also appeals to this Core Drive. Chou (2015) writes that a powerful way of increasing a certain behavior is to put a

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limit on it. This technique is called appointment dynamics. It utilizes a formerly declared, or reoccurring time where users have to take the desired actions to effectively reach the win-state. It can cause users to associate a certain time with the desired actions and plan accordingly to use the gamified system at this time.

Finally, another common method of appealing to this Core Drive is by using torture breaks (Chou, 2015). A torture break constitutes a “sudden and often triggered pause to the desired actions”. Often, it includes a timestamp for when a user can come back to continue their actions. Because the user was forced to stop, it can cause them to become obsessive about wanting to return to the game. Therefore, this method appeals more strongly to the

Impatience aspect of this Core Drive.

Scarcity can induce feelings of obsession and urgency regarding obtaining items or features that are scarce, explaining its status as a Black Hat.

Core Drive 7: Unpredictability

Unpredictability refers to users not knowing what will happen next, therefore making it more engaging (Chou, 2015). Unpredictability in rewards has been found to have a positive effect on engagement (Howard-Jones & Demetriou, 2009). Psychologists have found that moderate risk-taking heightens motivation (Atkinson, 1957). Although differing theories exist on why this is the case (Weiner, 1985), an important factor is the release of dopamine in the midbrain area. Dopamine levels in this area of the brain have been linked to motivation to pursue a variety of pleasures, such as food, sex, gambling (Csikszentmihalyi & Csikszentmihalyi, 1992; Elliott, Friston, & Dolan, 2000) and video gaming (Koepp et al., 1998). Dopamine levels are at their highest when the likelihood of receiving a reward is roughly halfway between totally unexpected and completely predictable, i.e. 50% (Fiorillo, Tobler, & Schultz, 2003).

This same effect carries over to gamification techniques where unpredictability and

uncertainty are often used to engage and motivate users to continue using the platform (Chou, 2015). Among these techniques are the commonly used mystery boxes, often referred to as loot boxes. Mystery boxes utilize the Core Drive of unpredictability and curiosity through reward structures. By altering how rewards are given, either through altering the context in

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which a reward is given or the specifics of the reward itself. Often, rewards given to users are randomized to appeal to this Core Drive.

One could argue that there exists a link between unpredictability and gambling, and this is largely the reason that it is considered a Black Hat. Unpredictability is described as driving intrinsic motivation together with the drives Empowerment and Social Influence (Chou, 2015). This is because humans are by nature curious about uncertain outcomes. A player will experience more thrill to the experience and have an increased chance to maintain interest in game-mechanisms that have different outcomes even though the same action is performed. Chou’s (2015) described effects of interacting with unpredictable game-mechanism are influenced by Skinner’s (1938) theory on operant conditioning, which indicates the drives connection to core psychological functions in human beings.

Core Drive 8: Avoidance

This is the Core Drive that motivates through the fear of losing something or having undesirable events transpire (Chou, 2015). Often, failing to achieve something in-game or having your character die leads to negative consequences, whether that is in-game currency, amount of lives or something different. Logically, users will try to avoid this happening. Although lacking empirical research in the specific context of gamification, avoidance motivation is an established idea among psychologists. In avoidance motivation, behavior is instigated or changed by an undesirable, negative event, or possibility. This is opposite of approach motivation, where it is instigated by a positive or desirable event or possibility (Elliot, 1999). Many studies have found that people are more likely to change their behavior to avoid a loss than to make a gain (Belsky & Gilovich, 2010; Kahneman, 2013).

This same principle is applied to appeal to this Core Drive. Designers can create situations where the users stand to lose something in case they do not take the desired actions (Chou, 2015). This needs to be done in a careful manner, as too much reliance on this Core Drive actually de-motivates users. Additionally, a user’s response to this Core Drive is dependent on how much they have already invested in the experience, which means other Core Drives need to be present in the platform. If a user has already participated in the experience for many hours or days, they will respond more heavily to the possibility of losing something than if they had only invested a few minutes.

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Some ways of implementing this Core Drive into gamification systems include evanescent opportunities, countdown timers and the sunk cost prison (Chou, 2015). Evanescent

opportunities refer to an opportunity that will disappear if the user does not take the desired action immediately. Similarly, a countdown timer is a visual display that communicates the passage of time toward a tangible event. This can be either to signify the start or end of an opportunity. Both of these techniques create a sense of urgency among the users.

Another common technique that appeals to this Core Drive is the sunk cost prison (Chou, 2015). This occurs when a user has invested a substantial amount of time into something and continues performing the desired actions because they do not want to lose their progress, even if it is no longer fulfilling or enjoyable. The psychology of the sunk cost fallacy is well established (Arkes & Blumer, 1985), and it applies to gamification as well.

These techniques can create urgency and obsession and often leave players feeling

uncomfortable. Chou (2015) argues that they should exclusively be utilized in case the user has an urge to leave the system, as it can motivate them to stay.

2.6 User Acceptance of Information Technology

Hamari (2013) posited that the User Acceptance of IT model by Davis (1989) may be

relevant for gamification. The model consists of two variables that determine user acceptance of IT, namely perceived usefulness, and perceived ease of use. Perceived usefulness is

defined as "the degree to which a person believes that using a particular system would

enhance his or her job performance" (Davis, 1989, p. 319), perceived ease of use is defined as "the degree to which a person believes that using a particular system would be free of effort" (Davis, 1989, p. 319).

The constructs of perceived usefulness and perceived ease of use are a useful lens through which data can be interpreted. These constructs have previously been utilized in order to determine perceived benefits from gamification (Koivisto & Hamari, 2014). Especially the construct of perceived usefulness is expected to be a factor in determining user acceptance of Black Hats. Since Black Hats can cause unpleasant feelings (Chou, 2015), the cognitive evaluation of whether or not the technology is useful could decide acceptance among consumers.

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3. Methodology and Philosophy

In order to understand the logic and reasoning behind the authors’ statements and

conclusions, the ontological and epistemological beliefs of the authors need to be made clear as well as the methodical approach. These beliefs will dictate the authors’ argumentation and understanding them will aid in critiquing the research (Easterby-Smith, Thorpe, & Jackson, 2015).

3.1 Research Philosophy

This study uses an interpretivist philosophy. Interpretivism is a research philosophy that is contrast to positivism (Bell, Bryman, & Harley, 2018). It stems from the view that there are differences between people and objects of science and that the researcher attempts to grasp the subjective meaning of social action (Bell et al., 2018). It is these subjective meanings that are created by humans that should be studied in order to gain a more in-depth understanding of the social world in a specific context. By using an interpretivist philosophy, the researchers can better understand the meanings that consumers assign to Black Hats in gamified systems, how they are experienced and how these subjective meanings are relevant in the development of attitudes. Generalizing based on the meanings described by the respondents is common in interpretivism and even desirable (Williams, 2000).

Within the philosophy of interpretivism, this study utilizes a phenomenological approach. According to Welman and Kruger (1999, p. 189), “phenomenologists are concerned with understanding social and psychological phenomena from the perspectives of people involved”. Phenomenology assumes that people are active in experiencing the world and actively construct social reality. It then attempts to understand the meanings of these experiences. In this particular case, this study attempts to understand how Black Hats are experienced - and what this means. Phenomenology allows the authors to capture the subjective experiences of the users of Black Hat applications. Within phenomenology, the researcher is not disconnected from their own previously held views and should not pretend to be (Hammersley, 2000).

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3.2 Research Design

Given the choice of the philosophical paradigms, this thesis is qualitative. Qualitative

research is difficult to define since it encompasses various methods and strategies (Silverman, 1993). It is generally accepted that the key features of qualitative research are an interpretivist epistemology and the ontological position of constructionism, which poses that social

properties are outcomes of the interactions between individuals rather than phenomena separated from the individuals involved in their construction (Bell et al., 2018). Additionally, Bell et al. argue that qualitative research tends to have an inductive view of the relation between research and theory in the sense that research is what generates theory. Outside of these three assumptions, researchers are hesitant to specify the exact nature of qualitative research (Bell et al., 2018). The first reason given is that various research methods exist within qualitative thinking that differ significantly. Based on which method is chosen by the researcher, the process can be drastically different from other qualitative research methods (Bell et al., 2018). This makes it hard to assign specific qualities to qualitative research as a whole outside of the general assumptions given previously. Secondly, the link between theory and research is somewhat more ambiguous in qualitative research than quantitative (Bell et al., 2018). In qualitative research, theory is supposed to flow from research. The authors of this thesis subscribe to this view of qualitative research.

This study follows an exploratory approach. Exploratory research aims to gain a better understanding of a problem rather than to provide conclusive evidence (Saunders, Lewis, & Thornhill, 2012). The choice of this approach is motivated by the nature of this study, namely the investigation of experiences and attitudes of consumers toward Black Hat gamification. Little research into this specific topic has been conducted, indicating a need for an

exploratory study that lays a foundation for potential future conclusive and descriptive works. An exploratory research approach leaves the possibility of a multitude of possible

explanations or solutions for a problem, whereas other approaches attempt to land at a single final conclusion (Stebbins, 2001). This openness is appropriate for this research because it investigates experiences and attitudes but cannot conclusively prove why these experiences and attitudes exist. Instead, the experiences and attitudes will be explored, and possible explanations as given by the participants considered.

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3.3 Research Approach

This study is conducted with the use of abductive reasoning. Given the exploratory

qualitative nature of this thesis, it is not appropriate to make deductive inferences. This study cannot prove the inferences made due to the limited sample. Inductive reasoning is not utilized either as the study builds upon existing theory within gamification and more

particularly the framework of Octalysis. Given this reliance upon previous theory, this study cannot be regarded as purely inductive. Hence, abductive reasoning was chosen.

Abductive reasoning solves the problem of inductive reasoning in that building theory may not always be possible, regardless of how much empirical data is analyzed (Bell et al., 2018). Abductive research enables the researcher to select the “best” explanation from competing theories or explanations of the data (Lipton, 2004; Niiniluoto, 1999; Van Fraassen, 1980). Typically, abductive reasoning starts with a surprising fact and then attempts to explain it. In this case, the researchers have found the phenomenon of Black Hat technique implementation in popular mobile applications. Many of these applications are popular among consumers, despite Chou’s (2015) reservations about their possible negative effects on them. This study aims to clarify why this is the case by examining how the techniques are experienced by the consumers, what their attitudes toward Black Hats are and the reasons given for these attitudes.

3.4 Data Collection

The researchers considered various study designs, ultimately deciding to proceed using semi-structured interviews. A semi-semi-structured interview entails an interview in which the

interviewer has a series of questions but is able to change the sequence of these questions (Bell et al., 2018). Moreover, the interviewer is free to ask further questions in response to perceived significant replies (Bell et al., 2018). In qualitative interviews such as the semi-structured interview, interviewees are encouraged to answer extensively and formulate detailed answers as this can give the researcher new insights. Qualitative interviews tend to be flexible and allows the researcher to change emphasis based on answers given by the participants (Bell et al., 2018).

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Bell et al. note that in the case that researchers start research with a reasonably clear focus, semi-structured interviews are well employed to address these specific issues. Given that the aim of this study is to examine consumer experience and attitudes toward Black Hats

(unpredictability, scarcity, and avoidance) and the reasons given for these attitudes, semi-structured interviews are appropriate as they allow the interviewees to describe their experiences in detail. Additionally, the attitudes given by the participants can be described and explained at length. This grants the researchers relevant and profound qualitative data to analyze.

Prior to conducting the interviews, an interview guide was developed to aid the researchers in asking relevant questions. Although semi-structured interviews grant the researchers

flexibility to alter the order in which questions are asked, a certain amount of order to the areas of interest was established to promote flow within the interview. This is recommended by Bell et al (2018). Moreover, questions were developed with the research questions in mind – a clear connection to the purpose of this study is required. Additionally, the researchers were careful not to formulate leading questions.

The decision was made to conduct the interviews over Skype. The interviewees were instructed to perform the interview in a quiet place with little distraction to ensure higher quality of discussion. The researchers conducted the interviews from their own homes. Conducting the interviews through Skype allowed the researchers to simultaneously perform the interview while recording the audio through the same program. The interviews were conducted using audio only, therefore body-language and facial expressions were not captured. This decision was made after the first three interviewees all requested to use exclusively audio. For the sake of consistency, all subsequent interviews followed the same format. Each interview was audio-recorded through Skype and subsequently transcribed.

3.4.1 Challenges in Data Collection

This thesis purpose is partly investigating consumer motives, which is a concern regarding the data’s possibility to depict reality. After a study on motivation conducted by McClelland (1965), he concluded that people may have difficulties articulating their own motives and many times form these on perceived congruency with commonly accepted half-truths

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(McClelland, 1965). During the interview, participants received a description of the Black Hats and the Octalysis Framework by Chou (2015). This means that participants might have been influenced by this information in their responses on some of the questions.

According to Poggenpoel and Myburgh (2003), the researchers themselves can be the greatest threat to trustworthiness in qualitative interviewing. In order to reduce biases, the researchers spend time preparing for the interview and constructing appropriate questions. These questions were sent to an expert in the field of gamification studies to confirm the quality and reliability of these questions. Additionally, a pilot interview was conducted to aid the researchers in preparing for the subsequent interview sessions. This is important, as neither author of this thesis has prior experience in conducting qualitative interviews. Pilot studies provide the advantage of allowing the researchers to see where the interview could fail or are too complicated (Van Teijlingen & Hundley, 2001).

3.5 Research Strategy

In order for the data to be valid, the researchers wanted to give participants the chance to experience Black Hat gamification before the interviews were conducted to help familiarize them with the techniques. Even though Black Hat techniques are prevalent in mobile applications, the concepts as defined by Chou (2015) are rather abstract and difficult to conceptualize without having explicitly experienced their effects. The researchers decided that it was important to let the participants experience some applications that utilize Black Hat gamification for a period of time before the interview in order to promote relevant discussion. It may have otherwise been difficult to get relevant answers because even in the cases that participants already use the applications naturally, they may not necessarily consider specific design elements.

The participants received a guide instructing them to use the determined applications for at least five days before the interview, preferably a week or more. This places all participant within the same context of experiencing applications that include Black Hat design.

Criticisms may arise that this process to some extent imposes a predetermined format on the social world, as Bell et al. (2018) argue that a predetermined format tends to be the product of the researcher’s expectations of what might be found. There is some merit to this criticism.

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However, Black Hats by definition imply that negative experiences should arise upon encountering them. Providing practical examples of their application is intended to give the participants an idea of how a Black Hat technique may be experienced in practice, not to impose expectations of what they should experience. The process of selecting appropriate applications for the participants was grounded in the intentions to be as neutral as possible to avoid imposing expectations and biases.

3.5.1 Selection of Applications

Initially, the Black Hats needed to be individually understood and identified within applications. A review of the literature available on Black Hats was conducted to aid the researchers in identifying instances of applications where Black Hats are utilized. Once this was completed, the researchers tested an extensive selection of applications. Potential applications were drawn both from personal experience in addition to comprehensive testing of the most popular applications in Google Play. Other applications were identified by

reading online blogs and websites that discuss and promote mobile applications in the context of gamification. This process ensured that the applications in this study are applications that consumers can reasonably be expected to encounter naturally in their daily lives. In many cases, the participants had previous experience with the applications.

For a mobile application to be considered for this study, it had to fulfill the following criteria: 1. It is easily accessible for consumers.

2. It contains at least one of the three Black Hats; unpredictability, scarcity and/or avoidance. 3. It does not require payment or premium membership.

A total of 46 applications were considered for the study and analyzed. After conducting the initial exploration of applications that fit these criteria, 22 applications were identified as potentially viable for the study. This number was reduced to 8 by testing and considering how Black Hats were implemented within the applications. The applications that were removed in this step were considered either too narrow or did not have a robust enough implementation of Black Hats. Applications that did not have a robust enough implementation of Black Hats did contain Black Hats – but they would be difficult to examine and may be confusing for the

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participants. Additionally, applications that are subject to sensitive topics were removed from consideration. The applications remaining after this step all had an obvious and/or significant component of Black Hats in them that the researchers deemed useful to examine and discuss. Additionally, these applications were intuitive to use so that the features that utilize Black Hats were easily accessible. This means that the Black Hats were presented in a manner that is as neutral as possible and reduces interference by the researchers while still providing the opportunity for productive discussion in the interview sessions.

Out of the remaining eight applications, the researchers selected three applications that were to be used by all participants in the study. These applications were Wish, Duolingo and

Forest. Two more applications, Zombies, Run! and Slowly, were proposed to the participants

as optional. These applications could provide value to the researchers but were not of vital importance to the outcome of the study. A description of the three applications used for this study are provided below.

Wish

Owned by: Wish Inc. Version: 4.38.0

Description: Wish is an online shopping platform based in China that offers “over 100 million” (Google Play) items for low prices. Items include fashion, accessories, home goods and electronics, among other things.

Reasoning: Wish was chosen because the application has a clear element of unpredictability as described by Chou (2015). Unpredictability comes in the form of a wheel that users can spin once a day which grants them a certain number of discounts on a selection of items. The number of items that the discount applies to is decided by the wheel. Once the wheel has been spun, the discounts are available for 10 minutes, which introduces an element of avoidance.

Duolingo

Owned by: Duolingo Version: 4.55.1

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Description: Duolingo is a tool for language learning in multiple languages to improve users’ skills in writing, speaking, listening, and reading abilities. During the learning process you gather points, achievements, and in-game currency.

Reasoning: Duolingo has several elements of scarcity and avoidance. Scarcity is experienced due to the hearts system. A player can have at most five hearts. If a question is answered incorrectly, the user loses a heart. Once the user has used up all their hearts, they have to wait until the next day when the user receives five new hearts. The scarcity refers to the hearts, which can only be obtained by waiting until the next day or through purchasing with in-game currency. Additionally, scarcity is experienced through the effect of not being allowed to complete lessons as a result of not having any hearts remaining.

Avoidance is implemented into Duolingo with the streak counter. Every day, once the user

has completed a lesson, a notification is received that states how many days in a row the user has completed at least one lesson. This motivates players to do more lessons with the purpose of not breaking the streak.

Forest

Owned by: SEEKRTECH CO., LTD. Version: 4.14.3

Description: Forest is an applications designed to help you use your phone less and focus by planting a tree and keeping it alive. While using this application, you cannot use your phone for other purposes until the tree has fully grown, otherwise it will die. This game has an in-game currency you can buy additional types of trees for your forest.

Reasoning: Forest is an app that is built around the principles of avoidance. The user is motivated to stay in the app because leaving the app means that the tree dies. Users should avoid this happening.

Additionally, Forest has implemented an element of scarcity. Additional types of trees are available in the application’s store. This can be done by paying for them with in-game currency, which can only be earned by successfully growing trees.

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3.6 Sampling

A non-probability sampling design was used and more specifically, convenience sampling. This sampling method bases the selection of participants on their perceived accessibility. This may include individual’s in the researcher’s immediate surroundings and existing social network (Easterby-Smith et al., 2015). Although issues of generalizability exist with convenience sampling, Bell et al. (2018) write that studies using convenience sampling can be used as a “springboard for further research or allow links to be forged with existing findings in the data” (p. 201). Given the qualitative and exploratory nature of this thesis, making generalizable claims is not the aim. Instead, this study aims to provide initial insights into this relatively new field that provide a basis for future quantitative studies.

This research’s qualitative data was not statistically analyzed. Representation of the sample as part of the population is of less concern as this thesis research method aims at exploring the lived experience and meaning assigned by consumers rather than measuring variables. In interpretivist qualitative research, convenience sampling is an accepted method (Collis & Hussey, 2014, p. 131). Thus, selecting a sample under an interpretivist paradigm allowed the researchers to use a non-probability sampling method.

Students were found to be the most accessible individuals to participate in the study because of the authors pre-existing network in that particular social sphere. Furthermore, the sampling frame was set to be students at the Universities the authors previously had conducted studies in, which included Jönköping University (Sweden), SSE Riga (Latvia), Yonsei University (South Korea), and Corvinus University of Budapest (Hungary).

All individuals who accepted the request were included in the sample. There was a total of 8 participants, whereof seven were male and one was female. The nationalities of the

participants were Austrian, Dutch, French, Greek, Hungarian, Lithuanian, Swedish, and American (USA).

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29 3.6.1 Challenges in Sampling

By not having any restrictions on who can participate in the research there is a potential risk of self-selection bias (Easterby-Smith et al., 2015). This is because those who chose to participate in the research may have different characteristics than those who did not. A possible consequence of this is creating a biased sample.

Additionally, the use of statistical comparisons and aggregation of data is not possible since the findings from this research contain non-numerical data and is based on a small sample size (Easterby-Smith et al., 2015). It is unfeasible to claim that the findings in this research are applicable to larger groups of the population because of the small sample size.

3.7 Interview Guide

After the sample had been decided upon, the participants were interviewed using the aforementioned semi-structured interview method. An interview guide was developed in order to aid the researchers in asking relevant questions. This interview guide was divided into two main sections. The first section consisted of questions about the individual applications that the participants were asked to use. The second section introduced the

matters of Black Hats by providing the participants with a definition of each individual Black Hat as given by Chou (2015), followed by more questions and discussion. A more detailed description of the interview process is given below.

Introducing the Research

Prior to each interview, the participants were thanked for their participation. Moreover, the participants were informed about their right to withdraw from the interview at any time, abstain from answering any questions and request the researcher to stop recording. Additionally, participants received the information that the answers given would be completely confidential and anonymous.

After permission to record the conversation was granted by the participant, the researcher started recording. A short description of the research problem was given, and the opportunity

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was given to the participants to ask questions or require clarification. Once this was completed, the interview moved into the next stage.

Application-specific Questions

In this stage of the interview, the participants’ experience with the applications of Wish, Duolingo and Forest were discussed, in that order. In the case that the participants utilized either optional applications (Slowly or Zombies, Run!), questions were prepared as well. The line of questioning started with inquiring about the participants’ experience with the

applications in general. Then, questions were asked about the specific mechanisms within the applications that utilize Black Hat gamification. These questions started out as general

inquiries about experiences, feelings and attitudes and were narrowed down or followed up on depending on the answers given by the participants. Some applications required more specific questions to specify what mechanisms should be discussed. This section’s aim was to get an accurate description of the participants’ experience with Black Hat gamification

elements without explicitly explaining what they are.

Black Hat Questions

The next section begins with the researcher presenting the participant with a definition of each Black Hat as given by Chou (2015). This was done to give the participants an opportunity to conceptualize the Core Drives before discussing them further. After each definition, the participants were given the chance to ask questions should the need for clarification arise. Once this was completed, questions were asked with more specific focus on participant attitudes toward the use of these Black Hat techniques. These questions were asked after presenting the definitions to promote relevant and informed discussion since Black Hats can be difficult to conceptualize in an interview. Again, the researchers followed up answers by asking further questions to perceived significant answers.

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31 Finishing the Interview

After all topics were discussed, the participants were given the chance to ask questions or engage in further discussion. Subsequently, the researcher thanked the participant for participating in the research and stopped recording.

3.8 Reliability and Validity

Reliability and Validity are matters that are of primary concern within quantitative research but are relevant in qualitative research as well. Reliability refers to whether the results of the study are repeatable (Bell et al., 2018). Given the qualitative and exploratory nature of this study, results may not be repeatable as different people have different experiences and attitudes and might provide vastly differing answers. Reliability tends to be more important for quantitative research than qualitative (Bell et al., 2018), no less due to the smaller sample size qualitative studies tend to have.

Validity accounts for the integrity of the conclusions that research proposes (Bell et al., 2018). While translation issues from quantitative research to qualitative exist for this construct as well, Mason (2017) argues that reliability and validity in qualitative research essentially refers to whether the researcher is observing, identifying, or measuring that which they say they are. The researchers attempted to accomplish this by describing in detail the procedure and reasoning behind decisions made in the research process.

3.9 Data Analysis

Once the interviews were completed, the audio recordings were transcribed. The data emerging from this was subsequently divided into relevant categories for the purpose of the research through the process of coding. Coding is described by Bell et al (2018) as a process in which transcribed data is broken down into component parts that are assigned labels. For this this thesis, the components included affective responses and cognitive evaluations of each Black Hat. Moreover, themes emerged regarding the alignment of Black Hats and consumer interests, and ethical considerations. All categories are presented in the results

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chapter along with the empirical support provided by the data. A more in-depth analysis can be found in the analysis chapter.

3.10 Ethical Discussion

An application form for processing of personal data in thesis work has been signed as an assurance that the researchers have followed the regulations in accordance to Article 30 of the General Data Protection Regulation (GDPR).

The researchers have taken the following steps to assure that both GDPR and any other addressed ethical issue was followed:

1. Interviewees were informed on the potentially scientific contributions and purpose of the research prior to their participation.

2. An interview transcript was sent to the participants in adherence with the interviews as an ethical stance to the participants willingness to answer the questions.

3. Consent upon the request of recording the interviews were obtained from participants prior to the interview.

4. The researchers informed the participants that their responses during the interview could potentially be subject for quoting and analyzed for scientific contribution through this thesis.

5. Anonymity in participating in the research was assured to make participants feel safe, and in turn, allow for extraction of honest responses on questions.

6. Transcription of the recorded material was conducted thoroughly to assure that everything was included, correctly interpreted, and not misheard.

7. Participants were also informed that they could withdraw from the study at any point.

This means the researchers have addressed and prioritized any ethical issues during the creation of this thesis. Jönköping International Business School was assigned as the data controller for this thesis and have granted the permission to conduct this research.

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4. Findings

This section presents the data resulting from the interviews empirically. Results are divided into themes that emerged from categorizing the answers given. First, the affective responses are presented for each individual Black Hat. This helps create a clear image of what was experienced in terms of feelings and emotions by the participants. Then, the most relevant cognitive, thought-based evaluations for each Black Hat are presented. In the second section, the more general cognitive evaluations that apply to all Black Hats are described. This way, both components of attitude as described by Eagly and Chaiken (1993) are presented in accordance with the research question. A more in-depth examination of the themes presented here can be found in the analysis section.

Distinction between affective responses and cognitive evaluations

Affect is the first component of Eagly and Chaiken’s (1993) definition of attitudes. Affective responses concern people’s feelings and emotions regarding an attitude object. The cognitive response is the second component of evaluation of an attitude object (Eagly and Chaiken, 1993). It refers to the thoughts and beliefs about the attitude object, in this case Black Hat techniques.

4.1 Avoidance

“This is the Core Drive that motivates through the fear of losing something or having undesirable events transpire. It is the motivation to avoid something

negative from happening” (Chou, 2015, p. 309)

Avoidance was featured primarily in the Forest application. The user is motivated to stay in the app because leaving the app means that the tree dies. Users should avoid this happening. Moreover, elements of

avoidance were present in Wish as users only have 10 minutes to use the discounts obtained by spinning the wheel. Lastly, Duolingo introduced avoidance through the daily streak counter. If no lesson is completed on a given day, the streak accumulated by the player is reset to zero. This

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34 4.1.1 Affective Responses

Several answers by the participants indicated an affective response to experiencing elements of avoidance. These are categorized below.

Fear

First, participants mentioned a feeling of fear when using systems with avoidance.

“So, we kind of fear losing something you really worked on. This is kind of a serious drive so let’s say that I am playing a game for like months or years let’s say- you put in a lot of effort into making it then you are basically losing a level that took a lot of time – then it makes you quite crazy I think in general” (P4).

Additionally, the Black Hat can make one feel “crazy” according to this participant. Another participant mentioned fear but used it to describe a lack of fear of losing in Forest.

“… since I did not care for the tree at all, it could not work for me, there was no fear of losing the tree” (P2).

Regret and Guilt

Additionally, feelings of regret and guilt were indicated as well, particularly when asked to elaborate on their experience with killing a tree in Forest.

“The one that I killed, I kind of had to because I had to make a call, but it was still bad because it asked me if I’m sure about it and it gave me a few seconds to kind of regret it or like for a second, thought about it” (P6).

“There is kind of like a guilt element. You know it is not a real tree, but still. I think they nailed it; I like the concept. Because, you know, it is like killing an animal” (P6).

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35 Sadness and Disappointment

Having to give up on one’s goal and killing the tree in Forest induced feelings of sadness and disappointment for some participants. Reasons given for this were desires to stick to a

commitment and to avoid giving up.

“And it would be very sad if you give up right before you do the time” (P1). “Actually, you would probably be disappointed in yourself if you don’t stick to it”

(P8).

Pushy and Predatory

Some participants referred to the use of avoidance in Wish as pushy. The countdown timer was compared to store vendors pushing a sale.

“… it kind of looks like a very pushy- they are trying to really push the sale and give you just 10 minutes to do it or else you lose it” (P3).

“It’s the same as if a vendor would pressure me in a store to buy something, you know. I wouldn’t stay in a store if the vendor was pushy like that” (P2).

Additionally, one respondent experienced the countdown timer as predatory.

“I don’t know how to put it, maybe a bit predatory? It makes sense from a business standpoint, that’s why they use it, they kind of impulse me” (P5).

Motivation and Encouragement

All aspects of affective experience in relation to avoidance thus far are inherently unpleasant or uncomfortable. In contrast to these are answers that indicate feelings of encouragement and motivation due to the exposure to avoidance in Forest and Duolingo.

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“I think it’s quite motivating” (P1).

“It actually encourages me to use more of Forest […]. Because, fundamentally it is good for me to use forest, because I need to focus” (P6).

Summary Affective Responses Avoidance

In summary, avoidance induced many emotional responses that can be categorized as inherently uncomfortable or unpleasant. These feelings were fear, regret, guilt, sadness, and disappointment. Additionally, participants called the use of avoidance in Wish pushy and predatory. However, the same techniques that caused these emotions were perceived as simultaneously encouraging and motivational, sometimes by the same participants who had initially discussed them negatively.

Lastly, not all participants exhibited a strong affective response, instead indicating an indifference to the game elements that appeal to avoidance.

4.1.2 Cognitive Evaluations

It helps you do something positive

The most common cognitive response to the use of Black Hats in applications was that it was desirable because it helped the users accomplish something positive. This was only the case for Duolingo and Forest, no participant discussed similar thoughts for Wish.

“Well, since Duolingo and Forest, they are really for a good thing and you’re learning something or you’re putting away your phone, those are good things. So, I think, I don’t mind it” (P1).

“Kind of like this, put your phone away and focus on what you are doing right now, and I can imagine that a lot of people have a problem in doing so, and that this app could benefit them a lot” (P8).

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“So, those kind of apps that want to make people to concentrate, to study, and maybe to do something, to maybe go to the gym, I think they should use those. Because then people also think about what is good for them” (P6).

This reason was especially common for avoidance, it rarely occurred in discussion about scarcity and never for unpredictability.

“Because, I feel like this Wish wheel, it could be very effective, but for me it just didn’t really work at all because I just ethically don’t want to use the app at all. And I guess that the same techniques that were used there were also used in Duolingo and Forest, and there I had a completely different experience, so, for me it really depends. I don’t have anything against these techniques if they are used

in a good context” (P1).

4.2 Unpredictability

Unpredictability is understood in Octalysis as “users not knowing what will happen next, therefore making it more engaging. This Core Drive is the main force behind our infatuation with experience that are uncertain or involve chance” (Chou, 2015, p.

271).

Unpredictability was experienced by participants in Wish through a wheel that users can spin once a day which grants them a certain number of discounts on a selection of items. The number of items that the discount applies to is decided by the wheel. The wheel in Wish was the only mechanism that appealed to unpredictability in the applications used for this study.

Figure 3, the Wish wheel that was used by the participants to experience an element with unpredictability

Consumer Attitudes toward Black Hats : An Exploratory Study of Motivational Designs in Gamification