Gamifying OTT: a study on consumer attitudes toward game elements and OTT media service provider brands in gamification

概要

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Gamifying OTT: A study on consumer attitudes toward game elements and OTT media service
provider brands in gamification

Abstract
Purpose: The purpose of this study is to examine consumer attitude toward gamification in the context
of over-the-top (OTT) media service. The study focuses on game mechanics within the MechanicsDynamics-Aesthetics (MDA) framework and its effects on consumer attitude toward both
gamification and OTT media service provider brands.
Design/Methodology/Approach: A 2×2×2 between-subjects factorial experiment was conducted to
examine the three core elements of game mechanics—components, controls, and courses on
consumer attitude—which was operationalized in 8 vignettes with a sample size of 296.
Findings: It was found that the three elements in game mechanics demonstrated a multiplicative effect.
The different combinations of elements in game mechanics resulted in eliciting different consumer
attitudes toward gamification and OTT provider brands. Despite one combination that was
associated with high positive consumer attitude toward gamification in OTT, this combination was
not effective in creating a positive attitude toward OTT provider brands. The findings demonstrate
the need for OTT providers to be clear regarding their gamification objectives before selecting the
combination of game mechanics.
Originality: This is the first paper to examine consumer attitudes toward gamification and OTT
providers based on game mechanics. It provides an understanding regarding the interaction of
elements in game mechanics and reveals that different element combinations can be utilized to meet
different goals.
Research Limitations/ Implications: This study adds to the body of knowledge on consumer attitude
toward gamification, particularly in the OTT market.
Practical Implications: OTT providers must determine their objectives for using gamification and
design the game mechanics according to the optimal combination of elements—components,
controls, and courses.

Keywords: Gamification, Mechanics-Dynamics-Aesthetics (MDA) framework, game mechanics,
attitude toward game mechanics, attitude toward brand, OTT, components, courses, controls

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1. Introduction
The consumption of entertainment has undergone tremendous transformation with over-the-top
(OTT) providers introducing new rules to the game (Deloitte, 2019; Kim and Shin, 2017). The market was
expected to enjoy continual growth to reach $161.37 billion at an estimated compounded annual growth
rate (CAGR) of 55% in 2020 (Business Wire, 2020). The COVID-19 global pandemic—which led to the
closing of national and international borders, restricted travel, and reduced outings and public gatherings—
also contributed to the expansion of the OTT business in 2020 (Adgully, 2020; Business Wire, 2020). This
has also prompted broadcasters and digital media companies to boost their presence in OTT business
(Hodjat, 2020; Layton, 2020).
OTT is defined as an “online video distributor that delivers video programming content to
consumers over the Internet” (FCC, 2013) such as Netflix, Hulu, and Amazon Prime Video and it has
transformed and disrupted the manner in which individuals consume and interact with online content
(Balanzategui et al., 2018; Vassileva, 2012).
As the industry flourishes, various players continually enter the market, including TV and film
giants such as NBC and Disney (Ferm, 2019). In Japan, the OTT landscape is saturated with a mix of global
and local players, providing a plethora of choice for the consumer while ensuring stiff competition for OTT
providers (Hanabishi, 2020). YouTube is a major player in the streaming market in Japan, along with
AbemaTV, Amazon Prime Video, and TVer (Ochiai, 2019; Tsuchiya, n.d.). AbemaTV and TVer are
Japanese OTT providers, the latter being the outcome of a joint collaboration between five commercial
broadcasters in the Kanto region that is made up of Tokyo and its neighboring 6 prefectures (Tsuchiya,
n.d.).
Despite the immense market growth, research on OTT services in the area of consumer behavior is
mainly limited to adoption behavior (Barnajee et al., 2013; Cha, 2013; Tse, 2016). Studies have indicated
that content and experience play significant roles in determining consumer acceptance, adoption, and
loyalty (Barnajee et al., 2013; Cha, 2013; Communications Today, 2019; PricewaterhouseCoopers (PwC),
2019), thereby leading to more OTT providers venturing into the creation of original content.
The introduction of OTT has revolutionized the video-on-demand (VOD) landscape, where
OTT—as a subset of VOD—has brought changes through the introduction of multiple subcategories. VOD
comprises of two categories—one that requires a TV or cable subscription and the other is OTT, where
content is accessed through the internet and the need for traditional cable subscription is eliminated. Various
factors have attributed to the strong growth experienced by the OTT sector, such as the availability of
infrastructure and other forms of market enablers, such as the proliferation of access to mobile devices,
high speed broadband, and changes in consumer demand (Ooyala and Vindicia, 2015). The value
proposition of OTT has also contributed to popularizing OTT, as if offers the flexibility to consume content

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at any time and any place, particularly for young consumers who are digital natives and more comfortable
with using technology (Docomo Digital, 2019).
Social computing has changed the OTT landscape further, creating enriching consumer experiences
through active social media connections (El Sawy, 2003; Lopasso, 2011; Oestreicher-Singer and
Zalmanson, 2013). This transformed the OTT platform from merely content delivery to include social
interaction (Lopasso, 2011; Yan et al., 2013). Oestreicher-Singer and Zalmanson (2013) found that while
consumer engagement with content and other consumers through sharing, commenting, and posting lead to
enhanced experiences, OTT providers focus more on content instead of social experiences. Thus, studies
on OTT and the consumer have been focused on the consumer’s motivation in OTT adoption (Cha, 2013;
Cha and Chan-Olmsted, 2012), while social experiences remain unexamined. Studies have also reflected
that creating and enhancing the social aspect is the biggest challenge for OTT providers (Crumlish and
Malone, 2015; Oestreicher-Singer and Zalmanson, 2013; Porter, 2008). This creates a need for further
research on exploring the requirements for and means of crafting social interaction and engagement.
Gamification has been identified as an effective approach to create engagement (Dominguez et al.,
2013; Merino de Paz, 2013). It increases consumer participation and provides unique experiences (Koivisto
and Hamari, 2019; Yang et al., 2017). This is a sentiment echoed by OTT providers, as they experiment
with gamification. Through gamification consumers are provided with enjoyable experiences, regardless of
the outcome (Snodgrass et. al., 2016; McGonigal, 2011). Gamification has been embraced by various
brands to gain wider awareness, establish presence in the market, grow their consumer base, foster stronger
bonds, and strengthen consumer engagement and loyalty (Blank, 2020; Ligue de Football, 2020; Punzo,
2019).
Against this background, this study specifically examines game elements that influence consumer
attitude toward game contents and OTT providers. Various industry reports have highlighted that younger
consumers are the main consumers of digital content and connected devices (Docomo Digital, 2019; Ooyala
and Vindicia, 2015), thereby supporting the relevance of this study. Thus, the following research questions
are posed:
RQ1: Which game element affects attitude toward the game?
RQ2: Which game element affects attitude toward the brand of the OTT provider?
RQ3: Which combination of game elements affects attitude toward the game?
RQ4: Which combination of game elements affects attitude toward the brand of the OTT provider?
Using the Mechanics-Dynamics-Aesthetics (MDA) framework by Hunick et al. (2004), this study
investigates the effects of elements such as badges, levels, and quizzes on consumer attitudes when offered
by OTT providers in varying degrees and combinations through gamification. Consumer attitude is
explored from two different angles—attitude toward game elements and attitude toward the OTT provider.

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The present study seeks to uncover not only how different elements affect consumer attitudes, but also
which element and what combinations are best in eliciting positive attitudes. The examination of game
elements and the influence on consumer attitudes is reflected by the items related to participants’ attitudes
using fictitious vignettes through an experimental design method.
This study also extends the MDA framework (Hunick et al., 2004) from gaming to gamification.
By investigating the elements that constitute game mechanics, this study delineates the intricacies of
interaction among the elements that generate different consumer attitudes. OTT providers can leverage the
findings of this study by testing different combinations to gain consumer engagement and loyalty.
In the next section, the concepts of gamification, the MDA framework, and game elements are
discussed. Thereafter, the experimental design, stimuli, sample, measures, and procedure involved are
outlined in the methodology section. This is followed by the results, discussion, and implications. Finally,
conclusions, limitations, and directions for future research are provided in the last few sections.

2. Theoretical Background
2.1 Gamification
The term gamification was first defined as taking game mechanics and utilizing them to other web
properties to enhance engagement (Terill, 2008). This scope has since been expanded to refer to the use of
game design elements in non-game environments (Deterding et al., 2011). Kapp (2012) defined
gamification as the incorporation of game-based mechanics as well as game-thinking and aesthetics to
create engagement, drive action, encourage learning, and solve problems. Gamification does not embrace
full-fledged contests but rather adopts elements of gaming—such as rewards, achievements, and
competition—and applies them in non-game settings (Prince, 2013).
Gamification has been extensively used in various fields, such as marketing, computer sciences,
education, health care, and tourism (Barata et al., 2015; Chou, 2017; Lucassen and Jansen, 2014; Mollick
and Rothbard, 2014; Nah et al., 2014: Prince, 2013; Zichermann and Linder, 2010). Store memberships,
both online and offline, and frequent flier programs are examples of gamification in providing loyalty
incentives. Customers who sign up for store memberships or frequent shopper cards are awarded points
based on their purchases and these points can be used as virtual currency to reduce the amount paid on their
next purchase. Frequent flier programs also grant points based on miles traveled, number of flights taken,
and fare paid (Gudmundsson et al., 2002; Prince, 2013). In the OTT industry, major players like Netflix
have introduced a choice-based narrative and timers in Bandersnatch, where consumers select their own
adventures and the unveiling of ZEE5 Super Family (ZSF) by ZEE5 that allows consumers to place bets on
TV characters and win prizes.

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The application of game elements in non-game contexts have been found to be effective across
different environments, such as customer loyalty programs, physical fitness, idea competition, and
sustainable consumption (Hamari et al., 2014; Prince, 2013; Witt et al., 2011). Studies have also found that
gamification helps foster desired behaviors and actions, such as studying and embracing greener or healthier
living (Brigham, 2015). The results of gamification have been studied extensively, predominantly
demonstrating positive outcomes that are dependent on the context and users (Hamari et al., 2014; Nevin
et al., 2014). However, certain game elements do not aid educational outcomes (Christy and Fox, 2014;
Hanus, and Fox, 2015) owing to the argument that gamification can be heavily focused on elements that
exploit extrinsic motivation from the reward environment (Brigham, 2015).
Gamification is not only focused on providing enjoyment but also increases engagement,
motivation, and activity—such as learning and problem-solving—thereby leading to the growth of social
media and mobile applications that utilize it (Brigham, 2015; Deterding et al., 2011; Seaborn and Fels,
2015). It leverages different motivators, like rewards, to drive and engage customers and users in
completing quotidian tasks (Prince, 2013). If designed well, gamification can create a stronger motivation
to continuously intensify participation. Increased engagement that often leads to retention and loyalty also
contributes to the creation of communities and collaboration (Brigham, 2015).
2.2 Game Elements
Gamification shares similar mechanics with games. Even though gamification utilizes game
mechanics to create a gratifying and absorbing experience, it differs from serious games. Serious games
offer a full-game environment with success tied to performance in controlling a character or object
(Deterding et al., 2011; Simões et al., 2013), while there is no full-game environment and rewards are
earned based on performance in an application software ((Högsdal, 2011). In order to motivate the
individual to complete the task, various elements are used, such as displaying an individual’s progress and
using leaderboards that introduce the component of competition, provide an environment of challenge, and
create a sense of accomplishment (Brigham, 2015; Hamari et al., 2014). The elements that are utilized by
gamification capitalize on competitiveness and the innate human nature of ambition to perform better
(Brigham, 2015). They also evoke a sense of gratification. Moreover, the mechanics afford a higher level
of consumer participation and boost interaction with others (Koivisto and Hamari, 2019; Yang et al., 2017).
Game elements are identified as the core components of gamification applications (Sailer et al.,
2017). The classification of elements vary according to the model—for example, based on the levels of
abstraction (Deterding et al., 2011) or in a hierarchical order (Werbach and Hunter, 2012). Werbach and
Hunter (2012) suggested that gamification elements exist hierarchically, comprising three levels in the
shape of a pyramid, known as the Game Element Hierarchy. Dynamics that sit on the top level of the
pyramid, provide the big picture aspects and motivation through various features like progression, emotions

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and constraints. Mechanics, the middle layer encompass processes such as turns and rewards, that motivate
player involvement. Components, the bottom layer of the pyramid refer to the specific examples of
mechanics and dynamics such as points, badges, or quests. They further categorized 15 typical game design
elements, such as badges, rewards, leaderboards, levels, missions, and progress as the most common
components (Werbach and Hunter, 2012). Brigham (2015) identified badges, points, and leaderboards as
easy to implement, while the creation of story, character, and interactive feedback require expertise.

2.3 The MDA Framework
The MDA framework by Hunick et al. (2004) was developed to analyze game elements by
simplifying them into three distinct components of consumption and mapping them to their design
equivalents. This framework helped put into perspective the relationship between the player and designer
and has been adopted in and adapted to various gamification contexts (Robson et al., 2015; Ruhi, 2015;
Winn, 2007). The definition of mechanics and dynamics in the MDA framework differs from that in the
Game Element Hierarchy. Mechanics refer to the specific components of the game at the level of both
algorithms and data representation (Hunick et al., 2004). In terms of game consumption, mechanics describe
the rules and define how the game is played. On the other hand, dynamics pertain to the behavior resulting
from the interaction between player and mechanics or, basically, the system from the perspectives of
consumption of games. It tells the player what needs to be done by applying the rules determined by the
mechanics. Finally, what is known as the fun component in game consumption, from the design aspect, is
identified as aesthetics. Aesthetics refer to the emotional responses that are aroused in the player when
interacting with the game system.
Hunick et al. (2004) postulated that from the player’s perspective, the component that creates the
tone of the game is aesthetics; aesthetics are shaped by dynamics, and dynamics are driven by mechanics.
However, from the perspective of the game designer, mechanics generate dynamic system behavior and
that produces aesthetic experiences (see Figure 1). Even though the starting point for both player and
designer are on opposite sides of the spectrum, it emphasizes the importance of both perspectives when
working with and crafting games. Simultaneously, it reflects that mechanics essentially shape the gaming
experience.
While the MDA framework breaks down game elements into three core parts that are causally
linked and interact and create the game, each of these components can be viewed separately (LeBlanc,
2004). Hence, this research adopts the concept of mechanics based on the definition in the MDA framework
and intends to delve into the single component of game mechanics to further examine the interaction among
components and its effect on the attitude toward a component as well as the OTT provider brand.

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2.2 Game Mechanics
Mechanics define the “win” conditions of the game. Mechanics encompass the rules and
components that define what the player can take on, the processes that guide the actions that the player can
take, and the stipulation for advancement and progression (Hunick et al., 2004; LeBlanc, 2005; Ruhi, 2015).
In this context, Ruhi (2015) categorized three core areas: components, controls, and courses (see Figure 2).
Components include points, badges, virtual goods, leaderboards, and avatars and serve as
representations of achievements and status (Ruhi, 2015). Components could also reflect the contribution
made—for example, reviewers who post on TripAdvisor or Yelp get badges and level progression to
motivate more contributions and engagement. On the other hand, Chorney (2012) suggested that a game
design that is based on points, badges, and leaderboards (PBLs) are insufficient in making gamification
successful.
Controls refer to mechanics that indicate to the player to improve performance, such as skills tests,
player turns, and task timers (Ruhi, 2015). Tests or quizzes serve to gauge the knowledge of the player,
while task timers test the skills of the player and serve as motivators. Sigala (2015) found that gamification
essentially affects motivational behaviors. The results and experience of using controls motivate the player
to either continue to develop, enhance, or improve the necessary skills to attain level progression.
The final element, courses, is the aspect of mechanics that guides the player to higher levels.
Courses and components are closely interlinked in enabling the players to undergo a sequence of relevant
achievements (Ruhi, 2015). There are various courses of action that essentially steer the player to attain a
higher position on the leaderboard, such as quests and levels.
An examination of the interaction among the three elements has been scant, as studies tend to
address components but not courses or controls (Siemon, 2017; Turan et al., 2016; Urh et al., 2015). Courses
and controls are hypothesized to moderate components, as components are the basic achievement of
gamification, thereby playing an essential role in attracting and motivating consumers to engage. Thus, the
following hypotheses are proposed and presented in Figure 3:
Hypothesis 1 (H1): Components, controls, and courses influence consumers’ attitude toward game
mechanics, where consumers have a positive attitude toward (a) high components, (b) high controls, and
(c) high courses.
Hypothesis 2 (H2): Components, controls, and courses influence consumers’ attitude towards OTT provider
brands, where consumers have a positive attitude toward (a) high components, (b) high controls, and (c)
high courses.

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Hypothesis 3 (H3): Controls and courses moderate the effect of components on attitude toward game
mechanics.

Hypothesis 4 (H4): Controls and courses moderate the effect of components on attitude toward OTT
provider brand.

3. Methodology
This research examines the effect of the interaction between the elements of game mechanics and
consumer attitude. In order to manipulate the variables and measure the effect on consumer attitude, a
quantitative approach using a between-subject factorial design experiment was conducted with eight
different experimental situations (see Table 1). Factorial design was suitable for this study, as one of its
advantages is that it enables simultaneous assessment of two or more parameters within the same sample
(Montgomery et al., 2013). Moreover, it identifies interaction among variables and the effects of numerous
variables on certain responses. Simultaneously, it restricts the desirability bias and confines the effect of
extraneous variables that might confound the findings.
To test the hypotheses, a web-based questionnaire was administered by an internet research
company that disseminated the questionnaire randomly to a pool of participants from its online panel. The
questionnaire was translated into Japanese and then back-translated into English to ensure accuracy and
consistency. The data was then analyzed using confirmatory factor analysis (CFA) and analysis of variance
(ANOVA) using SPSS ver. 26.

3.1 Design and Procedure
A 2×2×2 between-subjects experiment was designed for this study. The factorial design comprised
components (two levels: high, low), controls (two levels: high, low), and courses (two levels: high, low).
High and low refers to the quantity of elements made available to the consumer—for example, in the case
of high components, this implies numerous different types of component options such as badges, points,
and avatars that are made available to the consumer. In contrast, low components would translate to merely
one or two options. In this study, an experiment was selected over a survey, as experiments have the
advantage of reducing desirability bias in the responses. Survey participants have a higher tendency to
provide responses that are socially desirable, thereby increasing desirability bias (Mohr et al., 2001). The
examples used to illustrate components, controls, and courses were taken from Ruhi (2015).
Based on the combination of the three factors, eight cells were constructed to denote the respective
combinations of the three factors. The combinations were presented using vignettes and a picture depicting
the example of a mobile version of an OTT app. Both vignettes and picture constituted the stimuli and were

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administered to the participants along with the measures. The data collection was conducted in Japan using
an online panel. An initial screening was performed to exclude those who were not OTT media service
subscribers, leading to a final sample size of 296. After screening, the participants participated in two rounds
of data collection; the first was the selection of the elements for game mechanics, followed by the main
study conducted three weeks later, after the elements were finalized based on the first survey. The 296
participants, aged between 14 to 24 years (Mage= 17.84 , SDage = 3.11), were randomly assigned to the 8
conditions, with 37 respondents per cell.

3.2 Stimuli
The stimuli used in this study consisted of a picture and eight different vignettes. Vignettes were
selected as the stimuli, as they are commonly utilized in consumer behavior studies (Leclerc et al., 1995).
The vignettes were designed to reflect the composition of each category of game mechanics (components,
controls, courses), according to each condition of the (2×2×2) factorial design (see Appendix A for the
translated version of the original in Japanese). The content of each vignette included
a. a description of the mobile OTT app picture, and
b. a description of the condition of the components, controls, and courses.
A pre-test was conducted on the 8 vignettes with a group of 20 undergraduate and 20 master’s
students. They were provided with the definition of each condition and asked to assign each vignette under
specific conditions. Modifications were made to the vignettes that were incorrectly identified and this
process was repeated until all vignettes were correctly categorized. In order to avoid the misunderstanding
of OTT media, an example picture of a mobile OTT app was created based an existing app with the
provider’s name removed. A call-to-action (CTA) was created and imposed on the picture to serve as an
example of gamification CTA (see Appendix B).

3.3 Measures
To measure attitude toward the game mechanics, a four-item attitude scale (not fun/fun,
unnecessary/necessary, unfavorable/favorable, unenjoyable/enjoyable), developed by MacKenzie and Lutz
(1989), Moore et al. (1995), Voss et al. (2003) with a six-point semantic differential scale was utilized.
With regard to the attitude toward the OTT brand, a four six-point semantic differential scale:
bad/good, negative/positive, dislike/like, unfavorable/favorable (Bruner et al., 2001) was adopted. Further,
an even-numbered scale was used to reduce the tendency of the Japanese to select midpoint answers (Chen
et al., 1995; Lee et al., 2002). The questionnaires were translated and back-translated between English and
Japanese, with a pre-test conducted among 37 respondents. The pre-test was necessary to ensure that the
questionnaire was clear and easy to answer.

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4. Results
4.1 Sample Description
The sample comprised male (40%) and female (60%) young OTT media service consumers. In
terms of age, the sample ranged from the ages of 14–24 years, with 14-year-olds being the largest group at
23%; a large majority were students (85%). Most of the respondents consumed more than one OTT media
service, with Amazon Prime Video having the highest number of users at 31.4%. (see Table 2).

4.2 Dependable Variables
CFA was conducted using the scale data of attitude toward game mechanics and attitude toward
brand. The results demonstrated a good fit with the data (𝜒2(28) = 1001.79, p < 0.0001). The normed fit
index [NFI] = 0.913, confirmatory fit index [CFI] = 0.937, root mean square error of approximation
[RMSEA] = 0.093. While the RMSEA value reflects a mediocre fit (Browne and Cudeck, 1992; MacCallum
et al., 1996), various researchers have cautioned against adopting the RMSEA fit index cutoff criteria as
the golden rule of thumb (Hayduk and Glaser, 2000; Marsh et al., 2004; Steiger, 2000), owing to the fit
index value being influenced by various factors such as, df (Chen et al., 2008), number of variables analyzed
(Kenny and McCoach, 2003) and sample size (Marsh et al. 2004; Mulaik, 2009). The variable for attitude
toward game mechanics recorded a Cronbach’s alpha value of 0.850 and that of corporate attitude was
0.707. The correlation between both the dependent variables is 0.408 (p < 0.0001).

4.3 Analysis of Variance
The results of the ANOVA for the two dependent variables are presented in Table 3 and Figure 4.
The results indicate that controls and courses demonstrate a significant effect on respondents’ attitude
toward game mechanics. High controls (M = 3.55) demonstrated a significantly stronger effect by the
respondents than low controls (M = 3.10; F(1,288) = 13.15, p < 0.0001). The element of courses also has a
significant main effect on consumer attitude toward game mechanics (F(1,288) = 27.89, p < 0.0001). Based
on the means, the effects were stronger for low courses (M = 3.65) as compared to high ones (M = 3.00).
Components did not show any significant effect on attitude toward game mechanics (F(1,288) = 1.64, p =
0.20). Hence, the results did not support H1a, while H1b and H1c were strongly supported.
For the second dependent variable, attitude toward OTT brand, components also did not show any
significance (F(1,288) = 0.78, p = 0.38); thus, H2a was not supported. Significant main effects were
demonstrated in the attitude toward OTT brand for both controls and courses, thereby demonstrating strong
support for H2b and H2c. Controls had statistical significance, with significantly stronger effects for high
controls (M = 4.15) than low controls (M = 3.45, F(1,288) = 44.13, p < 0.0001). For courses, low courses
recorded stronger effects (M = 4.11) compared to high courses (M = 3.49, F(1,288) = 35.30, p < 0.0001).

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As predicted in H3, the three factors demonstrate a multiplicative effect on attitude toward game
mechanics (F(1,288) = 5.43, p < 0.02); however, the interactions reflect the mean square of low magnitude.
The interaction between controls and courses is isolated across components, and the results indicate that
the interaction between controls and courses on attitude toward game mechanics depend on components,
where high components show a significant effect (F(1,144) = 23.73, p < 0.0001) while low components
have no significant effect (F(1,144) = 1.60, p < 0.21). The results indicate that the respondents display a
more positive attitude toward gamification that adopts a combination of high components, high controls,
and high courses.
In terms of attitude toward OTT brand, as hypothesized in H4, a three-way multiplicative interaction
is revealed (F(1,288) = 2.70, p < 0.07). The interaction between controls and courses is dependent on the
level of components. The results reflect that low components have a significant effect (F(1,144) = 6.08, p
< 0.006), whereas high components show no significant effect (F(1,144) = 0.021, p < 0.88) on the
interaction. Respondents demonstrate a more positive attitude toward the OTT brand when the game
mechanics comprise low components, high controls, and low courses.

5. Discussion
This study expands the MDA and improves understanding of the effect of the mechanics of
consumer attitude. The results reveal that components define the interaction between controls and courses.
The level of components (high or low) affects the consumer attitude. While all three elements are vital, an
optimal amount is required to create a favorable experience for the consumer and to ensure that the
company’s objectives are met.
The findings demonstrate a contrast between focusing on the consumer’s attitude toward the
gamification experience versus toward the OTT provider brand. When merely focusing on gamification,
the respondents preferred the game mechanics to contain a high degree of all three elements, thereby
providing them more choices and an experience that resembles gaming. However, when the objective was
to create a positive attitude toward the OTT brand, the results indicated that reducing both components and
courses and increasing controls was the best combination. While a vast array of elements may create a fun
experience, the player focuses only on the gamification. However, when the brand is attempting to make a
statement of its values and personality, providing controls that motivate emotions and imparting
experiences in line with what the company stands for is the most effective.
The findings also extend prior research by demonstrating that combinations of varying game
elements can determine the success of gamification, as PBLs alone are insufficient to determine the success
of gamification (Chorney, 2012). As OTT providers lack emphasis on enhancing social components

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(Ericsson, 2016; Oestreicher-Singer and Zalmanson, 2013; Yan et al., 2013), the results of this study
contribute to the understanding of creating and enriching consumer experience through gamification.

6. Implications
6.1 Theoretical Implications
This research contributes to theory in two ways. First, it enhances the body of knowledge on the
extension of the MDA framework from gaming to gamification—particularly the elements of game
mechanics. Generally, studies on the MDA framework mainly adopt a more general approach that
encompasses MDA as well as the creation of a game from either the designer or user perspective. However,
this research centers on the elements that constitute game mechanics.
As existing studies on gamification are focused on other industries—for example, education and
health care (Prince, 2013; Zichermann and Linder, 2010), this study serves to create literature on OTT and
gamification. Further, as businesses expand their efforts toward enhancing customer engagement, new
knowledge and ideas are required. Gamification is identified as an effective means to foster engagement
(Blank, 2020; Punzo, 2019), which creates a demand for information and research on this topic. Therefore,
this study fills the need by presenting findings that can contribute to research on gamification in OTT.

6.2 Managerial Implications
This study demonstrated that consumers’ favorable attitudes toward game mechanics are dependent
on the amount of each game element presented. This indicates that OTT providers must focus on utilizing
the optimal amount of the elements, even if only a single element is adopted as their gamification strategy.
In addition, by examining the interaction among all three elements, the current study provides insights into
the combinations that would elicit the maximum favor among consumers.
Further, this indicates that OTT providers must avoid increasing game mechanics across the board,
as it will not lead to a positive outcome among consumers. They must be aware of the preference level of
the three elements in order to maximize consumer favorability and engagement with the gamification and
the brand. They ought to explore, experiment, and develop different combinations to suit their specific
needs and objectives.

7. Conclusion
This research examined consumer attitude toward the adoption of game mechanics taken from the
MDA framework in creating gamification within an OTT environment. The findings clearly outlined the
prevalence of an interaction effect among the elements of game mechanics that differs according to the
objective of the gamification usage.

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The results of this study are of interest to both OTT providers and gamification researchers, as it
provides a closer look at the core elements of game mechanics that ultimately shape the aesthetics of
consumption. Unlike in the OTT sector, gamification for building engagement has been extensively utilized
in education, travel, and retail (Chou, 2017; Christy and Fox, 2014; Gudmundsson et al., 2002). Hence, this
study paves the way for adopting gamification to increase the subscriber base.

8. Limitations and Recommendations for Future Research
This study has a few limitations. First, the gender distribution was imbalanced, with 60% female
respondents and 40% male respondents. Further, the number of respondents were not equally distributed
across age groups. Hence, for future research, multiple rounds of data collection could be performed to
obtain a more balanced gender composition and equal representation from different ages, should the initial
data collection yield an imbalance in both gender and age distribution. With regard to age, this study could
also be expanded to explore the effect of age on the attitude toward game mechanics in OTT media service
and the preferred elements of game mechanics.
Respondents relied on their imagination to visualize the gamification. This possibly affected the
responses, as the respondents may have visualized it differently from each other. Researchers could create
a more “real” experience in terms of stimuli, such as creating a fictitious OTT media app embedded with
gamification features and letting the respondents try it out before answering the questionnaire.
Lastly, this study focused solely on game mechanics; for future research, a broader approach can
be adopted where study is expanded to encompass the other two components of the MDA framework:
dynamics and aesthetics. Finally, this study can be replicated and expanded using a mixed-methods
approach to obtain more accurate findings.

14
References
Adgully (2020, September 11). “OTT subscription purchase and viewing witness spike during COVID-19.”
Retrieved September 13, 2020, from https://www.adgully.com/ott-subscription-purchase-andviewing-witness-spike-during-covid-19-flyx-96338.html

Anderson C. A. (2004). An update on the effects of playing violent video games, Journal of
Adolescence, 27, 113–122.

Balanzategui, J., L. Burke, and Golding. D. (2018). Recommending a new system: An audience-based
approach to film categorisation in the digital age. Participations: Journal of Audience and
Reception Studies, 15(2), 297.

Banerjee, A., Rappoport, P.N., and Alleman, J. (2014). Forecasting video cord-cutting: The bypass of
traditional pay television. Demand for Communications Services–Insights and Perspectives (pp.
59–82), Springer.

Barata, G, Gama, S, and Jorge, J. (2015). Gamification for smarter learning: Tales from the trenches. Smart
Learning Environments, 2(10), 1–23.

Bartlett C. P., Branch O., Rodeheffer C., and Harris R. (2009). How long do the short-term violent video
game effects last? Aggressive Behavior, 35, 1–12.
Blanchard, A., and Markus, M. (2004). The experienced “sense” of a virtual community. SIGMIS Database,
35(1), 64-79.

Blank, F. (2020, January 30 ). The 2020 vision for OTT: Storytelling, Engagement and Gamification.
SportsPro.

https://www.sportspromedia.com/opinion/ott-streaming-2020-amazon-netflix-

sportradar

Bosche W. (2010). Violent video games prime both aggressive and positive cognitions. Journal of Media
Psychology, 22, 39–146.

Brigham, T.J. (2015). An introduction to gamification: Adding game elements for engagement. Medical
Reference Services Quarterly, 34(4), 471-480,

15

Browne, M.W., and Cudeck, R. 1993. Alternative ways of assessing model fit. In Bollen, K., Long, J.,
(Eds.), Testing Structural Equation Models (pp. 136-162), Sage.

Bruner, G. C., Hensel, P. J., and James, K. E. (2001). Marketing scales handbook. American Marketing
Association.

Business Wire (2020, May 20). Global OTT Streaming Market (2020 to 2030)—COVID-19 growth and
change. https://www.businesswire.com/news/home/20200520005350/en/Global-OTT-StreamingMarket-2020-to-2030---COVID-19-Growth-and-Change---ResearchAndMarkets.com.

CBC News (2020, May 10). U of S research finds video games can relieve stress, improve mental health.
https://www.cbc.ca/news/canada/saskatoon/u-of-s-research-finds-video-games-can-relieve-stressimprove-mental-health1.5563824#:~:text=or%20Animal%20Crossing.-,But%20University%20of%20Saskatchewan%2
0computer%20science%20professor%20Regan%20Mandryk%20says,stress%20and%20improve
%20mental%20health.

Cha, J. (2013). Predictors of television and online video platform use: A coexistence model of old and new
video platforms. Telematics and Informatics, 30(4), 296-310.

Cha, J., and Chan-Olmsted, S. M. (2012). Substitutability between online video platforms and television.
Journalism and Mass Communication Quarterly, 89(2), 261–278.

Charlton, J. P., and Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of
online game playing. Computers in Human Behavior, 23(3), 1531–1548.

Charlton, J. P., and Danforth, I. D. (2010). Validating the distinction between computer addiction and
engagement: Online game playing and personality. Behaviour and Information Technology, 29(6),
601–613.

Chen, C., S. Lee, and H.W. Stevenson. (1995). Response style and cross-cultural comparisons of rating
scales among East Asian and North American students. Psychology Science, 6, 170–175.

16
Chen, F., Curran, P. J., Bollen, K. A., Kirby, J., and Paxton, P. (2008). An empirical evaluation of the use
of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Methods
and Research, 36(4), 462-494.

Chorney, A. (2012). Taking the game out of gamification. Dalhousie Journal of Interdisciplinary
Management, 8, 1.

Chou, T.-J., and Ting, C.-C. (2003). The role of flow experience in cyber-game addiction. CyberPsychology
and Behavior, 6(6), 663–675.
Chou, Y. (2017). “A comprehensive list of 90+ gamification studies with ROI stats” [Blog post]. Retrieved
January 6, 2020, from https://yukaichou.com/gamification-examples/gamification-stats-figures/

Christy, Katheryn R., and Jesse Fox. (2014). Leaderboards in a Virtual Classroom: A Test of Stereotype
Threat and Social Comparison Explanations for Women’s Math Performance. Computers and
Education, 78, 66–77.

Colwell J. (2007). Needs met through computer game play among adolescents. Personality and. Individual
Differences, 43, 2072–2082

Communications Today (2019, February 12). U.S. Consumers Still Seeking Content As OTT Pricing Starts
To

Rise.

https://www.communicationstoday.co.in/u-s-consumers-still-seeking-content-as-ott-

pricing-starts-to-rise/

Crumlish, C., and E. Malone. (2015). Designing social interfaces: Principles, patterns, and practices for
improving the user experience. 2nd ed. O’Reilly Media.

Deloitte Center for Technology, Media and Communications (2019). 2020 Telecommunications, Media,
and

Entertainment

https://www2.deloitte.com/content/dam/Deloitte/us/Documents/technology-mediatelecommunications/us-tme-tmt-outlook-2020.pdf

Outlook.

17
Deterding, S., Dixon, D., Khaled, R., and Nacke, L. (2011). From game design elements to gamefulness:
Defining “gamification”, Proceedings of the 15th International Academic Mind-Trek Conference:
Envisioning Future Media Environments (MindTrek '11). ACM, New York, NY, USA, pp.9-15.
Ducheneaut, N., Yee, N., Nickell, E., and Moore, R. (2013) “Alone together?”: Exploring the social
dynamics of massively multiplayer online games.” Proceedings of the SIGCHI conference on
Human Factors in computing systems (pp. 407–416).New York: ACM.
Docomo Digital (2019, Oct). The rise and rise of OTT Media. A perspective on the ecosystem and what lies
ahead.

https://d8yt7ovwsvs6k.cloudfront.net/uploads/2019/10/Rise-of-OTT-

Media_DOCOMO_Web.pdf

Dominguez, A., Saenz-de-Navarrete, J., de-Marcos, L., Fernandez-Sanz, L., Pages, C., and MartinezHerraiz, J.-J. (2013). Gamifying learning experiences: Practical implications and outcomes.
Computers and Education, 63, 380–392. doi:10.1016/j.compedu.2012.12.020.

El Sawy, O. A. (2003). The IS core IX: The 3 faces of IS identity: Connection, immersion, and fusion.
Communications of the Association for Information Systems, 12(1), 588–598.

Ericsson

A.B.

(2016).

Customer

experience

in

the

internet

era.

https://www.ericsson.com/spotlight/media/seamless-experience.

FCC (2013). Annual assessment of the status of competition in the market for the delivery of video
programming. MB Docket No. 12-203. FCC 13-99.
Ferguson, C. J., Trigani, B., Pilato, S., Miller, S., Foley, K., and Barr, H. (2016). Violent video games don’t
increase hostility in teens, but they do stress girls out. Psychiatric Quarterly, 87, 49–56.

Ferm, B. (2019, November 15). The growth of OTT video streaming and its impact on the pay TV-industry.
Intertrust. https://www.intertrust.com/blog/the-growth-of-ott-video-streaming-and-its-impact-onthe-pay-tv-industry/
Geslin, E., Bouchard, S., and Richir, S. (2011). Gamers’ versus non-gamers’ emotional response in virtual
reality. Journal of Cyber Therapy Rehabilitation, 4, 489–493.

18
Gudmundsson, S. V., de Boer, E. R., and Lechner, C. (2002). Integrating frequent flyer programs in
multilateral airline alliances. Journal of Air Transport Management, 8(6), 409–417.
Hamari, J., Koivisto, J., and Sarsa, H. (2014). “Does gamification work? A literature review
of empirical studies on gamification.” Proceedings of the 2014 47th Hawaii International
Conference on System Sciences (HICSS '14). IEEE Computer Society, Washington, DC, USA,
pp. 3025-3034.

Hanabishi Kabushikigaisha (2020, May 31). Doga haishin sabisu (VOD) no riyo jokyo o tettei chosa!
Manzoky do wa Neflix de 8-I, joi wa? (Thorough investigation of the usage status of video on
demand

(VOD)

satisfaction

ranks

Netflix

8th,

who

is

the

top?).

PR

Times.

https://prtimes.jp/main/html/rd/p/000000004.000053976.html.

Hanus, M.D., and Fox. J. (2015). Assessing the effects of gamification in the study on intrinsic motivation,
social comparison, satisfaction, effort, and academic performance. Computers and Education, 80
(1), 152–166.
Hasan Y. (2015). Violent video games increase voice stress: an experimental study. Psychology of Popular
Media Culture, 6, 74–81.
Hasan Y., Bégue L., and Bushman B. J. (2013). Violent video games stress people out and make them more
aggressive. Aggressive Behavior, 39, 64–70.
Hayduk, L.A., and Glaser, D.N. (2000). Jiving the four-step, waltzing around factor analysis, and other
serious fun. Structural Equation Modeling, 7(1), 1–35.

Hodjat, A. (2020, February 7). Streaming giants: The global growth of OTT subscription video on demand
services. Intertrust. https://www.intertrust.com/blog/streaming-giants-the-global-growth-of-ottsubscription-video-on-demand-services/

Högsdal, N. (2011). Serious games, simulationen und planspiele: Same but different? WBV.

Hunicke, R., LeBlanc, M., and Zubek, R. (2004). MDA: A formal approach to game design and game
research, Proceedings of the Challenges in Games AI Workshop, Nineteenth National Conference
of Artificial Intelligence, pp. 1–5.

19
Koivisto, J., and Hamari, J. (2019). The rise of motivational information systems: A review of gamification
research. International Journal of Information Management, 45, 191–210.
Layton, M. (2020, September 30). LatAm streamer Europa+ launches, with ‘Doctor Who’ and ‘Vernon
Subutex’. Television Business International. https://tbivision.com/2020/09/30/lat-am-streamereuropa-launches-with-doctor-who-vernon-subutex/
LeBlanc, M. (2004). “ìMechanics, dynamics, aesthetics: A formal approach to game design,” Lecture at
Northwestern University, April 2004. http://algorithmancy.8kindsoffun.com/MDAnwu.ppt
LeBlanc, M. (2005). “Game Design and Tuning Workshop,” FuturePlay 2005 International Academic
Conference on the Future of Game Design and Technology. East Lansing, MI.

Leclerc, F., Schmitt, B.H. and Dube, L. (1995), Waiting time and decision making: Is time like
money? Journal of Consumer Research, 22 (June), 110-119.

Lee, J.W., Jones, P.S., Mineyama,Y., and Zhang, X.E.. (2002). Cultural differences in responses to a Likert
scale. Research in Nursing and Health, 25(4), 295–96.

Lobel A., Granic I., and Engels R. (2014). Stressful gaming, interoceptive awareness, and emotion
regulation tendencies: a novel approach. Cyberpsychology, Behavior and Social Networking, 17,
222–227.

Lopasso, G. (2011). Dealing with over-the-top services. Stockholm: Ericsson AB.

Lucassen, G. and Jansen, S. (2014). Gamification in consumer marketing—future or fallacy? Procedia—
Social and Behavioral Sciences, 148, 194–202.

Kapp, K.M. (2012). The gamification of learning and instruction: Game-based methods and strategies for
training and education. Pfeiffer.

Kenny, D. A., and McCoach, D. B. (2003). Effect of the number of variables on measures of fit in structural
equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 10, 333–351. doi:
10.1207/ S15328007SEM1003_1

20

Kim, T.Y., and Shin, D.H. (2017). The survival strategy of branded content in the over-the-top (OTT)
environment: Eye-tracking and Q-methodology approach in digital product placement. Telematics
and Informatics, 34(7), 1081–1092.

Koivisto, J., and Hamari, J. (2019). The rise of motivational information systems: A review of gamification
research. International Journal of Information Management,. 45, 191–210.

Ligue

de

Football

(2020,

April).

Sport and

gamification.

https://strivesponsorship.com/wp-

content/uploads/2020/04/Sport-and-gamification-report.pdf

MacCallum, R.C., Browne, M.W., and Sugawara, H.M. (1996). Power analysis and determination of
sample size for covariance structure modeling. Psychological Methods, 1, 130–149.

MacKenzie, S.B. and Lut, R.J. (1989). An empirical examination of the structural antecedents of attitude
toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48–65.

Marsh, H.W., Hau, K.T., and Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing
approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s
(1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11, 320–341.

McGonigal, J. (2011). Reality is broken: Why games make us better and how they can change the world.
Penguin.

Merino de Paz, B. (2013). Gamification: A tool to improve sustainability efforts. University of
Manchester, Manchester. Master’s Thesis.

Mollick, E.R., and Rothbard, N. (2014). Mandatory fun: Consent, gamification and the impact of games at
work. The Wharton School Research Paper Series.
Moore, D. J., Harris, W. D., and Chen, H. C. (1995). “Affect intensity: An individual difference response
to advertising appeals. Journal of Consumer Research, 22(2), 154–164.

21
Montgomery, A.A., Peters, T.J. and Little, P. (2003). Design, analysis and presentation of factorial
randomised

controlled

trials. BMC

Medical

Research

Methodology, 3, 26.

https://doi.org/10.1186/1471-2288-3-26

Moyler, A., and Hooper, M. (2009. November 20). Over the Top TV (OTT TV) Platform Technologies.
BCi

Ltd.

and

Endurance

Technology

Ltd.

http://www.endurancetech.co.uk/media/documents/OTT%20TV%20White%20Paper%20Rel%20
1%20Ver%201.pdf

Mohr, L. A., Webb, D. J., and Harris, K. E. (2001). Do consumers expect companies to be socially
responsible? The impact of corporate social responsibility on buying behavior. Journal of
Consumer Affairs, 55(1), 45-71.

Mulaik, S.A (2009). Linear causal modeling with structural equations. Chapman and Hall/CRC

Nah, F.F.H., Zeng, Q, and Telaprolu, V.R. et al., (2014). Gamification of education: a review of literature.
International conference on HCI in business, Heraklion Crete, Greece, June 22-27, 2014, pp.401–
409. Springer International Publishing.

Nevin, C. R., Westfall, A.O., Rodriguez, J. M., Dempsey, D. M., Cherrington, A., Roy, B., Patel, M., and
Willig, J. H., (2014). Gamification as a tool for enhancing graduate medical education.
Postgraduate Medical Journal, 90 (1070), 685–693.
Ochiai, A. (2019, February 12). “Doga sabisu no shicho jittai seikatsusha to eizo kontentsu no ima korekara
daiichikai. Video service viewing conditions-Consumers and "video content" "now and in the
future.” Part 1. https://www.videor.co.jp/digestplus/media/2019/02/35462.html

Oestreicher-Singer, G., and Zalmanson, L. (2013). Content or community? A digital business strategy for
content providers in the social age. MIS Quarterly, 37 (2): 591–616.

Oliver M. B., Bowman N. D., Woolley J. K., Rogers R., Sherrick B. I., and Chung M. (2015). Video games
as meaningful entertainment experiences. Psychology of Popular. Media Culture, 5, 390–405.

22
Ooyala and Vindicia (July 2015). Prospects for Premium OTT in the USA. A snapshot of industry
perspectives on the evolution of the market. MTM Whitepaper. http://go.ooyala.com/rs/447-EQK225/images/Ooyala-and-Vindicia-MTM-whitepaper.pdf

Paliwal. S. (2020). How OTT platforms are using gamification as an engagement strategy. Exchange4media.
Ligue

de

Football.

https://strivesponsorship.com/wp-content/uploads/2020/04/Sport-and-

gamification-report.pdf
Porter, A.M., and Goolkasian, P. (2019). “Video games and stress: How stress appraisals and game content
affect cardiovascular and emotion outcomes”, Frontiers in Psychology, 10, 967.

Prince, J. D. (2013). Gamification. Journal of Electronic Resources in Medical Libraries, 10(3), 162–169.

Porter, J. (2008). Designing for the social web. Peachpit Press.

Punzo, G. (2019, June 14). Gamification for sports broadcasting: A hidden goldmine? Forth Source.
https://www.fourthsource.com/online-video/gamification-for-sports-broadcasting-a-hiddengoldmine-23913

PwC (2019) Video streaming shakeup. Survey of consumer attitudes and preferences. PWC.
https://www.pwc.com/us/en/services/consulting/library/consumer-intelligence-series/consumervideo-streaming-behavior.html

Ravaja, N., Turpeinen, M., Saari, T., Puttonen, S., and Keltikangas-Jarvinen, L. (2008). The
psychophysiology of James Bond: phasic emotional responses to violent video game events.
Emotion, 8, 114–120.

Reinecke L. (2009). Games and recovery: the use of video and computer games to recuperate from stress
and strain. Journal of Media Psychology, 21, 126–142.

Robson, K., Plangger, K., Kietzmann, J. H., McCarthy, I., and Pitt, L. (2015). Is it all a game?
Understanding the principles of gamification. Business Horizons, 58(4), 411–420.

23
Roy, A., Ferguson, C. J. (2016). Competitively versus cooperatively? An analysis of the effect of game
play on levels of stress. Computers in Human Behavior, 56, 14–20.

Rupp, M.A., Sweetman, R., Sosa, A.E., Smither, J.A., and McConnell, D.S. (2017). Searching for Affective
and Cognitive Restoration: Examining the Restorative Effects of Casual Video Game Play. Human
Factors, 57, 1403-1416.

Ruhi, U. (2015). Towards a descriptive framework for meaningful enterprise gamification. Technology
Innovation Management Review, 5(8), 5-16.
Russoniello C. V., O’Brien K., and Parks J. M. (2009). The effectiveness of casual video games in
improving mood and decreasing stress. Journal of Cyber Therapy and Rehabilitation, 2, 53–66.

Sailer, M., Hense, J.U., Mayr, S.K., and Mandl, H. (2017). How gamification motivates: An experimental
study of the effects of specific game design elements on psychological need satisfaction. Computers
in Human Behavior, 69, 371–380.

Seaborn, K., and Fels. D.I. (2015). Gamification in theory and action. International Journal of HumanComputer Studies, 74, 14-31.

Siemon, D., and Eckardt, L. (2017). Gamification of teaching in higher education. In Gamification Using
Game Elements in Serious Contexts (pp.93-109). Springer.

Sigala, M. (2015). Applying gamification and assessing its effectiveness in a tourism context: Behavioural
and psychological outcomes of the Tripadvisor’s gamification users. Asia Pacific Journal of
Information Systems, 25, 179–210.

Simões, J., Díaz Redondo, R., and Fernández Vilas, A. (2013). A social gamification framework for a K–6
learning platform. Computers in Human Behavior, 29, 345–353.

Snodgrass, J. G., Dengah, H. J. F., Lacy, M. G., and Fagan, J. (2013). A formal anthropological view of
motivation models of problematic MMO play: Achievement, social, and immersion factors in the
context of culture. Transcultural Psychiatry, 50(2), 235–262.

24
Snodgrass, J. G., Dengah, H. J. F., Lacy, M. G., Fagan, J., Most, D., Blank, M., et al.
(2012). Restorative magical adventure or warcrack? Motivated MMO play and
the pleasures and perils of online experience. Games and Culture, 7(1), 3–28.

Snodgrass, J. G., Lacy, M. G., Dengah, H. J. F., Batchelder, G., Eisenhower, S., and Thompson, R.S. (2016).
Culture and the jitters: Guildliation and online gaming eustress/distress. Ethos, 44, 50–78.

Steiger J. H. (2000). Point estimation, hypothesis testing, and interval estimation using the RMSEA: Some
comments and a reply to Hayduk and Glaser. Structural Equation Modeling, 7, 149–162.

Stenros, J. and Waern, A. (2011). Games as activity: Correcting the digital fallacy. In M. Evans, (Ed.),
Videogame Studies: Concepts, Cultures and Communication. Oxford.

Terill, B. (2008, June 16). My coverage of lobby of the social gaming summit. Bret on Social Games.
http://www.bretterrill.com/2008/06/my-coverage-of-lobby-of-social-gaming.html
Tse, Y. (2016). Television’s changing role in social togetherness in the personalized online consumption of
foreign TV. New Media and Society, 18(8), 1547–1562.

Tsuchiya, A. (n.d.). How Japanese broadcasters are uniting to compete in OTT. Streamhub.
https://streamhub.co.uk/how-japanese-broadcasters-are-uniting-to-compete-in-ott/

Triberti S. (2016). This drives me nuts! How gaming technologies can elicit positive experiences by means
of negative emotions. Villani D., et al. (Eds.), Integrating Technology in Positive Psychology
Practice. IGI Global.

Turan, Z., Avinc, Z., Kara, K., and Goktas, Y. (2016). Gamification and education: Achievements,
cognitive loads, and views of students. International Journal of Emerging Technologies in
Learning, 11 (7), 64-69.
Urh, M., Vukovic, G., Jereb, E., and Pintar, R. (2015). The Model for Introduction of Gamification into Elearning in Higher Education. In 7th World Conference on Educational Sciences, (WCES-2015),
Novotel Athens Convention Center, Athens, Greece; 2015; Greece, Athens: Elsevier. pp. 388–395.

25
Vassileva, J. (2012). Motivating participation in social computing applications: A user modeling
perspective. User Modeling and User-adapted Interaction, 22(1–2), 177–201.

Villani D., Carissoli C., Triberti S., Marchetti A., Gilli G., and Riva G. (2018). Videogames for emotion
regulation: a systematic review. Games for Health Journal, 7: pp. 85–99.

Voss, K.E., Spangenberg, E.R., and Grohmann, B. (2003). Measuring the hedonic and utilitarian
dimensions of consumer attitude. Journal of Marketing Research, 40(3), 310–320.

Werbach, K., and Hunter, D. (2012). For the win: How game thinking can revolutionize your business.
Wharton Digital Press.

Williams, D., Ducheneaut, N., Xiong, L., Zhang, Y., Yee, N., and Nickell, E. (2006). From tree house to
barracks. Games and Culture, 1(4), 338–361.
Wijman, T. (2020, May 8). The world’s 2.7 billion gamers will spend $159.3 billion on games in 2020; The
market will surpass $200 billion by 2023. Newzoo. https://newzoo.com/insights/articles/newzoogames-market-numbers-revenues-and-audience-2020-2023/

Winn, B. M. (2007). The design, play, and experience framework. In R. E. Ferdig (Ed.), Handbook of
Research on Effective Electronic Gaming in Education (pp. 1010–1024), Information Science
Reference.

Witt, M., Scheiner, C., and Robra-Bissantz, S. (2011). Gamification of online idea competitions: Insights
from an explorative case. In INFORMATIK 2011. Berlin, Germany.

Yang, Y., Asaad, Y., and Dwivedi, Y. (2017). Examining the impact of gamification on intention of
engagement and brand attitude in the marketing context. Computers in Human Behavior, 73, 459–
469.

Yan, N., H. Qian, and X. Ji. (2013). Netflix Social Redesign. Los Gatos, California, US: Team Netflixers.

Yee, N. (2006). Motivations for play in online games. Cyber Psychology and Behavior, 9(6), 772–775.

26
Zichermann, G., and Linder, J. (2010). Game-based marketing: Inspire customer loyalty through rewards,
challenges, and contests. Wiley.

27

Figure 1: MDA Framework

Designer
Mechanics

Dynamics

Aesthetics

Player

Source: Hunick, LeBlanc & Zubek (2004)

Figure 2: Elements in Game Mechanics

Components

Controls

Courses

Ex. Points, Badges,
Leaderboards,
Virtual goods,
Avatars

Ex. User turns,
Skills Tests,
Quizzes, Task
Timers

Ex. Quests,
Groups, Levels

Source: Ruhi (2015)

28

Figure 3: Game Mechanics: Relationships under investigation

Controls

Attitude
towards
game
mechanics

Courses

Attitude
towards OTT
provider
brand

Components

Figure 4: Results of ANOVA
a) Impact of Components, Controls and Courses on Attitude Towards Game Mechanics
4.00
3.00

2.00
1.00
0.00
Components

Controls
Low

High

Courses

29

b) Interaction on Attitude Towards Game Mechanics
3.60

4.00

3.40

3.00

3.20

2.00

3.00

1.00
0.00

2.80

Low

Low

High

Components

Controls

Low

High

Components

High
Courses

4.00
3.00
2.00
1.00
0.00

Controls

Courses

c) Impact of Components, Controls and Courses on Attitude Towards OTT Provider Brand
5.00
4.00
3.00
2.00
1.00
0.00
Components

Controls

Low

High

Courses

30

d) Interaction on Attitude Towards OTT Provider Brand
6.00

4.50

4.00

4.00

2.00

3.50
3.00

0.00
Low
Components

High
Controls

6.00
4.00
2.00

0.00
Low
Controls

High
Courses

Low
Components

High
Courses

31

Table 1: Factorial Design Experiment Conditions

Condition
1
2
3
4
5
6
7
8

Components
High
High
High
High
Low
Low
Low
Low

Courses
High
High
Low
Low
High
High
Low
Low

Controls
High
Low
High
Low
High
Low
High
Low

Table 2: Overview of Respondent Characteristics
Frequency Percentage
N=296
Gender
Male
Female

118
178

39.9
60.1

68
12
28
42
32
38
8
18
16
18
16

23.0
4.1
9.5
14.2
10.8
12.8
2.7
6.1
5.4
6.1
5.4

250
16
16
4
12

84.5
5.4
5.4
1.4
4.1

Age
14
15
16
17
18
19
20
21
22
23
24

Job
Student
Full-Time
Part-Time
Homemaker
Others

Frequency Percentage
N=420
OTT Media Services Consumed
AbemaTV
46
11.0
Amazon Prime Video
132
31.4
Anime Houdai
4
1.0
Basket Live
4
1.0
dAnime Store
14
3.3
DAZN
10
2.4
Disney+
8
1.9
dTV
26
6.2
FOD
2
0.5
Hulu
42
10.0
J:Com on Demand
8
1.9
LINE LIVE
8
1.9
Netflix
62
14.8
PacificLeague TV
2
0.5
Paravi
4
1.0
SKY PerfecTV
2
0.5
Telasa
2
0.5
TVer
26
6.2
U-NEXT
8
1.9
WOWOW On- Demand
8
1.9
YouTube
2
0.5

32

Table 3: Effects of game mechanics on attitude toward gamification and OTT media service
brands
Direct effects

Components (Comp)
High (H)
Low (L)
Controls (Cont)
High (H)
Low (L)
Courses (Cour)
High (H)
Low (L)
Components x Controls
Components x Courses
Controls x Courses
Components x Controls x Courses
Comp (H) x Cont (H) x Cour (H)
Comp (H) x Cont (H) x Cour (L)
Comp (H) x Cont (L) x Cour (H)
Comp (H) x Cont (L) x Cour (L)
Comp (L) x Cont (H) x Cour (H)
Comp (L) x Cont (H) x Cour (L)
Comp (L) x Cont (L) x Cour (H)
Comp (L) x Cont (L) x Cour (L)

Dependable Variable
(A)
(B)
Attitude toward game
Attitude toward OTT Provider brand
mechanics
F
p-value
Mean
F
p-value
Mean
1.64
.20
.78
.38
3.25
3.76
3.40
3.85
13.15
.00
44.13
.00
3.55
4.15
3.10
3.45
27.89
.00
35.30
.00
3.00
3.50
3.65
4.11
1.01
.14
.16
.69
.853
.36
.44
.51
17.683
.00
4.173
.04
5.43
.02
3.30
.07
3.64
3.79
3.60
4.06
2.09
3.02
3.63
3.74
3.32
4.10
3.62
4.25
2.95
3.04
3.61
4.00

Notes: ANOVA (A) R2 =.202, adjusted R2 =.182 ; ANOVA (B) R2 =.234 , adjusted R2 = .216

33

Appendix A : Examples of Vignettes (translated from the Japanese versions that were used)

High Components, High Controls, High Courses

OTT media service provider X is introducing a new feature in their mobile app. Users can now access the
mobile app to participate in the world of entertainment and sports and have the opportunity to collect points
and win prizes. Get your knowledge tested on movies, dramas, anime and sports! Collect points and badges
and view your accomplishments on real-time leaderboards. Win trophies! Take turns to play and challenge
your friends! Compete against the timer to solve puzzles. You can also get badges and points through levels
of progress from joining discussions, and reviews on movies, dramas, anime, and sports or embarking on
quests.

Add more fun to your entertainment with us through all these!
*points

*quizzes

* take turns in challenges with your friends

*badges

*quests

*trophies

*levels of progression * reviews

*leaderboard

*race against the timer

* discussions

Low Components, High Controls, Low Courses

OTT media service provider X is introducing a new feature in their mobile app. Users can now access the
mobile app to participate in the world of entertainment and sports and have the opportunity to collect points
and win prizes. Get your knowledge tested on movies, dramas, anime and sports! Collect points through
levels of progress and view your accomplishments on real-time leaderboards. Take turns to play and
challenge your friends or gain points from joining discussions, and reviews on movies, dramas, anime, and
sports.

Add more fun to your entertainment with us through all these!
*points

* take turns in challenges with your friends

*leaderboard

* quizzes

*reviews

*discussion

34
*levels of progression

Appendix B: Example of picture of a mobile OTT app (modified to include call-to-action)

この論文で使われている画像