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INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY: APPLIED
BUSINESS AND EDUCATION RESEARCH
2023, Vol. 4, No. 3, 897 – 916
http://dx.doi.org/10.11594/ijmaber.04.03.22
How to cite:
Torralba, E. M. (2023). Playing Games to Earn Money: The Conceptual Framework of Interaction between Gender,
Learning Styles, Problematic Gaming Behavior and Success-Economic Gain Motivation of Playing Games. International
Journal of Multidisciplinary: Applied Business and Education Research. 4(3), 897 – 916. doi: 10.11594/ijmaber.04.03.22
Research Article
Playing Games to Earn Money: The Conceptual Framework of Interaction
between Gender, Learning Styles, Problematic Gaming Behavior and
Success-Economic Gain Motivation of Playing Games
Edwin M. Torralba*
College of Information and Computing Sciences University of Santo Tomas 1008, Philippines
Article history:
Submission March 2023
Revised March 2023
Accepted March 2023
ABSTRACT
This study identified the constructs of problematic gaming behavior
that significantly impact the success-economic gain motivation of
gamers. Furthermore, this study explored the role of gender, number
of games played, and learning styles in problematic gaming behavior
and the success-economic gain motivation of gamers using an online
survey (N = 136). This study identified escape from adverse moods
and preoccupation as the significant determinants of success-eco-
nomic gain motivation of gamers. Escape from bad moods and preoc-
cupation mediates the relationship between gamers' gender, number
of games played, and success-economic gain motivation. Regression
analysis reveals that active-reflective and sequential-global learning
styles moderate the relationship between escapism, preoccupation,
and success-economic gain motivation of gamers. The results suggest
that the combination of active-global learning style and reflective-se-
quential learning style has the highest impact on the success-eco-
nomic gain motivation of gamers. The results led to two conceptual
frameworks that show how gender, learning styles, problematic gam-
ing behavior, and success-economic gain motivation all play a role in
game play.
Keywords: Asia, City Schools Division of San Fernando, descriptive-cor-
relational design, Educational Management, La Union,
Philippines, school heads, school performance, transforma-
tional leadership.
*Corresponding author:
E-mail:
emtorralba@ust.edu.ph
Introduction
Over the last few decades, online games
have gradually replaced more traditional video
games as a way to have fun. Online games, un-
like in the past, are now being used in a variety
of fields, including education (Arango-López et
al., 2019), mental health treatment (Dias et al.,
2018), and e-commerce promotions (Yu &
Huang, 2022). There has been a lot of progress
in digital consoles, platforms, and distribution
systems for games. Recent research in game de-
velopment usually focuses on why people play
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 898 Volume 4 | Number 3 | March | 2023
games, how playing games affects their behav-
ior, how gamification and game-based learning
work, and how they can be used in different
fields (Hamari & Keronen, 2017; Qin et al.,
2021; Calvo-Morata et al., 2021; Haberlin & At-
kin, 2022). While some studies explore the con-
cept of earning money through gambling while
playing games, most of this research focuses on
the behavioral changes on the part of the play-
ers (Mills & Nower, 2019; Zendle, 2020; Macey,
2021). On the part of game developers, their
top priority is to learn the reasons why people
play games and apply the appropriate revenue
streams for the benefit of investors. However,
it doesn't seem to be very common in the liter-
ature to find studies that look into the possibil-
ity of games as a way to earn money.
Video games can be treated as any other
sport. It entails wit, perseverance, dedication,
and determination for a player to beat human
or computer-generated (e.g., artificial intelli-
gence) opponents and obstacles. Aside from
the aesthetics and the mechanics of the game,
players are attracted to the game due to the fol-
lowing: the layers of goals that need to be
achieved; the sense of gratification for any
achievement attained; the opportunity to earn
monetary and non-monetary rewards; the op-
portunity to engage in healthy competition
based on game-rules; and the fun of playing it.
These reasons are coined based on the pro-
posed framework of gamification that analyzes
why people are hooked on games (Nah et al,
2013). Still, this question might linger in the
minds of game developers, which is "What is
the best motivator for gamers to continue play-
ing my games?" Scholars and academicians
have extensively studied these possible moti-
vators that keep people from playing games.
Based on the self-determination theory, Ryan,
Rigby, and Przybylski (2006) proposed two im-
portant motivating factors for why people play
video games (Ryan, 2006). First, in the form of
autonomy where players use their intuition
and strategy to win against their opponent. Sec-
ond is the enhancement of players’ competence
by providing possibilities to develop new expe-
riences or gaming skills, to be adequately
tested, or to obtain positive feedback, which all
contribute to increased perceived competence
and, thus, intrinsic motivation. Perceived com-
petence would be strengthened in gaming envi-
ronments where gameplay interfaces and con-
trols are intuitive and easily grasped, while
tasks inside the game continue to present ideal
challenges for constructive feedback. On the
other hand, gaming landscapes, mechanics, and
environments can foster an enduring, upbeat
motivational attitude for gamers to continue
playing their preferred video games (Granic et
al., 2014). This motivational method, in turn,
may be generally applicable to academic and
professional settings. Additionally, certain
types of games may nurture these healthy mo-
tivational patterns more than others. Aside
from these insights, any ordinary person, gam-
ers or non-gamers, would agree that money is
the best reward and motivation that will make
them continue playing the game.
Tool Theory of Money
Money is a highly efficient, potent, and
straightforward motivator (Furnham, 2012).
Money stimulates and more money motivates
people to work even harder. It is normal for
people to stay competitive, and when they are
compensated for superior work, performance
and expectations are enhanced for everyone.
Additionally, while it is not always prudent or
practical to promote individuals at work,
money can be utilized to reward all workers in
an equitable and extremely acceptable manner.
In addition, because money is a universal re-
ward, it's always a good thing for people to
have it, no matter where they are or what
they're doing. The power of money to motivate
people to do things can be explained by the
"Tool Theory of Money" (TTM). TTM posits that
money is a tool for exchanging tangible or in-
tangible resources. Money has no intrinsic
value in itself, but the value of money rests on
its ability to simplify trade and develop a uni-
versal framework for exchanging goods as
compared to the traditional barter system. Fol-
lowing the Tool Theory, humans do not require
money psychology at all, or only in a restricted
sense: what people need is an understanding of
the function of money and the human cognitive
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 899 Volume 4 | Number 3 | March | 2023
framework that enables us to utilize it (Lea &
Webley, 2006). The tool theory of money em-
phasizes that money is not meant to be used as
an instant reward, but rather it is meant for de-
layed gratification. For instance, if you would
like to earn money, you have to do something
or produce something so that can trade it in ex-
change for money. As a result, customers will
only purchase video games once they are bug-
free and available in the marketplace. As a re-
sult of trade, people would be able to enjoy the
gaming experience. This would be a form of lei-
sure and entertainment (McCauley, 2020;
Bender & Sung, 2021; Rega & Saxena, 2022).
Tool Theory of Money, Game Development,
and Game Play
In in-game development, money serves as a
tool of the trade that reflects the value and
quality of games. The number of game charac-
ters, the quality of game graphics, and the num-
ber of functions that allow multiple people to
play a single game determine the monetary
value of games based on the perspectives of in-
vestors. This will then be used as the basis for
how the game will be priced as a byproduct in
the marketplace, as well as its game compo-
nents such as loot boxes, weaponry, assets,
game characters, and other game-related as-
sets. As a byproduct of leisure and entertain-
ment, people will use their money to buy games
to experience the fun of playing them. In return,
the money that the investors would get from
selling video games in the marketplace will be
used for employee salaries, the company’s op-
erational expenses, and income distribution for
shareholders. Klimas (2017) has identified the
3 common game monetization models to en-
sure the flow of revenue streams for game de-
velopment. First, games as a byproduct for lei-
sure and entertainment can be sold to people
through the one-time payment of the game;
one-time payment from selling the basic fea-
tures of the game and another payment for the
premium or additional features of the game;
and selling games through subscription or mul-
tiple-fix payment (monthly, quarterly, or an-
nual) for playing the game. The second model is
Freemium or providing the game as a free com-
modity to clients, and money will be earned
through the payment of advertisers and selling
game byproducts or in-app purchases. The
third model is selling the game by providing li-
censes through royalty fees (Klimas, 2017).
Games and other related assets can be sold for
the redevelopment of new game versions; as-
sets for movies, tv shows, or commercials; and
assets for fashion’s by-products (e.g., t-shirts,
jeans, jackets, stickers for cars, advertise-
ments). The monetization models of game de-
velopment reinforce the sustainability of earn-
ing money from the point of view of the game
developers. But what about video game play-
ers? Is TTM biased towards the monetary
needs of game developers? Is it safe to assume
that video game players are only interested in
the joy and fun that the game brings?
Based on the premise of the Tool Theory of
Money, consumers or video game players also
perceive money in the same manner that game
developers do. It is already established that
people play games to enjoy them (Egli & Mey-
ers, 1984; Greitemeyer et al., 2019; Holl et al.,
2020). However, the view that people are only
playing games for fun and enjoyment limits the
perspective of using money as a tool to moti-
vate people to play. Video game developers
should adapt to a new perspective of letting
their consumers earn money while playing the
game. "Earning while playing" is not a new con-
cept in the game industry, although previous
studies have focused on the gambling aspect of
it, such as betting on Counter-Strike or DOTA
game matches (Holden & Ehrlich, 2017)). Aside
from games or esports betting, players may sell
their distinct game character skins, assets, or
other in-game assets (Oh & Ryu, 2007). An-
other emerging money-generating framework
for the benefit of video-game players is the in-
tegration of cryptocurrency and non-fungible
tokens (NFT) in the blockchain-based game in-
dustry. Non-fungible tokens (NFTs) have al-
ready emerged as the new topic of conversa-
tion for the bitcoin market's scientific and in-
dustrial sectors. The phenomenon is driven by
their functions and profitable trades, as evi-
denced by the $24.4 million sales of a bundle of
101 NFTs out of the "Bored Ape Yacht Club" in-
ventory (Darayam, 2021). Unlike conventional
cryptocurrencies such as Ethereum, Binance,
Dodge, and Bitcoin, where all coins are identi-
cal, interchangeable, and "fungible," NFTs are
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 900 Volume 4 | Number 3 | March | 2023
described as digital currencies which can't be
traded for other digital products. As a result,
NFTs are one-of-a-kind and "non-fungible"
(Wang et al., 2021). This inherent property en-
ables NFTs to prove the authenticity and own-
ership of a variety of different items in a variety
of different fields, which explains its rapid
adoption in play-to-earn games, digital gather-
ings, electronic memorabilia, and metaverses
(Nadini et al., 2021; Wang et al., 2021). Indeed,
in recent months, venture capitalists and gam-
ers have flocked to the play-to-earn online
games and metaverse, setting new records for
virtual land sales and token values. As evi-
dence, digital lands in the Decentraland
metaverse and the Axie Infinity have been pur-
chased for $2.4 million (Manfredi, 2022) and
$2.5 million (Venkataramakrishnan & Steer,
2022). Additionally, their equivalent digital
currencies, AXS and MANA have been incorpo-
rated into the top 40 cryptocurrencies by mar-
ket capitalization as a result of their price gain
(Ledesma, 2022).
Problematic Gaming Behavior
When played in excess, online games have
been linked to negative outcomes, including
functional impairment (Billieux et al., 2017).
Internet gaming disorder was added as a "con-
dition requiring more investigation" to the
DSM-5 in 2013 (American Psychiatric Press,
2013), while the ICD-11 adds the gaming disor-
der diagnosis in a section devoted to disorders
associated with substance abuse and behav-
ioral addictions (WHO,
https://icd.who.int/dev11/l-m/en. [Accessed
13 March 2022].). On the other hand, games can
be used as a stress reliever (Pallavicini et al.,
2021) and might have a positive impact on stu-
dent's academic achievement (Torralba, 2020).
Numerous labels have been used to refer to a
problematic or pathological trend of video
game usage in the current literature, including
online game addiction (Han et al., 2012; Han et
al., 2014), Internet gaming disorder (Petry &
O’Brien 2013), problematic video game use
(Mentzoni et al., 2011), problematic online
gameplay (Kim et al., 2012), and internet game
addiction (Zhang et al., 2015). However, in the
context of play-to-earn games, it is important to
consider the role of money as the primary mo-
tive for why people exhibit problematic gaming
behavior. Players may treat video games as a
source of income, which is similar to entrepre-
neurial activity. Based on the analysis of differ-
ent researchers that is related to entrepreneur-
ship and addiction, it was found that entrepre-
neurs may suffer some form of addiction in the
pursuit of money (Keskin et al., 2015). Thus,
problematic gaming behaviors can also be at-
tributed to the fact that gamers are sacrificing
some of their routine activities for the oppor-
tunity to play and earn money. As stated in the
TTM, people may treat gameplay as a form of
work where they exert effort to learn all of the
game mechanics and strategies to win over
their opponents. Players will build their game
reputation, game statistics, game levels, and in-
game assets. This way, the player can make
money by giving social media tutorials, selling
their game skin or level, or trading their assets
in exchange for money or cryptocurrency.
Learning Styles
Research has examined potential mediators
between problematic game use and negative
outcomes, including demographic factors such
as gender (Baloğlu et al., 2020), age (Laconi et
al., 2015), and education status (Meduna et al.,
2020). Furthermore, the literature has ex-
plored the relationships between problematic
game behavior and individual factors including
personality (Seong et al., 2019), self-efficacy
(San-Martin et al., 2020), self-esteem (Cudo et
al., 2020), and social factors such as loneliness
(Tras, 2019; Ok, 2021) or broader societal func-
tioning (Eijnden et al., 2018; Cheng et al., 2018).
Additionally, some studies have addressed the
association between family dysfunction and ex-
cessive gaming engagement (Throuvala et al.,
2019; Stavropoulos et al., 2019). No study has
examined the relationship between adoles-
cents' learning styles, problematic gaming be-
havior, and the motivation of gamers to earn
money from games. Learning the game me-
chanics to develop a gaming strategy follows
the same learning principles that are being im-
plemented in classrooms.
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It has long been established by educational
researchers and psychologists alike that play-
time provides critical possibilities for learning
(Yogman et al., 2018; Rapp et al., 2019). Stu-
dents who engage in play and recreational ac-
tivities in which natural behaviors appear to be
shaped develop their psychomotor skills and
critical thinking skills to react appropriately to
different situations that might occur. For exam-
ple, playing Counter-Strike trains the player's
instincts to anticipate the game strategy and
the location of their opponent. Thus, the play-
ers can develop and implement their strategy
along with their teammates to beat their oppo-
nents. Throughout the play, the person is often
deeply involved, confronted with complicated
sequences of events, and challenged to react
immediately, all within a fail-safe atmosphere
receptive to exploration. This situation creates
excellent conditions for learning to occur. Addi-
tionally, play is often social, which adds an im-
portant incentive component. As demonstrated
by computational approaches to learning, these
are optimal settings for increasing behavioral
flexibility and adaptability in learning how to
learn [57](Nguyen & Oudeyer, 2012). Like-
wise, play can be viewed as a natural conse-
quence of development and can be used to eval-
uate performance in a much more stimulating
and natural manner (Wortham et al., 2012).
It's worth noting that one of the critical suc-
cess criteria for game development is a thor-
ough understanding of the personality and
learning styles of video game players. As with
any other type of learner, video game players
employ a variety of strategies for processing,
engaging with, and dealing with knowledge.
These approaches or inclinations are referred
to as learning styles (Aljaberi, 2015). For in-
stance, some people prefer to learn by doing,
while others prefer reading (Felder & Soloman,
2022). Understanding a gamer's learning style
enables game developers to enhance the learn-
ing process for game adaptation. For example,
game developers can tailor resources to gam-
ers who learn in a certain way, which increases
their level of satisfaction and learning out-
comes while cutting down on the amount of
time it takes to learn. Kolb's model, Dunn and
Dunn's VAK model, the Big Five model, the
Honey and Mumford models, the Felder and Sil-
verman models, the Gregorian model, the Carl
index model, and Brick Meyers, Howard Gard-
ner, and Chris Jackson's style are all examples
of common learning styles (Khenissi et al.,
2016; Deborah et al., 2014). Among the several
learning styles, many researchers prefer Felder
and Silverman's because it provides a more de-
tailed description of the learner's "learning
style," including four distinct dimensions of the
learner's preferences and psychological com-
ponents of learning. Felder and Silverman's
styles of learning can be broken down into four
groups: active/reflective, sequential/global,
visual/verbal, and sensing/intuitive.
Active learners retain and comprehend in-
formation best when they are actively engaged
in it, discussing, applying, or articulating it to
others. Reflective students prefer to contem-
plate it over quietly first. Active learners are
more likely to enjoy group work than reflective
students, who prefer to work alone. Sensory
learners prefer to memorize facts; intuitive
learners frequently prefer to explore possibili-
ties and relationships. Sensory learners fre-
quently prefer to solve problems using well-es-
tablished methods and despise difficulties and
surprises; intuitive learners value innovation
and despise repetition. Sensors are more likely
to be resentful of being tested on material not
formally discussed in class than intuitors. Vis-
ual learners retain information best when it is
presented in the form of images, illustrations,
flow diagrams, time frames, movies, and work-
shops. Verbal learners benefit more from ver-
bal explanations than written or spoken ones.
Everyone gains a greater understanding when
information is presented visually and verbally.
Sequential learners often acquire knowledge in
linear phases, with each step logically following
the previous one. Global learners frequently
make significant leaps in their learning, absorb-
ing stuff almost randomly and failing to per-
ceive connections until suddenly grasping it.
Global learners may be able to solve compli-
cated matters rapidly or put things together in
creative ways once they comprehend the big
picture, but they may have difficulties express-
ing how they did it.
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Methods
The sample was obtained from the fresh-
men Computer Science and Information Tech-
nology students of the Institute of Information
and Computing Sciences, University of Santo
Tomas. A purposive sampling procedure was
adopted. The selection of the participants or re-
spondents was based on their availability to an-
swer the research instruments that were used
in this study. All participants were enrolled
during the school year 2019-2020. The study
utilized a 4-part research instrument. The first
part was a researcher-made instrument that fo-
cused on the socio-demographic profile of the
respondents, such as gender, course, and the
video/online games that they were playing.
Frequency counts and simple percentages
were used to describe the socio-demographic
profiles of the respondents, such as age and
gender. Respondents were asked to give a Yes
(1) or No(0) answer if they were playing the
following games: Warcraft III, League of Leg-
ends, Heroes of Newerth, DOTA 2, Dragon Nest,
Cabal Online, Continent of 9th Seal, Counter-
Strike, Mercenary Online, Point Blank, Cross-
Fire, Special Force, Left 4 Dead. The sum was
then computed by the researcher. The second
instrument was adapted from the 18-item
Video Game Dependency Scale (Rehbein et al.,
2015); the third instrument was adapted from
the Index of Learning Style Questionnaire (Litz-
inger et al., 2007); and the fourth instrument
was adapted from the Success and Economic
Profit subscale of the Online Game Addiction
scale (Basol & Kaya, 2018). The respondents
were advised to honestly respond by checking
the choices of the items. The computation of the
weighted mean was employed for the 18-item
Video Game Dependency Scale, the 8-item Suc-
cess Motivation subscale, and the 4-item Eco-
nomic-Gain Motivation subscale of the Online
Game Addiction Scale to be used for the regres-
sion analysis. The combination of the Success
Motivation subscale and the Economic-Gain
Motivation subscale aims to explore the per-
ceptions of players to learn if achievements and
monetary benefits motivate them during game-
play. For the Index of Learning Style, the re-
sponses were tallied for the subscales of
Active/Reflective, Sensing/Intuitive, Vis-
ual/Verbal, and Sequential/Global.
The ILS questionnaire presents a collection
of items that can be used to determine a learn-
er's learning style. Because 11 questions are
presented with each of the 4 dimensions, the
resulting index of choice for each dimension is
represented as an odd integer ranging between
[-11, +11]. Each question has two alternative
solutions, one with a value of +1 and the other
with a value of -1. For example, when a learner
answers a question with a reflective prefer-
ence, their score is increased by one, and when
they answer with an active preference, their
score is reduced by one (i.e., -1 is added). The
outcomes are interpreted as follows for each
dimension: -11 to 0 means a preference for Ac-
tive, Sensing, Visual, and Sequential repre-
sented by 1. On the other hand, values from 1 to
11 mean a preference for Reflective, Intuitive,
Verbal, and Global is represented by 2. The
learning style with the most points on each sub-
scale was used to describe the person's four
main learning styles.
For statistical analysis, SPSS 22 was used in
this study. Skewness and kurtosis were used to
check for normality at the item level and found
no problems. The outliers were removed and
they were identified using the Mahalanobis,
Cook's, and leverage values in the regression
analysis of SPSS. Cronbach's alpha was used to
assess the reliability of the responses. The im-
pact of the independent variables, gender, the
number of videos/online games played by re-
spondents, and the determinants of the Video
Game Dependency Scale (Preoccupation, With-
drawal, Tolerance, Reduce/Stop, Continue De-
spite Problems, Give up other activities, Escape
Adverse Moods, Deceive/Cover-up, and
Risk/Loss) on the three dependent variables,
Success-economic gain motivation, were deter-
mined using regression analysis. After figuring
out which variables were important, model 3 of
Andrew Hayes' Processing (Hayes, 2022) was
used to look into how the respondents' learning
styles might be moderating the results. Model 4
of Haye's Processing was also used to look at
how gender, the number of videos/online
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 903 Volume 4 | Number 3 | March | 2023
games played by respondents, and the depend-
ent variable were all linked together.
Results and Discussion
Descriptive Results
The original number of participants was
148, composed of 110 male and 38 female stu-
dents. The Mahalanobis, Cook’s, and Leverage
Values functions of SPSS were used to identify
and remove the outliers, which left a total of
136 participants, composed of 100 male and 36
female students. Out of the 136 participants,
39.7% played Warcraft III, 49.3% played
League of Legends, 42.6% played DOTA 2,
30.9% played Dragon Nest, and 10.3% played
Cabal Online. 67.6% played Counter-Strike,
27.2% played Cross-Fire, and 23.5% played
Special Force. 19.1% of players played Point
Blank, 11.8% played Heroes of Newerth, 3.7%
played Mercenary Online, and 1.5% played
Continent of the 9th Seal. Figure I shows the
frequency distribution of the most common
games that are being played by the respond-
ents.
Figure I. Frequency distribution of the most common games that are being played by the respondents
Table I shows the descriptive statistics of the 9 subscales of the Video Game Dependency Scale
Table I: Subscales of Video Game Dependency Scale
Subscales
N
Minimum
Maximum
Mean
Std. Deviation
Preoccupation
136
1.00
4.00
2.0184
0.862
Withdrawal
136
1.00
4.00
1.9485
0.850
Tolerance
136
1.00
4.00
2.2169
0.910
Reduce/Stop
136
1.00
4.00
1.9265
0.815
Continue Despite Problems
136
1.00
4.00
1.8199
0.783
Give-up Other Activities
136
1.00
4.00
1.8346
0.741
Escape Adverse Moods
136
1.00
4.00
2.6140
0964
Deceive/Cover-Up
136
1.00
4.00
1.7757
0.788
Risk/Lose
136
1.00
4.00
1.6765
0.783
Table II: Success-Economic Gain Motivation
N
Minimum
Maximum
Mean
Std. Deviation
Success-Economic Gain motivation
136
1.00
4.00
2.6991
0.701
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IJMABER 904 Volume 4 | Number 3 | March | 2023
Table III shows the descriptive statistics of the 4 dimensions of Felder and Soloman's Index of
Learning Style, which is Active/Reflective, Sensing/Intuitive, Visual/Verbal, and Sequen-
tial/Global.
Table III: Felder and Soloman's Index of Learning Style
Active/Reflective
Sensing/Intuitive
Visual/Verbal
Sequence/Global
N
136
136
136
136
Mean
3.507
2.404
2.103
2.610
Std. Deviation
0.6085
0.9139
0.8007
0.7997
Regression Results
Stepwise regression was employed to find
the best model between the 9 subscales of the
Video Game Dependency Scale as the inde-
pendent variables and the Success Motivation
and the Economic Gain Motivation dependent
variables. After implementing the regression
analysis, three regression models were pro-
duced to describe the relationships between
the independent and dependent variables. The
significant subscales of the Video Game Depend-
ency Scale, which are "escape from adverse
moods", "preoccupation", and "risk/loss" of the
three regression models, have a Cronbach al-
pha value of 0.803, 0.836, and 0.757, respec-
tively, indicating that all responses are valid
and reliable. To ensure that there is no colline-
arity between the independent variables of the
model, Pearson r correlation was used. It was
found that collinearity existed between the var-
iable’s "preoccupation" and "risk/loss." Thus,
the study adopted the second regression model
(R = 0.764, R-square = 0.584), which shows that
"Escape Adverse Moods" (β = 0.377, P < 0.000)
and "Preoccupation" (β = 0.274, P < 0.000) posi-
tively predict the Success and Economic-Gain
Motivation of gamers, as presented in Table IV.
According to this result, the reason respond-
ents play games is that they are obsessed with
the game and want to get away from their prob-
lems by playing games instead of doing other
things
Table IV: Regression Results of Significant Subscales of Video Game Dependency with respect to DV
Model
β
Standard Error
t
Sig
Constant
1.161
0.119
9.741
0.000
Escape Adverse Moods
0.377
0.050
7.551
0.000
Preoccupation
0.274
0.056
4.902
0.000
Dependent Variable: Success and Economic-Gain Motivation of playing games
R = 0.764, R-square = 0.584
The Mediating Roles of Escape Adverse
Moods and Preoccupation
A separate stepwise regression was per-
formed using "gender" and " actively played
games " as the independent variables and the
dependent variable "Success and Economic-
Gain Motivation" of playing games. After the re-
gression analysis, it was found that the "number
of games that the respondents were actively
playing" (β = 0.083, P < 0.000) significantly pre-
dicted the "Success and Economic-Gain Motiva-
tion" of the respondents, as shown in Table V.
This result implies that the more games that the
respondents play, the greater their chances of
success and economic gain.
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 905 Volume 4 | Number 3 | March | 2023
Table V: Regression Results of Actively played games with respect to DV
Model
β
Standard Error
t
Sig
Constant
2.376
0.087
27.393
0.000
Actively played games
0.083
0.017
4.849
0.000
Dependent Variable: Success and Economic-Gain Motivation of playing games
R = 0.386, R-square = 0.149
This study employed the use of model 4 of
Andrew Haye’s Process to explore the mediat-
ing roles of "Escape from Adverse Moods" and
"Preoccupation" between "Actively played
games" and the dependent variable. Results
show that the "number of games that the re-
spondents were actively playing" significantly
predicts "Escape from Adverse Moods" (see Ta-
ble VI) with a coefficient of 0.1125 (p < 0.000)
as well as "Preoccupation" (see Table VII) with
a coefficient of 0.0814 (p < 0.0005). The direct
effect of "Actively played games" on the depend-
ent variable "Success and Economic-Gain Moti-
vation" is 0.0218 (p < 0.10). As shown in Table
VIII, "Escape from Adverse Moods" and "Preoc-
cupation" have a direct effect on the dependent
variable with a coefficient of 0.3545 (p < 0.000)
and 0.2629 (p < 0.000) respectively. This im-
plies that the more games that the respondents
play, the more opportunities there are for the
gamers to escape from their adverse moods
and the more likely they are to be distracted by
games instead of doing their work at home or
school.
Table VI: Regression Results of Actively played games with respect to DV
Model
β
Standard Error
t
Sig
Constant
2.1772
0.1196
18.2016
0.000
Actively played games
0.1125
0.0236
4.7598
0.000
Outcome Variable: Escape Adverse Moods
R = 0.3803, R-square = 0.1446
Table VII: Regression Results of Actively played games with respect to DV
Model
β
Standard Error
t
Sig
Constant
1.7022
0.1100
15.4811
0.000
Actively played games
0.0814
0.0217
3.7488
0.0003
Outcome Variable: Preoccupation
R = 0.3081, R-square = 0.0949
Table VIII: Regression Results of IV’s with respect to DV
Model
β
Standard Error
t
Sig
Constant
1.1572
0.1184
9.7698
0.0000
Actively played games
0.0218
0.0130
1.6772
0.0959
Escape from Adverse Moods
0.3545
0.0513
6.9041
0.0000
Preoccupation
0.2629
0.0559
4.7062
0.0000
Outcome Variable: Success and Economic-Gain Motivation of playing games
R = 0.6673, R-square = 0.4453
The indirect effect of "Escape from Adverse
Moods" (0.0399) and "Preoccupation" (0.0214)
on the "Success-Economic Gain" motivation
proves to be significant as the bootstrap confi-
dence interval does not include zero as shown
in Table IX. Thus, the roles of "Escape from Ad-
verse Moods" (0.0399) and "Preoccupation" be-
tween the independent and dependent varia-
bles were established as shown in the concep-
tual model of Figure 2. It is noteworthy to
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 906 Volume 4 | Number 3 | March | 2023
mention that the direct effect of the "Actively
played games" on the dependent variable
dropped from 0.083 (see Table 5) to 0.0218
(see Table 8) due to the mediating effects of the
variables "Escape from Adverse Moods" and
"Preoccupation".
Table IX: Mediating Effect of “Escaped from Adverse Moods” and “Preoccupation”
Effect
BootSE
BootLLCI
BootULCI
Total
0.0613
0.0141
0.0351
0.0904
Escape from Adverse Moods
0.0399
0.0104
0.0216
0.0623
Preoccupation
0.0214
0.0066
0.0095
0.0356
Indirect Effect of the independent variable (number of games that the respondents were actively
playing) to the dependent variable (Success and Economic-Gain Motivation of playing games)
Additionally, this study examined the effect
of "Gender" on the independent variables "Es-
cape from Adverse Moods," "Preoccupation,"
and " Actively played games" on the dependent
variable "Success and Economic Gain Motiva-
tion." According to the findings, "Gender" does
not have a direct effect on the dependent varia-
ble. Table X demonstrates that "Gender" has a
statistically significant effect on "Escape from
Adverse Moods" (β=-0.7217, P 0.0005), "Preoc-
cupation" (β=-0.5161, P 0.005), and "Actively
played games " (β=-2.9378, P 0.0001). The re-
sults suggest that male respondents are more
likely to flee their negative moods and become
preoccupied while playing the game than fe-
male respondents.
Table X: Effect of Gender Roles
Effect
Sig
R
R-square
GENDER → Escape from Adverse Moods
-0.7217
0.0000
0.3315
0.1099
GENDER → Preoccupation
-0.5161
0.0018
0.2653
0.0704
GENDER → Actively played games
-2.9378
0.0000
0.3991
0.1593
The Moderating Role of Learning Styles Be-
tween Escape from Adverse Moods and Suc-
cess and Economic-Gain Motivation
Model 3 of Andrew Haye’s Process was em-
ployed to explore the moderating roles of the
different dimensions of respondents' learning
styles. Based on the results, it was found that
the interaction between "Escape from Adverse
Moods", “Active-Reflective” and the "Sequential-
Global" dimension of learning style is statisti-
cally significant (β = -0.4120, P < 0.05) as shown
in Table XI.
Table XI: Moderating Effect of Learning Styles
Model
β
Standard Error
t
Sig
Constant
2.7062
0.0423
63.9523
0.0000
Escape from Adverse Moods
0.5068
0.0452
11.2121
0.0000
Active/Reflective
-0.0708
0.0901
-0.7859
0.4334
Sequence/Global
-0.0991
0.0916
-1.0812
0.2817
Interaction (Escape from Adverse
Moods * Active/Reflective * Se-
quence/Global)
-0.4120
0.1852
-2.2248
0.0278
Outcome Variable: Success and Economic-Gain Motivation of playing games
R = 0.7366, R-square = 0.5426
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 907 Volume 4 | Number 3 | March | 2023
Figure II shows the different slope tests of
the regression line between "Escape from Ad-
verse Moods" (-1 sd, mean, and +1 sd) and the
dependent variable "Success and Economic-
Gain Motivation" due to the moderation effect
of the "Active-Reflective" and "Sequential-
Global" dimensions of learning style. Table XII
shows how two dimensions of learning style,
"Active-Reflective" and "Sequential-Global,"
moderate the effect of the independent variable
"Escape from Adverse Moods" on the depend-
ent variable "Success and Economic-Gain Moti-
vation".
Figure II: Slope tests of the regression line between "Escape from Adverse Moods" (-1 sd, mean, and
+1 sd) and the dependent variable "Success and Economic-Gain Motivation"
Table XII: Effect of Learning Styles between “Escape from Adverse Moods” and DV
Learning Style
Conditional effects of the
focal predictor at values
of the moderators
Sig
Interpretation
Active
Sequential
0.4478
0.0000
"Escape from Adverse Moods"
strongly predicts the "Success and
Economic-Gain Motivation"
Active
Global
0.5909
0.0000
"Escape from Adverse Moods"
strongly predicts the "Success and
Economic-Gain Motivation"
Reflective
Sequential
0.6189
0.0000
"Escape from Adverse Moods"
strongly predicts the "Success and
Economic-Gain Motivation"
Reflective
Global
0.3500
0.0026
"Escape from Adverse Moods"
strongly predicts the "Success and
Economic-Gain Motivation"
The Moderating Role of Learning Styles Be-
tween Preoccupation and Success and Eco-
nomic-Gain Motivation
The result also reveals that the interaction
of “Preoccupation”, “Active-Reflective”, and "Se-
quential-Global" dimension of learning style is
statistically significant (β = -0.7151, P < 0.005)
as shown in Table XIII.
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 908 Volume 4 | Number 3 | March | 2023
Table XIII: Effect of Learning Styles between “Preoccupation” and DV
Model
β
Standard Error
t
Sig
Constant
5.1562
1.0392
4.9618
0.0000
Preoccupation
-0.7141
0.4729
-1.51
0.1335
Active/Reflective
-2.5755
0.7054
-3.6512
0.0004
Sequence/Global
-2.5697
0.7159
-3.5897
0.0005
Interaction (Escape from Adverse Moods
* Active/Reflective * Sequence/Global)
-0.7151
0.2283
-3.1327
0.0021
Outcome Variable: Success and Economic-Gain Motivation of playing games
R = 0.6912, R-square = 0.4777
Figure III shows the different slope tests of
the regression line between "Preoccupation" (-
1 sd, mean, and +1 sd) and the dependent vari-
able "Success and Economic-Gain Motivation"
due to the moderation effect of the "Active-Re-
flective" and "Sequential-Global" dimensions of
learning style. Table XIV shows how two di-
mensions of learning style, "Active-Reflective"
and "Sequential-Global," moderate the effect of
the independent variable "Preoccupation" on
the dependent variable "Success and Economic-
Gain Motivation".
Figure III: Slope tests of the regression line between "Preoccupation" (-1 sd, mean, and +1 sd) and the
dependent variable "Success and Economic-Gain Motivation"
Table XIV: Moderating Effect of "Active-Reflective" and "Sequential-Global” Learning Styles
Learning Style
Conditional effects of the
focal predictor at values
of the moderators
Sig
Interpretation
Active
Sequential
0.4425
0.000
"Preoccupation" strongly predicts the
"Success and Economic-Gain Motivation"
Active
Global
0.6724
0.000
"Preoccupation" strongly predicts the
"Success and Economic-Gain Motivation"
Reflective
Sequential
0.6541
0.000
"Preoccupation" strongly predicts the
"Success and Economic-Gain Motivation"
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 909 Volume 4 | Number 3 | March | 2023
Discussion
The phenomenon of earning money
through playing games is gaining popularity
among gaming aficionados. The results of this
study validate the growing trend that playing
games is being propelled not only for entertain-
ment but also for the monetary benefits that
come with it. Furthermore, the identified prob-
lematic behavior of gamers can be traced to
their motivation to earn something in return
for their effort of studying the game mechanics
and strategies to win over their opponents.
The Conceptual Framework of the Relation-
ship of Gender, Games, Escapism, Preoccupa-
tion, and Success-Gain Motivation
The results of this study paint the role of
gender and the number of games in the prob-
lematic gaming behavior and success-economic
gain motivation of gamers. Figure 4 illustrates
the conceptual links between the variables
"Success and Economic Gain Motivation", "Gen-
der," "Escape from Adverse Moods," "Preoccu-
pation," and "Number of games that respond-
ents were actively playing."
Figure IV: Conceptual framework on the role of gender and the number of games in the problematic
gaming behavior and success-economic gain motivation of gamers.
The conceptual framework of Figure IV de-
scribes the role of gender when it comes to the
number of games that are actively being played
during the study. The results validate the study
by Statista (2022) that states that online games
are still dominated by male players in the Phil-
ippines (Statista Research Department, 2022).
The top five most popular games among re-
spondents are: Counter-Strike, Left 4 Dead
(first-person shooter games (FPS), League of
Legends (multiplayer online battle arena
(MOBA), Warcraft (real-time strategy (RTS),
massively multiplayer online role-playing
games (MMORPG), and DOTA 2 (real-time
strategy (RTS), multiplayer online battle arena
(MOBA). These games can be considered tradi-
tional fighting and shooting games that are
popular among male gamers (Ruvalcaba et al.,
2018). Female gamers in the Philippines prefer
puzzle games, while tactics and RTS games are
the least popular because they are more likely
to engage in non-time-consuming games
(Gismundo, 2020). RTS games like Warcraft,
Dota 2, and League of Legends take a long time
to finish, but most puzzle games can be com-
pleted in a short amount of time or paused and
restarted at any time the player wants. Women
appear to prefer to be spectators and fans ra-
ther than participate in actual game competi-
tions, particularly in FPS, MMORPG, RTS, and
MOBA, which are common themes in esports.
In esports, as a male-dominated industry, re-
ports of aggression (Lopez-Fernandez et al.,
2019, #), harassment (Darvin, 2021), stereo-
typing (Madden et al.,, 2021), and sexism (Ru-
valcaba et al., 2018) by male gamers alienate fe-
male gamers from joining gaming competi-
tions. However, some female gamers are start-
ing to participate in online gaming competi-
tions through hosting and social media stream-
ing of games. The niche of game streaming
gives female gamers a chance to make money
by getting more popular on social networks
and using advertisements and subscription
monetization strategies to make money.
Male gamers are playing games to escape
their adverse moods. Many people like the ex-
perience of leaving the current world and
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 910 Volume 4 | Number 3 | March | 2023
immersing themselves in a fictional one
through activities such as playing online games.
FPS, MOBA, MMORPG, and RTS games enable
players to escape reality and immerse them-
selves in the world of gaming (Bass, 2015).
Gamers can use it as a way to deal with negative
emotions or thoughts like fear of rejection, anx-
iety, and failure as long as they play the game.
In the same manner, male gamers are also
prone to be preoccupied with the opportunity
to play, which may result in the neglect of per-
forming their daily tasks at home. However, es-
capism and preoccupation during gameplay do
not always connote problems, as one should
look into context at the other motivations of
players in playing games. As figure 4 shows, es-
capism and preoccupation predict the success
and economic gain motivation of players dur-
ing gameplay, while gender does not have a di-
rect impact on the dependent variable. Video-
games, just like any other sport, provide chal-
lenges and obstacles to induce healthy compe-
tition. When monetary rewards are added to
the equation, it makes the game more competi-
tive and intense. Thus, players are expected to
devote their time to studying the game me-
chanics and crafting their strategies to win over
their opponents. The more victories they have,
the more popular and influential they will be-
come. This provides more opportunities for
gamers to reap monetary rewards from their
game expertise.
Furthermore, the more games a gamer
plays, the more likely it is that they will earn
money while playing. As figure 4 implies, es-
capism and preoccupation mediate the impact
of the number of games played on the success-
economic gain motivation of playing games.
The list of games that most of the respondents
are playing includes game functionalities that
can monetize game assets. In the case of Coun-
ter-Strike, which garnered the most frequency,
it has highly precise mechanics and rules as an
e-sports game that provides intense competi-
tion between two opposing teams. Players earn
money by planting or defusing bombs,
eliminating other avatars, and surviving
around. The monetary economy is governed by
a complicated set of rules that include how well
people do statistically. In the case of League of
Legends, top players can earn points through
matchmaking rating (MMR) boosting. MMR is a
practice in League of Legends in which a player
(the booster) connects to some other person's
account (the boostee) to play a rated game.
Gamers may earn a solid living by promoting
their accounts to the next category. On the
other hand, MMR boosting is discouraged be-
cause it can have a variety of detrimental im-
pacts on the game and other players, as well as
jeopardize account security. Another way to
profit from League of Legends is to sell gaming
accounts. While League of Legends is indeed a
free-to-play game, some players are willing to
take part in purchasing accounts. When an ac-
count has been invested with value, it will sell
for a higher price. For instance, if a player has
rare or premium skins and higher player statis-
tics and ranks, experienced gamers will be
more interested in your account and be more
committed to putting more money into it.
These competitive gamers can begin playing
ranked without having to grind for the whole
week to complete higher levels.
There are other ways to make money while
playing video games. Gamers and social
streamers generate material for social media
exposure. Gamers and viewers promote, dis-
seminate, endorse, and spread the game con-
tent or tutorials. In return, advertisers and do-
nors provide tangible support to content crea-
tors, encouraging them to produce more game-
related content. Additionally, competitions and
game betting are prevalent in "player versus
player" games such as FPS, MOBA, RTS, and
MMORPG games. Naturally, as the game be-
comes more popular, the reward pools grow
bigger. If the gamer is competent enough to
participate in an esports team, she or he may be
able to make a living wage via prizes and spon-
sorships. Competitive gamers also use live
streams to supplement their revenue.
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 911 Volume 4 | Number 3 | March | 2023
Figure V: Conceptual framework on the moderating effect of learning styles between escapism, pre-
occupation and success-economic gain motivation
The moderating influence of active-reflec-
tive and sequential-global learning styles on
the independent and dependent variables is il-
lustrated in Figure 3. The combination of reflec-
tive-sequential and active-global perspectives
enhances the beneficial effects of escapism and
preoccupation on the gamers' success-eco-
nomic gain motivation during gameplay. Re-
flective learners frequently ponder and evalu-
ate concepts before gaining a complete under-
standing of the subject. When it comes to game
development, Hsiao (2009) observes that
games that offer a large number of possible ac-
tions hinder players' ability to reflect on and
think critically about their future moves (Hsiao,
2009). As a result, under time constraints, the
player is compelled to make snap decisions,
even if they contradict past acts and achieve-
ments in the game. Regarding game mechanics
and monetary systems, game creators should
consider restricting gamers' decision-making
capabilities by limiting the number of available
options. The narrative for these game choices
should be clear and tied to the player's previ-
ous decisions. The connection of game choices
can be managed or altered by game-imple-
mented reinforcement and genetic machine
learning algorithms. Additionally, game devel-
opers may investigate the integration of cryp-
tocurrency and non-fungible tokens into their
games' reward pool systems. According to the
tool theory of money, gamers will become more
circumspect and calculated in their gaming
judgments and methods if they are aware that
money is being used as a kind of reward or pun-
ishment through cryptocurrency or NFT. On
the other hand, active learners are more likely
to experiment and collaborate with team mem-
bers in order to learn. Active learners are more
likely to engage in team-clan recruiting, mes-
saging systems, and player collaboration in
games such as FPS, MOBA, RTS, and MMORPGs.
Additionally, because "active learners" benefit
from practice, game creators should create a
"free-to-play" framework for this demographic
of players.
Sequential learners prefer to learn in a
structured and sequential fashion. A sequential
learner observes a phenomenon via the lens of
interrelated, hierarchical, and procedural con-
cepts (Huang, 2015). Thus, each thought se-
quence is critical for comprehending the signif-
icance of little patterns. For sequential learn-
ers, consistency in game mechanics and struc-
ture is critical. By carefully engineering the lev-
els (easiest-difficult), armament, game assets,
obstacles, and computer-generated opponents,
sequential learners will be able to adapt to the
game. The reward pool system of the game
should follow a structural policy that compels
the gamers to perform the interconnected mis-
sion or daily quest while distributing the game
rewards based on the statistical performance
of the players. To avoid cheating and player
confusion, the steps for winning and claiming
game rewards should be clear and concise.
However, the element of mystery and unpre-
dictability should remain in the game since it
forces reflective and active learners to pause
and rethink their game strategy. Global learn-
ers, on the other hand, frequently make enor-
mous leaps in their learning and like to think
EM Torralba, 2023 / Playing games to earn money: The conceptual framework of interaction
IJMABER 912 Volume 4 | Number 3 | March | 2023
holistically. Global learners, according to
Huang (2015), place a higher emphasis on per-
ceived ease of use. Global learners are easily
distracted, particularly when dealing with a
large number of components, buttons, icons,
and procedures involved in completing a given
function. When it comes to making games, sim-
ple interfaces and good user experiences will
help players learn the game's mechanics. Ex-
cessive material or information will overwhelm
and frustrate global learners, discouraging
them from further exploring the game. Other
than games with a lot of content, assets, charac-
ters, and material, the user interface for all
games (mobile, console, and web) should be
straightforward to comprehend and not re-
quire gamers to navigate through pages of doc-
uments before they can even begin playing. Ad-
ditionally, any tutorials explaining how to play
the game should be integrated into the user in-
terface and should be brief and straightfor-
ward. Whenever designing and building online
or mobile games, all icons and buttons should
point towards the next sequence in the game-
play and must not be utilized as click bait or
misleading links to direct visitors to other web-
sites where game developers can generate ad-
vertising income. While this strategy may pay
off over the short term, it would erode con-
sumer trust and make gamers less inclined to
choose the game.
Conclusion
The study affirms the mediating role of es-
capism and preoccupation in the number of
games played and the success-economic gain
motivation of gamers. Escapism and preoccu-
pation may be viewed in the context of playing
games to earn money. Just like any business
venture or entrepreneurial endeavor, people
will play games if they know that there will be
monetary rewards aside from the joy and en-
tertainment that games provide. Furthermore,
the moderating role of learning styles in preoc-
cupation, escapism, and the success-economic
gain motivation of gamers provides an im-
portant insight for game developers. The find-
ings of this study emphasize the important
characteristics of active, reflective, sequential,
and global learners in developing the game me-
chanics and reward pool system of games. Even
though each learning style has its own unique
features, these features don't conflict with each
other and can be used together to make games
that are all-encompassing and fun to play.
Games should provide a means for players
to be independent and reflect on the role that
they have to play during gameplay as well as
the available choices to finish a game level or
quest. The functionalities of social media plat-
forms such as instant messaging, team collabo-
ration, and trading of game assets will promote
engagement between the stakeholders of the
game. The narrative and the mechanics of the
games should be interconnected and follow a
linear sequence to help the gamers assimilate
the goals of the game. Furthermore, the inter-
face of games should be simple and should not
contain unnecessary game assets or narratives
that will confuse the players. These ideas can be
used with the well-known principles of gamifi-
cation, user interface, and user experience re-
search when you make games for people to play
and enjoy.
The two conceptual frameworks developed
in this study should be utilized and tested in ex-
perimental research on lead generation, user
interface, and user experience for game devel-
opment. Game creators should consider the
various learning styles of players while design-
ing the game's mechanics and reward pool sys-
tem. Additionally, this study may add to the
body of knowledge regarding problematic
gaming behavior.
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