1. INTRODUCTION:

The mobile video game industry is characterized by being in constant change, evolving day by day, but especially for its exponential growth, it is remarkable the big difference between the games that are developed today versus the first game that the world had access to on their cell phone, the iconic Snake, which debuted in 1997 and although it had a simple design, without much difficulty to play it and few details, it was captivating and fulfilled the function of entertaining users, additionally the idea of incorporating games in the mobile device was a strategy that was designed from the marketing area of the product (Armanto, 2010). However, the factor that has influenced the growth of this industry is Wi-Fi, which has facilitated accessibility for the user, and has been the means by which people can download video games to their device (Yepes, 2021).

By 2008, Apple launches AppStore taking advantage of the boom in mobile video games in the world, the creation of this virtual store not only allowed the user to easily and quickly access these, but also opened the doors to purchase within the video games, during the same year Google creates its own version of the App Store under the name of Google Play Store virtual store that fulfills the same function and similar characteristics. On the other hand, in 2012 the Candy Crush game generated the Freemium model which consists of giving free access to download and make use of the game, however, while the user enjoys the game he can acquire certain aids or advantages in exchange for a payment for these, it is a model that is still in force and that at the time was cataloged as a commercial success (Colagrosso, 2011).

Video game creators are in search of having different ways of connecting with users, and are based on the exploration of emotions involuntarily provoked by the video game, in such a way that they analyze both positive and negative attitudes by the performance and the type of realism it has (Küster & Castillo, 2016). For the year 2019, mobile video games generated revenues of $73.8 billion dollars, while computer video games collected $33.1 billion dollars, while console video games obtained $19.7 billion dollars, and it is highlighted that the video game industry for mobile devices had a growth in profits of 12% over the

previous year (SuperData, 2020). In recent years, it has been observed how games that belonged to console or computer formats have migrated to the mobile device format, as is the case of Call Of Duty. According to App Anie (2020) the top most downloaded Free Games in the world are: Free Fire, Clash of Clans, Minecraft, PUBG Mobile, Call of Duty Mobile and Among Us, while the top video games in Colombia are led by Garena Free Fire, Minecraft and Destiny Run. Additionally, during 2020 mobile video games became the most important and preferred leisure activity for Colombians during isolation transforming into a tool for socializing (We Are Social, 2020).

A video game for a mobile device must contain three basic characteristics: gameplay and design, psychology and marketing (Yeeply, 2021). The gameplay and design refers to the user experience (Song, 2018), for this, the way to renew the genre must be taken into account, i.e. the ability to reinvent the concept of a classic game (Sweetser et al., 2017; Corvalán & Villegan, 2021), fluid user experience (Sepehr, & Head, 2018; Nurfuazan & Tangchan, 2021), easily accessible (Yin et al., 2022), and having a story, through the development of characters with strengths and weaknesses (Cai et al., 2022). In terms of psychology, the game should generate identification between the user and the characters (Soutter & Hitchens, 2016), gamification or generation of rewards to keep users in constant interaction with the game (Carradini & Hommadova, 2020), the creation of community or spaces where the user can give their opinion and exchange opinions about the game which will generate trust towards the brand that will be reflected in loyalty (Palomba, 2018; Cui et al..., 2022; Teng et al., 2022) and the cognitive flow with which to predict how the user reacts to the events that are presented in the game (Chan et al., 2022; Dieris-Hirche et al., 2022; Prevratil et al., 2022). Finally, marketing must provide popularity to position it (Ahmad et al., 2017; Conroy et al., 2022; Parshakov et al., 2022) in order to generate monetization (Loshe, 2019; Boghe et al., 2020; Camarero et al., 2021).

Video game creators are on a quest to have different ways of connecting with users, and they rely on exploring emotions triggered involuntarily by the video game, so they analyze both positive and negative attitudes by the performance and the type of realism it has (Küster & Castillo, 2016). For the year 2019, mobile video games generated revenues of $73.8 billion dollars, while computer video games collected $33.1 billion dollars, while console video games obtained $19.7 billion dollars, and it is highlighted that the video game industry for mobile devices had a growth in profits of 12% over the previous year (SuperData, 2020). In recent years, it has been observed how games that belonged to console or computer formats have migrated to the mobile device format, as is the case of Call Of Duty. According to App Anie (2020) the top most downloaded Free Games in the world are: Free Fire, Clash of Clans, Minecraft, PUBG Mobile, Call of Duty Mobile and Among Us, while the top video games in Colombia are led by Garena Free Fire, Minecraft and Destiny Run. Additionally, during 2020 mobile video games became the most important and preferred leisure activity for Colombians during isolation transforming into a tool for socializing (We Are Social, 2020).

Teng et al., 2022) and the cognitive flow with which to predict how the user reacts to the events that are presented in the game (Chan et al., 2022; Dieris-Hirche et al., 2022; Prevratil et al., 2022). Finally, marketing should provide popularity to position it (Ahmad et al., 2017; Conroy et al., 2022; Parshakov et al., 2022) in order to generate monetization (Loshe, 2019; Boghe et al., 2020; Camarero et al., 2021).

It is worth noting that several studies related to behavior towards video games have been developed, such as addictive use of internet and time to play video games (Dongil & Junwon, 2021), preferences for Chinese video games with characters emphasizing fantasy-style sexism (Song, 2018), attitude towards video game violence (Kort (2020), motivations for downloading and socializing with other players (Carradini & Hommadova, 2020), learning (Corvalán & Villegan, 2021), satisfaction as a predictor for playing online mobile games (Nurfuazan & Tangchan, 2021), gaming habits and gendered experiences (Goette et al. , 2019).

However, few studies have been developed for the identification of the different types of video game players (Braun et al., 2016; Manero et al., 2016; Fu et al., 2017), and there are no studies of this type in the Colombian context, which is why, this research aims to answer the question: what are the different types of video game players on mobile devices in the city of Bogota? This in order to identify the different types of video game players on mobile devices in the city of Bogota, and thus be able to compare the differences and similarities between the different types of video game players on mobile devices in the city of Bogota. Thus, knowing the context of the consumption of video gamers on mobile devices becomes a relevant input for both cell phone brands, as well as operating systems and video game creators themselves.

2. THEORETICAL BACKGROUND:

Segmentation is a technique in which the market is divided by subgroups that meet similar particularities and needs (Schifman & Kanuk, 2001), based on the behaviors and needs that these subjects share (American Marketing Association, 2006). Therefore, it is based on an analysis of needs, tastes and behaviors of the individuals to whom a brand or company wants to direct its marketing strategy, in short, this method allows the organization to know its target group in a deeper way.

However, the objective of lifestyle segmentation is to generate behavioral patterns in consumers based on their aspirations and purchase decision factors with a psychological and social approach (Vyncke, 2002). Thus, lifestyles are a consumption pattern that has an impact on consumers' choices when investing their time and money (Solomon, 2008); and are a reflection of consumer tastes and preferences (Limeira, 2008). For Giddens (1991), lifestyles are routine practices that are applied in clothing, eating and acting habits; however, these habits and ways are subject to change. However, lifestyles, based on habits and beliefs, can be viewed from a global, national, positional and individual perspective (Jesen, 2007). The global level is determined by universal consumption trends (Jesen, 2007), the national level depends on the particularities of each country, such as culture, since it is a common aspect among the inhabitants that configures them as a territory (Arnstberg, 2007), while the positional level focuses on the social structure and therefore takes into account variables such as socioeconomic stratum, educational level, gender, age, purchasing power, among others (Johansson, 1992) and finally, the individual level is related to the understanding of those aspects with which the consumer feels identified and how to use this to the consumer's advantage so that he/she feels represented by the product or service (Wilska, 2002).

This being so, segmentation by lifestyles allows identifying the activities and motivations of consumers which allows identifying unmet needs that should be addressed (Weinstein and Cachill, 2014). Although there are several lifestyle segmentation methods, the methodology based on Activities, Interests and Opinions (AIO) has had greater acceptance in the Latin American context (Arellano & Burgos, 2005; Cristancho et al., 2022). This method is based on a valuation system that allows identifying what the consumer finds motivating or values in life; this system is related to specific products or a brand that he/she consumes (Wind, 1971). On the other hand, psychographic studies conducted by Levy (1966) and Krishan (2011) have shown that in the AIO there is a kind of common code among people who adopt a certain lifestyle according to the group to which they belong or wish to belong, thus generating a pattern of use of certain goods and services that allows them to identify themselves and develop a personality that can be shared with others (Sarabia, 2009).

Table 1 shows the rational psychological variables proposed by Plummer (1974), compared to the AIO methodology, who states that the lifestyle is formed from rational, concrete and behavioral psychological variables, which allow the researcher to obtain a vision of the consumer, where it is believed that the individual adopts a lifestyle based on the strong social groups to which he/she belongs or aspires to belong.

Table N° 1. Variables of the AIO methodology

AIO model component	Variables
Activities	Work, hobbies, social events, holidays, entertainment, belonged to a club, community, shopping, sports, among others.
Interests	Family, home, work, community, recreation, fashion, food, media, achievements, among others.
Reviews	Of themselves, social affairs, politics, business, economy, future, education, products, culture, among others.

Source: Adapted from Plummer (1974: pág.34).

3. METHODOLOGY:

Based on a descriptive, cross-sectional, non-experimental study with a quantitative approach, the aim was to identify the different types of video game players on mobile devices, using as a reference the segmentation by lifestyles proposed by Plummer (1974). The target group was men between 18 and 32 years of age in the city of Bogota, who habitually use their mobile device to play video games. A non-probabilistic sample design by convenience was used, thus achieving a total sample of 422 people.

The data collection was done through a survey in digital format, which is composed of two sections. The first is composed of 7 closed polytomous and nominal questions in order to obtain the sociodemographic characteristics of the population. Subsequently, 33 items are related with a Likert-type scale response (1=Totally disagree, 5=Totally agree) in order to determine lifestyles through activities, interests and opinions.

The data analysis was developed through the SPSS v26 statistical program, the initial data treatment consisted of determining the dimensionalities of the model for which an exploratory factor analysis was used, followed by Cronbach's Alpha coefficient in order to determine the reliability of the constructs. In the case of segment identification, reference was made to the hierarchical cluster segmentation model followed by the K-means methodology. This technique is based on multivariate statistical methods of data classification, where the subjects or variables that present similar characteristics are grouped together to form the different clusters (Sokal and Sneath, 1963), which are homogeneous among the subjects that compose them, but at the same time heterogeneous among them and they comply with the characteristic of being different from each other (Aldas, 2008), the clusters are established a posteriori, that is, the researcher does not know from the beginning the number of clusters that will be obtained, nor the characteristics that define them, only after performing the segmentation exercise (Torrado and Berlanga, 2013).

On the other hand, the segmentation analysis by the K-means method allows the researcher to classify the subjects or variables based on the similarities between them, which are determined based on the centroids and these in turn correspond to the mean of the points assigned to each cluster (MacQueen, 1967, Duda & Hart, 1973). The K-means method is developed just after the cluster segmentation method, in such a way that it allows a more detailed segmentation process.

4. RESULTS:

The population that participated in the study was characterized by being between 18 to 25 years old (n= 282; 66.8 %) and 26- 32 years old (n= 140; 32.2%); in terms of gender the majority are men (n= 221; 52.4 %) than women (n= 189; 44.8%) and other (n=12; 2.8%); with a level of education in secondary school (n= 147; 34. 8%), technical technologist (n= 173; 40.9%), professional (n=92; 21.8%) and postgraduate (n=10; 2.36%); at the same time it can be observed that the predominant occupations are student (n= 120; 28.4%), studying and working (n= 154; 36.4%) and working (n=135; 31.9%) and those who neither study nor work (n=13; 3.3%). To determine the dimensionality of the instrument, an exploratory factor analysis was developed through the principal components method, with the varimax extraction method; values higher than 0.4 were taken as a reference for both the communalities and the factor loadings, so that the result converged in 5 factors which grouped all the questions or items of the instrument, explaining 63.23% of the variance. It is worth noting that both the Kaiser-Meyer-Olkin test (x^2=0.940, gl=528, p>0.01) and the significance in Bartlett's test of sphericity (p<0.001) are consistent for the model.

The first factor was named aspects for downloading a video game, the second factor was related to activities, the third to interests, the fourth to opinions and the last to preferences towards the video game. The result of the Cronbach's alpha statistic was optimal, i.e., at the construct level, the questions grouped in each dimension explain it. However, the lowest score was obtained for the activities dimension, although it is within the acceptable parameters of the research. These results can be seen in Table 2.

Table 2. exploratory factor analysis

Construct

Items

Variable

Factor Loadings

Alpha

Aspects when downloading a video game

The recommendations of other players

ADVJ1

0,777

0,902

Recommendations and ratings in the play store

ADVJ2

0,725

The quality of graphics and soundtrack

ADVJ3

0,688

No advertising during the game

ADVJ4

0,677

The developer of the game

ADVJ5

0,668

May have different roles (single player, multiplayer, etc.)

ADVJ6

0,664

The type of game

ADVJ7

0,649

Recommendations from a gamer or influencer community

ADVJ8

0,622

If you allow shopping

ADVJ9

0,597

The download size

ADVJ10

0,587

Gamer activities

Buy accessories to play on your phone

AG1

0,814

0,87

Get used to shopping in the video game

AG2

0,743

Used to participate in gamer tournaments

AG3

0,709

Usually wear clothes with images or designs allusive to video games

AG4

0,704

His interest in video games is already professional

AG5

0,549

Download video games constantly

AG6

0,494

Constantly interact with other players

AG7

0,489

Opinions towards the gamer

I feel frustrated not being able to advance in a game

OG1

0,8

0,898

For me it is important to pass levels

OG2

0,731

Sometimes I forget that this is just a way to hang out and I take it very seriously

OG3

0,672

Video games bring me more than people think

OG4

0,652

Sometimes I conflict with other players when I play in multiplayer mode

OG5

0,598

Video games are part of my lifestyle

OG6

0,58

Whenever he plays he’s obsessed with passing a level

OG7

0,493

Gamer interests

Stay informed about new video game updates and news

IG1

0,697

0,878

Interested in becoming part of gamer communities and participating in forums

IG2

0,691

Follow social media accounts related to video games

IG3

0,677

I’m interested in meeting people who are only interested in video games

IG4

0,428

I’m interested in having a cell phone where I feel comfortable playing

IG5

0,417

Preferences towards the video game

Remove games you stop using

PVJ1

0,767

0,801

Play whenever you have free time

PVJ2

0,743

His interest in video games is just for fun

PVJ3

0,738

Prefer only those video games that are free or have a free version

PVJ4

0,686

Source: Own elaboration

Table 4. Preferences around the use of video games in segments

Gamer

Casual

No Gamer

Variables

Ítems

F

%

Mean

F

%

Mean

F

%

Mean

Time dedication games

Less than 1 Hour

20

16

2,45

69

34

2,06

42

43

1,804

1 to 2 Hours

55

45

81

40

40

41

2 to 3 Hours

30

24

32

16

9

9,3

3 to 4 Hours

9

7,3

10

5

4

4,1

More than 4 Hours

9

7,3

10

5

2

2,1

Schedule to play

Morning

5

4,1

2,76

11

5,4

2,73

5

5,2

2,814

Late

31

25

38

19

18

19

Night

76

62

147

73

64

66

Early morning

11

8,9

6

3

10

10

Game of preference

Arcade

10

8,1

4,09

9

4,5

4,09

12

12

3,711

Simulators

6

4,9

22

11

7

7,2

Strategy

25

20

50

25

22

23

Shooting

51

42

75

37

34

35

Sports

9

7,3

16

7,9

11

11

Fear

0

0

2

1

0

0

Others

19

15

24

12

11

11

None of the Above

3

2,4

4

2

0

0

Note: F= Frecuency

Source: Authors’ own elaboration

According to table 5, it is possible to observe the comparison between the three segments, in the first place, the Gamer is characterized by being more demanding when downloading a video game on his cell phone, he takes into account several aspects, among these the comments of other players and the quality of the game. The interaction of the Gamer with other players is important because his interest is framed in strategy games, his main concern is focused on passing levels, which is why he keeps informed on social networks about updates and gamer content, for this segment the cell phone should offer him the comfort to play on it, eliminates the games he stops using and plays whenever he has free time, so being a video gamer is part of his lifestyle. And these aspects are less and less relevant for the Casual Gamer and Non Gamer, it is worth noting that the Casual Gamer plays for fun and entertainment, while the Non Gamer is a passive gamer that is to say he likes video games, but it is not his main hobby nor does he consider it as his lifestyle.

Table 5. Comparación de medias de cada dimensión para cada segmento

Construct

Items

Clúster

Gamer

Gamer Casual

No Gamer

Aspects when downloading a video game

The recommendations of other players

4,27

3,54

2,19

Recommendations and ratings in the play store

4,20

3,32

2,28

The quality of graphics and soundtrack

4,41

3,93

2,61

No advertising during the game

4,25

3,87

2,23

The developer of the game

3,91

3,02

2,10

May have different roles (single player, multiplayer, etc.)

4,38

3,79

2,16

The type of game

4,41

3,98

2,77

Recommendations from a gamer or influencer community

4,11

2,64

1,75

If you allow shopping

3,50

2,29

1,66

The download size

3,79

3,06

2,28

Gamer activities

Buy accessories to play on your phone

3,11

1,82

1,60

Get used to shopping in the video game

3,37

1,77

1,52

Used to participate in gamer tournaments

3,38

1,99

1,44

Usually wear clothes with images or designs allusive to video games

3,15

1,64

1,59

His interest in video games is already professional

3,30

2,02

1,56

Download video games constantly

3,76

2,56

1,85

Constantly interact with other players

4,24

3,06

1,65

Opinions towards the gamer

I feel frustrated not being able to advance in a game

4,02

3,15

1,66

For me it is important to pass levels

4,12

3,24

1,67

Sometimes I forget that this is just a way to hang out and I take it very seriously

3,80

2,48

1,47

Video games bring me more than people think

3,96

2,73

1,68

Sometimes I conflict with other players when I play in multiplayer mode

3,62

2,35

1,47

Video games are part of my lifestyle

4,01

2,65

1,65

Whenever he plays he’s obsessed with passing a level

4,12

3,52

1,60

Gamer interests

Stay informed about new video game updates and news

4,04

2,76

1,35

Interested in becoming part of gamer communities and participating in forums

3,81

2,33

1,41

Follow social media accounts related to video games

4,09

2,69

1,53

I’m interested in meeting people who are only interested in video games

3,59

2,27

1,48

I’m interested in having a cell phone where I feel comfortable playing

4,22

3,33

1,66

Preferences towards the video game

Remove games you stop using

4,34

4,01

2,81

Play whenever you have free time

4,20

3,61

2,57

His interest in video games is just for fun

3,98

4,16

2,60

Prefer only those video games that are free or have a free version

3,72

3,81

2,55

Source: Authors’ own elaboration

Once the dimensions of analysis were identified, we proceeded to develop the analysis by hierarchical clustering with the Euclidean distance grouping method, and took as initial reference the graphic method to determine the possible final clusters by means of the dendrogram, and based on the distance criterion, 3 segments were identified. In order to graphically represent the clusters, a scatter plot was developed. For this purpose, a two-factor factor analysis was developed, with the x-axis being factor 1 and the y-axis factor 2. Factor 1 was identified as activities, this dimension being the main one in the segmentation criteria, followed by interests. Illustration 1 shows the segments found, with segment 1 being the most activity-oriented, while segment 2 is more interest-oriented.

Figure 1. Scatter graph through hierarchical cluster targeting method

Source: Authors’ own elaboration

Based on these results, the K-means segmentation method was applied, and it was observed that there are significant differences between the distance of each center of the final clusters, a criterion that defines the heterogeneity between each segment (Kaufman and Rousseeuw, 1990). In addition, it was identified that segment 1 is composed of 123 subjects, segment 2 of 202 subjects, and segment 3 of 97 subjects. In order to identify whether there are significant differences in each segment, the one-factor ANOVA statistic was used on all the variables taken into account in the segmentation model, obtaining statistical significance for each variable, so it can be inferred that the segments are different from each other; the distribution of the segments can be seen in Figure 2.

from each other; the distribution of the segments can be seen in Figure 2.

Figure 2. Scatter graph through K-means segmentation method

Source: Authors’ own elaboration

Three segments were identified, which according to their characteristics were denominated as Gamer, Casual Gamer and Non-Gamer. The Gamer is the one who spends more time playing between 1 to 3 hours (69%), for all segments, the most preferred time to play is at night, with the most preferred games being shooting and strategy, and the least preferred being scary games. Arcade and simulator games are not more popular in the Gamer segment, while casual gamers are more versatile in their preferences. These results can be seen in Table 4.

5. DISCUSSION:

Several studies have tried to characterize the different types of video game players, as proposed by Manero et al. (2016) who identified 4 segments: full gamers, hardcore gamers, Casual gamers and Non gamers, so this research is in sync with what was proposed by Manero et al. (2016), since it identified three of these segments with similar characteristics and although the context of the research focused on console players, the characteristics and consumption preferences are the same even if the video game is on a cell phone. In the same way Braun et al. (2016) identifies three types of video game players according to their personality: Gaming addicts, non-gamers and regular gamers, this segmentation that aligns with the results of the present research, however, Braun et al. (2016) involves emotional instability as a predominant characteristic in the segments of greater approach to video games, but this characteristic is not so evident in those who prefer action games. On the other hand, Fu et al. (2017) also proposes a segmentation model taking as reference not only the activities and preferences with video games, but also their social interaction and role in this, where he identified several types of players among which Leaders and aggressive gamers, Explorers and Achievers stand out, although this segmentation is not in line with the proposal presented in this work if it involves the degree or level of importance of the video game for the user, such as dedication, feelings associated with frustration or success to climb a level, viewing gamer content in social networks, among others.

6. CONCLUSIONS:

It could be evidenced thanks to the segmentation by K-means that there are three types of video game players on cell phones: Gamer, Casual Gamer and Non-Gamer. It is observed that the Gamer segment prefers shooting games and the affinity towards multiplayer games where it can constantly interact with other players, however, although they consider as a priority to pass the levels it is not feasible to invest money in accessories to play on the cell phone, however, it does highlight the importance of having a good cell phone to play. Casual Gamer considers that downloading the game is only for fun. While the Non Gamer downloads games constantly but does not engage with them constantly.

In such a way that there are marked differences between each type of gamer since Gamer sees video games as a lifestyle, something that stopped focusing on a hobby and became an important moment in the day. However, the preferences in the games do not vary, being more downloaded those with shooting theme making them the most common today and also these have the multiplayer option, which allows to interact with more people, this being an important aspect when downloading a game.

In view of the results obtained, it is of great importance to highlight the fact that video games have become an important aspect or stage in the lives of young people, which is why it is important to learn to have limits and to be able to control how they behave in front of these, since the obsession to pass a level or the frustration of not passing it, in order to obtain rewards become the daily goal of some players, thus achieving instability in front of the priorities of the person. Now, video games on mobile devices do not have to be seen in a negative way because they have become a new way in which young people relate, it is now very common to observe that interactions between young people are given through multiplayer video games and online mode, where the fact that it is through the network allows you to have a global reach which allows you to generate in this way interactions with people all over the world, you can really get to talk about a true balance when the user is able to enjoy the experience offered by the video game without breaking the limits that come to harm him in his personal life. Seeing the exponential growth of video games, it is more important to talk openly with young people and teach the correct way to use them, the importance that should be given to them and also to expand the information of these, leaving aside the bad reputation and opening the field to the usefulness of these in a positive way.

Finally, taking into account that the market for video games on mobile devices is booming, Colombia is no exception, since Bogota concentrates video game development companies and exports to countries such as: United States, Canada, Peru, United Kingdom, France, Costa Rica, China and India, reason why understanding the preferences of the players will allow understanding the market and therefore the development of video games according to consumption preferences. For future research, it is important to develop studies oriented to the effect of advertising and its influence on consumption in the context of gamer content in social networks, as well as in the actions of the brand in video games.

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