WHAT INFLUENCED GENERATION Z DECISION TO ENTER E-SPORT AS A CAREER?

Current technological developments, especially in the gaming industry, have created new job opportunities in digital games and a new phenomenon known as e-sports. There is a relationship between e-sports and career. There is still limited research on e-sports and one's career, especially those related to the variables Self-efficacy, Extrinsic Motivation, Intrinsic Motivation, Influence by Third Parties, and Career Exposure, so this study aims to examine more deeply the relationship between these variables and career choices in the generation-z. Two hundred eighty respondents in the Greater Jakarta area were examined using a judgmental sampling technique. This study uses Smartpls 3.0 to test the hypotheses' validity, reliability, and results. The results of the study state that Self-Efficacy, Extrinsic Motivation, Intrinsic Motivation, and Career Exposure affect Career Choice, while Influence by Third Parties does not affect Career Choice


INTRODUCTION
The electronic sport or e-sport industry is growing, according to its understanding, namely as a form of sport where electronic devices facilitate the main aspects of this sport, players, teams, and the output of e-sports mediated by computers Parshakov et al., 2020) and have become an evolution of human sports behavior in the current information age (Yue et al., 2020) and has become the popular culture and are widely known by the wider community (McCutcheon et al., 2018). On the other hand, e-sports also refers to competitive video games where teams or individuals compete against each other (Ramirez et al., 2022). For most gamers, it can be a high-paying job, and a small proportion of Exposure is very important for a person's preferences in choosing their career path (Ng et al., 2017). A person's success in choosing his career path can also be seen from the extrinsic factors that allow a person to work for the expected rewards (Bainbridge, 2015), such as salary, better benefits, and job opportunities. Intrinsic factors are factors that are influenced by personal interests and choices (Jackling & Keneley, 2009), where someone will choose a career just because the field is interesting and makes them confident in getting good results in that career (Odia & Ogie Du, 2013). Influence of third parties, namely support from family, friends, teachers, and career consultants (Ng et al., 2017), participation from third parties is proven effective and supportive, which will ensure one's success in a future career (Meddour et al., 2016).
This research is used to explore what factors can influence someone deciding to make e-sports their career choice. Making e-sports a career is still being debated at this time. Caillois (2001) assumes that competing as a professional gamer has a negative effect because the concept of the game itself is a free activity. After all, it has playing activities in it, such as (unproductive and fictitious). However, several important elements can categorize e-sports as any other traditional sport (Thiel & John, 2018). This research is expected to answer the question of what factors influence the choice of e-sport for generation Z.

Self-Efficacy
Self-efficacy refers to the belief that a person can successfully perform certain behaviors based on their perceptions of their abilities and their likelihood of success in that activity (Blotnicky et al., 2018;Cribbs, Huang & Jimenez, 2021). Individuals with high Self-Efficacy will better understand opportunities for success and can more accurately predict the future (Krueger andBrazeal, 1994 in Qiao and. Self-efficacy has a considerable impact, not only involving feelings of oneself but also driving success in life; someone who believes in his ability to face future challenges and complete tasks successfully is said to have self-efficacy to succeed (Harun et al., 2021).
Self-efficacy in career choice refers to individual beliefs to engage in activities related to choosing a suitable career path (Ogutu, Odera & Maragia., 2017). Previous research suggests a significant relationship between Self-Efficacy and career choice (Meddour et al., 2016;Huang et al., 2018). Self-Efficacy has a considerable influence that impacts life success. Someone who believes in their ability to face future challenges in their career and can complete tasks successfully has the self-efficacy to succeed (Lent et al., 2017). Thus it can be hypothesized that: H1: Self-Efficacy has a positive influence on Career Choice of E-sport

Extrinsic Motivation
Extrinsic motivation refers to personal behavior in doing something to achieve a certain goal where the goal is attached to the activity itself (Pelletier et al., 2013;Vallerand et al., 1992;Giakoni-Ramirez et al., 2022) as well as motivation, goals, and learning styles of e-sports professionals change during the process of becoming professional (Kim & Thomas, 2015). In achieving a goal, extrinsic motivation drives the choice of a career in e-sports and directs professionals to pursue an award (Banyai et al., 2020;Brock, 2017).
Constructing measurements based on professional understanding can encourage involvement such as career development, career placement, receiving prizes for completing tasks, and reputation to increase individual placement in an e-sport community (Torhonen et al., 2019). Based on the findings of previous studies, it was found that extrinsic motivation has a positive influence on choosing a career (Giakoni-Ramirez et al., 2022;Porter & Woolley, 2014). Thus, it can be hypothesized that: H2: Extrinsic Motivation has a positive influence on Career Choice of E-sport

Intrinsic Motivation
Intrinsic motivation discusses an activity or something that makes a person feel personally satisfied (Ryan & Deci, 2000). Intrinsic motivation involves interest, pleasure, and satisfaction in doing something (Vansteenkiste et al., 2005). Individuals with high intrinsic motivation tend to show interest and pleasure (Shin & Lee, 2016). Intrinsic motivation also describes a positive experience experienced by someone because they undergo an activity or feel challenged (Ryan & Deci, 2000) but are not influenced by external factors such as pressure, gifts, or coercion from others (Giancola, 2014).
Based on previous research findings, intrinsic motivation has a positive influence on career selection and shows that intrinsic motivation is an important factor in choosing a career (Odia & Ogiedu, 2013). In addition, research on intrinsic motivation factors in choosing a career in the IT field states that intrinsic motivation has a positive influence on choosing a career because of the elements of personal pleasure, challenge, and satisfaction when faced with technology (Potter et al., 2009). Intrinsic factors also positively influence choosing a career (Ayodele, 2019;Panisoara et al., 2013). Thus, it can be hypothesized that:

Influence by Third Parties
The choice of a career can be influenced by external influences such as other individuals or groups of people such as family members, friends, teachers, or other individuals (Ng et al., 2017;Pablo-Lerchundi et al., 2015;Shumba & Naong, 2012). Students choose the right career path because they seek and receive advice from their parents or family members (Meddour et al., 2016). At the same time, high school teachers or instructors in college have an important role in the final choice of students choosing their business majors (Odia & Ogie, 2013), including relatives or friends in the individual's environment (Porter & Woolley, 2014).
Environmental parameters or external influences from individuals, such as support or social level barriers, create a potential influence on career choice positively or negatively as well as directly or indirectly (Lent et al., 2010). Based on previous research findings, it was found that third parties' influence positively influences choosing a career (Ayodele, 2019;Ng et al., 2017;Agarwala, 2008;Nakagomi et al., 2016). Thus, it can be hypothesized that: http://eduvest.greenvest.co.id

Career Exposure
In determining a career, of course, it is necessary to know the nature of the work and what type of career is offered in a field of work. Career Exposure is one of the main considerations in choosing one's career (Ghani et al., 2008). As is known, there are various types of jobs in the e-sport field, such as shout caster, analyst, content creator, event organizer, event administrator, physician, community manager, and the owner (Oliver, 2021). With greater exposure to career-related information, one can make better career choices (Ghani & Said, 2009).
Providing career-related knowledge or information can motivate us to choose a career path in the e-sport field. Previous studies show that career exposure has a positive and significant influence on career choice (Hatane et al., 2021;Ng et al., 2017;Ayodele, 2019). Based on the research results above, career exposure is an important factor in a person's preferences in choosing their career path. Thus, it is hypothesized that: H5: Career Exposure has a positive influence on Career Choice of E-sport

RESEARCH METHOD
The research design in this study is quantitative descriptive type research, which aims to obtain an accurate profile based on an event, the person, or the situation to be studied (Sekaran & Bougie, 2016) in the form of numerical data, and then a conclusion is drawn to reveal a relationship in the study (Albers, 2017;Creswell, 2010). This research was conducted cross-sectionally, where a study was conducted only once in a specified period (Sekaran & Bougie, 2016).
This study uses post-positivism, in which research believes in the truth of a theory even though it is not explained and understood perfectly (Saunders et al., 2019). This study uses primary data, which is collected directly from the main source through surveys, and uses secondary data sources because the data has been collected or processed beforehand (Bairagi & Munot, 2019).

Data Collection Method Data collection
This study used a questionnaire online, which helps researchers get broad coverage and save time. Respondents' answers were measured using a Likert scale which allows respondents to assess how strongly they agree or disagree with statements (Saunders et al., 2016) related to behavior or objects (Kumar et al., 2018). This scale shows the respondents' assessment of the level of agreement on a series of statements contained in the operational variables and instruments in the study (Maholtra, 2015).

Sampling Method
Individuals in Generation Z interested in choosing a career in e-sports are the subject of choice because they have the characteristics of attention in the scope they want to study (Sugiarto, 2017). The sample is obtained from a list of which members will be taken from the population (Bairagi & Munot, 2019). The sampling technique in this study used non-probability sampling, namely that elements in the population do not have an inherent probability of being selected as sample subjects by judgment sampling, which involves choosing the subject that is placed most advantageously or in the best position to provide the necessary information (Sekaran & Bougie, 2016). Sample size in conducting research Using the rule of 10 times the total indicators in the study (Hair et al., 2011), the indicators in this study were 28. Therefore the sample to be used was 280 respondents (10 x 28 indicators).

Measures
This study aims to determine how individuals want or choose a career in the e-sport industry. Individual elements or attributes in the data collected (Saunders et al., 2016). There are 28 statements for the 5 hypotheses, not including the demographic statement. This study uses a 5-point Likert scale with measurements from Strongly Disagree (1) to Strongly Agree (5)  . All variables will be measured using Partial Least Squares-Structural Equation Modeling (PLS-SEM) using SmartPLS 3, which is used to analyze data (Ringle et al., 2015). PLS-SEM is also considered suitable for this study because this research is exploratory research, which facilitates the combination of formative indicators and complex models (Hair et al., 2011), and can accommodate a small number of samples (Hair et al., 2019).

RESULT AND DISCUSSION
Based on the results of an online survey that was distributed, this study found a total of 280 respondents, most dominant with the age of the respondents at 15 -17 years with male (68.6%) and female (31.4%) gender, the respondent's domicile dominated by Jakarta (42.9%), while for jobs dominated by students/students by 61.1% followed by not yet working by 22.5% with last education dominated by high school by 59.3%. We also asked respondents about the game genres they participated in and obtained the results of Multiple Online Battle Arena (MOBA) (54.3%) at the top, followed by Battle Royale at 44.3%. http://eduvest.greenvest.co.id Before researchers test the 5 existing hypotheses, we will test each indicator item's level of reliability and validity to find the consistency and relationship. We use the Measurement Model, which consists of 3 categories: convergent validity, discriminant validity, and composite reliability (Hair, 2011). Outer models or measurement models are used to evaluate the relationship between indicator variables and existing constructs (Hair et al., 2012) and aim to calculate the reliability, internal consistency, and validity of the variables used (Ho, 2013). Variables that have a loading of 0.7 or greater are considered acceptable (Hair et al., 2011;Fornll & Larcker, 1981), and loadings that have a value below 0.7 must be eliminated. Convergent validity values are measured using average variance extracted (AVE) values; convergent values can be fulfilled if AVE ≥ 0.5 is found (Henseler et al., 2009). While the reliability test is used to test the consistency and stability of the indicators (Sekaran & Bougie, 2016), and the method used uses Cronbach Alpha, where one variable is considered reliable if Cronbach's Alpha > 0.6 (Malhotra, 2010).  Based on table 1, 2 variables are declared inappropriate or invalid for use in research, namely the SE3 variable with a factor loading value of 0.699 and the ITP 3 variable with a factor loading value of 0.445, so we eliminated these two variables. For other variables, it is declared feasible or valid for research use and can be used for further analysis because the results of factor loading > 0.7. Based on the 28 indicators in table 2, Cronbach alpha meets the requirements where each existing indicator results above 0.6 to be reliable. While the results of the AVE test for each indicator have been declared valid because the results obtained are ≥ 0.5.   (Ghozali, 2014). The adjusted R Square value of this research is 0.827 and then converted into percent form, which means that self-efficacy, extrinsic motivation, intrinsic motivation, influence by third parties, and career exposure have a combined effect of 82.7%, and the remaining 17.3 % is influenced by other factors not explained in this study. On the other hand, if the R-Square results are close to 1 (one), it can be said that the independent variable can predict the dependent variable very well. Predictive relevance or Q-Square value (Q²) has the objective of measuring how well the research value is carried out by the model and its parameters (Ghozali, 2016), and can be obtained using a blindfolding procedure, then applied to the variables to be tested with reflective measurements (Ghozali 2012;Hair et al., 2011). Based on table 5, it can be concluded that the indicators or constructs used have strong predictive relevance. This is because the Q-Square value is 0.516, which is considered sufficient if it shows a result of more than 0.35 (Latan & Ghozali, 2012), and a Q-Square that is greater than 0 (zero) indicates a predictive relevance value (Hair et al., 2011;Chin, 2010). This study uses a significance level of 5% with a confidence level of 95%. The value of the t-statistic must exceed the number > 1.96 with a significance value of <0.05 (Hair et al., 2011), so it can be concluded that the hypothesis has a significant effect. The hypothesis is insignificant if the t-statistic is less than <1.96 (Haryono, 2017). As seen in table 4 above, it can be seen that hypotheses 1, 2, 3, and 5 are fulfilled with the t-statistic criteria > 1.96 and p-value < 0.05. Meanwhile, hypothesis 4 (H4), with a p-value of 0.180 and a t-statistic of 1.344, is not supported because the p-value > 0.05 and the t-statistic value < 1.96. This is supported by previous research, which also says that the effect influence of third parties has no effect or has less influence on career selection (Wally, 2013;Odia & Ogiedu, 2013;Ng et al., 2017). With Generation Z, already born with quite advanced technology, influence from third parties such as family, colleagues, friends or others is considered less influential. This can be said because Generation Z can better understand and feel about technology themselves. Therefore, if they like the e-sport industry based on their wishes, then the influence of third parties does not play a role in choosing their career.
Self-efficacy is one of the important things in determining a career, especially for Generation Z. If their preferences are following the work to be occupied later, it will positively impact their future careers. Based on the results of hypothesis testing (H1) accepted, this is in line with previous research, which also said that self-efficacy is one of the references for individuals in choosing a career (Meddour et al., 2016;Huang et al., 2018). In the inherent personality of Generation Z, the confidence in their ability to choose a career will be an advantage for them. If they already have this, it will be a reference if Generation Z has the e-sports industry as their future career. Furthermore, extrinsic motivation can encourage Generation Z to choose a career they will choose later. This can be seen from the jobs available in the e-sports industry and the income they will get from carrying out that career. The second hypothesis (H2) is accepted, in line with previous research that extrinsic motivation has a positive influence on career selection, Peter and Wooley (2014) which states that extrinsic factors such as income and career stability are an encouragement to choose a career. Generation Z has high external motivation for choosing e-sports as their career path because they tend to see successful people in the e-sports industry.
Motivation in each individual in an activity that they carry out will encourage them to have a sense of personal satisfaction. Suppose the individual is more interested and happier about the activity being carried out or will be carried out. In that case, the individual will get a positive experience in carrying out the activity. Based on the results of the hypothesis test (H3), it is accepted that this is in line with previous research, which also says that intrinsic motivation has a positive influence on career choice (Ayodele, 2019;Ng et al., 2017;Agarwala, 2008;Nakagomi et al., 2016). Therefore, if Generation Z is motivated by the e-sport industry or enjoys playing games (Kiraly et al., 2018;Kim & Park, 2007) and wants to become a professional in the e-sport industry, they will be able to support these individuals in choosing a career in the e-sport industry in the future. It is known that the career path in the e-sports field is quite good and has been supported by the government by developing the e-sport ecosystem in Indonesia as an outstanding sport (Faiton, 2021). The higher the development of e-sport in Indonesia, the more types of jobs are available in the e-sport field, such as shoutcaster, analyst, content creator, event organizer, event administrator, physician, community manager, the owner (Oliver, 2021) and success in their careers also makes Generations-Z consideration in choosing a career. Based on hypoythesis test (H5) is accepted, this is in line with previous research that Career Exposure has a positive influence on Career Choice (Hatane et al., 2021;Ng et al., 2017;Ayodele, 2019). Thus, Career Exposure is one of Generation Z's considerations in Career Choice.

CONCLUSION
Overall, this study discusses the factors that influence the Generation Z, such as Self-Efficacy, Extrinsic Motivation, Intrinsic Motivation, Influenced by Third Parties, and Career Exposure to Career Choice. Based on the results of this study, 4 hypotheses were accepted, and 1 other hypothesis was rejected. Based on the hypothesis testing, Self-Efficacy, Extrinsic Motivation, Intrinsic Motivation, and Career Exposure significantly influence Career Choice. In contrast, being influenced by Third Parties negatively influences Career Choice. This research can be useful for education providers, especially educational institutions, to prepare new academic learning, namely e-sports, because they see the huge potential of the e-sports industry and also have a growing market. So, the Generation Z or later generations can prepare themselves to enter the e-sports industry and can be profitable for students and education providers. As a professional player, many derivative branches of e-sports can be utilized by education providers, such as shout casters, analysts, e-sports management, and e-sports organizers.