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Player Preferences on Optimal In-Game Leader (IGL) Characteristics and Behaviors

Jókai-Szilágyi, Gergő (2022)

 
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Jókai-Szilágyi, Gergő
2022
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022121227976
Tiivistelmä
The purpose of the thesis was to understand user desired preferences over the different leadership styles and characteristics in an online team-based competitive video game scene. The main research questions were what gamers’ preferences on leadership traits and behaviors are and which of these are preferred in a teammate in a leader-like role (such as an in-game leader).
A user-friendly, easy-to-follow survey was developed for this research. The questionnaire included twenty (20) questions; on average, the survey completion took less than five minutes for the partici-pants. All the questions were related to user preference, and there was not any limitation on the target groups, such as geographic or demographic aspects.
The responses showed that, in general, people prefer the characteristics and traits of a leader who promotes and actively practices the democratic leadership style. People desire an in-game leader (IGL) who actively engages with their teammates, whether strategizing together or giving and taking feed-back bi-directionally, supports and inspires the team to work as one, as well as to reach a common goal, such as winning a match. The leadership qualities and the preferences of users? of these leader attributes also lean towards the traits and characteristics of a democratic leader.
On the other hand, based on the findings and responses gathered, most of the respondents ranked and defined themselves supportive and participative) or often chose the capable but cautious dimension of the situational leadership style. This outcome indicates that team-based competitive esports environ-ments promote or prefer? the supportive leadership style and mindset of players who are playing to-gether for a common purpose.
Some aspects could have been utilized better to increase the quality of the collected data further. In the future, there could be more in-depth analysis based on the player preferences, more customized questions for the respondents, and some open-ended questions, which would inevitably improve the value of the data.
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