Generation Z’s Perception of the Stress of Beginner Executives Factor Analysis and Support Expansion Plan

Purpose: The main purpose of this paper is to analyze major stress factors that should be supplemented in order for Generation Z to expand their support as beginner executives, and based on this, consider measures that the Korean military should supplement. Method: The main research analysis targets and research methods were limited to Gen Z's unenrolled college students nationwide, so a survey and SPSS analysis were used for unenrolled college students in Gangwon-do, which is a military unit concentrated area and a border area. Results: Based on the analysis of major stress factors, in this article is to derive the following measures to improve the Korean military to expand support for beginner executives for Generation Z. First, it is the most important to increase the remuneration of beginner executives. Generation Z judged that beginner executives were paid less than other government and social organizations with the same working conditions. Second, it is considered an important value for military organizations to ensure growth conditions and prepare for the creation of beginner executives. Third, preventive measures should be guaranteed for command measures that are out of the regulations of the commander. Fourth, measures to reduce the responsibilities and obligations of beginner executives must be steadily sought. Conclusion: There has been no significant difference from the stressors and improvement measures of beginner executives that have been raised in our military, but it has become clear that it is urgent to supplement the system and come up with measures to revitalize the support of beginner executives of Generation Z and make them a rewarding service. The government should focus on improving and supplementing the working and work environment of beginner executives in order to foster strong national security and strong military developmen t in the era of ultra-low fertility, and to build an early AI-based complex system.