Optimizing Cadet Squad Organizational Satisfaction by Integrating Leadership Factor Data Mining and Integer Programming: Focusing on Leadership Factors That Affect Squad Organization

Hyunho Kim, Eunmi Lee and Sang-Yoon Cha
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Hyunho Kim: Korea Military Academy, South Korea
Eunmi Lee: Kookmin University, South Korea
Sang-Yoon Cha: University of Michigan, USA

International Journal of Data Warehousing and Mining (IJDWM), 2024, vol. 20, issue 1, 1-24

Abstract: Military academy cadets reside in a brigade organized by cadets. Despite its importance, squads have traditionally been organized based on the personal preferences of the fourth-year squad leader without considering the compatibility of the squad members. This study proposes a more scientific approach to increase cadet satisfaction with their squads and foster their leadership development. Initially, a multiple linear regression analysis was conducted to identify the leadership factors of squad leaders that significantly affect squad organizational satisfaction. The model maximized the sum of the factor scores among squad leaders to enhance squad organizational satisfaction and maximized the difference in factor scores to improve the effectiveness of leadership discipline. Applying the squad formation algorithm to data from cadets at the Korea Military Academy revealed that the squad organizational satisfaction and leadership discipline effectiveness were significantly increased compared to the existing squad formation methods.

Date: 2024
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