Journal of Information Technology Applications and Management

Korea Data Strategy Society (한국데이터전략학회)
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A Study on the Dissemination Structure of Unfilled Positions in Universities Across the Country using Big Data: Using Panel and Tobit Regression Model

빅 데이터를 활용한 대학의 지역·권역별 학과의 미충원 파급구조 연구: 패널회귀모형과 토빗회귀모형의 응용을 중심으로

  • Received : 2023.01.29
  • Accepted : 2023.02.22
  • Published : 2023.02.28
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Abstract

This study observes the difference in the actual regional ripple effect of the decrease in admission resources due to the decrease in school age population, which has been weak in empirical studies, and how much the decrease in competition rate by department nationwide provides a significant shock to the decrease in enrollment rate in the population unit. An empirical quantitative analysis was attempted. As a result of applying the panel-tobit regression model, a clear gap was confirmed in the decrease in the registration rate due to the decrease in the competition rate both nationally and in the provinces, and in particular, a highly significant relationship was derived with the decrease in the recruitment rate. In particular, the sensitivity of the risk of unrecruitment due to a decrease in competition rate was the highest in the Jeolla region (0.499), followed by the Gangwon region (0.475) and the Gyeongsang region (0.471), and the metropolitan region (0.158) was confirmed to be the most stable. This suggests that the gap in insufficient funding has gradually widened by region over the past 10 years, and that the shock wave becomes more pronounced in the provinces farther away from the metropolitan area. Based on this study, if we deviate from the standardized application of university development policies for the metropolitan area and regional universities, and present a customized higher education strategy for each region, it will be an opportunity to prevent local extinction due to a decrease in the school-age population and achieve coexistence with higher education institutions and regions at the same time.

Keywords

Acknowledgement

This research was supported by the Academic Research Fund of Hoseo University in 2022 (Hoseo University Research No : 2022-0229-0001). This paper is a summary and re-editing of papers presented at the 2022 KITA Spring Conference.

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