머신러닝의 로지스틱 회귀를 활용한 MZ세대와 시니어 세대의 기부의도 분석

• 영문명: Analysis of Donation Intention of MZ Generation and Senior Generation Using Machine Learning’s logistic Regression
• 발행기관: 한국IT서비스학회
• 저자명: 오민정(Min Jung Oh) 전익진(IkJin Jeon)
• 간행물 정보: 『한국IT서비스학회지』제23권 제2호, 1~12쪽, 전체 12쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2024.04.30

영문 초록

This study aims to find ways to increase the declining donation intention by using machine learning techniques. To this end, in order to predict factors that affect donations between the MZ generation and the senior generation, various machine learning algorithms, including logistic regression analysis, are applied to build a model to determine variables that affect donation intention, and provide statistical verification and evaluation indicators. In this study, differences in donation intention by generation were expected as a variable affecting donation intention, and the senior generation was expected to show a higher donation intention tendency than the younger generation. However, although the research results were not statistically significant, the younger generation showed a higher intention to donate, and these results are interpreted to mean that value consumption and ethical consumption, which are important to today's MZ generation, also influenced donations. However, there were differences between generations in the amount of donations, and higher donation amounts were confirmed among the senior generation (those in their 50s or older) than the younger generation. In addition, the results of the logistic regression analysis showed that previous donation experience had a positive effect on future donation intention, and the more motivation and importance of donation and various social participation activities online and offline, the more active one became in donating.

목차

1. 서론

2. 이론적 배경

3. 연구방법

4. 결론

참고문헌

키워드

Machine Learning Multiple Regression Analysis Logistic Regression Donation Senior