메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
이명희 (성신여자대학교 의류학과)
저널정보
한국의류학회 한국의류학회지 한국의류학회지 제32권 제7호
발행연도
2008.1
수록면
1,034 - 1,045 (12page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
The objectives of this study were to group female consumer types according to cosmetics benefits sought at online and off-line cosmetic shopping malls, and to investigate the differences in consumer values, cosmetic purchase behaviors, and demographic variables according to the consumer types. Subjects were 451 females residing in Seoul, of whom 212 were online shoppers and 239 were off-line shoppers. Five dimensions of cosmetics benefits sought were derived by factor analysis. These were functionality, economy, brand, fashion, and practicality. The female consumers were classified into four benefits sought types by cluster analysis of the five dimensions: T.1 'practicality sought type', T.2 'economy sought type', T.3 'brand function sought type', and T.4 'economic function sought type'. Economy sought consumers purchased cosmetics much more from online shopping malls than from off-line. The cosmetics expenses of practicality sought online consumers were low and many of them were in their 20's and middle-class. Economy sought online consumers preferred domestic brand, their cosmetics expenses were low, and many of them were career women. Practicality sought off-line consumers were high in independent value. Economy sought off-line consumers were low in independent value and social approval value, preferred domestic brand, and distributed more in college students than in career women. Brand function sought off-line consumers purchased cosmetics at department store and regarded social approval value as important. Economic function sought off-line consumers were distributed in middle-class and in diverse age range.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0