인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This study aimed to draw the sensory image to our traditional Obangsaek and analyze the preference, the interaction effect among demographic characteristics, and the sensory image according to demographic characteristics. This is a survey study using questionnaire and the sample comprised a total of 281 people from Gyeongnam and Ulsan. To analyze the collected data t-test, Factor analysis, ANOVA, Duncan multiple range test, Multivariate analysis were used by SPSS 20. The results obtained are as follows. The preference to Obangsaek according to demographic characteristics showed no significant differences according to gender and martial status but the significant differences for age, monthly income, and occupation. The interaction effect among variables showed the significant difference between marital status and monthly income, between age and monthly income, and between occupation and monthly income. The sensory images to Obangsaek were drawn as four factors of modernity and attractiveness, individuality, aesthetic, and conspicuousness. The difference of sensory image to Obangsaek according to demographic characteristics showed the significant difference in three factors for gender, age and occupation, in one factor for marital status, and two factors for monthly income. The results of differences analysis about sensory images showed the significant differences all in modernity and attractiveness, individuality, aesthetic, and conspicuousness according to gender, the significant differences in only aesthetic according to martial status, the significant differences in modernity and attractiveness, individuality, aesthetic according to age, the significant differences individuality and conspicuousness according to monthly income, and the significant differences in modernity and attractiveness, individuality, and aesthetic according to occupation.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-ECN-0101-2019-300-000542752