인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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지원사업
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학술저널
Full-text AI
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
Apartment purchase behavior continues to change and in line with such a change, the central government of Korea has introduced a series of apartment types including Bogeumjari Housing, Happy Housing, and Business-Type Rental Housing, but nevertheless, their profitability is generally low. The profitability depends on the number and price of sales and thus, to increase them, those apartments that apartment buyers want should be built. Accordingly, this paper, using a case of apartment sales in the Hanam–Misa District, describes the characteristics of the buyers and analyzes the determinants of the purchase behavior. A regression model based on stepwise selection finds that among environmental variables, the overall suitability of the housing location, superiority of the school district, distribution of neighboring apartment complexes (rental versus buying) and
convenience of public transit are significant in the order of their relative influences. Also, a structural equation model based on maximum likelihood estimation shows that in descending order of their
influences, attitudes toward the district environment, those toward the environment of the neighboring areas, and buyers’ socioeconomics are direct or indirect factors on the purchase intention. These findings imply that relative to the socioeconomics, the characteristics of the inner and outer environments of the apartment district considerably affect the intention of the apartment purchase. Grounded upon these empirical findings, the paper reaches a conclusion that by locating apartment complexes suited to buyers’ needs, apartment developers and governments can expect higher profitability and contribute to public welfare.
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.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2018-030-001231799
