인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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.
피인용 0
초록·키워드
This study examines the determinants of participation intention in marine leisure activities, focusing on surfing. By analyzing participation intention as a binary choice, this research explores the initial stages of demand formation, aiming to identify the relative influence of choice attributes versus individual characteristics and to clarify the underlying decision-making structure.
Survey data1 from marine leisure participants were analyzed, with future participation intention over the next period treated as the dependent variable. Independent variables included program, price, and human factors, with demographic and behavioral traits as control variables. Binary logistic regression was used to estimate average effects, while decision tree analysis explored conditional decision-making pathways.
Logistic regression revealed that individual characteristics—such as age, household income, and prior experience—significantly influenced participation intention, whereas choice attributes showed no significant direct effect. However, decision tree analysis demonstrated that choice attributes, specifically facility and price factors, operated as conditional determinants depending on the participant's age and income levels.
Overall, the findings suggest a staged decision-making process where individual characteristics primarily shape initial participation intention, while choice attributes exert secondary and context-dependent influences. This study provides critical insights for developing targeted policies and marketing strategies in the marine leisure industry.
Survey data1 from marine leisure participants were analyzed, with future participation intention over the next period treated as the dependent variable. Independent variables included program, price, and human factors, with demographic and behavioral traits as control variables. Binary logistic regression was used to estimate average effects, while decision tree analysis explored conditional decision-making pathways.
Logistic regression revealed that individual characteristics—such as age, household income, and prior experience—significantly influenced participation intention, whereas choice attributes showed no significant direct effect. However, decision tree analysis demonstrated that choice attributes, specifically facility and price factors, operated as conditional determinants depending on the participant's age and income levels.
Overall, the findings suggest a staged decision-making process where individual characteristics primarily shape initial participation intention, while choice attributes exert secondary and context-dependent influences. This study provides critical insights for developing targeted policies and marketing strategies in the marine leisure industry.
본문·목차
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