Earticle

The study investigates one of the long-standing, but still controversial issues in modern finance from the international and domestic perspectives. That is, financial components and differences on corporate profitability are identified and compared under the primary hypotheses. Empirical research settings include the sample data as KOSPI-listed chaebol firms, time reference covering the post-era of the global financial turmoil and two differently defined profitability indices measured by the market- and the book-value bases. A majority of total 7 explanatory variables except firm size and leverage ratio reveal their statistically significant power to explain profitability indices for the chaebol firms in the first hypothesis. The results are generally compatible with those obtained from their counterparts of non-chaebol firms. In the second hypothesis applying multinomial logistic model, the chaebol firms are classified into three groups according to the level of profitability. It is then confirmed that variables to represent the market-valued debt ratio, business risk and growth potential are financially discriminating factors among the three groups. Moreover, additional hypotheses to directly or indirectly identify financial profile of the chaebol firms are tested in the study for robustness checks of the results. The study may provide a new vision to identify financial factors of corporate profitability for Korean chaebol firms after the global financial crisis, which can enhance the benefits of interested parties at the government or corporate level in a virtuous cycle.

본 연구의 목적은 위드 코로나 시대, 방한 외래관광객의 참여활동 유형을 발견하고, 각 유형의 결정요인을 규명함으로써, 인바운드 관광 활성화 전략 수립에 일조할 기초자료를 확보하는 것이다. 2023년 외래관광객 조사자료 중, 참여 관광활동 관련 15개 항목을 추출하여 이단계 군집분석을 실시하였으며, 그 결과 ‘지역문 화 체험형’, ‘레저오락 추구형’, ‘K콘텐츠 중심형’, ‘역사유적 탐방형’, ‘뷰티의료 목적형’, ‘인기활동 집중형’, ‘소극적 참여형’과 같은 7개 유형을 도출하였다. 교차분석과 분산분석의 시행을 통해, 인구통계 및 관광행동 특성, 관광만족, 행동의도에 대한 유형 간 차이를 확인하였다. ‘소극적 참여형’을 준거로 추정한 다항 로지스 틱 회귀모형의 주요 결과는 다음과 같다. 첫째, ‘지역문화 체험형’의 경우, 단체여행, 최초방문 특성 등이 영 향 요인으로 나타났다. 둘째, ‘레저오락 추구형’에서는 성수기, 재방문, 동반자 관련 효과가 확인되었다. 셋 째, ‘K콘텐츠 중심형’의 경우, 개인여행, 비공식정보, 언어소통 등이 중요 요인으로 작용하였다. 넷째, ‘역사 유적 탐방형’에서는 비수기와 사전예약 부문에서 유의성이 발견되었다. 다섯째, ‘뷰티의료 목적형’의 핵심 요 인은 지출경비와 체류기간, 대중교통 등이었다. 여섯째, ‘인기활동 집중형’에서는 숙소유형, 치안, 기념품비 가 주요 영향요인이었다. 이외에도 성별, 연령, 주요 방문국가, 세부만족도, 재방문의사 및 추천의도 등이 구 체적으로 분석되었으며, 결론에서는 프로파일에 따른 실무적 시사점과 본 연구의 차별성이 논의되었다.

This study aims to identify the types of engagement activities of inbound tourists visiting South Korea in the with-corona era and to examine the determinants influencing each activity type, thereby providing foundational insights for sustainable inbound tourism strategies. Using 15 items from the 2023 International Visitor Survey, a two-step cluster analysis revealed seven segments: ‘Local Explorer (LE),’ ‘Recreation Seeker (RS),’ ‘K-Culture Fan (KF),’ ‘Heritage Visitor (HV),’ ‘Medical Tourist (MT),’ ‘Mainstream Seeker (MS),’ and ‘Passive Participant (PP).’ Cross-tabulation and ANOVA indicated significant differences among the types regarding demographics and tourist behavior characteristics. The primary findings of a multinomial logistic regression model, with PP as the reference group, are as follows: First, in the case of LE, group travel and first-time visits were influential factors. Second, for RS, peak season, repeat visits, and traveling with companions were meaningful. Third, in KF, individual travel, informal information sources, and language communication proved impactful. Fourth, HV demonstrated significance in off-peak seasons and advance reservations. Fifth, key factors for MT included expenditures, length of stay, and public transportation. Sixth, MS were influenced by lodging type, safety, and souvenir expenses. Additionally, gender, age, main country of origin, detailed satisfaction, and behavioral intentions were comprehensively analyzed. Practical implications based on these profiles and the distinct contributions of this study are discussed in the conclusion.

Statistical matching is a method of combining multiple sources of data that are extracted or surveyed from the same population. It can be used in situation when variables of interest are not jointly observed. It is a low-cost way to expect high-effects in terms of being able to create synthetic data using existing sources. In this paper, we propose the several statistical micro matching methods using a multinomial logistic regression model when all variables of interest are categorical or categorized ones, which is common in sample survey. Under conditional independence assumption (CIA), a mixed statistical matching method, which is useful when auxiliary information is not available, is proposed. We also propose a statistical matching method with auxiliary information that reduces the bias of the conventional matching methods suggested under CIA. Through a simulation study, proposed micro matching methods and conventional ones are compared. Simulation study shows that suggested matching methods outperform the existing ones especially when CIA does not hold.