http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
암 진단 고지 관련 국내외 연구주제의 텍스트 네트워크 분석
윤진희(Yun, Jin Hui),류은정(Ryu, Eunjung),이소영(Lee, So Young) 대한종양간호학회 2018 Asian Oncology Nursing Vol.18 No.3
Purpose: This study aimed to identify and compare research topics related to disclosure of cancer diagnosis among Korea and other countries using text network analysis. Methods: Abstracts from 119 studies for the period of 2000~2015 were analyzed. An integrative literature review and text network analysis were applied to examine the research. The keywords from each article’s abstracts were extracted by using a program, KrKwic, and analyzed using network-related measures including degree centrality, and clustering using the NetMiner program. Results: The most important core keywords; ‘patient’, ‘cancer’, ‘diagnosis’, ‘disclosure’, ‘truth’, ‘physician’, ‘family’, ‘telling’, ‘information’, ‘preference’, ‘member’, ‘age’, and ‘tell’ ranked highly. Asian countries as Korea, Japan, and China showed a similar high centrality of degree of connection in family, which appeared as a factor that influences cancer diagnosis disclosure. Conclusion: These findings showed knowledge structure of disclosure of cancer diagnosis and its research trends. The 11 topics identified in this comparative study can provide further starting points for research of communication with cancer patients and their family.
인공지능시스템에 대한 호텔 종업원의 양가적(兩價的) 인식과 사용자 저항의 영향 관계
윤진희(Jin-Hui Yun),왕단평(Dan-Ping Wang),정남호(Namho Chung) 한국관광학회 2024 관광학연구 Vol.48 No.2
이 연구는 직무요구-자원 모형을 활용하여 인공지능시스템에 대한 호텔 종업원의 인식(직무요구)이 전환비용(스트레스 요인) 및 전환이익(동기 요인)을 매개로 사용자 저항에 미치는 영향을 파악하고자 하였다. 또한 조직적 지원(직무자원) 정도에 따라 이러한 영향 관계가 어떻게 조절효과를 갖는지를 살펴보고자 하였다. 연구 목적 달성을 위해 호텔에서 인공지능시스템과 업무를 경험한 종업원들 대상으로 온라인 설문조사를 시행하였다. 연구 결과, 첫째, 종업원의 인공지능(Artificial Intelligence: AI)인식은 전환비용에 긍정적인 영향을 미치는 것으로 나타났으며, 전환이익에 유의한 영향을 미치지 않는 것으로 나타났다. 둘째, 전환비용은 사용자 저항에 긍정적인 영향을 미치는 것으로 나타났으며, 전환이익은 사용자 저항에 부정적인 영향을 미치는 것으로 나타났다. 셋째, AI 인식과 전환비용 및 전환이익 간의 영향 관계에 대한 조절효과를 살펴본 결과, 호텔 종업원이 지각하는 조직적 지원 수준에 따라 차이가 있는 것으로 확인되었다. 이러한 연구 결과를 바탕으로, 호텔 종업원의 인공지능시스템 사용 저항에 관한 이해를 확장하고, 호텔인공지능시스템 도입 환경에서 종업원이 지각하는 조직적 지원 정도가 중요한 역할을 하고 있음을 확인하였다. 또한 인공지능시스템을 도입했거나 도입을 계획하는 호텔 조직에 효과적인 인적 관리 전략을 개발하는 데에 학술적, 실무적 시사점을 제시하였다. Utilizing the job demands-resources model, this study investigated the impact of hotel employees' perceptions of artificial intelligence(AI) systems (job demands) on user resistance, as mediated by switching costs (stress factors) and switching benefits (motivational factors). Additionally, it sought to explore how these relationships are moderated by the level of organizational support (job resources). To achieve the research objectives, an online survey was conducted targeting hotel employees who experienced AI systems in their work. The research findings are as follows: Firstly, employees' AI perceptions had a positive impact on switching costs but did not significantly affect switching benefits. Secondly, switching costs had a positive influence on user resistance, while switching benefits negatively impacted user resistance. Thirdly, the level of organizational support moderated the relationships between AI perceptions, switching costs, and switching benefits. These study findings contribute to deepening the understanding of hotel employees' resistance to AI systems. It confirms the significant role of the level of organizational support when introducing AI systems. Consequently, this study suggests theoretical and practical implications for developing effective employee resource management strategies for hotel organizations that have introduced or plan to use extended AI systems.
윤진희(Yun, Jin-Hee),권오규(Kwon, O-Kyu),마강래(Ma, Kang-Rae) 한국지역개발학회 2014 韓國地域開發學會誌 Vol.26 No.2
There has been a rapid growth of Chinese population since mid-1990s. In Seoul, Chinese population now consists of the largest number of foreign population at more than 70%. Previous studies argued that the residential segregation of foreign migrants is associated with the language barriers and cultural differences. This study tried to investigate the extent to which the growth patterns of Korean-Chinese population differs from those of Non-Korean Chinese population, using the Adjusted Dissimilarity Index. The comparison of two ethnic groups revealed that the net growth of Korean Chinese people with no or low language barriers is more affected by the previous segregation pattern than that of Non-Korean Chinese population. The evidence of this study indicates that language and cultural differences have played a limited role in determining the residential segregation of Chinese population.