• Journal of Service Research and Studies
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• v.13 no.4
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• pp.142-159
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• 2023

As the core technologies of the 4th Industrial Revolution are introduced into luxury hotels, they are taking off as cultural and experiential spaces that provide new products and services to hotel users and new experiences. Therefore, this study investigated the effect of hotel users' perception of the experience of using technological amenity services on their trust and satisfaction, focusing on luxury hotels as smart hotel to identify the essential factors of smart hotels that can lead to continuous competitive advantage and improvements in the future. In addition, the study aimed to find an effective hotel marketing strategy and plan to satisfaction the smart hotel by maximizing customer satisfaction. To verify the research hypothesis, a survey was conducted targeting hotel users with experience using technological amenities in smart hotels within the last two years. As a result of the study, it was confirmed that all hypotheses were adopted except for the relationship between personification, intention to use technical amenities, and perceived performance expectations and satisfaction with smart hotels. Based on these research results, this paper presents theoretical and practical implications. Smart hotels are rapidly changing by introducing various smart technologies. Therefore, it will be meaningful data for securing a sustainable competitive advantage and establishing differentiated hotel management and marketing strategies.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.1-16
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• 2023

In 2005, the selection of 10 innovation cities was completed, and since 2013, public institutions began relocating to innovation cities. As a policy aimed at promoting balanced regional development, there were significant expectations from the regions. However, although the population moving to innovation cities has increased, it remains to be seen how much inflow is from the capital region and what spatial characteristics exist nationwide. Therefore, this study aims to analyze whether the innovation cities are fulfilling their roles by examining the patterns of inflow from the capital region and the spatial characteristics, and to reassess the policy direction for future innovation cities. We utilized the Microdata Integrated Service (MDIS) provided by Statistics Korea from 2013 to 2021. For the data collection reasons, we focused on analyzing the three cities. The results showed that in the initial stages of innovation city development, there was a significant influx of population from the capital region, leading to some effects on population dispersion and balanced regional development. However, over time, a phenomenon emerged where more people started to move back to the capital region, indicating a problematic trend. Furthermore, the Gyeongbuk Innovation City and Gwangju-Jeonnam Innovation City showed similarities in terms of reasons for migration, age of householder, and number of household members. However, the Gyeongnam Innovation City exhibited distinct characteristics compared to the other two cities. While the reasons for this phenomenon may be diverse, the current situation suggests that the goal of achieving "balanced national development" has reached its limits. Therefore, urgent measures need to be taken for improvement that take regional characteristics into account. Furthermore, in designing the second phase of the public institution relocation plan is required to avoid repeating the same issues and ensure a more thoughtful approach.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1397-1411
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• 2020

Purpose To survey the perception, knowledge, wishes, and expectations of Korean radiology residents regarding artificial intelligence (AI) in radiology. Materials and Methods From June 4th to 7th, 2019, questionnaires comprising 19 questions related to AI were distributed to 113 radiology residents. Results were analyzed based on factors such as the year of residency and location and number of beds of the hospital. Results A total of 101 (89.4%) residents filled out the questionnaire. Fifty (49.5%) respondents had studied AI harder than the average while 68 (67.3%) had a similar or higher understanding of AI than the average. In addition, the self-evaluation and knowledge level of AI were significantly higher for radiology residents at hospitals located in Seoul and Gyeonggi-do compared to radiology residents at hospitals located in other regions. Furthermore, the self-evaluation and knowledge level of AI were significantly lower in junior residents than in residents in the 4th year of training. Of the 101 respondents, only 16 (15.8%) had experiences in AI-related study while 91 (90%) were willing to participate in AI-related study in the future. Conclusion Organizational efforts through a radiology society would be needed to meet the need of radiology trainees for AI education and to promote the role of radiologists more adequately in the era of medical AI.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.868-880
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• 2023

This study is a qualitative study conducted to analyze the functions and needs of social robots for parents of children with developmental disabilities in order to utilize care robots for treatment of children with developmental disabilities. The subjects of the study were 11 primary caregivers with children under the age of 18 whose children were diagnosed with developmental disabilities or who had been receiving special education for more than one year. The interview questionnaire was composed of a semi-structured questionnaire and consisted of awareness, necessity, expectation, concern, and other opinions about social robots. The interview was conducted as a non-face-to-face online video interview due to COVID 19. As a result of the study, 4 themes and 7 sub-topics were derived. The four topics were derived from the unfamiliar but soon-to-be-faced reality, social robots with active functions, opinions on the appearance and materials of social robots, and concerns about social robots. Through this study, it was possible to identify the expectations and suggestions of the main caregivers for social robots, which could not be identified in quantitative studies, and if these can be reflected in social robots to be developed in the future, it is expected that positive results with higher acceptance will be derived.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.21-41
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• 2024

This study explores the relationship between users' attachment styles and their interactions with ChatGPT (Chat Generative Pre-trained Transformer), an advanced language model developed by OpenAI. As artificial intelligence (AI) becomes increasingly integrated into everyday life, it is essential to understand how individuals with different attachment styles engage with AI chatbots in order to build a better user experience that meets specific user needs and interacts with users in the most ideal way. Grounded in attachment theory from psychology, we are exploring the influence of attachment style on users' interaction with ChatGPT, bridging a significant gap in understanding human-AI interaction. Contrary to expectations, attachment styles did not have a significant impact on ChatGPT usage or reasons for engagement. Regardless of their attachment styles, hesitated to fully trust ChatGPT with critical information, emphasizing the need to address trust issues in AI systems. Additionally, this study uncovers complex patterns of attachment styles, demonstrating their influence on interaction patterns between users and ChatGPT. By focusing on the distinctive dynamics between users and ChatGPT, our aim is to uncover how attachment styles influence these interactions, guiding the development of AI chatbots for personalized user experiences. The introduction of the Perceived Partner Responsiveness Scale serves as a valuable tool to evaluate users' perceptions of ChatGPT's role, shedding light on the anthropomorphism of AI. This study contributes to the wider discussion on human-AI relationships, emphasizing the significance of incorporating emotional intelligence into AI systems for a user-centered future.

• Information Systems Review
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• v.19 no.1
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• pp.75-100
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• 2017

Today, firms are constantly transforming and innovating to survive under the rapidly changing business environment. The introduction of cloud computing services has become popular throughout society as a whole and is expected to result in many changes and developments not only in firms and but also in the public sector subject to innovation. The purpose of this study is to investigate the effect of the characteristics of cloud computing services on the perceived expected performance according to innovativeness based on innovation diffusion theory. The results of the analysis of the data collected from this research are as follows. The convenience and understanding of individuals' work as well as the benefits of cloud computing services to them depend on the innovative trend of cloud computing services. Further, the expectations for personal benefit and those for organizational benefit of cloud computing services are different from each other. Leading firms in the global market have been actively engaged in the utilization of cloud computing services in the public sector as well as in private firms. In consideration of the importance of cloud computing services, using cloud computing services as the target of innovation diffusion research is important. The results of the study are expected to contribute to developing future research models for the diffusion of new technologies, such as big data, digital convergence, and Internet of Things.

• The Korean Journal of Coaching Psychology
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• v.7 no.3
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• pp.1-26
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• 2023

This study aims to explore how professors at community colleges are experiencing career guidance for their students, uncovering key components related to causes, phenomena, contexts, coping strategies, etc., and deriving a paradigm model to structurally. To achieve this objective, focus group interviews were conducted with a total of 23 community college professors, and the results were analyzed using the grounded theory method (Strauss & Corbin, 1998). The analysis yielded 17 categories and 31 subcategories. The central phenomenon in the career guidance of community college professors was categorized into two groups: the distress experience in career guidance and attitude changes toward interactions with students..Three categories of causal conditions contributing to the occurrence of the central phenomenon were identified: professors' lack of expertise in career guidance, students' scope and needs for career guidance, and students' low interest and expectations. Additionally, four contextual conditions corresponding to special situations or circumstances that contributed to the central phenomenon were identified: increasing demand for career guidance, excessive burden and time constraints for career guidance, lack of communication about career guidance at the institutional level, and limitations within the career guidance support system. Furthermore, the study uncovered patterns of action-interaction, mediating conditions, and outcomes. This study is expected to contribute to a better understanding of the actual experiences of college professors in the career guidance process, and to stimulate consideration of the types of support required for effective career guidance for college professors in the future.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.228-240
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• 2023

Growing complexity in ecosystem structure and functions, under impacts of climate and land-use changes, requires interdisciplinary understandings of processes and the whole-system, and accurate estimates of the changing functions. In the last three decades, observation networks for biodiversity, ecosystems, and ecosystem functions under climate change, have been developed by interested scientists, research institutions and universities. In this paper we will review (1) the development and on-going activities of those observation networks, (2) some outcomes from forest carbon cycle studies at our super-site "Takayama site" in Japan, and (3) a few ideas how we connect in-situ and satellite observations as well as fill observation gaps in the Asia-Oceania region. There have been many intensive research and networking efforts to promote investigations for ecosystem change and functions (e.g., Long-Term Ecological Research Network), measurements of greenhouse gas, heat, and water fluxes (flux network), and biodiversity from genetic to ecosystem level (Biodiversity Observation Network). Combining those in-situ field research data with modeling analysis and satellite remote sensing allows the research communities to up-scale spatially from local to global, and temporally from the past to future. These observation networks oftern use different methodologies and target different scientific disciplines. However growing needs for comprehensive observations to understand the response of biodiversity and ecosystem functions to climate and societal changes at local, national, regional, and global scales are providing opportunities and expectations to network these networks. Among the challenges to produce and share integrated knowledge on climate, ecosystem functions and biodiversity, filling scale-gaps in space and time among the phenomena is crucial. To showcase such efforts, interdisciplinary research at 'Takayama super-site' was reviewed by focusing on studies on forest carbon cycle and phenology. A key approach to respond to multidisciplinary questions is to integrate in-situ field research, ecosystem modeling, and satellite remote sensing by developing cross-scale methodologies at long-term observation field sites called "super-sites". The research approach at 'Takayama site' in Japan showcases this response to the needs of multidisciplinary questions and further development of terrestrial ecosystem research to address environmental change issues from local to national, regional and global scales.

• Korean Journal of Adult Nursing
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• v.12 no.2
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• pp.184-195
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• 2000

It has been believed that cancer is an omnious factor threatening the future and life itself. Patients having the disease experience anxiety, fear, feeling of weakness, depression and feelings of uncertainty and hopelessness. Most cancer patients, however, have expectations of possible recovery and a better future, very different from the patients who feel hopeless. Therefore. hope allows people to respond effectively to the fatal disease they have and prevents them from detoriorating physically and spiritually, positively influencing their survival, response to treatment and sense of security. Studies previously performed showed that hope is positively correlated with social and family supports, self-esteem, spiritual well-being, responsive action, health promotion behavior and quality of life. Thus, the study attempted to provide basic information on nursing cancer patients by investigating their levels of hope and determining predictive factors which influence hope. For the study 200 cancer patients in two university hospitals located in Pusan were sampled as subjects. Data were collected for twenty nine days from Feburary 1, 1999 to March 1. Instrumets for the study included 10 items from the self-esteem scale by Rosenberg (1965), 39 hope measurements by Kim and Lee(1965), 16 of the social support scale by Tae(1986) and 16 of the general characteristics scale, all of which totaled 81 items. The data were analyzed using the SPSS program. General characteristics of the investigated based on numbers and percentage. Hope, self-esteem and social support were analyzed using means, minimum, maximum and standard deviation. Relations among the foregoing three factors were analyzed using Pearson' correlation coefficient. Levels of hope in cancer patients were determined using t-test, ANOVA and Scheffe test. Predictive factors influencing hope were investigated using multiple stepwise regression analysis. Results of the study are summarized as follows: 1. An average level of hope was $185.55{\pm}23.39$ points(96 min. and 234 max.) 2. Levels of hope showed a significant difference among them according to sex (t=-3.69, P=.000), age(F=4.714, P=.000), job(F=3.247, P=.008), monthly income (F=6.113, P=.003), treatment charge (F=3.796, P=.011), supportive resources (F=10.554, P=.000), diagnosis(F=2.287, P=.029), perceived health status(F=22.184, P=.000), level of pain(F=3.334, P=.021), religion (F=4.911, P=.001) and religion's effect in life (F=11.706, P=.000), 3. For the subjects, self-esteem and social support were $38.32{\pm}7.21$(13 min, and 50 max.) and $52.97{\pm}8.49$points(28 min, 80 max.). Concerning social support, average levels of family support and medical support were found $35.95{\pm}6.05$(18 min, and 40 max) and $27.02{\pm}4.99$ points(20 min and 40 max). The hope the cancer patients showed significant correlations with self-esteem (r=.588, P=.000), family support(r=.224, p=.001) and medical support(r=.221, P=.002). 4. The five variables related to hope (self-esteem, religion's effect in life, perceived health status, social support and age) accounted for 54.2 percent of the hope level; especially, self-esteem was the highest at 34.6%. As shown in the above results, predictive factors which most influence hope in cancer patients were self-esteem and religion's effect of life. Therefore, nursing interventions to increase self-esteem should be developed. Regarding religion's effects, studies on spiritual aspects should be carried out in a way that contributes to promotion of hope.