• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.5-12
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• 2019

Social exclusion, which does not fulfill the desire for respect as one of the most basic human desires, makes those who perceive themselves to be socially excluded seek physical warmth. However, very few studies have examined whether this phenomenon-wherein social exclusion develops a preference for warmth-can be generalized to the emotional or symbolic aspects, such as the color of lighting. This study aimed to verify the effects of perceived social exclusion on warm lighting preferences, and two experiments were performed for this purpose. In Experiment-1, participants who were respected by people the previous day were assigned to the group that did not perceive social exclusion (non-perceived social exclusion group), and those who were not respected were assigned to the group that perceived social exclusion (perceived social exclusion group). Following this, their preference for warm lighting (3000K), neutral lighting (4000K), and cold lighting (6000K) was measured. The results showed that the perceived social exclusion group had a stronger preference for warm lighting and a weaker preference for cold lighting than did their counterparts. Moreover, the perceived social exclusion group showed a strong preference for warm lighting over neutral lighting; they also showed a weak preference for cold lighting. In Experiment-2, after assigning the participants into groups as in Experiment-1, the participants' preference for a space with warm lighting, neutral lighting, and cold lighting was measured. The results showed that the perceived social exclusion group had a stronger preference for the space with warm lighting and a weaker preference for cold lighting than did their counterparts. Further, the perceived social exclusion group showed a strong preference for the space with warm lighting over the space with neutral lighting; they also showed a weak preference for the space with cold lighting. The findings of this study have implications that can be applied to designing living spaces for people who experience social exclusion, such as handicapped individuals, multicultural families, or immigrant workers, as well as developing artificial intelligence services and cyber-friend characters for this demographic.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• Korea Science and Art Forum
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• v.28
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• pp.105-116
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• 2017

This study is a basic research to suggest user-centered general hospital environmental design guidelines, which aims to analyze user's behavior characteristics across generation in general hospital. For this purpose, this study constructed an analysis tool through the literature review with regard to generation and behavior characteristics in general hospital. Besides, an online survey regarding user's behavior in general hospital was conducted targeting from 20s to 60s, 300 persons for each group, total 1,500 persons for about 3 weeks since September 1, 2016. The results of this study are as follows: (1) Based on the generation, there were significant differences in relevant categories of their visiting frequency, visiting purpose, visiting hour, transportation, companion, behavior during the wait and selection of a general hospital. (2) In all generation, they responded that they have visited once or twice per year. People in 20s and 30s responded that their visit for the hospital is to receive specific treatment, while other people in 40s, 50s and 60s visit the hospital majorly for routine check-ups. Therefore, it is imperative for a health check-up center to design an environmental plan that reflects the characteristics of elders in 40s, 50s and 60s. (3) People in 40s, 50s and 60s usually visit a general hospital in the mornings of weekdays, while generations in 20s and 30s responded that they mostly visit the hospital in the mornings of weekend. (4) When they visit a general hospital, people in their 20s are usually using public transportations, while people in their 30s to 60s are using their own vehicle. (5) People in their 20s majorly visited 'lobby'. In older generations, they tend to visit 'outpatient clinic'. Therefore, it is necessary to build an outpatient clinic environment that considers the elderly. (6) Patients majorly responded that they are using their cell phone, while waiting for their clinic call. In elder generations, they responded that they are more likely watching TVs, reading books/magazines or doing nothing. Therefore, it is essential to provide cell-phone related services and environmental supports. Visually attractive media can be utilized for this purpose.

• Korea Science and Art Forum
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• v.29
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• pp.319-331
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• 2017

South Korea has entered the age of aging society since the elderly population over 65 reached 13.1% in 2015. This increase rate is the fastest in the OECD members. as a part of the precaution, the Korean government has enforced the long term care insurance from July 2008 and the increase of related nursing homes until 2015 was 220.2% which is rapid and quantitative. It was natural that quantitative expansion leads to qualitative improvement. With regard to service environment conditions, color environment draws attention as one of the most effective measures. color environment supports nursing home's spatial functions and the aged class is subject to the research as the potential customers. This study aims to understand color environment, conduct surveys for color preference and attitude toward color environment, and suggest directions for color environment plan. The ultimate goal is to improve the quality of Korean nursing home environment. It studied definition, state, color environment and space functions of nursing homes as well as the preceding researches. With 100 people over 60s in Busan and Gyeongnam area (52 male and 48 female), the survey examined attitudes for color environment and color preference by space functions in nursing home. The research method is as follows. First, as a result of the consciousness survey on color environment in elderly nursing home, it considers service (37%), medical service (20%), and location (19%) heavily in order. color environment plan is not recognized significantly. However, the need of indoor color plan in the elderly nursing homes has "agree (32%) and "strongly agree (25%), which suggests that color introduction is required to the nursing homes. Second, the indoor coloration for the elderly nursing homes has various color preferences. The color preference order for bedroom was R, P, and G but this order changes in nursing space (program room) to G, R, and Y. The communal space such as lobby prefers R, G and Y in order. R color was preferred in general.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.73-83
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• 2024

The purpose of this study is to diagnose various problems arising around social enterprises in the sport field from the perspective of the organization and derive necessary tasks and implications. In order to achieve the purpose of the study, the study was largely divided into three stages, and the results were derived. First, the main status and characteristics of social enterprises in the sport field were examined. The current status was analyzed focusing on aspects such as background and origin, legislation and policy, organizational goals, organizational structure and procedures, and organizational characteristics. Social enterprises in the sport sector were in their early stages, and the government's social enterprise policy goal tended to focus on increasing the number of social enterprises in a short period of time through financial input. In addition, it was found that most individual companies rely on government subsidy support due to insufficient profit generation capacity. In the second stage, we focused on the situational factors that affect the functional performance of social enterprises in the sport field. As a result of reviewing the value, ideology, technology, and history of the organization, which are situational factors, it was derived that when certified as a social enterprise in the sport field and supported by the central government or local governments, political control is strong to some extent and exposure to the market is not severe. In the last third step, tasks and implications were derived to form an appropriate organization for social enterprises in the sport field. After the social enterprise ecosystem in the sport sector has been established to some extent, it is necessary to gradually move from the current "government-type" organization to the "national enterprise" organization. This is true in light of the government's limited financial level, not in the short term, but in order for the organization of social enterprises in the sports sector to survive in the long term.

• Health Policy and Management
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• v.34 no.2
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• pp.211-221
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• 2024

Background: The public health crisis caused by coronavirus disease 2019 emphasizes the need to expand and strengthen public hospitals. However, the overall perception of public hospitals remains negative. This negative perception can hinder the roles and functions of public hospitals, so this study aims to analyze the factors affecting negative perceptions of public hospitals. Methods: We used data from a survey on the public healthcare of Chungcheongbuk-do residents conducted by the Chungcheongbuk-do Public Health Policy Institute, and 1,916 adults aged 19 or older who responded to the survey were included in the study. Logistic regression analysis was used to analyze the impact of experiences with public hospitals use and evaluations of public healthcare and public hospital policies on the negative perception of public hospitals. Results: The experience of not using public hospitals (adjusted odds ratio [aOR], 1.69; 95% confidence interval [CI], 1.04-2.74) and negative evaluations of public healthcare and public hospital policies were found to significantly impact negative perceptions of public hospitals. In public healthcare policies, negative evaluations of the provision of essential medical care (aOR, 4.14; 95% CI, 2.59-6.62), regional disparities (aOR, 1.59; 95% CI, 1.02-2.49), coverage (aOR, 1.99; 95% CI, 1.25-3.16), and quality of care (aOR, 2.39; 95% CI, 1.50-3.80) were significantly associated with negative perceptions of public hospitals. In public hospital policies, negative evaluations of facilities and equipment (aOR, 3.74, 95% CI, 2.36-5.94), medical specialties and services (aOR, 1.91; 95% CI, 1.21-3.01), and quality of medical service (aOR, 2.71; 95% CI, 1.72-4.25) were also significantly associated with negative perceptions of public hospitals. Conclusion: This study emphasizes the need to improve perceptions of public hospitals by considering the experience with public hospitals use and evaluation of public healthcare and public hospital policies.