• Journal of agricultural medicine and community health
• /
• v.25 no.1
• /
• pp.133-147
• /
• 2000

To provide data for the improvement of primary health care through the study on the utilization rate of community health practitioner(CHP) post and its related factors toward some rural residents in Mooan County Chollanamdo, a questionnaire survey was made from 382 persons during August 1999. Comparison was made between persons at the seaside area under difficult transportation and persons at the railroad area under convenient transportation. The results are as follows: 1. For the last one year, 83.3% of seaside area residents and 67.0% of railroad area residents used CHP post. As the purpose of visit to CHP post at seaside area, 94.3% visited for medical care, 25.3% for chronic disease control and 22.2% for health counselling and 14.1% for chronic disease control. 2. By simple analysis, sex, age, marital status, educational level, residence area, distance from living village to CHP post, presence of chronic diseases, satisfaction with CHP and confidence on CHP were related significantly with the utilization of CHP post for the last one year. 3. By multiple logistic regression, statistically significant variables related with the utilization rate of CHP post for the last one year were analyzed as age, sex, residence area and distance from living village to CHP post.

• Journal of Distribution Science
• /
• v.9 no.3
• /
• pp.73-82
• /
• 2011

This study presents an effective and distinctive marketing strategy through the implementation of the aesthetic art marketing communication technique of storytelling. The reason applying art to marketing is effective is that it gives "class" and aesthetic beauty to the brand's image, which will lead to an increase in revenue and loyalty of consumers. The story stands in for the brand's subject of "desire." Luxury brand customers not only consume high-quality products, require the utmost in service, and value of the brand, they also appreciate the story the brand is telling. The story, combined with art, is called art marketing communication; it makes the brand more unique through its enhanced visual elements. The study discusses art collaboration, art exhibition, a transforming architecture project, art advertisement, a flagship store, and a human resource training center. Based on the "desire," I adopted the element and principle of storytelling. By visualizing the brand with a symbol, the company is able to relate to consumers' sentimentality. Through storytelling art marketing communication, and the strategy using relevance of brand and artist's popularity, the research shows efficient art marketing influences to the brand's image. The results of the research indicate that by using adequate art marketing communication that best reflects the identity and story of the luxury brand, it produces great results; the research also demonstrated, in various ways, that art marketing will succeed. The case showed the following outcomes. First, consumers have a tendency to choose a brand that is associated with an empathizing story. World renowned brands see through the market's "desires" for unique stories, and they also provide the ability to amuse consumers. The story in a product will become an important competitive element in future markets. Second, the art marketing communication applying a story rendered a brand with distinction. The most effective art marketing communications are art collaboration, art exhibition, locomotive architecture project, and others that are adopted as various means. Third, the brand's products were considered as an art piece, which led to not only strengthening the loyalty of consumers but also an increase in sales. In addition, the company could sustain a premium price for the goods sold. By adapting art to a brand's tradition, an innovative and creative new product provides consumer satisfaction, and producing goods in limited editions creates enthusiastic collectors. Fourth, this study suggests an abridged report, implication, limitation of the study, and directions for further research. Referring to the case for the adaptation of luxury brands, efficient art marketing strategies considering Korean company brand and efficiently study preceding Korean company brand art marketing strategy could be proposed.

• Journal of Climate Change Research
• /
• v.1 no.3
• /
• pp.189-203
• /
• 2010

The objective of this study is the estimate of $CO_2$ emissions by the energy consumption of functional technology introduced by classifying energy use in households according to functions as well as energy resources. This study also intends to provide the practical basis data in order to establish specific alternatives for GHG mitigation in residential sector with examining the cause analysis affecting $CO_2$ emission increases from 1995 to 2007. The results of this study show a 6.6% increase in the total $CO_2$ from 60,636 thousand tons in 1995 to 64,611 thousand tons in 2007 by using energy in residential sector. Heating is the greatest $CO_2$ emission sector by use, followed electric appliances, cooking, lighting and cooling. Heating sector shows 56.6% reductions from 71.5% in 1995 and as do cooling and electric home appliances, with a 2.4% increase from 0.6% and a 21.8% increase from 14.2% respectively. To analyze factors resulted in $CO_2$ emissions in residential sector, the relevant indicator change rate from 2005 to 2007 was examined. The results find that population, the number of household, housing areas, family patterns, and family income resulted in the $CO_2$ emissions increase in residential sector from 1995 to 2007. On the other hand, carbon intensity and energy intensity contribute to $CO_2$ reduction in residential sector with -2% and -38.7% respectively because of the energy conversion and the improvement of energy efficiency in electronic appliances. This study can be used as a reference when taken account of the reality and considered the introduction of highly effective measures to increase the possibility of mitigation potential in residential sector hereafter.

• The Korean Journal of Archival Studies
• /
• no.50
• /
• pp.273-309
• /
• 2016

Unlike other government agencies, the city of Seoul experienced a three-year gap between the establishment of a function classification system and the introduction of a business management system. As a result, the city has been unable to manage the current status of the function classification system, and this impeded the establishment of standards for records management. In September 2012, the Seoul Metropolitan Government integrated the department in charge of the standard sheet for record management with the department of function classification system into a new department: "Information Disclosure Policy Division." This new department is mainly responsible for record management and information disclosure, and taking this as an opportunity, the city government has pushed ahead with the maintenance project on BRM and Standards for Record Management (hereby "BRM maintenance project") over the past two years, from 2013 to 2014. The study was thus conducted to introduce the case for the improvement of standards for record management through the BRM maintenance project by mainly exploring the case of Seoul. During the BRM maintenance project, Seoul established a unique methodology to minimize the gap between the operation of a business management system and the burden of the person in charge of the BRM maintenance project. Furthermore, after the introduction of the business management system, the city government developed its own processes and applied the maintenance result to the system in close cooperation with the related departments, despite the lack of precedence on the maintenance of the classification system. In addition, training for the BRM managers of the department has taken place twice -before and after the maintenance-for the successful performance of the BRM maintenance project and the stable operation of the project in the future. During the period of maintenance, newsletters were distributed to all employees in an effort to induce their active participation and increase the importance of records management. To keep the performance of the maintenance project and to systematically manage BRM in the future, the city government has mapped out several plans for improvement: to apply the "BRM classification system of each purpose" to the service of the "Seoul Open Data Plaza"; to reinforce the function for task management in the business management system; and to develop the function of a records management system for the unit tasks. As such, the researchers hope that this study would serve as a helpful reference so that the organizations-which had planned to introduce BRM or to perform the maintenance project on classification system-experience fewer trials and errors.

• Information Systems Review
• /
• v.25 no.4
• /
• pp.131-159
• /
• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.52 no.2
• /
• pp.79-95
• /
• 2024

The purpose of this study was to find the changes in the habitat of wild birds caused by climate change in urban rivers and protected areas that greatly require ecological functions. In the future, this study can be used as a management index to protect the urban river ecosystem and maintain the health of sustainable urban rivers, thereby ensuring biodiversity. The Tancheon Ecological and Landscape Conservation Area, selected as a target site, has been affected by climate change. The four seasons of Korea have a distinct temperate climate, but the average annual temperature in Seoul has risen by 2.4-2.8℃ over the last 40 years. Winter temperatures tended to gradually increase. Precipitation, which was concentrated from June to August, is now changing into localized torrential rain and a uniform precipitation pattern of several months. Climate change causes irregular and unforeseen features. Climate change has been shown to have various effects on urban river ecosystems. The decrease in the area of water surface and sedimentary land impacted river shape change and has led to large-scale terrestrialization. Plants showed disturbance, and the vegetation was simplified. The emergence of national climate change indicator species, the development of foreign herbaceous plants, the change of dry land native herbaceous species, and wet intelligence vegetation were developed. Wild birds appeared in the territory of winter-summer migratory. In addition, species change and the populations of migratory birds also occurred. It was judged that fluctuations in temperature and precipitation and non-predictive characteristics affect the hydrological environment, plant ecology, and wild birds connecting with the river ecosystem. The results of this study were to analyze how climate change affects the habitat of wild birds and to develop a management index for river ecological and landscape conservation areas where environmental and ecological functions in cities operate. This study can serve as a basic study at the level of ecosystem services to improve the health of urban rivers and create a foundation for biodiversity.

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.23-43
• /
• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Intelligence and Information Systems
• /
• v.21 no.4
• /
• pp.17-35
• /
• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Journal of Korean Home Economics Education Association
• /
• v.20 no.4
• /
• pp.19-42
• /
• 2008

The purpose of this study was to develop practical problem-based home economics teaching.learning process plans about a unit 'the youth and consumer life' of middle school eighth-grade Technology and Home Economics by applying blended learning(BL) strategy. According to ADDIE instructional design model, this study was conducted in the following procedure: analysis, design/development, implementation, and evaluation. In the stage of design and development, the selected unit was converted into a practical problem-based unit, and practical problem-based teaching. learning process plans were designed in detail by using BL strategy. An online study room for practical problem-based home economics instruction grounded in BL strategy was prepared by using Edunet(http://community.edunet4u.net/${\sim}$consumer2). Eight-session lesson plans were mapped out, and study aids for students and materials for teachers were prepared. In the implementation stage, the first-session teaching plans that dealt with a minor question 'what preparations should be made to become a wise consumer' were utilized when instruction was provided to 115 eighth graders who were in three different province, and the other one was in a middle school in the city of Daejeon. The experimental teaching was implemented for two weeks in the following procedure: preliminary program, pre-online learning, main instruction and post- online learning. The preliminary program was carried out in a session in the classroom, and pre-online learning was provided before the main instruction was given in a session in the classroom. After the main instruction was completed, post-online learning was offered. In the evaluation stage, a survey was conducted on all the learners and teachers to find out their opinions and suggestions.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.107-129
• /
• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.