• The KIPS Transactions:PartD
• /
• v.13D no.3 s.106
• /
• pp.405-414
• /
• 2006

These days, business environments are rapidly change and companies are taking the pressure about a customer value enhance to the continuance from the market. Therefore companies propel various innovative and strategic initiatives for a customer value enhancement. Also Information Technology is rapidly becoming part of our everyday lives due to its fast development, the functions and responsibilities of CSC(Consolidated Service Center) are undergoing revolutionary change. The function of sales organization based on the manpower and human networks are gradually shrinking, and CSC is slowly establishing itself as the company's core parts as its function expands and its operations are in the spotlights. Among these, many organizations are currently introducing ITSM concept for primary processes as a means of achieving synergy in operational excellence, reducing costs and improving service quality. In this thesis, we propose an extended CSC, which is applied ITIL Process to traditional BMP. It also needs to manage more effectively business process model, to modeling rapidly changing business process, and to developing its business application programs whenever and whatever it is changed. The ITSM(IT Service Management), which is an ITIL tool, effectively managing for dynamically changing the business process.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.40 no.6
• /
• pp.47-59
• /
• 2012

In this study, species and seasonal scenery image were made using 3D simulation modeling to evaluate emotional image of street trees in the roads cape. Study site are set in Tongdaeguro, located in Daegu Metropolitan City and Cedrus deodara, Metasequoia glyptostroboides, Liriodendron tulipifera L., and Zelkova serrata were selected to evaluate the species. In the survey result, it appears that Zelkova serrata is the highest preference for summer landscape and Metasequoia glyptostroboides is the highest preference for fall and winter landscape. With regard to the factor analysis, in order to derive emotional evaluation factor, aesthetic factor, perception factor, individuality factor, natural factor, and spatial factor were derived and aesthetic factor is the greatest impact for preference common in all seasons. Preference and positive emotional image of Metasequoia glyptostroboides is evaluated as the highest in the winter and the aesthetic factor score reduction is less than the other species. This study will be used in offering objective data and landscape planning for making comfortable roads cape through the quantitative evaluation as each species and seasonal changes.

• Journal of Conservation Science
• /
• v.38 no.4
• /
• pp.347-359
• /
• 2022

Gongsanseong Fortress was registered of a World Heritage Site in 2015 as a representative cultural heritage from the Woongjin Baekje period, and it has been used throughout the entire period from Baekje Kingdom to the Joseon Dynasty. Within Gongsanseong Fortress, the area around Ssangsujeong is presumed the site of royal palace of the Woongjin Baekje. Also, the excavated culture layers of the Baekje Kingdom, the Unified Silla period, and the Joseon Dynasty were confirmed. In this study, paleotopography was modeled by digitally converting the elevation data obtained through surveying the excavation process, and the use of the topography in the Ssangsujeong area was considered by examining the variations in the topography according to the periods. As a result, the topography of the slope around the peak changed by periods, and the topography did not change on the flat land. The topography between the Baekje Kingdom and the Unified Silla period appeared to be almost identical, and it seems that the space of the Baekje period was maintained as it is. Also, during the Joseon Dynasty, it is confirmed that flat surfaces in the previous period were used. However, sediments on the slopes flowed down, reducing the area of the flatland, and architectural techniques that could utilize the natural topography of the changed slope were applied to interpret it as having a different topography from the previous period. In order to model and interpret the paleotopography, excavation data, geological and topographic analysis, and digital data must be secured. It is expected that location conditions and ancient human life can be identified if the analysis technique in the study is applied to other archaeological sites in the future.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.1
• /
• pp.48-59
• /
• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Journal of the Korean housing association
• /
• v.20 no.1
• /
• pp.59-70
• /
• 2009

The purpose of the study is to suggest the amount of space for each behavior according to the classification of behavior in the housing to plan the optimal floor space of the elderly housing. The method for calculating space for behavior begins with classifying behaviors, identifying them and then taking pictures of the model of elderly people who reproduce each behavior. Based on the pictures, body parts which are necessary for each behavior are assembled and the formula for behavioral space is created. The space for behavior is produced considering the body dimensions of Korean elderly in their sixty's as well as the furniture size and the psychological distance between people. 3D modeling is used to verify the result. Human behaviors can be classified into individual-related, housework-related, family-related, reception-related and other behaviors. These five behaviors are subdivided into more specific behaviors. The area for each specific behavior is calculated with the anthropometric data of the elderly, preferred furniture dimension and psychological area. As a result the required area for specific behaviors is as follows: the behavior of sleeping in a bed needs $4.3m^2$; the behavior of changing clothes on a chair, $1.7m^2$; the behavior of watching TV on the floor $1.3m^2$, the behavior of working and reading using a desk, $2.1m^2$, the behavior of exercise, $2.5m^2$; the behavior of showering on a chair, $1.3m^2$ and showering using a wheelchair, $1.9m^2$; the behavior of toileting using a wheelchair, $2.3m^2$; the behavior of washing up using a wheelchair, $1.9m^2$; the behavior of eating using a table for four persons, $4.4m^2$; the behavior of cooking and washing dishes, $0.9m^2$ per counter-top; the behavior of washing clothes using a washing machine, $0.9m^2$; the behavior of ironing on the floor $1.4m^2$; the behavior of reception(three persons) on the floor considering personal space, $4.0m^2$; the behavior of taking on and off shoes on a chair, $1.3m^2$. The result of the study is utilized as quantitative data to calculate optimal floor space for elderly housing. In addition, qualitative data such as characteristics of housing preference, spacial usage and storage capacity are necessary to produce the floor space which can provide convenient and safe living environment.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.1-23
• /
• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Global Scholars of Marketing Science
• /
• v.18 no.1
• /
• pp.1-31
• /
• 2008

Trust is central to human relationships, at all times and places. The importance of trust is fundamental in all areas of human life, not only in the area of business administration. 2,500 years ago in China, Confucius taught that the foundation of politics was the trust of the people, more important even than military strength or the supply of food. Shakespeare's play, "Much Ado about Nothing' is about trust and deception. These days, trust and transparency in a commercial organization's business culture form the basis of the 'social capital' by which that organization increases its productivity. A successful company raises productivity by the accumulation of social capital, derived from a trust relationship between business partners, and between the company and consumers. Trust is the crucial factor. At the national level, building trust determines a nation's competitiveness. For a company, long term trust relationships with customers are essential for its survival in a business environment of rapid change. Such relationships, based on trust, are important assets to ensure a company's competitive advantage, and need to be organic to that company's business culture. Because of this importance, trust relationships have been studied in diverse areas within business administration, and especially within marketing, where they form the basis of a successful relationship between producer and consumer. However, what has been lacking is a unified definition of trust. Research has been conducted on the basis of various definitions and models. The majority of researchers have not considered the multidimensional character of the concept of trust until now. Approaches based on a one dimensional model have undermined the value of research results. Furthermore, researchers have only considered trust and trustworthiness as a single component. The majority of research has explored the consequences of perceived trust for outcomes such as loyalty or cooperation, but has neglected the effects of trustworthiness upon the mechanisms of consumer trust. This study focuses on the dimension of trust from such a perspective. It seeks to verify the effect of trust on customer intentions by breaking it down into three separate components: 1) the salesperson, 2) the product/service, and 3) the company. The purposes of this paper are as follows: Firstly, we review the multidimensional nature of trust objects: the salesperson, the product/service, and the company. Secondly, we analyze the relationship between multidimensional trust and trustworthiness. Thirdly, we analyze the connection between trust and repeat purchase intentions for the maintenance of long term relationships. For these purposes the author has developed several hypotheses as follows: H1-1: The competence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H1-2: The benevolence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H2-1: The competence of product/service is positively associated with the trust given by the consumer to the product/service. H2-2: The benevolence of product/service is positively associated with the trust given by the consumer to the product/service. H3-1: The reputation of a company is positively associated with the trust given by the consumer to the company. H3-2: The physical environment of a company is positively associated with the trust given by the consumer to the company. H4-1: Trust in a salesperson is positively associated with repeat purchase intentions. H4-2: Trust in a product/service is positively associated with repeat purchase intentions. H4-3: Trust in a company is positively associated with repeat purchase intentions. The data was compiled from 366 questionnaires. 500 questionnaires were collected, but some of the data was considered unsuitable and inappropriate. The subjects of the survey were male and female customers purchasing products at department stores in Seoul, Daegu and Gyeongbuk. It was carried out between Oct. 25 and 29, 2007. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using LISREL 8.7. The result of the overall model analysis is as follows: Chi-Square=445.497, d.f.=185, p-value=0.0, GFI=.901, RMSEA=.0617, NNFI=.986, NFI=.981, CFI=.989, AGFI=.864, RMR=.0872. The results of the overall model analysis were coherent. It was found that trust is a multi-dimensional construct, that each of the dimensions of trust are meaningful influences on customer's repurchase intention. Trust in a company may be the most relevant, while trust in a product/service and a salesperson may be less relevant to repurchase intentions. The effective factors in determining trust in a salesperson and a company's product/service were found to be competence and benevolence. Factors in determining trust in a company were its reputation and physical environment, and the relationship of each effective trust factor has been verified in this research. As a result, it was found that competence and benevolence have a meaningful influence on trust in a salesperson and in product/service. It was also found that a company's reputation influences the overall trust in the company significantly but a company's physical environment does not have much effect.