• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.15-26
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• 2018

This study examines the effects of failure experience, re-startup's motivation, government support business and education for re-startup on the performance of re-startup firms after failure. In addition, we analyzed how the above factors affect the performance of re-startup firms by the condition of debt and credit problems. As a result of the analysis, the failure experience had no significant effect on the re-startup performance regardless of the credit problem, while re-startup's motivation, government support business and education for re-startup had a significant effect on re-startup firms' performance. In the re-startup group with the credit problem, the re-startup's motivation and the failure experience had a significant influence on the re-startup firms' performance. On the other hand, in the group that did not solve the credit problem, the re-startup's motivation and the failure experience had no significant effect on the re-startup performance, but the government support business and education for re-startup had a significant effect on re-startup performance. The results of this study are as follows: First, it shows that the characteristics of re-startups and the determinants of re-startups are different according to credit problems. Second, this study shows that it takes 56 months on average from the close of business to the re-start, and it may take more than 7 years due to the credit problems and bankruptcy. This suggests the necessity to consider re-startup in the concept of obsolete in consideration of time, when studying the direct/indirect influence of failure experience and re-startup, and establishing policy.

• Information Systems Review
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• v.7 no.2
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• pp.229-255
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• 2005

The Korea Development Bank promoted a total outsourcing for IT operation in 1999 for the first time in the banking industry. The Korea Development Bank became the center of public attention because the most banks were unwilling to take an outsourcing with external sources for the reason of financial operation accidents, securities, and threats of strikes. After the introduction of the total IT outsourcing, the Korea Development Bank has continuously diagnosed the problems of the IT outsourcing and adopted various proper complements for the enhancement of the IT outsourcing. As the result of the enhancement, the IT outsourcing of the Korea Development Bank marched into the joint liability operation period after going through the outsourcing operation period and the co-operation period. The joint liability operation which is the most leading outsourcing system which is adopted by the Korea Development Bank for the first time in the banking industry. Through the joint liability operation, the Korea Development Bank could accept the most up-to-date IT, concentrate internal manpower on the core capability, and secure flexibility of manpower. Also, the bank changed the relationship between the bank and the external sources from the one-sided relationship between a producers and a consumer to the joint liability relationship on which both sides are responsible for the operation, and could integrate the internal capacity with the professional know-how of the external IT outsourcing company. In this paper, we testified the soundness and validity for the worries of banks about the total IT outsourcing with external sources. And, we arranged the advantages and outcomes of the total IT outsourcing with external sources compared to the IT outsourcing with internal sources. Moreover, we expect that we can improve the closed financial IT outsourcing industry structure and raise the world competitive power of domestic IT outsourcing companies by correcting wrong ideas on the IT outsourcing with external sources.

• Journal of Korea Water Resources Association
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• v.45 no.10
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• pp.969-981
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• 2012

In this study, we analysed hydrologic variability in quantity and onset of annual maximum flow and low flow by impacts of the different phases of ENSO (El Ni$\tilde{n}$o Southern Oscillation) over the Han River Basin. The results show that annual maximum flow has increased statistically significant about 48.3% of all over the watershed. The onset of annual maximum flow was delayed in the west of the Han River basins and in the east of the basins was likely to be rapid onset. Also, this study shows that 7-day low flow was deceased statistically significant about 26.0% of the total area in the Han River Basin, and onset of 7-day low flow tends to be faster in the upper-middle basins of the Han River. The onset of annual maximum flow shows similar pattern during the CT (Cold tongue)/WP (Warm-pool) El Ni$\tilde{n}$o years, but annual maximum flow appeared less in 89.0% of all basins during the CT El Ni$\tilde{n}$o years. In addition, the onset of 7-day low flow tended to be faster about 17 days on average during the WP El Ni$\tilde{n}$o years, and 72.7% of the basins show significant increase during the CT El Ni$\tilde{n}$o years. Consequently, it was found that the different phases of CT/WP El Ni$\tilde{n}$o have effects on sensitivity to variability in quantity and onset of water resources over the Han River Basin. We expect that the present diagnostic study on hydrological variability during different phases of ENSO will provide useful information for long-term prediction and water resources management.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.65-74
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• 2016

This study mainly focuses on urban regeneration project as a countermeasure to resolve climate change issues by analyzing the carbon-reduction effect of Jeonju test-bed cases. First, an urban regeneration project is designed for city, Jeonju by analyzing its environmental problems and potential improvement. Then, carbon emission and reduction amounts are evaluated for different businesses and scenarios. Carbon emission sources are classified according to a standard suggested by IPCC, and the emissions are calculated by various standard methods. The result shows that carbon emission amount in Jeonju test-bed is 102,149 tCO2eq. The fact that 70% of the emission from energy sector originates from buildings implies that urban regeneration projects can concentrate on building portions to effectively reduce carbon emission. It is also projected carbon emission will decrease by 3,826tCo2eq in 2020 compared to 2011, reduction mainly based on overall population and industry shrinkage. When urban regeneration projects are applied to 5 urban sectors (urban environment, land use, green transportation, low carbon energy, and green buildings) total of 10,628tCO2eq is reduced and 4,857tCO2 (=15.47%) when only applied to the green building sector. Moreover, different carbon reduction scenarios are set up to meet each goal of different sectors. The result shows that scenario A, B, and C each has 5%, 11%, and 15% of carbon reduction, respectively. It is recommended to apply scenario B to achieve 11% reduction goal in a long term. Therefore, this research can be a valuable guideline for planning future urban regeneration projects and relative policies by analyzing the present urban issues and suggesting improvement directions.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.313-324
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• 2008

The purpose of the study is to investigate the influence of Ring-Back-Tone(RBT) music on the evaluation of the phone-call receiver's personality in dimensions of Openness, Extroversion, and Neuroticism. In a preliminary test, the subjects listened to 17 RBT music stimuli in random order and assessed the personality associated with liking for each music(N=15). Among the 17 RBTs, three were selected to be used in Experiments I and II and they were distinguished from each other in terms of the three personality dimensions(p<0.001). In Experiment I, the subjects were divided into four groups and were asked to make a call to interview an unknown receiver(N=60). Different RBT music was installed depending on the group to which each subject belonged. It was found that different RBT influences the caller's evaluation of the receiver's personality, supporting Hypothesis 1(p<0.001). Moreover, the ratings of the receiver's were highly correlated with those of the RBT music stimuli in terms of Openness(r=0.722, p<0.001) and Extroversion(r=0.753, p<0.001). In Experiment II, an identical experiment design was applied for a new group of subjects who were acquainted with the receiver(N=40). It was hypothesized that previous knowledge about a person would weaken the RBT effect. The results showed that RBT exerted no effect on the evaluation of the receiver's personality when the caller knew the receiver. It was also found that 12 personality traits, where each of the three personality dimensions is described by four traits, facilitated assessment of the character of the RBT music as well as the personality of the receiver.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of The Korean Association For Science Education
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• v.38 no.1
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• pp.57-68
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• 2018

The purpose of this study is to categorize learning style groups and to analyze students' learning interest and self-regulated learning abilities, according to their learning style and giftedness. One hundred and twenty-three (123) science-gifted student and 296 regular students participated in this study, responding to learning style, self-regulated learning, and learning interest questionnaires. Data were analyzed, using 2-stage cluster analysis, $x^2$ test, two way-MANOVA test, and $Scheff{\acute{e}}$ test. The results are as follows: First, by 2-stage cluster analysis, four groups were categorized: 'high-score thinking style,' 'external-liberal,' 'executive-conservative,' and 'low-score thinking style.' In the gifted group, high-score thinking style (51.2%) was the most popular, then executive-conservative (30.2%), external-liberal (17.1%), and low-score thinking style (1.6%); in the regular student group, the executive-conservative group was the biggest, then high-score thinking style (20.6%), external-liberal (11.6%), and then the low-score thinking style (8.7%). Second, in terms of learning interest, the analysis by thinking style showed that the high-score thinking style group had higher learning interest compared to the executive-conservative and the low-thinking style group. The high-thinking style group's thoughtful interest also scored the highest compared with the others. The gifted students' thoughtful interest and investigative interest also were higher than regular students '. Third, in terms of the self-regulated learning, the analysis by thinking style showed that the high-score thinking style group showed higher scores on all sub-variances than other groups, especially having highest control-belief scores. Also, gifted students had higher scores on control-belief and searching information. Based on these results, the ways for effective education and support were discussed.

• The Korean Journal of Air & Space Law and Policy
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• v.8
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• pp.231-248
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• 1996

이 논문(論文)은 한국(韓國)의 우주(宇宙) 산업(産業) 발달(發達)과 그 과정(過程)을 고찰(考察)하고 현재 진행 중인 통신위성(通信衛星)의 개발(開發)과 그 사업(事業)을 뒷받침해 주는 국가(國家)의 정책(政策)을 살펴보고 있다. KOREASAT라고 명명(命名)된 통신위성(通信衛星) 개발(開發)에 현재 여러 기관이 관계(關係)하고 있으나 그 중 KARI(한국항공우주연구소(韓國航空宇宙硏究所)), ETRI(전자통신연구소(電子通信硏究所)), SERI(시스템공학연구소(硏究所)), KAIST(한국과학기술연구소(韓國科學技術硏究所)) 등이 중추적인 연구(硏究)를 하고 있다. 특히 이 논문(論文)에서는 아래와 같은 문제(問題)를 다루고 있다 첫째, 최근(最近) 한국우주개발(韓國宇宙開發) 상황(狀況) 둘째, 장기(長期) 우주개발(宇宙開發) 계획(計劃) 셋째, 현재(現在) 우주개발(宇宙開發) 상황(狀況)과 미래(未來) 우주개발(宇宙開發)에 관련한 정책(政策)적 문제(問題) 넷째, 한국(韓國) 우주개발(宇宙開發)과 정책(政策) 방향(方向)에 대한 의견(意見) 최근의 한국우주개발(韓國宇宙開發) 상황(狀況)은 크게 한국(韓國)의 통신위성(通信衛星) 사업(事業)인 Koreasat program과 다목적 위성사업(衛星事業)인 KOMSAT로 나타나는데 한국(韓國)의 최초 상업용(商業用) 위성(衛星)인 Koreasat는 1호가 1995년도에 발사(發射)되었으나 정상궤도(正常軌道) 진입(進入)에 문제(問題)가 발생하여 발사업체(發射業體)로부터 보상문제(補償問題)가 제기(提起)되기도 하였으나 2호는 성공리에 발사(發射)되었다. 미국항공우주회사(美國航空宇宙會社)와 공동(共同)으로 개발(開發)중인 새로운 과학위성(科學衛星)인 KOMSAT는 한국우주과학기술(韓國宇宙科學技術)을 한단계 더 발전(發展)시킬 수 있을 것이고 1999년도에 발사(發射) 계획(計劃)이다. 한국항공우주연구소(韓國航空宇宙硏究所) 중심(中心)의 장기(長期) 우주개발(宇宙開發) 계획(計劃)에서 제시(提示)하는 4가지 우주개발(宇宙開發)의 기본목표(基本目標)는 첫째, 우주산업응용산업(宇宙産業應用産業)의 상호협조개발(相互協助開發)에 의한 우주산업(宇宙産業) 육성(育成) 둘째, 한국(韓國)의 현재 우주산업상황(宇宙産業狀況)에 알맞은 특정분야(特定分野)를 선정(選定)하고 이 분야(分野)에서 최단기에 세계(世界) 최고의 기술수준을 성취(成就)하도록 집중(集中) 셋째, 외국과 긴밀한 협조(協助)로 선진기술(先進技術)의 습득(習得) 넷째, 체계적이고 통합(統合)된 장기우주산업발전(長期宇宙産業發展) 계획(計劃) 성립(成立) 등이다. 이러한 계획(計劃)에 주요 사안(事案)으로는 2015년까지 19기의 인공위성(人工衛星) 보유(保有)를 위한 제작계획(製作計劃)과 2010년까지 발사체(發射體) 개발(開發)을 마련하는 것이다 현재 우주활동(宇宙活動)에 관련된 문제(問題)는 주로 Koreasat의 서비스와 사용계획(使用計劃)에 대한 것으로 위성개발사업(衛星開發事業)에 있어서 관련 정부부서간(政府部署間)에 의견(意見)을 달리하고 있는 형태이다. 한국통신(韓國通信)과 정보통신부(情報通信部)는 위성(衛星)의 DBS 트랜스폰더에 대해 디지털 방식(方式)을 적용(適用)할 것을 제안(提案)했지만 공보처(共報處)는 반대(反對)의 입장(立場)을 표명(表明)한 것과 방송국(放送局)의 관리(管理)와 통제(統制)는 공보처(共報處)에 있고 무선통신표준(無線通信標準)에 대한 면허(免許)는 정보통신부(情報通信部)에 있기 때문에 방송국(放送局)에 대한 면허(免許)는 각기 다른 두 단계(段階)로 구성(構成)되는 문제(問題)가 발생(發生)한다. 또한 DBS 서비스에서 사기업(私企業)의 참여(參與)와 관련하여 재벌(財閥)의 참여(參與)를 허용(許容)하느냐의 여부(與否)의 논쟁(論爭)이다. 다음으로 미래(未來) 우주산업개발(宇宙産業開發)에 관한 정책문제(政策問題)를 살펴보면 국가적(國家的) 차원(次元)에서 조직적(組織的)인 육성책(育成策)에 대한 문제(問題)로 현재 주관 부처가 과학기술처(科學技術處)와 통상산업부(通商産業部)로 나뉘어 추진(推進)되고 있다는 점이다. 그리고 차세대(次世代) 통신위성개발(通信衛星開發) 계획(計劃)에 대한 문제(問題)로 최소 2${\sim}$4개의 궤도확보(軌道確保)와 이미 정상궤도(正常軌道) 진입(進入) 실패(失敗)에 따른 Koreasat 1호의 생명단축(生命短縮)으로 새로운 통신위성(通信衛星)을 4년이내에 발사(發射)해야 한다는 문제(問題)이다. 결론적으로 장기(長期) 우주개발계획정책(宇宙開發計劃政策)에 있어서 첫째, 국제적 우주개발사업(宇宙開發事業)에 대한 적극적(積極的) 참여(參與), 둘째, 우주(宇宙)에서 독립적(獨立的)인 활동(活動)을 할 수 있는 국가안보체제(國家安保體制)의 개발(開發), 셋째, 국가(國家) 위상(位相)의 발전(發展)과 우주개발(宇宙開發)을 위한 인력활용(人力活用)의 개발(開發), 넷째, 무한한 우주(宇宙)에 도전(挑戰)할 수 있는 우수(優秀)한 인재(人才)의 교육(敎育), 다섯째, 21세기를 대비(對備)하여 한국(韓國)의 우주개발정책(宇宙開發政策)의 결정(決定) 등이 고려(考慮)되어야 할 5가지 요소(要所)들이다. 그리고 막대(莫大)한 비용(費用)이 드는 우주개발사업(宇宙開發事業)을 효율적으로 추진(推進)하기 위해서는 국가(國家) 최고(最高) 지도자(指導者)의 직접지휘(直接指揮)를 받는 정부기구(政府機構)가 수립(樹立)되어 정부차원(政府次元)에서 추진(推進)하되 산학연(産學硏)이 협조(協助)하여 우주개발계획(宇宙開發計劃)을 추진(推進)하여야 할 것으로 본다.