• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.39-48
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• 2016

This research aims to identify innovative companies' attention to the emotion and sensibility and its application by analyzing the contents of the corporate annual reports. Annual report is a good reference data because it describes not only various current products and services' annual activities and business performance but also corporate future direction. Sensibility is interpreted and used with various words internationally: various related terms such as sensibility, sense, emotion, feeling and affection are analyzed not only by the definition but also the interrelationship among them, and included for the contents analysis. To select the innovative companies, the researcher used 'Fast company' that is the economic journal and deducted the companies list via 'The world's 50 most innovative companies' in 2009 and 2014. Listed companies' 2009 and 2014 annual reports' contents were analyzed to identify the rate of the recognition and the application of sensibility to their business. Even though the quantitative result of the content analysis indicates not a strong relationship between corporate innovativeness and 'sensibility' qualitative result identifies companies are paying more attention to the 'sense' and 'feeling' during five years. In conclusion, the innovation that company pursues strategically is shifting from differentiation and the technological leadership to satisfying user experiences and the number of companies which express and measure user feeling and emotions are increasing.

• Korean journal of communication and information
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• v.60
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• pp.75-103
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• 2012

The purpose of this study is to explore the meaning and the effect of communication as social capital, which needs to be evaluated empirically focusing on corporate reputation. Also, it tried to analyze consumers' communication network in the structural, substantial, and relational level, which is to verify how characteristics and meanings of communication network structure affect to a good corporate reputation. A survey toward 200 participants was conducted during 5 days from March 29 to April 3, 2012. Characteristics of communication network structure of a corporation with higher reputation is analyzed using the index such as degree, degree centrality, and density. The findings of the study show that a corporation with higher reputation has higher network degree, degree centrality, and density compared to a corporation with lower reputation. Consumers of a corporation with higher reputation get information from various overlapping sources. It allows them to share similar interpretation, which could elevate the degree, degree centrality, and density of network. It also proved that when the network density is high, a corporation with higher reputation can distribute information much faster and easier. Moreover, in the substantial level of social capital, product/service information network has high degree and density rather than corporate issue information network. Likewise, degree and density of information acquisition network was higher than those of information provision network. Also, this study verified the effect and relationship between the network structure characteristics and corporate loyalty in a relational level. In this way, the positive effect of the degree centrality on corporate loyalty was supported. In conclusion, as consumers share more information from overlapping sources, the degree of communication network gets higher. Throughout this network, the diffusion of information among consumers would be activated, and this confirmed that corporate reputation and corporate loyalty is closely related.

• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.

• Knowledge Management Research
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• v.21 no.3
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• pp.229-247
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• 2020

In the remarkable growth of P2P financial platform in the field of knowledge management, only companies with big data and machine learning technologies are surviving in fierce competition. The ability to analyze borrowers' credit is most important, and platform companies are also recognizing this capability as the most important business asset, so they are building a credit evaluation system based on artificial intelligence. Nonetheless, online P2P platform providers that offer related services only act as intermediaries to apply for investors and borrowers, and all the risks associated with the investments are attributable to investors. For investors, the only way to verify the safety of investment products depends on the reputation of P2P companies from newspaper and online website. Time series information such as delinquency rate is not enough to evaluate the early stage of Korean P2P makers' credit analysis capability. This study examines the credit analysis procedure of P2P loan platform using artificial intelligence through the case analysis method for well known the top three companies that are focusing on the credit lending market and the kinds of information data to use. Through this, we will improve the understanding of credit analysis techniques through artificial intelligence, and try to examine limitations of credit analysis methods through artificial intelligence.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.155-168
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• 2018

This study singled out 30 smart car features and surveyed 250 respondents. Assuming that the relationship between fulfillment of a feature or a customer need and the satisfaction with that feature is not necessarily linear, this study was conducted using Kano's method. Two devices, Timko Deviation(TD) and Kano Distribution Index(KDI), were devised to help evaluate resulting Kano table quantitatively. Previous research based on Kano's original framework showed the limit to the analysis of new or unfamiliar features: more than 85% of the features surveyed turned out to be either Attractive or Indifferent attributes. This study attempted a new empirical approach by applying customer experiences, price conditions, and customer self-stated importance. The results showed that customer experience of the surveyed features affected the overall satisfaction level, signifying that Kano's method should be conducted with care when analyzing emerging technologies such as smart cars. It is expected that this study would be utilized for better understanding of the perception and trends of customers regarding new technologies. This study also suggests a new approach to the analysis of customer requirements by providing price conditions.

• Proceedings of the Technology Innovation Conference
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• 2004.06a
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• pp.170-213
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• 2004

생산자 중심에서 소비자 중심으로의 경영 패러다임이 변화함에 따라, 이제 디자인 경영(design management)의 시대가 도래하였다 즉, 제반 기능의 활동이 독립적이고 순차적으로 이루어지는 기존 경영방식(즉, 제품 개발 $\rightarrow$ 제품 디자인 $\rightarrow$ 제조 $\rightarrow$ 마케팅 $\rightarrow$ 판매)과는 달리, 디자인 경영은 디자인을 중심으로 제반 기능간의 통합과 조정을 이룬다. 이 결과, 디자인 경영은 조직간의 커뮤니케이션을 활성화시키며 소비자의 추상적인 욕구가 구체적으로 상품에 표현되도록 노력한다. 이렇게 함으로써, 디자인 경영은 기업 이미지 창조의 역할을 적극적으로 수행하는 것이다. 이와 같은 소비자 중심의 경영은 과거 제품의 판매(sales)지향적이던 기업 활동을 소비자와의 관계(relationship)지향적으로 변화시키고 있다. 본 연구의 분석 목적은 제품 디자인을 품질경쟁력의 결정요인으로서 포함시켜 품질경쟁력의 평가모형을 개발하고 품질경쟁력의 결정요인 및 상관관계와 품질함수를 추정함으로써 제품 디자인 및 디자인 경영의 기능적 역할을 규명하고 디자인 경쟁력 수준을 평가 및 측정할 수 있는 모형을 정립함과 동시에 이를 제고할 수 있는 정책방향을 제시하는 것이다. 이로써, 본 연구는 신상품의 개발과정에서 어떻게 제품 디자인이 연구개발, 제조, 마아케팅, 판매 등의 제반 기능들과 상호 작용하며 이들 기능들의 통합과 조정을 추구할 수 있는가를 보여주는 디자인 경영의 이론적 기초를 제공하고자 함이다. 상기와 같은 연구목적과 분석목표를 위하여, 한국 제조업 부문의 400개 표본기업에 대하여 소정의 설문조사를 통하여 추출된 측정변수들을 기초로 품질경쟁력의 결정요인을 분석하고 품질경쟁력 지수를 도출하여 산업부문별 및 제품유형별로 비교하였으며, 품질함수를 추정하였다. 전술한 분석결과를 토대로, 디자인 경영이론의 기초를 제공하기 위한 시도로서 제품 디자인의 파급효과와 인과관계에 대한 가설검정을 실시하였다. 본 연구의 분석 결과는 다음과 같이 요약될 수 있다. (1) 품질경쟁력의 결정요인으로서 주요 제품들의 기능성, 기본 성능, 제품성과의 기술적 성취도, 제품 수명(내구성), 신뢰성, 핵심 기술력, 사용 편의성, 서비스 편의성, 생산 용이성, 제품 디자인의 우수한 정도가 a=0.01 수준 하에서 유의적으로 추정되었다. 이들 변수들 중에서 품질경쟁력에 가장 큰 영향을 미치는 측정변수는 제품의 기본 성능, 수명(내구성), 신뢰성, 제품 디자인의 순서로 추정되었다. 이것은 한국 제조업이 아직 산업 디자인이 품질경쟁력에 크게 영향을 미치는 성숙단계에 이르지 못하였음을 의미한다. (2) 제품 디자인에게 영향을 끼치는 유의적인 변수는 연구개발력, 연구개발투자 수준, 혁신활동 수준(5S, TPM, 6Sigma 운동, QC 등)이며, 제품 디자인은 우선 품질경쟁력을 높여 간접적으로 고객만족과 고객 충성을 유발하는 것으로 추정되었다. 상기의 분석결과로부터, 본 연구는 다음과 같은 정책적 함의를 도출하였다. 첫째, 신상품 개발과 혁신을 위한 포괄적인 연구개발 프로젝트를 품질 경쟁력의 주요 결정요인(제품의 기본성능, 신뢰성, 수명(내구성) 및 제품 디자인)과 연계하여 추진해야 할 것이다. 둘째, 기업은 디자인 경영 마인드 제고와 디자인 전문인력 양성을, 대학은 디자인 현장 업무를 통하여 창의력 증진과 기획 및 마케팅 능력 교육을, 정부는 디자인 기술개발 및 디자인 교육지원의 강화를 통하여 각각 디자인 경쟁력$\rightarrow$품질경쟁력을 제고시켜야 할 것이다.

• Environmental and Resource Economics Review
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• v.15 no.3
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• pp.425-450
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• 2006

The index of energy intensity(energy/GDP) has been a primary policy concern since it can clarify industry sectors which use energy intensively and generate $CO_2$ emission heavily. Although energy intensity index may be suitable for estimating $CO_2$ emission from an isolated industry sector, we need an index for induced $CO_2$ emission since industrial activities are interconnected in terms of input and output. By employing Environmental Input-Output Table 2000, this paper analyses the flow of energy demand and pollutants after first estimating an induced $CO_2$ emissions from various industrial sectors and economic activities. The paper reports higher induced $CO_2$ emissions from industry sectors with larger energy intensity since they produces goods or services retaining relatively considerable environmental load. Furthermore, it is shown that environmental load and $CO_2$ emissions in overall economy are likely increasing when the products of energy intensive industrial sector is used as inputs for less intensive sectors' production process. The result suggests we need consistent policy efforts to reduce energy intensity to lower $CO_2$ emissions.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.537-549
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• 2015

The purpose of this study is to analyze the characteristics of two local festivals, already recognized as a successful regional cultural festival, over a period of time to apply the product life cycle theory. As a result of the analysis of the two festivals, in introduction stage, the festival organizers have focused mainly on settling down the festival's core programs and raising awareness on the subject of the festival for the stimulation for basic demands. Second, for maintaining increasing demands, the qualitative improvement of the core program, the development of new programs and the expansion of the programs for the visitors' convenience and safety were focused on. In addition, strategies for promoting awareness of the festival had modified the strategy to promote on the contents and programs of the festival, as well as public relations strategy, not only domestic but also the foreign countries, was established and fulfilled. Lastly, in maturity stage, to overcome declining the number of visitors and economic effect both festivals have showed providing sophisticated programs for the visitors' convenience and safety, improving service quality through the development of the existing programs, providing economic benefits such as admission cuts or giving gift certificates and expanding number of foreign visitors with strengthening the promotion that was implemented in growth stage and enhancing the better image of the festival through the social contribution. Therefore, strategies for the each stage mentioned above present the significant policy implications for festival organizers who were planning to establish a new festival or implementing a festival with experiencing the tepid growth.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.835-845
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• 2013

Association rule of data mining techniques is the method to quantify the relevance between a set of items in a big database, andhas been applied in various fields like manufacturing industry, shopping mall, healthcare, insurance, and education. Philosophers of science have proposed interestingness measures for various kinds of patterns, analyzed their theoretical properties, evaluated them empirically, and suggested strategies to select appropriate measures for particular domains and requirements. Such interestingness measures are divided into objective, subjective, and semantic measures. Objective measures are based on data used in the discovery process and are typically motivated by statistical considerations. Subjective measures take into account not only the data but also the knowledge and interests of users who examine the pattern, while semantic measures additionally take into account utility and actionability. In a very different context, researchers have devoted a lot of attention to measures of confirmation or evidential support. The focus in this paper was on asymmetric confirmation measures, and we compared confirmation measures with basic association thresholds using some simulation data. As the result, we could distinguish the direction of association rule by confirmation measures, and interpret degree of association operationally by them. Futhermore, the result showed that the measure by Rips and that by Kemeny and Oppenheim were better than other confirmation measures.

• Culinary science and hospitality research
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• v.15 no.1
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• pp.209-224
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• 2009

The objective of this study is to find out how well-being influences consumer behavior of dining-out. Based on this objective, this study covers plans for improving marketing strategies, which contributes to menu development and purchase behavior of consumers. This study consists of two parts : a research based on the review of the literature and empirical study methods. The finding of the study would also be valuable for the development of management of advertising strategies to be implemented in the foodservice industry. Based on the survey statistics, Program SPSS 12.0 and Amos 5.0 were used in order to look into a casual relationship among group units. The findings of the demonstration analysis are as follows. Most of previous research regarding well-being in local study is psychological well-being dealt with individual health and psychological satisfaction. On the other hand, social well-being is likely to focus on public relation rather than private concerns. The fact that the term 'well-being' have not been definitely defined yet was a problem in research. Also, well-being should not be recognized as a temporary trend but as a general trend. Therefore, it is necessary to understand consumer behavior which is changeable as the circumstance of the foodservice industry changes.