• Proceedings of the Korea Association of Information Systems Conference
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• 1998.10a
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• pp.79-86
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• 1998

본 연구는 예식장 운영에 관한 이론적 실무와 예식업 시장의 변화되는 요인을 제 시하여 예식장관리시스템의 새로운 모델을 정보시스템에 접목시키고자 한다. 예식정보시스 템은 예식서비스 부분을 획기적으로 개선하여 고객 만족도를 향상시킴으로 예식산업의 발전 과 예식장의 고객 대응 부당 요소인 시간, 경비, 서비스 문제를 개선하고 체계적인 소비문 화 정착에 크게 기여할 것이다. 특히 한국의 부산지역에 새로운 대형예식장이 신축 및 영업 중이며, 이들 예식장의 경영은 사전 전문지식과 노하우가 없이 운영되고 있는 현실에서 기 업의 경쟁력을 갖추기 위한 올바른 방향을 제시하고자 하였다.

• Knowledge Management Research
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• v.16 no.3
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• pp.149-169
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• 2015

In this study, we try to understand the role of online social recommendation and the similarity of preferences between the recommender and the recommendee on consumer decisions in the framework of the two stage purchase decision-making process. Applying construal level theory to our context, we expect that the role of social recommendation and the similarity of preferences would vary over the stages in the two-stage decision making process. To test our hypotheses, we collected the data through an incentive compatible experiment, and analyzed the data with nested logit model. As a result, we found that the role of online social recommendation varies over the stages. Consumers take recommendation from similar others at the stage of consideration set formation, but no longer consider it at the stage of final choice. Consumers take recommendation from dissimilar others at the stage of consideration set formation. At the stage of final choice, however, consumers avoid choosing the option recommended by dissimilar others. The results of our study enrich the understanding about the role of social recommendation, and have implication to marketing practitioners who attempt to make online social recommendation system more efficient.

• Knowledge Management Research
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• v.10 no.2
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• pp.15-33
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• 2009

Telecommunications-broadcasting convergence in the domain of IT is a representative phenomenon that is expected to provide the saturated existing markets with a new source of profit. Especially, T-Commerce combines familiarity of TV and immediacy of the Internet which are expected to cover all the users familiar with each media and expand the existing commercial transactions. Telecommunications-broadcasting convergence in Korea, however, is focusing on technical and regulatory aspects so that research on the real users is not up to the mark yet. This is the most fundamental problem in hampering growth in the corresponding service and market. Thus, we are proposing an adoption model on T-Commerce to rapidly expand the convergence service through understanding the potential users. Perceived utilitarian and hedonic values, perceived interactivity, media substitution and personal innovativeness have been examined as the factors influencing the users' intention to adopt a new convergence service. As a result of empirical analysis, it is verified that perceived utilitarian and hedonic values and personal innovativeness directly influenced the users' intention to adopt whereas perceived interactivity had indirect affect on them. T-Commerce service providers should not only emphasize on the benefit that the older media could not provide the users with, but also provide them with more pleasure and entertaining experience during the course of satisfying the users' needs to distinguish T-Commerce from the other existing media.

• Knowledge Management Research
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• v.19 no.1
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• Knowledge Management Research
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• v.21 no.2
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• pp.119-135
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• 2020

Owing to pandemic (COVID-19), the traditional face-to-face education method has been changed to the non-face-to-face real-time online education methods. Using a real time-based video conference system, synchronous education can be adopted by face-to-face class easily. Specially, it is very important to minimize the difference in learning effects between face-to-face and non-face-to-face in Entrepreneurship education. In this study, in order to derive the factors that affect the satisfaction of learners in synchronous online education, authors collected data from learners taking a synchronous entrepreneurship course. Through previous research, learned the reality of education and the composition of lessons. Spatiotemporal effectiveness, mentor ability, and educational environment influence learning satisfaction. PLS-SEM results revealed that it was confirmed that only spatiotemporal effects affect learner satisfaction. However, the education environment (fluent operation and convenience of function use of real-time based online conference system) effect teaching presence, class structure, and spatiotemporal effects. Through this research, we hope to provide theoretical and practical support for developing effective teacher activities, proper lesson structure, convenient function of the conference system, and learner-centered online learning environment when developing synchronous online classes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.848-849
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• 2014

실시간으로 고객의 피드백을 파악할 수 있는 방법으로 SNS 등과 같은 빅 데이터를 이용하는 것이 매우 효율적 이다. 따라서 최근 기업들은 온라인상의 빅 데이터 평판을 분석하는 시스템들을 이용하여 고객피드백에 관한 정보를 수집하고 분석하고 있다. 본 논문에서는 온라인상의 고객피드백의 보다 정확하고 효율적인 정보 수집과 분석이 가능하며 분석 지식체계의 근간을 이루는 서비스 모델구축 방법을 제안한다. 서비스 모델 구축방법은 서비스 산업군에 대한 시소러스 분석 체계를 정의하고 데스트베드 대상의 인터뷰 등을 통하여 분류체계 기본 방향을 수립하며 타겟 대상의 특화된 수집원 및 범위를 설정하는 방법 등으로 이루어진다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.603-605
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• 2022

추천시스템은 개개인의 성향에 따른 맞춤화 추천이 가능하기 때문에 음악, 영상, 뉴스 등 많은 분야에서 관심을 받고 있다. 일반적인 추천시스템 모델은 블랙박스 모델이기 때문에 추천 결과에 따른 원인 도출을 할 수 없다. 하지만 XAI 의 모델은 이러한 블랙박스 모델의 단점을 해결하고자 제안되었다. 그 중 KGAT 는 Attention Score 를 기반으로 추천 결과에 따른 원인을 알 수 있다. 이와 같은 AI, XAI 등의 딥 러닝 모델에서 각각의 활성화 함수는 상황에 따라 상이한 성능을 나타낸다. 이러한 이유로 인해 데이터에 맞는 활성화 함수를 적용해보는 다양한 시도가 필요하다. 따라서 본 논문은 XAI 추천시스템 모델인 KGAT 의 성능 개선을 위해 여러 활성화 함수를 적용해보고, 실험을 통해 수정한 모델의 성능이 개선됨을 보인다.

• Knowledge Management Research
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• v.22 no.2
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• pp.289-300
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• 2021

Proptech, which has applied information technology to the real estate market, is leading real estate transaction innovation by presenting various value creation models. This study categorizes and understands values that are created and shared in proptech-based businesses, and develops evaluation data that reflects the relative importance of individual value areas. To this end, the dimension of value creation of proptech was hierarchically constructed, and the degree of relative value creation of the sub-industries of the proptech industry was evaluated. In order to grasp the relative importance of the proposed indicators, AHP analysis was conducted for industry and academic experts. In the first stage, intangible values, relational values, and advanced values were presented. It was derived as weights between indicators through two-way comparison. This study aims to improve and develop the value-creation capability of the entire Korean proptech ecosystem in the future by evaluating the value-created competence of each sector of the proptech industry.

• Knowledge Management Research
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• v.22 no.1
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• pp.155-181
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• 2021

The purpose of this study is to verify the correlation between leader's machiavellianism and turnover intention. To this end, we tried to investigate the overall mechanism of the research model through the mediating effect of hindsight bias. To verify the hypothesis, surveys were conducted twice with 335 employees working at companies with more than 300 employees in various occupations. As a result of the study, first, it was found that the machiavellianism of the leader had a positive significant effect on the employee turnover intention. Second, it was found that hindsight bias had a positive significant mediating effect between the leader's machiavellianism and employee turnover intention. It can be inferred that the higher the machiavellianism tendency of the leader, the higher the hindsight bias is experienced and the negative impact on the effectiveness of the organization, the higher the employee turnover intention. Therefore, this study in-depth verifies the mechanism between the leader's machiavellianism, hindsight bias, and employee turnover intentions, suggesting new implications from a perspective different from the existing research flow, and suggesting future research tasks and limitations on the role of leaders.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.