• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.66
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• pp.191-218
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• 2015

This research is, first of all, a theoretical study concerning 'conflict.' Only then, we could obtain ways in which we manage and resolve various problems arising from conflicts in business between Korean and Chinese companies. In doing this, we also tried to grasp cultural characteristics, or factors, in Chinese ways of carrying out negotiations that lead to conflicts with us. On the basis of these preliminary considerations, we developed practical techniques of conflict management and types of negotiation strategy. We thereby could suggest broader strategic implications for better performance in international business. Concretely, this research investigates techniques of conflict management and types of negotiation strategy. For such techniques and types, we suggest, (1) Sharing technique or reconciliatory compromising negotiation and its compromise strategy, (2) collaborative technique or cooperative negotiation and its win-win strategy, (3) competitive technique or competitive negotiation and its profit-seeking attack strategy, (4) accommodative technique or receptive negotiation and its relation-maintaining yield strategy, (5) avoidant technique or evasive negotiation and its indifference-showing avoidance strategy. This research contributes to promote understanding on negotiation culture of chinese corporate. and we provide the guideline of the conflict management and the insight for the efficiency strategy of chinese business negotiation. But, empirical data and statistical examinations should be added to our present research for the future prospective ones.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.149-159
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• 2001

There have been lots of researches for providing a personalized service to a customer using one-to-one marketing and collaborative filtering techniques in E-Commerce. However, there are technical difficulties for providing the recommendation of products far users, which often involve high complexity of computation. In this paper, we have presented an integrated method of classification problem solving method and constraint based configuration techniques. This method can reduce a complexity of computation by classifying a solution domain space that has a higher complexity of composition. Thereafter, we have modeled customers constraints and the components of products to configure a complete system by passing it to constraint processing module in Constraint Satisfaction Problems. Constraint-based configuration uses the constraint propagation using the constraints of buyers and the constraints among PC components to configure a proper product for a customer. We have transformed and applied vector space modeling method in the field of information retrieval to consider a customer satisfaction in addition to the CSP. Finally, we have applied our system to test data fur evaluating a customers satisfaction and performance of the proposed system.

• International Commerce and Information Review
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• v.1 no.1
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• pp.179-201
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• 1999

CALS/EC is about doing business electronically. It is based on the electronic processing and transmission of data, including text, sound and video. It encompasses many diverse activities including electronic trading of goods and services, online delivery of digital content, electronic fund transfers, electronic share trading, electronic bills of lading, commercial auctions, collaborative design and engineering, online sourcing, public procuremet, direct consumer marketing, and after-sales service. It involves both products(e.g. consumer goods, specialised medical equipment) and services(e.g. information services, financial and legal services); traditional activities(e.g. healthcare, education) and new activities (e.g. virtual malls). CALS/EC will be emerging to replace and substitute the role of the conventional market. By changing and eliminating some processes of the transactions, the electronic market and the electronic commerce will redistribute the power and hence the benefits of the market activities. Traditional way of doing business may enter into the new electronic market because the role and function of trust and established reputation will be reinforced in the electronic market. The CALS/EC through the Internet has been in the spotlight in the shopping behavior of the consumers. Accordingly Corporates are trying to adapt themselves to those rapidly changing environments being affected by the Internet. Among others, particularly to be noted is the CALS/EC between corporations and consumers whose potential growth can be considered very substantial. This report, focusing on the introduction of CALS/EC for the logistics of SMEs, will allow us to prepare more efficiently for the coming 21st Century. It is obvious that CALS/EC is fast becoming the useful way of exchanging not only information but products in business between firm-to-firm and firm-to-customer.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• 대한공업교육학회지
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• v.36 no.2
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• pp.273-292
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• 2011

The Purpose of this research is to investigate how Project Based Learning(PBL) cognitive department and among the learner and instructor in the industrial highschool. Theoretical framework for the study is based on PBL, collaborative learning and module learning. The importance of the PBL has been continuously reviewed by many educational researchers. In addition, it was supported by previous research results. Based on theoretical frameworks and previous researches on the PBL provided design principles and method for learning in the industrial highschool. As a result of this study, we have developed and applied to investigate (1) differences between the types of departments(agriculture, industry, commerce) of cognition on learner's and instructor's task solving process, (2) correlation between the type of groups(learner, instructor) and type of departments(agriculture, industry, commerce) cognition on task solving process. The total of 100 learners and 50 instructors from industrial highschool in the study for the period of sixteen weeks. Based on the type of groups and departments, participants were divided into six groups such as learner and instructor of agriculture, industry, commerce department. The result of the study can be summarized as follows: First, in the study, between the types of departments(agriculture, industry, commerce) of cognition on learner's and instructor's task solving process are differences. Second, correlation between the type of groups(learner, instructor) and type of departments(agriculture, industry, commerce) of cognition on task solving process are differences. Although the differences were insignificant for cognition of PBL's help, however, four items(accomplishment, application subject, hereafter application) showed significant differences in performances. The implication of the result indicated the cognition of PBL in the industrial highschool seem significant for departments and subjects characteristic of learning. In future research it is recommended that PBL model designs should consider components of group and department types.

• The Journal of Information Systems
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• v.9 no.1
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• pp.87-108
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• 2000

The tourist industry is expecially one of the successful areas for the application of electronic commerce because it is an information-intensive and consumer-oriented industry where information and services play a large part in transaction processes. A electronic tourism market which integrates tourist information systems, reservation systems, and real-time broadcasting systems based on the Internet Web was developed by a collaborative team of Dongguk University and Daou Tech. Inc. with sponsorship of Kyongbuk province and Minister of Information Communications of Korea. Based on the development case of the system, this paper proposes development and operations strategies of electronic market in the tourist industry. The paper reviews the development strategies in the perspective of potential travelers, technology, cooperation among players, and development methodology. The paper also discusses strategies which are able to be employed as the guideline in order to operate the system.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.2
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• pp.185-208
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• 2015

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems. Recommender systems are personalized information filtering used to identify a set of items that will be of interest to a certain user. This paper reviews recommender systems and presents their pros and cons.

• The Journal of Information Systems
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• v.17 no.4
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• pp.321-340
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• 2008

Collaborative planning, forecasting and replenishment (CPFR) is the most recent successful management initiative that provides supply chain collaboration. By adopting CPFR, companies can dramatically improve the effectiveness of supply chain. The CPFR process has three major sub-processes; planning, forecasting and replenishment, which are formed by a number of steps. Despite the existence of a detailed and comprehensive process model, which is published by the Voluntary Interindustry Commerce Standards Association, in practice CPFR can take a number of different forms. Therefore, this research suggests that business process management system (BPMS) can be utilized as a base system on which a CPFR is consistently constructed and implemented, regardless of a number of its possible forms. We illustrate how a CPFR protype is implemented by using a BPMS and then describe how the prototype is agilely extended to adopt a variety of changes of CPFR collaboration process.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.289-292
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• 2000

인터넷이 생활의 일부분이 되어감에 따라 인터넷상에서 이루어지는 전자상거래는 빠르게 발전하고 있다. 지금까지의 전자상거래는 고객이 요구하는 제품을 판매하는 단순한 형태였다. 하지만 앞으로의 전자상거래에서는 고객이 선호할 만한 제품을 예상하여 고객에게 해당 제품을 추천해 줌으로서 양질의 서비스를 제공하고 더 많은 이익을 창출 할 수 있는 전자상거래 시스템이 요구되고 있다. 본 논문에서는 전자상거래시스템에서 이용될 수 있는 추천시스템을 개발하기 위하여 추천시스템의 핵심이 되는 사용자간 유사도에 기초한 GroupLens의 협동적 필터링 알고리즘을 실제 Data Set을 통해서 실험하였다. 또한 Data Set을 분석하여 아이템을 대표할 수 있는 장르를 결정하여 전체 학습데이터로부터 대표장르에 속하는 데이터들만을 분리하여 학습데이터로 사용하는 추천시스템을 제안하였고, 실험을 통하여 제안한 추천시스템의 타당성을 보였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.609-610
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• 2006

This paper introduces a methodology for construction of ontology-based product knowledge Map. For CPC(Collaborative Product Commerce) environment, engineering application of ontology has been studied . However, there are no generic and comprehensive methodologies for ontology construction yet because of such problems: dependency on experience of ontologist and domain experts and insufficiency of detail stages or rules. To solve those problems, we propose a methodology to construct ontology from engineering documents in semi-automatic. We use middle-out strategy and term's axioms, sub-definitions, to build ontology map. 5-turple ontology structure, semantic network and First order logic (FOL) are used for ontology definition in this study.