• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.1044-1047
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• 2010

개인화는 사용자에게 개인의 필요와 목적, 지식, 흥미 또는 상황에 맞는 상품과 서비스 그리고 정보를 제공한다. 개인화 서비스의 과정을 통하여 개인 사용자는 자동적으로 선별된 정보만을 제공받음으로써 정보화 사회의 정보과잉 문제를 완화하고, 시간의 절약을 가져올 수 있다. 본 연구에서는 제주물산업의 주요 분야인 병입수, 기능성 주류 및 음료, 수치료 등에 적용할 수 있는 개인화 기술에 대해 연구하고 제주 맥주를 위한 개인화 시스템을 설계 및 구현하였다. 본 연구의 성과로 제주물산업을 통해 개발되는 다양한 상품과 서비스에 대해 고객 개별적인 맞춤형 서비스를 제공해 줌으로 해서 고객의 만족도를 극대화하고 제주물산업의 상품을 글로벌 브랜딩화하는데 기여할 수 있다.

• Journal of Distribution Research
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• v.11 no.4
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• pp.97-124
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• 2006

This study investigates the relationship between the relationship marketing factors, relationship quality and store loyalty in retail specialty stores. The customization of a retail specialty store was found to be having a larger effect on relationship quality than other factors such as expertise, bonding and communication and the moderating effects of customer characteristic was found be having a larger effect on relationship quality all factors except to communication. The result of this study has some practical implications. First of all, the customization strategy for individual customers is needed because customers trusted employees who provide a customized service more. Second, the employees' expertise is important to obtain the trust of customers. Third, the findings of the study showed that the communication with employees did not affect the trust. Rather, customers more often want price discounts, useful information, other benefits related to transactions. The communication is also necessary to bond a strong relationship with customers, as well as to respond customer's requests immediately Fourth, the marketing managers of the store have to effectively manage the customer relationship with the special consideration to the customer's gender, transaction experience, and variety seeking disposition.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.402-407
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• 2007

웹2.0이라는 개념과 트랜드는, 개방성, 사용자 참여, 집단 지성, 인간중심의 IT 서비스 등을 키워드로 하는, 플랫폼 기반 비즈니스 모델을 통칭한다. 전세계적 블로그 열풍이나, Googlization으로 불리기도하는 주요 웹포탈의 성장은 이러한 현상을 뒷받침하는 증거이며, 미래 인터넷 시장을 개척하는 엔진으로 자리잡고 있다. 그런데 웹2.0을 기술적으로(descriptive) 소개하거나 관련된 요소기술에 대한 문헌은 많음에도 불구하고, 이러한 현상을 경영/경제학적 시각에서 체계적으로 분석한 연구는 의외로 많지 않다. 본 논문에서는 기존의 웹(웹1.0)과 웹2.0 서비스 모형을 경영 경제학적 관점에서 구조화하고, 이들 서비스 모형을 Stakelberg 게임의 관점에서 분석한다. 특히 본 연구에서는 웹2.0의 다양한 국면 중에서 프로슈밍(prosuming)에 초점을 맞춘다. 분석 결과, 웹2.0에서 사용자 후생이 웹1.0에 비해 크게 증가한다는 것을 확인할 수 있었다. 또한 사용자 스스로 맞춤화된 정보를 창출하는 노력과 한계편익간의 비율을 나타내는 ${\delta}_c$('고객화 요소'로 부름) 분포의 범위(파라미터 ${\delta}$)가 사회후생에 중요한 역할을 함을 발견하였다. 이는 고객화 요구의 다양성이 커짐에 따라 사용자 후생을 비롯한 사회후생도 증진됨을 의미한다.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.127-142
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• 2006

As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative, coordinating, and information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. The purpose of this paper is to propose an ontology-based product family modeling framework. The ideas of product family, ontology and Semantic Web were investigated in depth. A Semantic Web is originally defined as a web of data that can be processed directly or indirectly by machines, which operates intelligently. A Web Ontology Language (OWL) is designed for use by applications that need to process the content of information instead of just presenting information to humans. For the selected cellular phone product family, ontology was constructed and implemented using prot$\acute{e}$g$\acute{e}$-2000.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.311-317
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• 2016

In a smart commerce market, customers are seeking customized shopping services optimized for personal tastes and customized shopping experiences based on customers' tastes. Accordingly, individually customized services are needed more than anytime now. According to this demand, companies provide messaging services to the consumer, but do not include a personalized service for each individual. The purpose of this study is to combine the techniques of personalized services with messaging services and presents system construction plan and integrated model system for corporate messaging services and thereby possible are maximizing marketing effects and analyzing effects of cost savings. Applying the operation of the integrated model is proposed and message transmission scheme through effective personalization can be applied to personalized model using the personalized information according to customers' requirements. The integrated model of personalization on this study is expected to be highly effective when combined with the search service.

• Journal of Engineering Education Research
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• v.9 no.3
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• pp.49-61
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• 2006

The objective of this study was to propose a new framework for the creative engineering in the product family design coursework. The idea of product family design is a good solution to fulfill customer's requirements and to respond quickly for the technology change. Mass customization based on product family and product platform is a new paradigm with variety and customization through flexibility and quick responsiveness. In this study, the subjects of product family, product platform, product family map, platform leveraging strategy, morphological matrix and module based product family design were reviewed and presented. A new idea generation scheme utilizing SCAMPER method was combined with the morphological matrix approach. For the effective product family and platform design, creative efforts and approaches were utilized and implemented in the coursework process. This will help students to develop creative thinking and approaches in the engineering problem solving.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.555-557
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• 2019

본 논문은 고객 가치를 극대화한 솔루션 전용화를 통해 전략시장을 집중 공략하고, 제품 진입 영역 확대 및 고부가가치 시장 창출을 주도한 LS산전의 Application 전용 저압 드라이브 개발 현황에 관한 것이다. 다양한 지역별 & Application별 목표 시장 공략을 위해 대응한 사례인 북미 오일 Pump Jack, 북미 향 Hoist, 인도 직물 공장, 중동 엘리베이터, 국내 PVC 장판 생산용 Winder 시장 등의 분야에서 전용화 한 사례들에 대한 전반적인 내용을 설명한다. 이와 같은 글로벌 Application 분야를 발굴하여 신 성장 동력을 창출하고, 고부가 가치를 고객별로 맞춤형 최적 Solution 적용하여 LS산전의 드라이브 시장에서 경쟁력과 시장 점유율을 증대하고자 한 사항을 확인 해 볼 수 있다.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.113-134
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• 2003

With SDI service provided in libraries and information centers traditionally, this paper studies component technologies and structure of system platform in PIS(personalization information service based on the customized information service served currently in some institutions. The PIS system should provide relevant information as an output through the learning system analyzing user information searching behavior as an input value with personal profile information. To do it, this paper studies requirements and algorithms to develop PIS, and proposes learning system and recommendation system as core components in PIS.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.6
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• pp.949-957
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• 2009

The fashion apparel industries have demanded to be extremely consumer-oriented. Therefore, the need of personalization arises. The purpose of this study is to investigate the relationship between apparel shopping orientation and various personalization strategies provided in the apparel shopping process. A total of 422 questionnaires were used for statistical analysis. Canonical correlation and ANOVA were conducted. Results indicated that higher level of demand for "sale-promotion personalization" and "personalized customer relationship" were significantly related to high level of fashion innovativeness and price consciousness. Consumers who seek for high level of "personalized advice" and "personalized fit" were likely to be price conscious and conforming to clothing but not innovative in terms of fashion and clothing. Shopping orientation group differences were also reported in the study. In personalizing of apparel products, distinctive but relevant strategies should be implemented according to the need of the consumers.