• Journal of Korean Library and Information Science Society
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• v.38 no.3
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• pp.277-296
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• 2007

This study aims to propose that archives introduce marketing strategies for their archival reference services. Target marketing which is based on market segmentation for customer satisfaction is popular among enterprises in these days. Market segmentation strategy of target marketing need to be used for user centered archival reference services in archives. This study proposed that demographic, geographic, psychographics, and use variables can be used for archival user segmentation. And for the user segmentation, archives should collect data of use and users systematically.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.97-106
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• 2015

In recent, hybrid market segmentation techniques have been widely adopted, which conduct segmentation using both general variables and transaction based variables. However, the limitation of the techniques is to generate incorrect results for market segmentation even though its methodology and concept are easy to apply. In this paper, we propose a novel scheme to overcome this limitation of the hybrid techniques and to take an advantage of product information obtained by customer's transaction data. In this scheme, we first divide a whole market into several unit segments based on the general variables and then agglomerate the unit segments with higher QAP correlations. Each product network represents for purchasing patterns of its corresponding segment, thus, comparisons of QAP correlation between product networks of each segment can be a good measure to compare similarities between each segment. A case study has been conducted to validate the proposed scheme. The results show that our scheme effectively works for Internet shopping malls.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.23-38
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• 2007

Corporations adopt a segmentation depends on the existence of target variables, in general. In this paper, for the case of no target variables, a strategy through segmentation is proposed for corporations having a special status based on the management index. In case of segmentation using cluster analysis, however, if one classify according to many variables then he will be in face of difficulties in characterizing. Therefore, after extracting representative factors by factor analysis, a segmentation method through 2 step cluster analysis is employed on the basis of these representative factors. As a result, six segmentation groups are found and the resulting strategy is proposed which strengthens prominent factors and makes up defective factors for each group.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.37-44
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• 2006

본 연구는 모바일기기 사용자들의 특성을 알아보고자 사용자들의 모바일기기 휴대의도에 영향을 미치는 변수들을 기준으로 사용자들을 세분화 하였다. 선행문헌연구를 통해 휴대의도에 영향을 미치는 변수들로 유용성, 즐거움, 불안감과 사회적 영향인 주관적 규범, 가시성, 이미지, 자발성 등을 도출하였다. 자료수집을 위해 서울 및 수도권에 거주하고 휴대폰이나 노트북, PDA등을 소유한 대학생 및 대학원생과 직장인들을 대상으로 설문조사를 실시하였다. 휴대의도의 영향변수 분석결과 불안감과 주관적 규범이 휴대의도에 유의한 양의 영향을 미치는 것으로 검증되었다. 이를 기준변수로 군집분석을 통해 전체 표본을 네 집단으로 세분화 하였다. 세분화 결과 군집 1은 주관적 규범만이 영향을 미치는 집단으로 전체응답의 36.25%를 차지하고 있으며, 군집 2는 불안감만이 영향을 미치는 집단으로 전체 응답의 13.44%를 구성하는 것으로 나타났다. 군집 3은 불안감과 주관적 규범 모두 영향을 미치지 않는 집단으로서 전체 응답에서 19.06%를 차지하고 마지막으로 군집 4는 불안감과 주관적 규범 모두 영향을 미치는 집단으로 전체응답의 31.25%를 구성하는 것으로 나타났다.

• Journal of Distribution Research
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• v.10 no.3
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• pp.87-101
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• 2005

Market segmentation has been an important issue in marketing for a long time. Many models and statistical methods have been developed by many scholars. The purpose of this research provides one insight for market segmentation based on clustering technique in channel benefit sought. We proposed a sequential approach in market segmentation. A sequential approach means that we do market segmentation by multi-stage method based on the benefits sought in marketing channel. To achieve this approach, we divided the main benefits sought into subcategories. That is to say, after dividing each benefit sought into more detailed concepts, we did market segmentation sequentially.

• The KIPS Transactions:PartA
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• v.18A no.3
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• pp.115-122
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• 2011

It is very hard to obtain a general algorithm for solution of all the constraint satisfaction optimization problems. However, if the whole problem is separated into subproblems by characteristics of decision variables, we can assume that an algorithm to obtain solutions of these subproblems is easier. Under the assumption, we propose a problem classifying rule which subdivide the whole problem, and develop backtracking algorithms fit for these subproblems. One of the methods of finding a quick solution is efficiently arrange for any order of the search tree nodes. We choose the cluster head positioning problem in wireless sensor networks in which static characteristics is dominant and interference minimization problem of RFID readers that has hybrid mixture of static and dynamic characteristics. For these problems, we develop optimal variable ordering algorithms, and compare with the conventional methods. As a result of classifying the problem into subproblems, we can realize a backtracking framework for systematic search. We also have shown that developed backtracking algorithms have good performance in their quality.

• Korean Business Review
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• v.14
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• pp.129-148
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• 2001

The purpose of this study is to survey the LOV(List Of Values) composed with the consumer's psychographic variables and is to segment consumer's value system through the LOV. Referring to the previous studies such as Rokeach's RVS, Kahke's LOV, Razzaque's Asian values, and author's Korean values, this study conducted researches of consumer's value segmentation. The result of this study finds that the Korean consumer's value system is categorized into (1) value of influence, (2) value of mammonism, (3) value of latest, (4) value of venture, (5) value of salvation, (6) value of sociality, (7) value of curiosity, (8) spirituality, and (9) value of conservativeness in order. This results will help contribute toward segmentation of Korean consumer's value. Another result of this study shows by way of ANOVA(analysis of variance) that the Korean consumer's value dimensions are closely related to demographic variables: sex, marital status, education, occupation, total families income by monthly, family structure, and age.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.90-93
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• 1998

입？출력 데이터 쌍만을 이용하여 규칙 및 소속 함수를 자동적으로 결정하는 자기 학습 퍼지 알고리즘 중에서, 가장 이해하기 용이하고 퍼지 규칙 및 소속 함수 생성이 빠른 방법으로 기울기 강하를 이용한 방법들이 있다. 기울기 강하를 이용한 방법중에서 가장 대표적인 Araki가 제안한 방법은 퍼지 조건부가 퍼지 집합 형태이고 결론부는 단일값으로 구성된 알고리즘으로써 입력 퍼지 공간을 세분화하면서 시스템을 규명해나가는 간단하면서도 효율적인 알고리즘이다. 그러나 이 방법은 퍼지 입력 변수가 증가하면 퍼지 공간이 세분화 되면서 소속 함수 및 규칙 생성 개수가 급격히 제곱배로 증가하는 문제점을 가지고 있다. 따라서, 본 논문에서는 퍼지 입력 변수가 증가함에 따라 급격히 퍼지 규칙 및 소속 함수의 수가 증가하는 Araki 알고리즘의 문제점을 분석하여 소속 함수 및 규칙 수의 급격한 증가를 억제하고 Araki 방법에 비해 학습속도가 현저히 향상된 새로운 방안을 제안한다. 연구 결과, Arki 방법이 입력 변수의 개수가 증가 할수록 규칙 수가 기하 급수적으로 많이 필요하였던 것에 비해 제안한 방법은 훨씬 적은 규칙 수로 우수한 성능을 얻을 \ulcorner 있었다.

• The Journal of the Korea Contents Association
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• v.6 no.5
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• pp.131-144
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• 2006

This study tries to segment musical market to provide Korean musical marketers with marketing strategy implication. We focused university students who are known to form attractive market in the musical market through existing studies. For this research, we divided whole musical market using various variables such as musical audience' demographic, lifestyle and purchasing behavior variables. Using mixture model, we could divided as four significant segments : 'the type of musical mania', 'the type of musical preference', 'the type of musical medium' and the type of indifferent musical'. Each segment showed different musical purchase behaviors, lifestyle and demographical characteristics, also we suggested marketing strategy to each segment. Our research results can contribute to understand objectively musical market.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.203-206
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• 2000

신경망을 이용해 고객집단을 분류하고 고객의 특성에 따라 세분화된 고객들에 대해 다단계 연관규칙을 적용해서 고객의 상품 구매패턴을 찾아 줌으로써 마케팅 전략 결정을 지원하는 구매패턴분류 시스템을 설계한다. 고객분류를 위한 신경망 시스템은 다층 퍼셉트론에 역전파 알고리즘을 이용한다. 주소, 구매금액, 구매횟수, 고객 구분, 상긴 등과 같은 고객정보를 입력층에 입력변수로 지정하고, 이에 따른 우량/일반고객을 출력변수로 지정한 후 신경망을 학습시키면, 실제의 우량/일반의 간과 예측되는 우량/일반의 값의 차이론 최소화시키면서 모형을 형성시켜 나가게 된다. 구매패턴 분류 시스템은 다단계 연관규칙을 이용한다. 고객분류 서브시스템을 통해 고객집단이 세분화되면 각각의 고객집단에 대해 TID와 품목 트랜잭션을 입력으로 cumulate 알고리즘과 개념계층을 이용해 일반화 과정을 수행하면서 빈발 항목을 찾게 되고 이론 근거로 항목간의 연관규칙을 찾아내게 된다.