• Journal of Information Management
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• v.35 no.1
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• pp.51-69
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• 2004

Libraries have been made effect to satisfy customer by reflecting information need of customer on libraries. They have considered introducing the data mining techniques to analyze complicated and massive data of libraries and the Customer Relationship Management(CRM) to produce suitable services to each customer segmentation. The purpose of this study is to apply the CRM and data mining techniques to a library, ultimately intends to suggest rules for the collection management and the customer management.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.387-390
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• 2021

최근 전자 상거래 시장이 급격한 성장을 이루면서 고객들의 급변하는 니즈를 파악하는 것이 기업들의 수익에 직결되는 요소로 인식되고 있다. 이에 기업들은 고객들의 니즈를 신속하고 정확하게 파악하기 위해, 기축적된 고객 관련 각종 데이터를 활용하려는 시도를 강화하고 있다. 기존 시도들은 주로 구매 행동 예측에 중점을 두었으나 고객 행동의 전후 과정을 해석하는데 있어 어려움이 존재했다. 본 연구에서는 고객이 구매한 상품을 확정 또는 환불하는 행동을 취할 때 해당 행동이 발생하는데 있어 어떤 요소들이 작용하였는지를 파악하고, 어떤 고객이 환불할 지를 예측하는 예측 모형을 새롭게 제시한다. 예측 모형 구현에는 트리 기반 앙상블 방법을 사용해 예측력을 높인 XGBoost 기법을 적용하였으며, 고객 의도에 영향을 미치는 요소들을 파악하기 위하여 대표적인 설명가능한 인공지능(XAI) 기법 중 하나인 SHAP 기법을 적용하였다. 이를 통해 특정 고객 행동에 대한 각 요인들의 전반적인 영향 뿐만 아니라, 각 개별 고객에 대해서도 어떤 요소가 환불결정에 영향을 미쳤는지 파악할 수 있었다. 이를 통해 기업은 고객 개개인의 의사 결정에 영향을 미치는 요소를 파악하여 개인화 마케팅에 사용할 수 있을 것으로 기대된다.

• Cement
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• s.193
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• pp.24-27
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• 2012

시대가 디지털화 되어감에 따라서 아날로그에 대한 고객들의 향수는 더욱 증가하고 있다. 아날로그 제품은 차별적인 가치를 추구하는 고객들을 대상으로 프리미엄화에 성공하고 있다. 고객 가치 발굴 프로세스 안에서 최근 디지털의 트렌드 뿐 아니라 아날로그 시절의 감성을 결합해 본다면 고객들에게 더 의미 있는 가치를 발굴할 수 있을 것이다.

• Management & Information Systems Review
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• v.29 no.1
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• pp.145-176
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• 2010

In most service organization, salespeople are the most visible representatives of the company. Salespeople are exposed to greater ethical pressures than individuals in many other jobs. In this context, the salesperson's ethical behaviour can play a critical role in the formation and maintenance of long-term buyer-seller relationships. Moreover, it can even generate liability problems for salespeople's organizations through both intentional and inadvertent statements. The purpose of this research focuses on the analysis of the role of ethical sales behaviour, as perceived by customer, in developing and maintaining relationship between the salesperson and the customer. Thus this study examines the relationship among perceived ethical sales behaviour, customer satisfaction, customer trust, and customer loyalty. The results of empirical analysis can be summarized by the following: First, perceived ethical sales behaviour had a significant direct effect on customer satisfaction, customer trust and customer loyalty. Second, customer satisfaction had a positive effect customer trust and customer loyalty. Third, perceived ethical sales behaviour had a significant indirect effect on customer loyalty through customer satisfaction and customer trust. Therefore, These finding will spawn both academic and practitioner interest in the salesperson's ethical sales behaviour and serve as a foundation for further research in this important area.

• Journal of Distribution Research
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• v.12 no.4
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• pp.79-108
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• 2007

In this study, we measured customers' perception of organization citizenship behaviors of employees which are known as the important factor for improving performance of companies, and examined the path relationship among related variables such as service quality, customer satisfaction, trust, and positive word of mouth. Although there have been many studies of OCB in the marketing field, the majority of these studies measured employee's OCB from the organization's perspective. This study has extended the prior studies by measuring employee's OCB from the customer's perspective. Customers of beauty salons and public houses were researched such that OCB may be applied to more various customer contact situations. The result is as follows. First, employees's OCB had a direct effect on perceived service quality and trust, and had an indirect effect on customer satisfaction. It means that customers evaluate the service quality of employees and trust frontline employees when they observed employees helping other organizational members, orientated customer facilitation beyond the regulated role and showed positive attitudes for their organization. As a result, customers feel more satisfied. Secondly, OCB had an indirect effect on positive word of mouth through mediation of service quality, satisfaction, and trust. Finally, consumer facilitation had the largest effect on consumer attitude among three dimensions of OCB-consumer facilitation, organization involvement, and sportsmanship. We understood the relationship between frontline employee's OCB and customer attitudes, and the necessity of multidimensional approach in measuring employee's OCB from the customer's perspective.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.136-138
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• 2004

CRM은 기존 고객을 잘 관리하면서 새로운 고객을 유치하는 마케팅비용은 기존고객 유지비용의 몇 배라는 기본적인 원칙에 의한 접근이다. 물론, 데이터베이스 마케팅, 이메일 마케팅이 기존고객 유지의 수단이 될 수도 있다. 본 논문에서 개발한 신경망을 이용한 분석 eCRM 시스템의 컴포넌트를 설계 구현하였다. 이는 특성화된 컴포넌트 기반으로 개발되었으며, 기존 데이터 환경을 효율적으로 이용할 수 있는 모듈(module) 개발을 통하여 사용자들이 쉽게 이용할 수 있는 환경을 지원한다.

• Asia Marketing Journal
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• v.12 no.1
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• pp.1-30
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• 2010

Customers often experience waiting for buying service. Managing customers' waiting time is important for service providers since customers who are dissatisfied with waiting, secede from a service place at last. Not a few studies have been done to solve waiting time problem and improve customers' waiting experience. Hui & Tse(1996) identify evaluation factors in customers' behavioral mechanism as customers wait. That is, customers experience perceived waiting time, waiting acceptability and emotional response to the wait when they wait. Since customers evaluate the wait using these factors, service provider should manage these factors in order to minimize customers' dissatisfaction. Therefore, this study explores that evaluation factors of waiting are influenced by customers' situational and experiential characteristics, which include customer loyalty, transaction importance for customer and waiting expectation level. Those situational and experiential characteristics are usually given to service providers so they can't control these at waiting point. The major findings derived from two exploratory studies can be summarized as follows. First, according to the result from the study 1 (restaurant setting), customers' transaction importance has the greatest positive influence on waiting experience. The results show restaurant service provider could prevent customers' separation effectively through strategies which raise customers' transaction importance, like giving special coupons for important events. Second, in study 2 (amusement part setting) customer loyalty has large positive impact on waiting experience as well as transaction importance. This results show that service provider could minimize customers' dissatisfaction using strategies which raise customer loyalty continuously. This results show customer perceives waiting experience differently according to characteristics of service place and service itself. Therefore, service provider should grasp the unique customers' situational and experiential characters for each service and service place. It could provide an effective strategy for waiting time management. Third, the study finds transaction importance and waiting expectation level have direct influence customers' waiting experience as independent variables, while existing studies treated them as moderators. Customer loyalty which has not been incorporated in previous waiting time research is known to affect waiting experience. It suggests that marketing strategy which builds up customer loyalty for long period of time is also quite effective, compared to short term tactics to help customers endure waiting time. Fourth, this study reveals the importance of actual waiting time along with perceived waiting time. So far most studies only focus on customers' perceived waiting time. Especially, this study incorporates the concept of patient limit on waiting time to investigate effect of actual waiting time. The results show that there were various responses to the wait depending on how actual waiting time exceeds individual's patent limit on waiting time or not, even though customers wait about the same period of time. Finally, using structural equation model, conceptual path between behavioral responses is verified. As customer perceives waiting time, then she decides whether she can endure it or not, and then her emotional response occurs. This result are somewhat different from Hui & Tse(1996)'s study. The study also includes theoretical contributions as well as practical implications.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.597-602
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• 2007

본 연구는 추천시스템에서 협업필터링 알고리즘을 이용하여 특정 상품에 대한 고객의 선호도를 예측함에 있어 고객이 상품에 대해 평가한 선호도 평가치를 고객별로 표준화시켜 예측하여 기존의 예측 정확도를 향상시키는 방법에 대하여 연구하였다. 일반적으로 상품에 대한 고객의 선호도를 평가하기 위하여 절대적 기준의 수치적 척도가 제공되지만 개인에 따라서는 상품에 대한 선호 정도가 절대적 척도에 다르게 반영되어 개인별 선호도에 차이가 발생할 수 있다. 이러한 개인적 특성이 동일한 척도의 평가치로 예측되면 예측 결과의 오차를 크게 할 가능성이 있다. 또한 개인이 평가한 선호도 평가치의 편차가 협업필터링 알고리즘을 통한 선호도 예측 정확도와 밀접한 관계를 가지고 있음을 알 수 있었으며 이러한 문제를 해결하기 위하여 개별 고객이 평가한 선호도 평가치를 표준화시켜 표준화된 선호도 평가치를 이용한 선호도 예측을 실시하였다. 분석결과 표준화된 선호도 평가치를 이용한 예측 결과가 비표준화 선호도 평가치를 이용한 예측 결과보다 예측력이 우수함을 알 수 있었으며 결과에 대한 통계적 분석을 통하여 표준화된 선호도 평가치를 이용한 선호도 예측 방법과 비 표준화 선호도 평가치를 이용한 선호도 예측 방법을 혼합할 경우 선호도 예측 정확도를 더 향상시킬 수 있음을 알 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.784-786
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• 2002

정보통신 기술의 발달과 전자상거래의 도래로 기업가치의 중심이 점차 고객으로 이동함에 따라 고객 관련 정보의 체계적인 통합 관리를 위한 CRM(Customer Relationship Management)의 구축이 급속도로 진행되고 있다. 특히 고객과의 접점 채널을 중심으로 e-CRM(Electronic-Customer Relationship Management) m-CRM(Mobile-Customer Relationship Management)과 같은 다양한 방법론이 제기되고있지만 고객과의 접근 방식 자체를 세부적으로 분석하고 최소화할 수 있는 방법의 제안은 현실적으로 부족하다고 볼 수 있다. 따라서 본 논문에서는 고객 접점 방법을 간소화시킬 수 있는 방법으로e-CARM(Electronic-Customer Approach Relationship Management)을 제안하였다. 또한 인중 메커니즘을 통한 e-CARM의 모델을 제시함으로써 제안된 방법론이 가질 수 있는 유용성을 보여 주었다.

• Information Systems Review
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• v.12 no.2
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• pp.75-88
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• 2010

This paper proposed a method that segmented customers utilizing SOM(Self-organizing Map) and predicted the customers' response of a marketing promotion for each customer's segments. Our proposed method focused on predicting the response of customers dividing into customers' segment whereas most studies have predicted the response of customers all at once. We deployed logistic regression, neural networks, and support vector machines to predict customers' response that is a kind of dichotomous classification while the integrated approach was utilized to improve the performance of the prediction model. Sample data including 45 variables regarding demographic data about 600 customers, transaction data, and promotion activities were applied to the proposed method presenting classification matrix and the comparative analyses of each data mining techniques. We could draw some significant promotion strategies for segmented customers applying our proposed method to sample data.