• Asia Marketing Journal
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• v.13 no.4
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• pp.213-226
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• 2012

As the Korean rental car industry turned into a mature stage, the competition level has become stronger than ever. In 2006, AJ Rent a Car declared customer satisfaction management as its vision to make a breakthrough. Through various service innovation efforts, AJ has been successfully offering meaningful and differentiated values to the customers. As results, the complaints rate has decreased, while service quality index has significantly increased. These service quality indicators have led to improved customer satisfaction level which was measured by re-purchase intention and customer satisfaction index, and AJ outran its major competitors in these dimensions of competition. The first key success factor of AJ is its effective service system. AJ manages the VOC, ERP, and CRM system in a well organized manner. AJ's another key success factor is a effective service process, which helps the organization share and respond to customer complaints in an efficient way. Finally, the management communicates the clear vision and strategic direction not only with the customers but also with the entire organization. With these three factors combined, AJ has created the service oriented corporate culture. Based on the culture. AJ has been able to develop a strong and sustainable competitive advantage in customer satisfaction management.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.313-322
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• 2009

Recently, According to computer technology has been improving, Massive customer data has stored in database. Using this massive data, decision maker can extract the useful information to make a valuable plan with data mining. Data mining offers service providers great opportunities to get closer to customer. Data mining doesn't always require the latest technology, but it does require a magic eye that looks beyond the obvious to find and use the hidden knowledge to drive marketing strategies Automotive market face an explosion of data arising from customer but a rate of increasing customer is getting lower. therefore, we need to determine which customer are profitable clients whom you wish to hold. This paper builds model of customer loyalty detection and analyzes customer patterns in automotive market with data mining using association rule and basic statics methods. With 4he help of information technology.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.2 s.150
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• pp.221-232
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• 2006

The purposes of this paper were to identity the present condition of the imported fashion luxury brands' market arid to analyze the differences of marketing strategies according to the types of retailers. We selected 3 department stores, 5 luxury brands, 5 stores in Dongdeamun Market, and 5 internet luxury shopping malls, and conducted key informant survey to 20 experts. The brands in department stores consisted the goods according to VIPs' pre-orders, sales of the previous year, and fashion trends, and offered the differentiated customer services to VIPs. The stores in Dongdaemun Market bought the products from the parallel importers or imported the goods from the original nations of the brands by themselves. The goods in stock and steady sellers were comprised of the main portion of all products, and leather goods were dominated. The price of goods in stock was about $30\∼50\%$ lower than the normal price of department stores, but the new products' price was only about 10$\%$ lower than that of department stores. Luxury shopping malls could be classified into two types; one conducted both product buying and commission sale, and the other conducted commission sale only. In former case, however, the product buying portion was under 30$\%$. Product assortments and the price strategy were similar to the stores of Dongdeamun Market, and CRM was conducted partially.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.85-91
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• 2018

Most banks use only demographic information such as gender, age, occupation and address to segment customers, but they do not reflect financial behavior patterns of customers. In this study, we aim to solve the problems by using various big data in a bank and to develop customer segmentation method which can be widely used in many banks in the future. In this paper, we propose an approach of segmenting clustering blocks with bottom-up method. This method has an advantage that it can accurately reflect various financial needs of customers based on various transaction patterns, channel contact patterns, and existing demographic information. Based on this, we will develop various marketing models such as product recommendation, financial need rating calculation, and customer churn-out prediction based on this, and we will adapt this models for the marketing strategy of NH Bank.

• International Commerce and Information Review
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• v.3 no.1
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• pp.139-155
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• 2001

The managing strategies of each enterprise has been fundamentally changed due to the emergence of digital economics by using the internet. Therefore it is indispensable for each enterprise to be changed their business strategies. With a view to meeting the change of new economic paradigm, they are efforting to build a infrastructure for information and communication, induce foreign capital, reconsider their conditions of location, draw the law concerned and reinforce education for experts etc. In consideration of these change, the KwangYang port have to introduce e-Business for the purpose of increasing the level of their competition. We - our government, the companies - concerned with port management should recognize and use efficiently our core competence and potentiality of our port management. To achieve it, firstly port industries are to handle not only international logistic system but also communication, finance and sightseeing. Secondly, the developed off-line system have to be harmonizing with the on-line. Therefore, this paper are focused to suggest the theoretic background by analyzing the strategic points of e-port which are divided in 6C - Contents, Community, Connection, Commerce, Communication and Customization.

• Journal of Distribution Research
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• v.9 no.2
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• pp.29-43
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• 2004

This research analyzed multi-channel strategy from the viewpoint of the customer relationship management. We hypothesized that the purchase frequency, monetary, purchase quantity of the existing customers should have increased after they used multiple channels of a company for shopping, All the hypothesis were supported in an empirical test using the customer database of a Korean TV home-shopping company, The result showed that the multi-channel strategy can be used to increase the life-time value of existing customers. Still there were a lot of customers who insists using traditional channel, which calls for a new strategy inducing them to use multi- channel for shopping.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.209-212
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• 2011

디지털 혁명이라는 모바일 시대로의 진입과 더불어 디지털마케팅의 다양한 형태로의 발전은 매우 빠른 속도로 진행 되고 있다. 기존의 TV, 신문, 잡지 등의 전통적인 마케팅 방식에서 소셜 마케팅, 서치엔진 마케팅, PPC 관리, 인터넷 브랜딩, 웹 프로모션 등의 다양한 형태가 모바일 기반 기술로 연구발전 되고 있다. 각각의 디지털마케팅 방식은 기업의 기간 정보 시스템과는 별도의 운영이 필요한 경우가 많다. 이로 인해 새로운 디지털마케팅 시스템과 여기에서 산출되는 결과 데이터 등은 기존 기업의 기간 정보시스템인 ERP, CRM, BI 등의 레거시 시스템과의 효율적인 연계의 어려움이 있다. 따라서 기업은 디지털 혁명의 모바일 시대의 디지털마케팅을 적용하기 위해 각각의 디지털마케팅 형태에 따라 별도의 시스템 및 조직운영을 고려가 필요하다. 이로 인해 기업은 각각의 시스템의 운영 및 이 기종 시스템간의 연결 구현을 위해 시스템 운영, 관리 조직 및 시스템 인터페이스에 대한 중복 투자가 불가피한 실정이다. 따라서 본 논문에서는 디지털마케팅에 사용되는 시스템과 기업의 기간 정보시스템과의 효율적 연계를 위한 융합형 디지털 마켓팅 플랫폼의 연계 방안을 연구하고 제안한다. 융합형 디지털 마켓팅 플랫폼은 이종시스템간의 인터페이스뿐만 아니라 운영에 필요한 새로운 관리 조직 형태의 제안 또한 포함 된다. 다양한 디지털마케팅의 발전에 따른 기존 기업의 기간 정보 시스템과의 연계 인터페이스를 위한 새로운 플랫폼이 필요하며, 이를 통해 디지털마케팅을 기존의 레거시 시스템과의 효율적인 연계 방법으로 구현하여 기업의 새로운 디지털 마케팅 환경으로의 패러다임 변화에 대처할 수 있는 방법을 확인 할 수 있을 것이다.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.505-521
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• 2021

This study analyzed the effects of consumer confusion on shopping fatigue and negative purchasing behaviors in an internet shopping environment. Further, the effects of shopping fatigue on negative purchasing behaviors were analyzed. The survey was conducted among consumers in their 20s and 40s in the Seoul metropolitan area who had experience of purchasing fashion products through internet shopping. A total of 392 questionnaire were analysis, with frequency, reliability, factor, correlation, and regression analysis completed using the SPSS statistics program. The results of the study showed that consumer confusion and shopping fatigue in internet shopping environment affected negative purchasing behaviors. First, consumer confusion comprised overload confusion, similarity confusion, and ambiguity confusion. It was found that overload confusion and similarity confusion significantly affected shopping fatigue. Second, shopping fatigue significantly affected negative purchasing behaviors, and an increased level of shopping fatigue result in, increased purchase delay and non-purchase behavior. Third, consumer confusion (overload confusion, similarity confusion, ambiguity confusion) significantly affected purchase delay behavior, while similarity confusion and ambiguity confusion significantly affected non-purchasing behavior. These results will provide useful data for e-CRM and marketing directions of internet companies and will contribute to rational decision-making of internet consumers and improve the quality of consumer life.