• CRM연구
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• 제1권1호
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• pp.49-69
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• 2006

기존의 초기 기술 수용 모델(TAM)과 후기 기술 수용 모델(PAM)을 사용한 연구에서는 설문 조사를 통해 어느 한 시점의 상황만을 분석할 수 있어 제품 수명 주기에 따른 수요의 변화를 시계열적으로 나타낼 수 없는 한계점이 있었다. 이러한 문제를 해결하고자 본 연구에서는 시스템 다이내믹스 방법론을 활용하여 TAM과 TAM2에 대한 시뮬레이션 모델을 구축하여 개선 방안을 알아보고, 기존의 연구를 바탕으로 초기 수용부터 재구매에 이르는 수요의 변화를 시간의 흐름에 따라 동태적으로 분석하는 시뮬레이션 모델을 수립하였다. 특히 본 모델은 현재 국내의 실제 휴대 전화 시장을 고려하여 설계되었는데, 본 모델을 이용한 시뮬레이션 결과, 현재 우리나라의 휴대 전화 확산 패턴과 유사하게 나옴으로써 본 모델의 타당성을 확인할 수 있었다. 본 시뮬레이션 모델은 시간에 따른 소비자의 제품 수요 변화를 시각적인 그래프 형태로 제공하기 때문에 시장 상황에 따른 수요 변화에 대한 탁월한 학습 도구의 역할을 수행할 수 있으며, 따라서 IT 기업들의 시장 수요 예측 등에 활용될 수 있을 것으로 판단된다.

• 대한안전경영과학회지
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• 제10권4호
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• pp.189-198
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• 2008

At present, companies write daily work record or use bar-code in order to collect distribution flow data in real time. However, it needs additional works to check the record or read the bar-code with a scanner. In this case, human error could decrease accuracy of data and it would cause problems in reliability. To solve this problem, RFID (Radio Frequency Identification) is introduced in many automatic recognition sector recently. RFID is a technology that identification data is inserted into micro-mini IC chip and recognize, trace, and manage object, animal, or person using wireless frequency. This is being emerged as the core technology in future ubiquitous environment. This study is intended to suggest RFID application method in franchise business. Traceability and visibility of individual product are supplied based on EPCglobal network. It includes DW system which supplies various assessment data about product in supply chain, financial transaction system which is based on product transaction and position information, and RFID middleware which refines and divides product data from RFID tag. With the suggested application methods, individual product's profile data are supplied in real time and it would boost reliability to customer and make effective cooperation with existing operation systems (SCM, CRM, and e-Business) possible.

• Journal of Information Processing Systems
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• 제9권4호
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• pp.633-650
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• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

• 한국정보시스템학회지:정보시스템연구
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• 제22권3호
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• pp.25-42
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• 2013

Recently various kinds of Information Technology services are created and the quantities of the data flow are increase rapidly. Not only that, but the data patterns that we deal with also slowly becoming diversity. As a result, the demand of discover the meaningful knowledge/information through the various mining analysis such as linkage analysis, sequencing analysis, classification and prediction, has been steadily increasing. However, solving the business problems using data mining analysis does not always concerning, one of the major causes of these limitations is there are some analyzed data can't accurately reflect the real world phenomenon. For example, although the time gap of purchasing the two products is very short, by using the traditional sequencing analysis, the precedence relationship of the two products is clearly reflected. But in the real world, with the very short time interval, the precedence relationship of the two purchases might not be defined. What was worse, the sequence of the purchase intention and the sequence of the purchase realization of the two products might be mutually be reversed. Therefore, in this study, an expanded sequencing analysis methodology has been proposed in order to reflect this situation. In this proposed methodology, the purchases that being made in a very short time interval among the purchase order which might not important will be notice, and the analysis which included the original sequence and reversed sequence will be used to extend the analysis of the data. Also, to some extent a very short time interval can be defined as the time interval, so an experiment were carried out to determine the varying based on the time interval for the actual data.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.271-275
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• 2006

RFID(Radio Frequency Identification)기술은 초소형 IC 칩에 식별정보를 입력하고 무선주파수를 이용하여 사물, 동물, 사람 등을 인식, 추적, 관리할 수 있는 기술로서 미래 유비쿼터스 환경의 핵심 기술로 대두되고 있다. 본 연구에서는 를 기반으로 한 개별상품의 라이프사이클을 효율적으로 관리하기 위한 통합시스템 설계를 제안한다. 제안되는 통합 시스템은 개별상품의 라이프사이클(제조/물류/유통) 단계에서의 상품 Traceability와 Visibility를 제공하는 EPCglobal 네트워크 기반의 물류(유통), 금융 정보 통합 시스템으로서, 상품 정보 및 이력 데이터를 실시간으로 제공함으로써 Digital Manufacturing과 RTE(Real Time Enterprise)의 인프라를 제공하고, 기존 레거시 시스템(ERP, CRM, SCM)과의 효과적인 정보공유를 가능하게 할 것이다.

• Asia pacific journal of information systems
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• 제16권4호
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• pp.239-254
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• 2006

Location-based advertising or application has been one of the drivers of third-generation mobile operators' marketing efforts in the past few years. As a result, many studies on location-based marketing or advertising have been proposed for recent several years. However, these approaches have two common shortcomings. First. most of them just suggested the theoretical architectures, which were too abstract to apply it to the real-world cases. Second, many of these approaches only consider service provider (seller) rather than customers (buyers). Thus, the prior approaches fit to the automated sales or advertising rather than the implementation of CRM. To mitigate these limitations, this study presents a novel advertisement recommendation model for mobile users. We call our model MAR-CF (Mobile Advertisement Recommender using Collaborative Filtering). Our proposed model is based on traditional CF algorithm, but we adopt the multi-dimensional personalization model to conventional CF for enabling location-based advertising for mobile users. Thus, MAR-CF is designed to make recommendation results for mobile users by considering location, time, and needs type. To validate the usefulness of our recommendation model. we collect the real-world data for mobile advertisements, and perform an empirical validation. Experimental results show that MAR-CF generates more accurate prediction results than other comparative models.

• 한국항해항만학회지
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• 제35권5호
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• pp.387-392
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• 2011

태양광발전은 독립전원으로써의 가치는 미미하나 도시전체의 탄소발생량 저감 및 화석연료 사용 저감을 위한 분산전원으로써 가치가 매우 높은 전력원이다. 하지만 태양광발전의 경우 기상조건에 따른 발전량 변동이 심하기에 분산전원으로써 효율적으로 사용하기 위해서는 큰 변동폭을 효과적으로 제어하기 위한 실시간 모니터링이 이루어져야 한다. 하지만 태양광발전량을 좌우하는 일사량은 예측치가 존재하지 않기에 이를 예측해야 하고 본 연구에서는 과거의 일사량을 직산분리 하여 구름의 짙은 정도나 두께 등을 유추할 수 있는 대기투과율을 일기예보에서 발표하는 날씨별로 대푯값을 산정하고 이를 일사량 예측식에 대입하여 일사량을 예측하였다. 그리고 실측 일사량 및 CRM(Cloud Cover Radiation Model)기법인 Kasten and Czeplak의 식을 통해 계산된 예측일사량과의 비교를 통해 검증하였다.

• Bulletin of the Korean Chemical Society
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• 제28권8호
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• pp.1375-1382
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• 2007

A column preconcentration method with pulverized Amberlite XAD-4 loaded with bismuthiol I (BI) has been developed for the determination of trace Cd(II) and Cu(II) in various real samples by flame atomic absorption spectrophotometry. Various experimental conditions, such as the size of XAD-4, adsorption flow rate, amount of bismuthiol I, stirring time for adsorbing bismuthiol I on XAD-4, pH of sample solution, amount of XAD-4- BI, desorption solvent, and desorption flow rate, were optimized. Also, the adsorption capacity and the adsorption rate of Cd(II) and Cu(II) on XAD-4-BI were investigated. The interfering effects of various concomitant ions were investigated, Bi(III), Sn(II) and Fe(III) were found to affect the determination. But the interference by these ions was completely eliminated by adjusting the amount of XAD-4-BI resin to 0.70 g, although the adsorption flow rate was slower. For Cd(II) our proposed technique obtained a dynamic range of 0.5-40 ng mL-1, a correlation coefficient (R2) of 0.9913, and a detection limit of 0.3 ng mL-1. For Cu(II), the corresponding values were 2.0-120 ng mL-1, 0.9921 and 1.02 ng mL-1. To validate this proposed technique, the aqueous samples (stream water, reservoir water, tap water and wastewater), the diluted brass sample and the plastic sample, as real samples, were used. Recovery yields of 91-103% were obtained. These measured data were not different from ICP-MS data at 95% confidence level. Our proposed method was also validated using rice flour CRM (normal, fortified) samples. From the results of our experiment, we found that the technique we present here can be applied to the determination of Cd(II) and Cu(II) in various real samples.

• 한국콘텐츠학회논문지
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• 제7권11호
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• pp.59-68
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• 2007

최근 서비스 산업이 발전하면서 고객들이 보다 편하게 택시를 사용하기 위해 콜택시 서비스를 일반적으로 사용하고 있지만, 기업 입장에서 콜 센터를 구축하기 위해서는 막대한 비용이 소비된다. 본 논문은 기존에 사용되는 단말기 방식의 콜 시스템이 아닌 핸드폰을 사용해 콜 센터 구축에 소비되는 비용을 최소화했다. 그리고 CTI(Computer Telephony Integration)를 이용해 택시 콜 센터의 고객관리, 업소관리, 기사관리, 주문관리, 정산관리 등의 업무를 보다 효율적으로 통합 관리 할 수 있는 시스템을 UML(Unified Modeling Language)을 적용해 설계 및 구축했다. CTI를 보다 효과적으로 구현하기 위한 장치로써 현재 상용화 되어 있는 CID(Caller Identify Display)를 이용해 고객의 발신 번호를 PC에서 받아 실시간으로 고객의 정보를 Database에서 검색했다. 이 시스템은 저렴한 비용으로 구축이 가능하고, 효율적인 고객관리 기능으로 고객 서비스를 개선할 수 있다.