• Journal of Distribution Research
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• v.4 no.3
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• pp.1-22
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• 2000

Many foreign freight forwarders make inroads into domestic markets. Korean freight forwarders are not competitive on th domestic logistics area because of higher customer services by foreign freight forwarders in Korea. The purpose of this research is to analyze degree of satisfaction on customer services attributes of freight forwarders in Korea, and to strengthen the competitiveness of customer services by Korea freight forwarders in contrast to foreign investment freight forwarders in Korea. The results of the research could be summarized as follows.: When freight forwarders are selected, the most important customer service attributes have been ranked in order with 'the accuracy management of shipping order' , the reasonable offers of freight rate' and 'the quick arrangement of vessels' when freight forwarders are selected.

• Journal of Internet of Things and Convergence
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• v.7 no.1
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• pp.79-89
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• 2021

This study attempted to identify the information gap about Internet of Things (IoT) devices and services in the era of digital transformation. To this end, we analyzed differences in perception of predicting future issues about IoT devices and services, and analyzed differences in the need for digital technology and help in life according to perceptions and experience of using IoT devices and services. Also, the level of education and demand for education were analyzed. A survey was conducted from February 15th to March 7th, 2021 for residents in Gwangju Metropolitan City and Jeollanam-do, and 232 respondents responded. Analysis was performed using SPSS 21.0, and all statistical values were presented as average values. The results of the study are as follows. First, the future issues of the intelligent information society according to the recognition of the intelligent information society, the help of life provided by artificial intelligence devices and services, and the need for intelligent information technology were presented. Second, the difference in Life help provided by artificial intelligence according to the recognition and use experience of artificial intelligence devices was presented. Third, the difference in life help provided by artificial intelligence according to the recognition and use experience of artificial intelligence service was presented. Fourth, the difference in necessity according to artificial intelligence technology recognition and use experience was presented. Fifth, the educational level and educational demand of the intelligent information society were investigated and presented. Through the results of this study, a suggestion for resolving the information gap in the era of digital transformation was suggested.

• Information Systems Review
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• v.9 no.3
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• pp.99-132
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• 2007

As customer management rises by important issue in electronic commerce, virtue study about CRM have proceeded much. However, because existent researches were positive researches of most statistical base, There are some limitation that does not show dynamic change with CRM flow by flowing of time, and can not forecast propriety and future result about CRM strategy. Therefore, in order to overcome existent limitation on these CRM study, this study designed dynamic model which draws factors that compose CRM strategy of on-line shopping mall, and do based on technique in system dynamics so that can analyze dynamic change between these factors. Concretely, atomized customer focuses in the on-line shopping mall and does based on Permission marketing theory, and applied CRM of different level to atomized customers and know change of customer satisfaction measurement and discomfort degree accordingly. According to the result of Simulation practice, situation that achieve CRM strategy of different level by atomize customer more increase the customer satisfaction than situation that is not so. Dynamic pattern that presented in this study is expected that can verify validity about CRM achievement strategy of different level at each CRM point of contact & how Internet enterprise including on-line shopping mall is establishing CRM strategy reasonably.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.1-18
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• 2011

Context-aware computing aims to enable the on-line applications and services to be executed in a timely and automated manner. Many of such applications and services involve group-level interactions. For more smoothing communication within a community, specific group-level issues such as group dynamics must be considered. To do so, obtaining group-level contexts such as the role, conflict resolution and norms, are key ingredients to improve group performance. Since group context is not the same as a simple summation of individual context, as group is not just a simple set of individuals, awaring individual context is not sufficient for group-level communication support. However, context-aware computing research still has stressed more on individual context. This leads us to the motivation of searching for group context aware method. Hence, the of this paper is to propose a novel methodology which automatically recognizes group context. Especially, we focus on group conhesiveness in this paper just because group cohosiveness is one of the important variables to control the performance of group interaction. To verify the applicability of the proposed method, an empirical test has been conducted to compare the performance of the proposed methodology with that of conventional methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.987-993
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• 2002

최근 들어 전자상거래의 급속한 발달로 전 세계적으로 수송 물동량이 급격히 증대되고 있고, 이로 인해 택배사업이 대단히 활성화되고 있다. 출발지와 목적지가 서로 상이한 무수히 만은 수송 요구가 들어오면 수송 요구화물의 신속한 집배송을 위한 배차계획 및 수송계획을 세우는 것이 택배회사의 주요 업무이다. 이러한 배차 계획 및 수송 계획을 어떻게 수립하느냐에 따라 전체 수송비용뿐만 아니라 고객들의 서비스 수준에 상당한 영향을 미치게 된다. 그러나 이러한 운영적 차원에서의 의사결정 이전에 훨씬 중요하게 고려해야 할 내용이 택배네트워크의 설계 문제이다. 이러한 택배네트워크의 설계에는 터미널 개수 및 위치를 결정하는 전략적 문제와 영업소들을 터미널에 할당하는 전술적 문제로 구분될 수 있다. 현재 우리 국내에는 크고 작은 수많은 택배사업자들이 있으나, 그 중에서 비교적 규모가 큰 주요 택배회사들은 대부분 전국에 걸쳐 다수의 터미널을 설치하여 두고 수송화물의 집배송을 위한 물류거점으로 운영하고 있다. 이와 같은 터미널 위치 및 개수가 정해진 상태에서 전국에 걸쳐 분포되어 있는 영업소들을 어떤 터미널에 할당하여 처리되도록 하느냐의 여부는 수송비용 측면에서뿐만 아니라 고객들에 대한 서비스 측면에서 대단히 중요한 의사결정 중의 하나이다. 본 연구에서는 비용과 시간을 고려하여 전국에 걸쳐 분포되어 있는 영업소들을 어떤 터미널에 할당해야 하는지를 결정하기 위한 수리적 모형을 제시하고, 이에 대한 탐색적 해법을 제시하며, 국내의 택배회사 사례를 대상으로 모형을 적용해 보고자 한다.무가 많이 발생하는 유통 분야의 프랜차이즈 산업을 대상으로 기업정보시스템 구현 및 경쟁력 강화를 뒷받침하기 위해서, 기업간 프로세스 협업(collaboration) 부분의 데이터 및 서식, 이를 취급하는 기능과 프로세스에 대란 분석을 통해 업무 프로세스 모델링 방법론과 관련한 모델링 지침 및 메타모델을 이용한 표준 업무 프로세스 모델을 개발하여 기업간 업무 프로세스 표준화에 대한 체계적인 관리에 대한 방안을 연구하고자 한다.의Bullwhip effect를 감소시킬 수 있는 장점이 있다. 동시에 이것은 향후 e-Business 시스템 구축을 위한 기본 인프라 역할을 수행할 수 있게 된다. 많았고 년도에 따른 변화는 보이지 않았다. 스키손상의 발생빈도는 초기에 비하여 점차 감소하는 경향을 보였으며, 손상의 특성도 부위별, 연령별로 다양한 변화를 나타내었다.해가능성을 가진 균이 상당수 검출되므로 원료의 수송, 김치의 제조 및 유통과정에서 병원균에 대한 오염방지에 유의하여야 할 것이다. 확인할 수 있었다. 이상의 결과에 의하면 고농도의 유기물이 함유된 음식물쓰레기는 Hybrid Anaerobic Reactor (HAR)를 이용하여 HRT 30일 정도에서 충분히 직접 혐기성처리가 가능하며, 이때 발생된 $CH_{4}$를 회수하여 이용하면 대체에너지원으로 활용 가치가 높은 것으로 판단된다./207), $99.2\%$(238/240), $98.5\%$(133/135) 및 $100\%$ (313)였다. 각

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.