• Information Systems Review
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• v.13 no.3
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• pp.123-139
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• 2011

This paper researches the value of domestic telecommunication bundle products. Customers evaluate each telecommunication products differently according to their attributes. The attributes affecting the customer value of telecommunication bundling can be categorized in 3 ones as follows; corporate image, service feature, and service price. Also authors analyze the difference of importancy that customers consider when they evaluate each products, and propose the optimal scenario for bundling. In conclusion, other two companies A, C excluding B should invest more resources into the portion that strengthen the attributes of company image, and service feature to upgrade their 'corporate image', and 'service feature'. According to 6-scenarios analysis on the bundle products, the QPS expansion of company A was the most advantageous position, but if companies B, C expand DPS made use of their strengths, they can prevent from decreasing additivity rapidly with sequential scenario. The above results show that one company may have equable power in each area, but if another company having strengths in special areas makes up for its weakness and differentiates gradually it can contribute to strengthen its competitiveness. This contributed much more theoretical and practical than the existing researches. Supposing that additivity index evaluated by consumers can be changed by efforts of companies, this scenario planning is the result of study showing that the investment and publicity of each company have to be considered as its characteristic of each product at the same time.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.890-901
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• 2008

This study explores an initial framework for online product categorization by examining the relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories. A total of 217 usable questionnaires were obtained from respondents in a southwestern state in the United States. A path model using a correlation matrix with maximum likelihood was estimated using LISREL 8.53. Findings indicated that Internet motivations consisted of four factors: Diversion, Economic, Information, and Social motivations. In addition, online products were classified into three categories based on purchase intentions: Sensory, Cognitive, and Search products. Estimated path model showed that diversion and economic motivations affected impulse buying tendency, whereas economic, information and social motivations influenced planned buying tendency in the online context. Also, the buying tendencies were significantly related to online purchase intentions for the product categories. Purchase intentions for sensory products were more strongly affected by impulse buying tendency, whereas purchase intentions for cognitive and search products were more strongly affected by planned buying tendency. Theoretical and managerial implications were discussed for devising an appropriate e-market strategy for specific product categories.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.53-59
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• 2014

The objectives of this research is to compare UX elements influencing the satisfaction of users in Korea and North America according to product types of mobile commerce services, to determine UX INDEX suitable for each type of service, and to derive positively influencing UI factors through analyzing the relationship between UX INDEX and UX design detail factors. This research showed that there was difference in perceived reliability according to selling product types and there was difference in both perceived usefulness and reliability according to users in Korea and North America. Also, this research found out that, in analysis of relationship between UX INDEX and UX design detail factors, UI factors to understand a service structure generally showed close relationship but factors such as troubleshooting and help showed difference between users in Korea and users in North America.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.608-613
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• 2006

There are many e-showing mall because of revitalization of e-commerce system. It is necessary to recommending system of products that is for saving time and effort of customer. In this paper, we propose the system that is applying classification among data mining techniques to analysis of log data of customer. This log data contains access of user and purchasing of products. The proposed system operates in two phases. The first phase is composed of data filter module and association extraction module among web pages. The second phase is composed of personalization module and rule generation module. Customer can easily know the recommended sites because the proposed system can present rank of the recommended web pages to customer. As a result, the proposed system can efficiently do recommending of products to customer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1414-1423
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• 2014

This paper aims to analyze destination composition patterns included in package products and to identify the characteristics of the tourism destinations through social network analysis using data collected from tour packages distributed by major Korean travel agencies, targeting Singapore as a key destination. Such tour package data were transcribed into data matrix using Pajek, UCINET, and Cytoscape for analysis. The density and centralization scores derived from the analysis indicated clearly that each destination was almost connected to each other. The centrality scores indicated that the destinations with higher degree of centrality also has higher betweenness centrality within the network. Based on centrality scores, POI(point of interests) of tourism destinations showed concentration in southern area of the target region. Finally, through component analysis, subgroups of tourism destination networks are isolated. Practical implications were also presented for industry practitioners.

• International Area Studies Review
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• v.22 no.3
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• pp.85-119
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• 2018

This paper investigates the effects of exchange rate and labor skill composition on Vietnam's trade balance with her twenty main trading partners. Using balanced panel data from 2000 to 2016, the authors analyze Vietnam's total trade balance and the trade balance which is disaggregated based on labor skill sophistication. Three main findings are presented. Firstly, exchange rate has a positive effect on Vietnam's trade balance, but the small value of estimated coefficient indicates that its effect is limited. Secondly, Vietnam's trade balance of the high labor-skill produced and medium-skill white collar labor-produced goods is worsened when VND (Vietnamese Dong) depreciates. Thirdly, moving up the labor skill ladder and promoting the none-price competitiveness of the high labor-skill produced and medium-skilled white collar labor-produced goods can improve Vietnam's total trade balance, while promoting the low-skill labor-produced and medium-skill blue collar-labor produced goods can no longer contribute to Vietnam's total trade balance.

• Proceedings of the CALSEC Conference
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• 2002.01a
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• pp.307-312
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• 2002

□가장 일상적으로 사용하는 체계 □상품의 모든 처리 단계에서 데이터의 색인을 구성 - 수요예측 - 주문서 작성 - 송장 -입고확인 -재고관리 -판매 □각 기업은 나름의 식별코드 □각 산업은 나름대로의 식별코드(중략)

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.149-152
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• 2008

본 연구는 협업 추천 시스템에 적용되는 상품에 대한 고객의 선호도 예측 알고리즘 중 메모리기반 협업필터링 알고리즘의 선호도 예측 특성에 대하여 연구하였다. 메모리기반의 협업필터링 알고리즘은 선호도 예측 대상 고객과 유사한 성향을 가질 것으로 예상되는 고객들의 선호도 평가를 기반으로 특정 상품에 대한 선호도 예측이 이루어진다. 일반적으로 시스템을 이용하는 고객들과 선호성향이 다른 고객들은 선호도 예측 성과가 낮은 것으로 알려져 있으며 이들이 추천시스템의 선호도 예측 정확도를 떨어뜨리는 원인으로 알려져 있다. 본 연구에서는 고객이 상품들에 평가한 선호도 평가의 패턴이 선호도 예측 정확도와 관련성이 높음을 보여 선호도 예측 알고리즘의 개선에 기초 자료를 제공하고자 한다. 고객의 선호도 평가 패턴은 과거 고객이 평가한 자료로부터 얻을 수 있는 사전정보로써 선호도 예측 알고리즘을 적용하기 이전에 이용할 수 있는 정보이다. 본 연구에서는 사전정보를 이용하여 고객의 선호도 예측 오차의 특성을 연구함으로써 이들의 선호도 예측 정확도를 개선시킬 수 있는 알고리즘의 보정방법에 대하여 연구한다. 알고리즘의 보정방법을 선호도 예측 이전에 고객의 선호도 평가 특성으로 판단하여 적용함으로써 사전정보를 이용한 선호도 예측 정확도를 향상시키기 위한 접근법은 기존의 이웃 구성의 접근법과 다른 방법을 취함으로써 알고리즘 개선의 새로운 방향을 제시할 것으로 기대된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.833-836
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• 2003

영국 BT의 모든 도매 xDSL 상품은 'end-to-end' 방식으로만 제공되고 있는데 이것이 OLO에게 있어서는 자신의 망을 사용하는데 범위를 제약하기 때문에, OLO들은 BT 망과의 상호접속을 통하여 가능하면 자신의 망으로 대체할 수 있는 방안을 모색하고 그들 최종이용자의 트래픽을 전송하기 위하여 BT의 ATM 망의 ATM 교환기에서의 상호접속을 요청하게 되었다. 이에 따라 Oftel은 OLO의 요구사항을 검토한 결과, 요청 상호접속서비스가 BT의 기존 도매 DSL 상품과 상응하지 않기 때문에 이는 BT가 제공하여야 한 새로운 형태의 상호접속 서비스라고 규정하게 되었다. 본 논문에서는 기존 사업자인 BT의 데이터 망 구성과 제공 상품 내용, OLO의 상호접속 요청서비스에 대한 개념과 의미, 그리고 Oftel의 최종 결정사항의 주요 내용을 살펴됨으로써, 신규 상호접속서비스 규정에 대한 Oftel의 접근 방식과 시사점을 도출하고자 한다.