• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.3068-3085
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• 2021

The economics of big data knowledge, especially cloud computing and statistical data of consumer preferences, has attracted increasing academic and industry practitioners' attention. Firms nowadays require purchasing not only external private patent knowledge from other firms, but also proprietary big data knowledge to support their new product development. Extant research investigates pricing strategies of external private patent knowledge and proprietary big data knowledge separately. Yet, a comprehensive investigation of pricing strategies of these two types of knowledge is in pressing need. This research constructs an overarching pricing model of external private patent knowledge and proprietary big data knowledge through the lens of firm profitability as a knowledge transaction recipient. The proposed model can help those firms who purchase external knowledge choose the optimal knowledge structure and pricing strategies of two types of knowledge, and provide theoretical and methodological guidance for knowledge transaction recipient firms to negotiate with knowledge providers.

• Asia pacific journal of information systems
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• 제29권4호
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• pp.752-770
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• 2019

The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

• 융합보안논문지
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• 제17권3호
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• pp.51-57
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• 2017

VOD 서비스는 일반 유료방송가입자들 사이의 보편적인 인기뿐만 아니라 가입자 기반 수신료, 광고료와 같은 기존 방송사의 수익 외의 추가 수익을 제공하고 있다. 이와 같은 이유로 각 방송사들은 자신의 VOD 서비스를 개발하고 매출을 높이기 위해 잦은 개선 작업을 수행하기 때문에 개발업체는 이런 개발 요구들에 효과적으로 대응할 방법이 필요한 실정이다. 이 에 본 연구는 사례연구들을 통해 그 효율성이 입증된 대표적 피처지향 분석모델인 FODA (Feature-Oriented Domain Analysis)를 VOD 서비스 개발에 적용하였다. FODA는 카네기멜론대학 SEI에서 개발한 피처지향 분석모델로서 특정 도메인에 해당하는 소프트웨어의 피처모델을 개발하고 이를 기반으로 고객이 원하는 소프트웨어 형상을 결정하는 도구를 제공한다. 본 연구는 개발업체와 함께 VOD 서비스 도메인의 피처모델을 개발하고 VOD 서비스 개발 프로세스 향상을 위한 피처모델 기반의 VOD 서비스 기능과 테스트케이스들을 개발하였다.

• 경영과학
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• 제22권1호
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• pp.179-197
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• 2005

This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.

• 한국IT서비스학회지
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• 제16권4호
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• pp.177-195
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• 2017

Traditionally, news was consumed only through printed newspapers and broadcasting media, such as radio and television. However, the Internet has enabled people to consume news content online. Since most of online news content has been provided for free, it is not easy for news providers to charge the fixed subscription fee for online news content. Therefore, as an alternative strategy, some online news providers have tried to adopt the Pay-What-You-Want (PWYW) pricing model, which allows users (readers) to pay as much as they want after consuming news content. As this pricing model shows some possibility to grow and replace the unsuccessful monetization strategy of online news content, we therefore examined the comparative importance of seven heuristic attributes (i.e., article evaluation, article share, article comment, article information design, article length, writer SNS, and writer information) affecting readers' voluntary payment behavior through a conjoint analysis with 379 news articles collected from online news Website (i.e., Ohmynews.com) where the PWYW model has been working successfully. This study found that article share and article length are the most important factors which affect online news content users' voluntary payment. Finally, two major and eight minor propositions are suggested based on the findings of the study. This study would suggest guidelines for how to create online news content which induces much more voluntary payment.

• 디지털융복합연구
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• 제16권12호
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• pp.217-229
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• 2018

이 연구에서는 미분양 아파트 단지의 세대별 계약 자료에 데이터 마이닝 기법인 의사결정나무, 신경망, 로지스틱 모형을 적용하여 세대별 초기계약을 예측하는 모형을 개발한다. 모형 개발에는 위례신도시 미분양 아파트 단지의 계약 자료가 이용되며, 이 자료는 훈련용 자료와 검정용 자료로 분할되어 분석에 투입된다. 훈련용 자료에서는 신경망, 의사결정나무, 로지스틱 모형 순으로 예측력이 뛰어났지만 검정용 자료에서는 로지스틱 모형이 가장 우수하게 나타났다. 이 같은 결과는 신경망이 훈련용 자료에 최적화된 모형으로 구축되면서 검정용 자료에 대한 적응성이 떨어져 나타난 결과로 판단된다. 의사결정나무와 로지스틱 모형을 병행 적용한 결과, 층수, 향, 세대 위치, 전기 및 발전기실의 소음, 청약자 거주지, 청약 종류가 초기계약에 영향을 주는 것으로 나타났다. 이는 두 가지 모형을 같이 사용하는 것이 초기계약 결정요인 발굴에 더 효과적이라는 것을 의미한다. 이 연구는 데이터 마이닝의 적용 범위를 주택 분양 예측까지 확장함으로써 융복합 분야 발전에 기여하고 있다.

• 전자공학회논문지
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• 제50권2호
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• pp.11-19
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• 2013

인터넷 서비스 제공자들은 차등화 서비스를 제공하기 위한 정책적인 수단으로, 혹은 일부 악의적인 사용자들로 인한 회선의 독점적 사용을 막기 위한 수단으로 각 사용자의 최대 데이터 전송 속도를 일정 수준 이하로 제한하고 있다. 이 논문에서는 이러한 최대 접속 속도의 제한이 서비스 제공자의 수입과 서비스 가격 결정에 미치는 영향을 분석하고자 한다. 우리는 먼저 최대 접속 속도의 제한을 고려한 현실적인 인터넷의 서비스 품질 모델을 제안하고, 각 사용자에 대한 최대 접속 속도의 제한이 사용자들의 서비스 가입 결정에 어떻게 영향을 미치는 지 분석한다. 또한 그에 따라 변화하는 서비스 제공자의 수입이 안정성을 보장 받기 위한 조건을 유도하여, 수입을 최대화하기 위한 가격 결정 방법을 최적화 문제로 나타낸다.

• 한국도서관정보학회지
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• 제29권
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• pp.27-63
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• 1998

The purpose of this study is to analyze the document delivery service(DDS) of the academic libraries and suggest its improvement model in Korea. DDS means providing copies of information requests in any format and from any source. And DDS is gaining in importance as libraries turn to 'just-in-time' access rather than 'just-in-case' collection to meet user information needs. By good fortune, rising journal subscription prices, declining financial resources, canceling some of journal subscriptions, electronic transmission technologies, and the rise of commercial document delivery services have allowed libraries to begin to deliver articles to users in a much more rapid and acceptable time frame. Therefore, the library paradigm for the 2000s must be the creation of new document delivery structures which capitalize on the access tolls and structures created by librarians during the past generations. First of all, library-based document service requires a close review of existing library-to-library delivery mechanisms, application of technology to transfer of facsimiles of materials and facilitated use of existing fee-based document sources. The ideal document delivery system would feature a transparent, seamless electronic service incorporating searching and browsing identification and marking of desired items, and transmission and fulfillment of requests. And requested items would be supplied from library collection, commercial suppliers, or other sources. But the future of DDS will succeed when physical resources, policies, personnel, and practices are organized to provide timely information delivery to users.

• 한국IT서비스학회지
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• 제20권2호
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• pp.77-90
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• 2021

Online and mobile games represent digital entertainment. Not only the game grows fast, but also it has been noted for unique business models such as a subscription revenue model and free-to-play with partial payment. But, a recent revenue mechanism, called a loot-box system, has been criticized due to overspending, weak protection to teenagers, and more over gambling-like features. Policy makers and research communities have counted on expert opinions, review boards, and temporal survey studies to build countermeasures to minimize negative effects of online and mobile games. In this process, speed was not seriously considered. In this study, we attempt to use a big data source to find a way of observing a trend for policy makers and researchers. Specifically, we tried to apply the Word2Vec data mining algorithm to news repositories. From the findings, we acknowledged that the suggested design would be effective in lightening issues timely and precisely. This study contributes to digital entertainment service communities by providing a practical method to follow up trends; thus, helping practitioners have concrete grounds for balancing public concerns and business purposes.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.193-208
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• 2020

Purpose Due to COVID19, the over-the-top media service (OTT) market is growing faster than expected at an annual average of 26.4%. In Korea, WAVVE, which integrated SKT's Oksusu and POOQ in September 2019, outperformed Netflix in the number of users immediately after its launch, but the number of users gradually decreased. Research on OTT investigated the spread of new media due to changes in regulations or policy, mostly in broadcasting media. On the other hand, OTT research in information systems began after the success of Netflix. It investigated consumers' satisfaction with information technology using the Information Technology Acceptance Model (TAM). This study investigates changes in consumer perceptions in the OTT market, which has grown after the Netflix's entry into Korea, the emergence of WAVVE and new OTT service providers, and the spread of COVID19. Design/methodology/approach This study selects contents, fees, service quality, and additional services as factors to evaluate consumer perception using AHP. Findings According to the 101 respondents, the content was the most important factor, followed by service quality, fees, and additional services. Contrary to previous findings that price is the determining factor in service adoption, this study reveals that consumers are willing to pay a reasonable amount for rich content and excellent service quality. Future research will use demographic analysis to reveal differences in consumer's perceptions of service selection.