From free to fee for digital content through utility-based business analytics = 효용 기반 비즈니스 애널리틱스를 이용한 디지털 콘텐츠의 유료화에 관한 연구

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This study proposes a novel framework for designing business analytics to assist digital content providers in effectively converting free-only users (FOUs) into fee-paying cus-tomers. To achieve the objective of the seller’s profit maximization, the traditional frequency-driven rule analytics was expanded by integrating three business-relevant factors (potential demand, conversion profit, and conversion likelihood) into the process of generating recom-mendations for FOUs in digital content markets. The framework was tested using two differ-ent types of empirical analyses. An analysis of data regarding over 300,000 transactions col-lected from an e-book seller was carried out to examine the effectiveness of the proposed ap-proach. In addition, a field experiment with real data from a national e-book store was con-ducted to determine how FOUs responded to the recommendations generated by the frame-work. The results from the analyses indicate that the proposed framework can benefit sellers both on and after free-to-paid conversion. In addition, some implications were obtained re-garding the factors proposed in this study. The findings suggest that utility-based business analytics can significantly enhance the business performance of digital content providers.
Advisors
Han, Ingooresearcher한인구researcherOh, Wonseokresearcher오원석researcher
Description
한국과학기술원 :경영공학부,
Publisher
한국과학기술원
Issue Date
2014
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 경영공학부, 2014.2,[iv, 72 p. :]

Keywords

utility-based business analytics▼afree-to-fee conversion▼arecommender system▼aassociation rule mining▼autility-based recommendation▼afree-to-paid conversion▼apotential demand; conversion profit▼aconversion likelihood; 효용 기반 비즈니스 규칙 분석▼a유료 사용자 전환▼a디지털 콘텐츠▼a추천 시스템▼a연관 규칙 마이닝▼a효용 기반 추천▼a잠재 수요▼a유료화 이익▼a유료화 가능성

URI
http://hdl.handle.net/10203/241651
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=708777&flag=dissertation
Appears in Collection
MT-Theses_Ph.D.(박사논문)
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