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dc.contributor.author박현석-
dc.date.accessioned2019-12-04T06:09:48Z-
dc.date.available2019-12-04T06:09:48Z-
dc.date.issued2018-01-
dc.identifier.citationIEEE ACCESS, v. 6, page. 3573-3584en_US
dc.identifier.issn2169-3536-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8244268-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/117263-
dc.description.abstractA technology evaluation system is mandatory to successfully implement a technology-based financial support system. Technology evaluation has generally been relied on the experts' manual work. Various quantitative indicators have been presented to improve the efficiency of this manual work. Among these indicators, the spillover effect is perceived as useful for the disposal of patents of a firm, which received credit guarantee but lost its ability to service its debt. A model for measuring the spillover effects has already been proposed, but it has low reliability. Therefore, this paper presents a systematic approach for measuring technological spillover effects between technology classes. The approach mainly relies on patent data due to its features of the latest reliable sources of technological intelligence. We first extract co-classification information from patent data and generate association rules between technology classes. The relationships represented by the rules, however, can only depict the direct effects. Therefore, we first derive the indirect effects from the direct ones and then integrate both the effects to measure the technological spillover effects. We conduct an empirical study to show the applicability of the presented approach using patents granted in the Korean Intellectual Property Office. We expect that this paper can contribute to establish a quantitative evaluation model to help assess technologies for successful technology-based credit guarantee system. It will improve the reliability of the technology assessment by reducing the variance of the qualitative evaluation results due to the individual differences of the evaluator. Furthermore, it will also enhance the efficiency of evaluation work.en_US
dc.description.sponsorshipThis work was supported by the National Research Foundation of Korea through the Basic Science Research Program funded by the Ministry of Science, ICT and Future Planning under Grant NRF-2014R1A1A1005317 and Grant NRF-2015R1C1A1A01056185.en_US
dc.language.isoen_USen_US
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_US
dc.subjectAssociation rule miningen_US
dc.subjectDEMATELen_US
dc.subjecttechnological spillover effecten_US
dc.subjecttechnology evaluationen_US
dc.subjecttechnology financingen_US
dc.titleAnalyzing Technological Spillover Effects Between Technology Classes: the Case of Korea Technology Finance Corporationen_US
dc.typeArticleen_US
dc.relation.volume6-
dc.identifier.doi10.1109/ACCESS.2017.2788918-
dc.relation.page3573-3584-
dc.relation.journalIEEE ACCESS-
dc.contributor.googleauthorChoi, Sungchul-
dc.contributor.googleauthorNoh, Maeng Seok-
dc.contributor.googleauthorYoon, Janghyeok-
dc.contributor.googleauthorPark, Hyunseok-
dc.contributor.googleauthorSeo, Wonchul-
dc.relation.code2018011916-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF INFORMATION SYSTEMS-
dc.identifier.pidhp-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INFORMATION SYSTEMS(정보시스템학과) > Articles
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