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Cited 6 time in webofscience Cited 6 time in scopus
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dc.contributor.authorLEE, HWARANG-
dc.contributor.authorKIM, HANSUNG-
dc.contributor.authorCHOI, DONG GU-
dc.contributor.authorKOO, YOONMO-
dc.date.accessioned2022-08-04T00:20:06Z-
dc.date.available2022-08-04T00:20:06Z-
dc.date.created2022-08-03-
dc.date.issued2022-09-
dc.identifier.issn2211-467X-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/113466-
dc.description.abstract© 2022 The AuthorsSustainable energy transition is garnering attention as a method to achieve emission reduction targets. In this transition, technology learning and spillovers, which are representative sources of technological change, have significant implications. Most previous studies focused on inter-country and inter-region spillovers, although spillovers can be observed at the various levels. This study develops the industrial energy system model, which explores learning and inter-industry spillovers at the technology level, and investigates learning and spillover effects on climate policy performance. The model reflects spillovers between industrial common technologies based on an iterative approach and describes the effects of learning and spillovers on technology characteristics, such as technology efficiency. The results describe that not only the speed of learning but also the existence of spillovers is important for sustainable industrial energy systems. Spillovers also help to mitigate industrial emissions with less subsidies for efficient technologies and affects the preference of industries for a carbon tax. The government should create an appropriate environment for efficiency improvements and their diffusion in industries. Moreover, a wider range of policy options is available if industries are more cooperative in diffusing their technology innovation.-
dc.languageEnglish-
dc.publisherElsevier-
dc.relation.isPartOfEnergy Strategy Reviews-
dc.titleThe impact of technology learning and spillovers between emission-intensive industries on climate policy performance based on an industrial energy system model-
dc.typeArticle-
dc.identifier.doi10.1016/j.esr.2022.100898-
dc.type.rimsART-
dc.identifier.bibliographicCitationEnergy Strategy Reviews, v.43-
dc.identifier.wosid000837144800001-
dc.citation.titleEnergy Strategy Reviews-
dc.citation.volume43-
dc.contributor.affiliatedAuthorKIM, HANSUNG-
dc.contributor.affiliatedAuthorCHOI, DONG GU-
dc.identifier.scopusid2-s2.0-85135515339-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.type.docTypeArticle-
dc.subject.keywordPlusRESEARCH-AND-DEVELOPMENT-
dc.subject.keywordPlusBOTTOM-UP MODEL-
dc.subject.keywordPlusKNOWLEDGE SPILLOVERS-
dc.subject.keywordPlusRENEWABLE ENERGY-
dc.subject.keywordPlusCURVE THEORY-
dc.subject.keywordPlusTRANSITION-
dc.subject.keywordPlusINNOVATION-
dc.subject.keywordPlusPOWER-
dc.subject.keywordPlusSUSTAINABILITY-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordAuthorTechnology learning-
dc.subject.keywordAuthorTechnology diffusion-
dc.subject.keywordAuthorClimate policy performance-
dc.subject.keywordAuthorEnergy efficiency-
dc.subject.keywordAuthorBottom-up energy system model-
dc.relation.journalWebOfScienceCategoryEnergy & Fuels-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEnergy & Fuels-

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최동구CHOI, DONG GU
Dept. of Industrial & Management Eng.
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