Yanghon Chung

Yanghon Chung

orcid

Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2015 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
CWChungwon Woo
Chungwon Woo
YCYanghon Chung
Yanghon Chung
DCDongphil Chun
Dongphil Chun
HSHangyeol Seo
Hangyeol Seo
SHSungjun Hong
Sungjun Hong

1 January 2016 in Journal of Cleaner Production
Verified
Journal Article
Closed access
CWChungwon Woo
Chungwon Woo
MKMoon Gyu Kim
Moon Gyu Kim
YCYanghon Chung
Yanghon Chung
JRJae Jeung Rho
Jae Jeung Rho

26 July 2013 in Business Strategy and the Environment
Verified
Journal Article
Closed access
PDF file
CWChungwon Woo
Chungwon Woo
YCYanghon Chung
Yanghon Chung
DCDongphil Chun
Dongphil Chun
SHSeunghun Han
Seunghun Han
DLDukhee Lee
Dukhee Lee

1 July 2016 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
SHSungjun Hong
Sungjun Hong
YCYanghon Chung
Yanghon Chung
JKJongwook Kim
Jongwook Kim
DCDongphil Chun
Dongphil Chun

24 March 2015 in Technology Analysis & Strategic Management
Verified
Journal Article
Closed access
DCDongphil Chun
Dongphil Chun
YCYanghon Chung
Yanghon Chung
SBSungsig Bang
Sungsig Bang
Technological innovation through R&D is a critical element in enhancing and fostering firm performance. In particular, measurement of R&D efficiency throughout the innovation and commercialisation stages is important. However, almost of R&D efficiency-related studies assumed that R&D is a single stage. This study aims at analysing relative efficiency scores throughout the stages of the R&D process using a two-stage data envelopment analysis (DEA) model with a sample of 1039 Korean manufacturing firms. Based on our preliminary results, this study was extended by comparing subsample groups categorised by firm size and industry type. The key findings include: (1) firms show imbalanced R&D efficiency throughout the two stages and (2) R&D efficiency is different by firm size and industry type. The empirical results and findings may assist policy- and decision-makers to enhance R&D efficiency at the firm level. Moreover, introduction of the two-stage DEA model and comparative analysis methods to firm-level data contributes to scholars.

1 January 2015 in Energy
Verified
Journal Article
Closed access
SHSungjun Hong
Sungjun Hong
YCYanghon Chung
Yanghon Chung
CWChungwon Woo
Chungwon Woo