학력

• 2002 - 2007 Ph.D in Technology Management, Economics and Policy Program (TEMEP), Seoul National University

• 1998 - 2002 B.Sc. in Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST)

경력

• 2018 - 2018   Visiting Scholar, Duke University, U.S.

• 2008 - 2018   Research Fellow, Korea Energy Economics Institute

• 2007 - 2008   Post-Doctoral Researcher, Georgia Institute of Technology, U.S.

관심분야

[수업 관심분야]

• Management of Technology, Project Management, Business Statistics, Methodology for Technology Market

[연구 관심분야]

• Management of Technology

• Sustainable Management

• Demand Forecasting Using Bayesian Inference

• Analysis of Consumer Preference

• Discrete Choice Analysis

학술활동 및 교외봉사활동

• 편집위원, 한국혁신학회, 2018.1.1 ~ 2019.12.31

• 이사, 한국신재생에너지학회, 2016.8.3 ~ 현재

학술지 발표

- Park, C., Lim, S., Shin, J. and Lee, C.-Y.. (August 31, 2022). How much hydrogen should be supplied in the transportation market? Focusing on hydrogen fuel cell vehicle demand in South Korea, Technological Forecasting and Social Change, 181, 121750 (SSCI, IF: 8.593, JCR: 7.3%).

- Chul-Yong Lee, Jung-Woo Jang, Minkyu Lee (Oct. 1, 2020). Willingness to accept values for vehicle-to-grid service in South Korea. Transportation Research Part D: Transport and Environment, 87, 1-10. (SSCI, IF: 4.577).

- JongRoul Woo, Sungsam Chung, Chul-Yong Lee , and Sung-Yoon Huh (Sep. 1, 2019). Willingness to participate in community-based renewable energy projects: A contingent valuation study in South Korea. Renewable & Sustainable Energy Reviews, 112, 643-652 (SCI, IF: 12.110, JCR: 5.4%)

- Hyunsuk Byun, Jung-Woo Shin and Chul-Yong Lee* (Feb. 1, 2018). Using a discrete choice experiment to predict the penetration possibility of environmentally friendly vehicles. Energy, 144, 312-321 (SCI, IF: 4.520, JCR: 5.2%). 

- Gobong Choi, Sung-Yoon Huh, Eunnyeong Heo, and Chul-Yong Lee* (Feb. 1, 2018). Prices versus quantities: Comparing economic efficiency of feed-in tariff and renewable portfolio standard in promoting renewable electricity generation. Energy Policy, 113, 239-248 (SSCI, IF: 4.140, JCR: 14.4%). 

- Sung-Yoon Huh and Chul-Yong Lee* (August 1, 2017). A demand-side perspective on developing a future electricity generation mix: Identifying heterogeneity in social preferences. Energies, 10(8), 1-19 (SCIE, IF: 2.262, JCR: 48.9%). 

- Chul-Yong Lee, Seung-Hoon Yoo, and Minkyu Lee (June 1, 2017). Willingness to pay for replacing traditional energies with renewable energy in South Korea. Energy, 128, 284-290 (SCI, IF: 4.520, JCR: 5.2%). 

- Chul-Yong Lee and Sung-Yoon Huh (July 1, 2017). Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea. Applied Energy, 197, 29-39 (SCI, IF: 7.182, JCR: 3.0%). 

- Hyunsuk Byun and Chul-Yong Lee* (June 1, 2017). Analyzing Korean consumers’ latent preferences for electricity generation sources with a hierarchical Bayesian logit model in a discrete choice experiment. Energy Policy, 105, 294-302 (SSCI, IF: 4.140, JCR: 14.4%). 

- Chul-Yong Lee and Sung-Yoon Huh (March 1, 2017). Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea. Renewable and Sustainable Energy Reviews, 69, 207-217 (SCI, IF: 8.050, JCR: 5.4%). 

- Jung-Woo Shin, Chul-Yong Lee*, and Hongbum Kim (Nov. 1, 2016). Technology and Demand Forecasting for Carbon Capture and Storage Technology in South Korea. Energy Policy, 98, 1-11 (SSCI, IF: 4.140, JCR: 14.4%). 

- Chul-Yong Lee and Hyejin Heo (July 1, 2016). Estimating willingness to pay for renewable energy in South Korea using the contingent valuation method. Energy Policy, 94, 150-156 (SSCI, IF: 4.140, JCR: 14.4%). 

- Sung-Yoon Huh and Chul-Yong Lee* (June 1, 2014). Diffusion of Renewable Energy Technologies in South Korea on Incorporating Their Competitive Interrelationships. Energy Policy, 69, 248-257 (SSCI, IF: 4.140, JCR: 14.4%). 

- Jongsu Lee, Chul-Yong Lee*, and Kichun Sky Lee (Sep. 30, 2012). Forecasting Demand for a Newly Introduced Product Using Reservation Price Data and Bayesian Updating. Technological Forecasting and Social Change, 79(7), 1280-1291 (SSCI, IF: 2.625, JCR: 7.3%). 

- Jongsu Lee, Chul-Yong Lee*, and Tai-Yoo Kim (Dec. 31, 2009). A Practical Approach for Beginning the Process of Technology Roadmapping. International Journal of Technology Management, 47(4), 306-321 (SSCI, IF: 1.036, JCR: 56.5%). 

- Chul-Yong Lee, Jung-Dong Lee, and Yeonbae Kim (Jan. 31, 2008). Demand Forecasting for New Technology with a Short History in a Competitive Environment: The Case of the Home Networking Market in South Korea. Technological Forecasting and Social Change, 75(1), 91-106 (SSCI, IF: 2.625, JCR: 7.3%). 

- Jongsu Lee, Youngsang Cho, Jung-Dong Lee, and Chul-Yong Lee (May 31, 2006). Forecasting the evolution of demand for the large sized television of next generation using conjoint and diffusion models. Technological Forecasting and Social Change, 73(4), 362-376 (SSCI, IF: 2.625, JCR: 7.3%). 

- 오승환, 이철용* (2014.9.30.) “국내 신재생에너지 R&D 사업의 경제적 성과 분석”, 에너지경제연구 제13권, 제2호, pp.171-197. 

- 이민규, 이철용* (2012.12.15) “태양광·풍력 국가경쟁력 분석 : OECD국을 대상으로”, POSRI경영경제연구 제12권, 제3호, pp.44-75. 

- 이철용 (2011.8.31) “베이지안 모형을 이용한 중장기 국제유가 전망 연구”, POSRI경영경제연구, 제11권, 제2호, pp.58-86.

- 이철용, 이종수 (2007.12.3) “진술선호 자료와 현시선호 자료를 이용한 신제품의 수요예측: 한국의 텔레매틱스 시장을 대상으로”, Telecommunications Review, 제17권, 제5호, pp.855-865. 

- 이철용, 이종수 (2007.6.30) “기술 로드맵의 기초 작성을 위한 컨조인트 분석과 QFD”, 기술혁신연구, 제15권, 제1호, pp.65-86.

- 이철용, 이종수 (2005.12.15) “재구매를 고려한 이동통신단말기 시장의 확산 분석”, 정보통신정책연구, 제12권, 제4호, pp.179-201. 

- 이철용, 이정동, 김연배 (2005.6.30) “소비자 선택을 고려한 신기술 혁신의 확산 예측: 한국의 홈네트워킹 시장을 대상으로”, 기술혁신연구, 제13권, 제1호, pp.1-24. 

- 이종수, 조영상, 이정동, 이철용* (2004.12.31) “선택기반 확산모형을 이용한 차세대 대형 TV의 수요예측”, 정보통신정책연구, 제11권, 제4호, pp.57-81.

수상 및 서훈

• 대한민국 국무조정실장 표창, 2018.02.08