Analyzing the Learning Path of US Shale Players by Using the Learning Curve Method
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Cited by:
- Jong-Hyun Kim & Yong-Gil Lee, 2021. "Factors of Collaboration Affecting the Performance of Alternative Energy Patents in South Korea from 2010 to 2017," Sustainability, MDPI, vol. 13(18), pages 1-25, September.
- Thomassen, Gwenny & Van Passel, Steven & Dewulf, Jo, 2020. "A review on learning effects in prospective technology assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
- Jong-Hyun Kim & Yong-Gil Lee, 2018. "Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources," Sustainability, MDPI, vol. 10(9), pages 1-11, September.
- Jong-Hyun Kim & Yong-Gil Lee, 2020. "Patent Analysis on the Development of the Shale Petroleum Industry Based on a Network of Technological Indices," Energies, MDPI, vol. 13(24), pages 1-15, December.
- Jong-Hyun Kim & Yong-Gil Lee, 2020. "Progress of Technological Innovation of the United States’ Shale Petroleum Industry Based on Patent Data Association Rules," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
- Hongxun Liu & Jianglong Li, 2018. "The US Shale Gas Revolution and Its Externality on Crude Oil Prices: A Counterfactual Analysis," Sustainability, MDPI, vol. 10(3), pages 1-17, March.
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Keywords
learning rate; US shale; E&P industry; shale gas; tight oil; productivity;All these keywords.
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