The dynamics of incremental costs of efficient television display technologies
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DOI: 10.1016/j.techfore.2014.02.016
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- Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
- Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
- Desroches, Louis-Benoit & Garbesi, Karina & Kantner, Colleen & Van Buskirk, Robert & Yang, Hung-Chia, 2013. "Incorporating experience curves in appliance standards analysis," Energy Policy, Elsevier, vol. 52(C), pages 402-416.
- McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
- Dale, Larry & Antinori, Camille & McNeil, Michael & McMahon, James E. & Sydny Fujita, K., 2009. "Retrospective evaluation of appliance price trends," Energy Policy, Elsevier, vol. 37(2), pages 597-605, February.
- Bass, Frank M, 1980. "The Relationship between Diffusion Rates, Experience Curves, and Demand Elasticities for Consumer Durable Technological Innovations," The Journal of Business, University of Chicago Press, vol. 53(3), pages 51-67, July.
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Cited by:
- Park, Won Young & Phadke, Amol A., 2017. "Adoption of energy-efficient televisions for expanded off-grid electricity service," Development Engineering, Elsevier, vol. 2(C), pages 107-113.
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Keywords
Televisions; Efficiency; Experience curves;All these keywords.
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