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Managing Advanced Technology System Deployment: An Optimal Allocation Between R&D And Prototype Funding

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Abstract

The research and development manager allocates R&D funds to maximize the expected discounted net value of the R&D programme. Because public R&D managers do not have the same market discipline (or rewards) as private R&D managers, public R&D managers require a methodology for maximizing the expected net benefits. The US National Research Council of the National Academies in Prospective Evaluation of Applied Energy Research and Development at DOE (Phase One): A First Look Forward (2005) proposed a cost-benefit methodology to evaluate US Department of Energy's Research, Development, and Demonstration (RD&D) programmes. This paper specifies and extends this methodology, e.g., by adding cost targets into each stage of the RD&D process. Expected benefits are modelled as a function of funding levels, stage durations, stage transition probabilities, and target costs. With this method, the paper determines an optimal allocation of pre-prototype R&D funding, given a total funding constraint for an advanced energy system.

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  • G. Rothwell, 2007. "Managing Advanced Technology System Deployment: An Optimal Allocation Between R&D And Prototype Funding," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 16(6), pages 419-432.
    • Handle: RePEc:taf:ecinnt:v:16:y:2007:i:6:p:419-432
    DOI: 10.1080/10438590601153894
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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economic Development Technological Change, and Growth > Management of Technological Innovation and R&D

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    Cited by:

    1. Siddiqui, Afzal & Fleten, Stein-Erik, 2010. "How to proceed with competing alternative energy technologies: A real options analysis," Energy Economics, Elsevier, vol. 32(4), pages 817-830, July.
    2. Muhammad Yousaf Raza & Yingchao Chen & Songlin Tang, 2022. "Assessing the Green R&D Investment and Patent Generation in Pakistan towards CO 2 Emissions Reduction with a Novel Decomposition Framework," Sustainability, MDPI, vol. 14(11), pages 1-19, May.
    3. Kahouli, Bassem, 2018. "The causality link between energy electricity consumption, CO2 emissions, R&D stocks and economic growth in Mediterranean countries (MCs)," Energy, Elsevier, vol. 145(C), pages 388-399.
    4. Gren, Ing-Marie & Carlsson, Mattias, 2013. "Economic value of carbon sequestration in forests under multiple sources of uncertainty," Journal of Forest Economics, Elsevier, vol. 19(2), pages 174-189.

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