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A decision support system for public funding of experimental development in energy research

: Hirzel, Simon; Hettesheimer, Tim; Viebahn, Peter; Fischedick, Manfred

Fulltext urn:nbn:de:0011-n-4972584 (1018 KByte PDF)
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Created on: 22.6.2018

Energies 11 (2018), No.6, Art. 1357, 18 pp.
ISSN: 1996-1073
Journal Article, Electronic Publication
Fraunhofer ISI ()
energy research funding; proposal evaluation; public research and development (R&D) funding; public funding; decision support in energy research; multi-criteria decision making; policy support

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.