[Journal:] The International Journal of Management Science and Information Technology (IJMSIT) [ISSN:] 1923-0273 [Issue:] 6-(Oct-Dec) [Publisher:] NAISIT Publishers [Place:] Toronto [Year:] 2012 [Pages:] 1-27
NAISIT Publishers, Toronto
This paper presents and demonstrates a qualitative and quantitative methodological approach to the evaluation of public Research and Development (R&D) funding. This approach aims to support rather than replace traditional evaluation approaches, by focusing on the input, output and behavioural effects of public R&D funding. This study employs as an evaluation model an adapted impact analysis model of the Finnish Funding Agency for Technology and Innovation (TEKES), including additionality theory and other evaluation methods. In addition, an evaluation tool is proposed in which R&D indicators are arranged in portfolios. Furthermore, a data repository mechanism is designed, and a computational tool for computing and displaying evaluation results is employed - a customised web-based application centred by an ontological evaluation model. The methodological approach is articulated, explained, illustrated and discussed by employing R&D programmes granted by the Greek funding agency. The results display both a standardised approach that can be applied to R&D funding evaluation, as well as a flexible and modular approach that can be adapted according to the objectives and policies of funding agency. The main benefits of this methodology are the ease of decoding quantitative and qualitative evaluation attributes in an automated way with low cost; and the ability to evaluate results objectively, in addition to producing outcomes in a broad and comparative manner. The challenge in this methodological approach is focused on three key areas: the exploitation of new evaluation tools, the elevation of hidden information, and the formulation of appropriate questions beneficial to revealing the effectiveness of government R&D funding mechanism.
R&D evaluation methodological approach qualitative and quantitative evaluation ontology model