Development of an evaluation framework for publicly funded R&D projects: The case of Korea's Next Generation Network
Eungdo Kim,
Soyoung Kim and
Hongbum Kim
Evaluation and Program Planning, 2017, vol. 63, issue C, 18-28
Abstract:
For decades, efforts have been made globally to measure the performance of large-scale public projects and to develop a framework to perform such measurements due to the complexity and dynamics of R&D and stakeholder interests. Still, limitations such as the use of a simply modified model and the lack of a comprehensive viewpoint are prevalent in existing approaches. In light of these research gaps, this study suggests a practical model to evaluate the performance of large-scale and publicly funded projects. The proposed model suggests a standard matrix framework of indices that evaluates the performance of particular elements in an industrial ecosystem in vertical categories and the economic and technological outcomes of those elements in horizontal categories. Based on the application of a balanced scorecard, this study uses mixed methodologies such as social network analysis, inter-industry analysis, and the analytic hierarchy process. Finally, the model evaluates the performance of Korea's Next Generation Network project as a case study.
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0149718915301105
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:epplan:v:63:y:2017:i:c:p:18-28
DOI: 10.1016/j.evalprogplan.2017.02.012
Access Statistics for this article
Evaluation and Program Planning is currently edited by Jonathan A. Morell
More articles in Evaluation and Program Planning from Elsevier
Bibliographic data for series maintained by Catherine Liu ().