A Comprehensive Methodology for Evaluating R&D Projects on the Valorisation of Big Data in the Field Open Innovation According to the Frascati Manual

Abstract

In the dynamic landscape of Research and Development (R&D), there is still a gap in the evaluation of projects dealing with big data and open innovation. Integrating the resource-based view (RBV) as a theoretical basis and the Frascati Manual principles to bridge theory and practice, this paper aims to provide a methodology for analyzing in a quantitative way the value of R&D projects dealing with big data. Leveraging Analytic Hierarchy Process (AHP) and Fuzzy Set Theory (FST), the proposed approach provides a hierarchical structure that measures the relative significance of the resources. The findings underscore a comprehensive evaluation methodology that captures the nuanced challenges of R&D projects in big data and open innovation fields, thus improving the capacity for strategic decision-making by enabling companies to optimize their projects. Policymakers can employ the insights from this contribution to develop policies that encourage innovation and the efficient use of resources in R&D investments.