A Methodological Framework for Tailoring National Indicators to Regional Contexts

Abstract

Innovation systems are made up of multiple entities within the quadruple helix model, including their interactions and connections. The role of smart technologies and ICT (Information and Communication Technology) is critical for the operational effectiveness of such systems. Additionally, the regional context is considered essential for the evaluation of the level of innovation within these systems. A significant barrier to this approach, is the absence of adequate data at a regional level. To address this gap, this paper presents a new methodology to adapt national level numerical indicators to regional contents. This methodological model-fit approach employs regression analysis to tailor national indicators to the regional level using comparable available data. The method is evaluated using data from Greek NUTS 2 (Nomenclature of Territorial Units for Statistics) regions, yielding regional-level estimates for four innovation indicators based on four existing indicators that are found to be significantly correlated to them. However, the same technique may be used to any EU (European Union) member country or the entire EU The findings, their implications for future research, and prospective applications are discussed. Overall, the provision of regional-level indicators is seen as critical for formulating effective development strategies.