Measuring the regional dimension of innovation through an economic model based on rectifying technology audits according to the AICTT-RTA protocol.
DOI:
https://doi.org/10.14738/abr.26.710Abstract
The aim of this paper is to give an answer to the question “how to detect the regional dimension of innovation?”. So, in this paper, a method to be used as an operational tool that is able to grasp regional specificities in the innovation process, based on the optimization of measurement activity, is proposed. Evidence in the scientific literature shows that data and indicators are able to quantify the contribution of different regions, identify the different technological profiles of the regions and measure the technological performances of regional systems, the innovative performances of firms and the density and quality of systemic interactions between the main institutional actors, but these items are often not developed through an analytical model of measure control cost based on the optimization of certain influencing factors.
The proposed approach is based on two main points:
1) Define the opportune methodology to detect the innovation level of a single firm. For this aim it has been considered the AICTT-RTA protocol. Each SME, is considered as innovative or as non-innovative according to the outcome of a Technology Audit (TA) conducted in compliance with the AICTT-RTA protocol.
2) Determine, starting only from some of the SMEs in a certain monitored area, if the entire area is innovative or not, through TA on a optimal sample size of SMEs analyzed. For this second point the approach uses a bayesian analysis of the Deming cost model.
This approach considers a wide area, industrial or urban, in which SMEs are present and treats it as a lot of N items.
Through the proposed approach, to characterize the regional innovation it’s sufficient to characterize just only some SMEs, however detecting the whole regional innovation profile.
In this paper this aspect is valorized and set in the form of a useful operational tool for regional institutions, innovation managers, entrepreneurs and researchers.
Simulation results complement the proposed theoretical model.
References
Acs, Z.J., Audretsch, D.B., 1988. Innovation in large and small firms: an empirical analysis. The American Economic Review 78, 678–690.
Acs, Z., Anselin, L., Varga, A., 2002. Patents and innovation counts as measures of regional production of new knowledge. Research Policy 31, 1069– 1085.
Acs, Z., Audretsch, D., Feldman, M., 1992. Real effect of academic research: comment. The American Economic Review 82 (1), 363–367.
Amable, B., Petit, P., 2001. The diversity of social systems of innovation and production during the 1990s. In: Paper Presented at the DRUID Conference, Aalborg, June, 2001.
Anselin, L., Varga, A., Acs, Z., 1997. Local geographic spillovers between university research and high technology innovations. Journal of Urban Economics (42), 422–448.
Archibugi, D., 1992. Patenting as an indicator of technological innovation: a review. Science and Public Policy 19, 357–368.
Archibugi, D., Pianta, M., 1996a. Measuring technological change through patents and innovation surveys. Technovation 16, 115–121.
Archibugi, D., Pianta, M., 1996b. Innovation surveys and patents as technology indicators: the state of the art. In: Innovation, patents and technological strategies. Paris, OECD.
Arundel, A., Kabla, I., 1998. What percentage of innovations are patented? Empirical estimates for European firms. Research Policy 27, 127–141.
Asheim, B., Gertler, M., 2005. In: Fagerberg, Mowery, Nelson (Eds.), The Geography of Innovation: Regional Innovation Systems.
Athreye, S., Keeble, D., 2002. Specialized markets and behaviour of firms: evidence from the United Kingdom’s regional economies. International Regional Science Review 25 (1), 38–62.
Audretsch, D., 1998. Agglomeration and the location of innovative activity. Oxford Review of economic policy 14-2, 18–29.
Bania, N., Calkins, L.N., Dalenberg, D.R., 1992. The effects of regional science and technology policy on the geographic distribution of industrial R&D laboratories. Journal of Regional Science 32 (2), 209–228.
