A growing number of innovation policies rely on publicly funded innovation intermediaries to provide knowledge-intensive services to firms, particularly small and medium-sized ones. The performance of innovation intermediaries is often assessed using indicators that need to be closely aligned with policy objectives to be effective. However, this alignment is difficult to achieve and is often overlooked in practice. We analyse the relationship between performance indicators and the behaviour of intermediaries by examining a case study of innovation intermediaries funded with public resources in Tuscany (Italy). The intermediaries implemented actions that allowed them to achieve their performance targets rapidly. However, due to a misalignment between indicators and policy objectives, these actions were not entirely consistent with the latter. After reviewing the literature on this key issue, we build on our findings to suggest how to design performance indicators that can induce intermediaries to more effectively support the achievement of policy objectives.

The aim of this study is to capture a technology's pathway by identifying emerging subdomains in a complex system of economic processes. The objective is to uncover indirect latent relations among agents interacting in a specific techno-economic segment (TES). A methodology, including an "Extract-Transform-Load" (ETL) process preceding the two steps aimed for analysis, is developed to analyse a TES regarding R&D economic processes of the photonics technology. In the first step, economic relevant R&D activities (EU funded projects and patents) are analysed through a multilayer network (MLN) of agents, considering their interactions in three dimensions, which represent occurred and latent relationships: co-participations in economic activities, common geographical location provenance, common use of technological terms. Then communities are detected (Infomap Algorithm for MLN), and their ongoing within and between connections are studied, as potential factors that affect the entire structured technological ecosystem. In the second step, technological subdomains associated with method-oriented and application-oriented activities are identified through topic modelling. Using the MLN structure, the textual information of the corpus of documents describing the aforementioned economic R&D activities is associated to agents, and the topic model (Latent Dirichlet Allocation) uncovers additional potential semantic connections among them. Subsequently, the results of the MLN community detection and of the topic modelling based on the descriptions of economic activities are considered. Hence, the latent relations of agents are mapped.

No abstract

No abstract