1,721,210 research outputs found
Vincoli e opportunità strutturali per l’industria italiana: come muoversi dentro la foresta dei prodotti?
Controllo delle Infezioni da BVDV, realizzazione ed applicazione di un piano a livello provinciale
Data-aided and phase-independent adaptive equalization for data transmission
A data-aided variant of the Godard algorithm for adaptive equalizatio
Synthesis of (S)-.beta.,.beta.,.beta.-trifluorolactic acid and (S)-.alpha.-methoxy-.alpha.-(trifluoromethyl)phenylacetic acid from (R)-methyl p-tolyl sulfoxide
Financial Support to Innovation: the Role of European Development Financial Institutions. DISEI, Working Papers - Economics, N.10/2020.
This paper explores the role of Development Financial Institutions (DFIs) in supporting innovation by facilitating the access to finance for start-ups and high-growth small and medium enterprises. After having mapped the population of DFIs in Europe, we benchmark their portfolio of equity deals to those of other European financial institutions (venture capital and private equity). We build a unique sample of European 12,437 M&As within the 2008–2017 period and for each target company we match the related patenting and economic data. We obtain a dataset of 80,713 yearly observations which allows us to empirically analyse the pre and post-deal patenting activity of companies targeted by both DFIs and other financial institutions. Our findings show that the target company patenting performance improves after receiving the support of financial institutions, and this effect is on average higher when DFIs participate to the equity deal. We also find that partnerships among DFIs and other financial institutions are associated with the best patenting performance of the target companies. These results are confirmed when a propensity score matching technique is adopted to address biases associated to the potential endogenous selection of the target company
BVD control program in Lecco and Como provinces (Italy) : herd risk categories to modulate interventions
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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