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        <title type="main" level="a">A composite indicator to measure regional investment policies on R&amp;D and innovation</title>
        <author>
          <persName n="1" ref="https://orcid.org/0000-0002-1420-8422" type="ORCID">
            <forename>Sergio</forename>
            <surname>Salamone</surname>
            <placeName type="affiliation">ISTAT, Italian National Institute of Statistics, Italy</placeName>
          </persName>
          <persName n="2">
            <forename>Alessandro</forename>
            <surname>Faramondi</surname>
            <placeName type="affiliation">ISTAT, Italian National Institute of Statistics, Italy</placeName>
          </persName>
          <persName n="3">
            <forename>Stefania</forename>
            <surname>Della Queva</surname>
            <placeName type="affiliation">ISTAT, Italian National Institute of Statistics, Italy</placeName>
          </persName>
        </author>
        <respStmt>
          <resp>This is a section of <title>ASA 2022 Data-Driven Decision Making</title>(DOI: <idno type="DOI">10.36253/979-12-215-0106-3</idno>) by </resp>
          <name>Enrico di Bella, Luigi Fabbris, Corrado Lagazio</name>
        </respStmt>
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      <publicationStmt>
        <publisher>Firenze University Press</publisher>
        <pubPlace>Firenze</pubPlace>
        <date when="2023">2023</date>
        <idno type="DOI">https://doi.org/10.36253/979-12-215-0106-3.34</idno>
        <availability>
          <p>Available for academic research purposes</p>
          <p>Open Access</p>
          <p>Copyright Author(s)</p>
          <licence source="text" target="https://creativecommons.org/licenses/by/4.0/legalcode">
            <p>Content licence CC BY 4.0</p>
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        <p>This is original content, published for academic research purposes</p>
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      <abstract xml:lang="en">
        <p>The aim of this work is to illustrate the application of a tool to monitor regional smart specialization strategies, a place-based european approach characterised by the identification of strategic areas for intervention on r&amp;s and innovation as a driving factor for development and territorial competitiveness. Therefore a new classification of enterprises has been defined, that represents all the dimensions of smart specialization, such as innovation, r&amp;s, human capital, business relations, environmental sustainability, ability to drive the territorial development. This work introduces the results of a composite indicator on the microdata of the italian business census 2019, integrated with Istat business registers, identifying a score for each individual enterprises, rather than on aggregates (e.g. territorial). The idea is to have a synthetic value on microdata in order to calculate indicators on aggregates, for example on economic activities of enterprises, defined with respect to new policy needs. The results provide indications of potentials and strategic development trajectories of regional economies. The methodology adopted offer different opportunities for analysis: it’s possible to evaluate the areas of smart specialization chosen by each Italian region for the coesion funds' 2021-2027 planning, which dimensions are stronger or weaker on each area, in order to give indications on investments and intervention priorities. It's possible to get an objective analysis of the region or country current situation in terms of research, innovation, industrial structures, skills and human capital. The output of this work is presented through different dashboards of outcome indicators for the Italian smart specialization areas at the regional or national level.</p>
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      <textClass>
        <keywords>
          <list>
            <item>Composite indicator</item>
            <item>Innovation</item>
            <item>R&amp;S</item>
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      <p>It is available online at https://doi.org/10.36253/979-12-215-0106-3.34<ref target="https://doi.org/10.36253/979-12-215-0106-3.34" /></p>
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        <listBibl>
          <head>References</head>
          <bibl n="112073">
            <bibl>Balland, P.-A., Boschma, R., Crespo, J., Rigby, D.L., 2019. Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification. Reg. Stud. 53, 1252–1268.</bibl>
            <idno type="DOI">10.1080/00343404.2018.1437900</idno>
          </bibl>
          <bibl n="112074">
            <bibl>D’Adda, D., Guzzini, E., Iacobucci, D., Palloni, R., 2019a. Is Smart Specialisation Strategy coherent with regional innovative capabilities? Reg. Stud. 53, 1004–1016.</bibl>
            <idno type="DOI">10.1080/00343404.2018.1523542</idno>
          </bibl>
          <bibl n="112075">Gianelle, C., Guzzo, F., &amp;amp; Marinelli, E. (2019). Smart Specialisation Evaluation: Setting the Scene. Smart Specialisation – JRC Policy Insights, JRC116110, March.</bibl>
          <bibl n="112076">Barca F. (2009), An Agenda for a reformed Cohesion policy. A place-based approach to meeting EU Challenges and Expectations. Independent Report to D. Hubner. Bruxelles: Commissioner of Regional Policy</bibl>
          <bibl n="112077">OECD (2008) &amp;quot;Handbook on constructing composite indicators: methodology and user guide&amp;quot;. OECD Pubblications, Paris</bibl>
          <bibl n="112078">Lazarsfeld P.F. (1953), Mathematical thinking in the social sciences. Glencoe: The Free Press. Journal Article</bibl>
        </listBibl>
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