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Chapter 6 Regions, Innovation, and the North-South Divide in Italy

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Background – Helen Lawton Smith

  • Applicability of the Triple Helix concept through time and space and its capacity for understanding synergies and inter-disciplinarity research and application.
  • Triple Helix in diverse country regional and sectoral contexts

e.g. in Oxfordshire, Cambridgeshire, Centro region in Portugal and Gothenburg

    • Understanding alignment and agency in triple helix models especially at the regional level
    • How do regions change over time as a consequence of interaction between firm level and regional level changes?
    • How do interactions change as governance structures change (inc. dialogue, leadership, power relationships)?

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The Triple Helix in a context of global change: continuing, mutating or unravelling?

  • Never has the Triple Helix mission been more timely. Globally the economy faces significant challenges – unemployment, low or no growth, spiralling healthcare needs, rapidly emerging digital business models, unsustainable changes to the environment. The need for universities and businesses to work together and take action alongside governments is critical. The 2013 Triple Helix Conference will integrate highly topical contributions on challenges in each of the three spheres of the triple helix: universities, industry and government to address the key question:��How can the Triple Helix approach build ‘the enterprising state’ in which universities, businesses and governments co-innovate to solve the global economic challenges?
  • Application to Italy?��

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Prometheus 2014

  • In this paper the evolution of the metaphor of a Triple Helix (TH) of university-industry-government relations is elaborated into an evolutionary model, and positioned within the context of global economic changes. We highlight how triple-helix relations are both continuing and mutating or changing, and the conditions under which a Triple Helix might be seen to be unraveling in the face of pressures on each of the three helices – university, industry, and government. The reciprocal dynamics of innovation both in the Triple Helix thesis and in the global economy are empirically explored: we find that “footloose-ness” of high-tech manufacturing and knowledge-intensive services counteract upon “embedded-ness” prevailing in medium-tech manufacturing. The geographical level at which synergy in TH-relations can be expected and sustained varies among nations and regions.

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Chapter 6 analysis

  • Analysis, regionally and nationally, of triple helix synergy among geographical and size distributions of firms and technology classes in Italy for 2008, 2011 and 2015 based on 20 regions.
    • cross-sectional study design allows researchers to compare many different variables at the same time (firms, sectors, regions).
  • Italy is knowledge-based and knowledge-intensive but considerable internal disparity in performance
    • Also raises issues of geographical scale - most synergy found by considering Italy as two parts – Northern and Southern with Tuscany in the North
  • Policy application – need for different innovation strategies to be developed

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Cultural, methodological v economic geography issues

  • History of Italy and its culture – unified state for 150 years
  • Cultural traditions and second languages (French and German) (and have a marginal impact on synergy in the Northern Region)
  • 20 regions, 107 provinces (aligned with EU NUTS classification)
  • Industrial districts – 2011 census 141 + 611 local labour market system (SSL)(commuting patterns)
    • Assuming SSL overlap with industrial districts, data allow for economic analysis at district level – but industrial districts – not a separate administrative unit
    • Many of us cut our (academic) teeth in the 1990s and early 2000s on understanding regional innovation-led economic development/industrial transformation through works on the ‘Third Italy’ (Bagnasco 1977) (e.g. Bianchi 1991, Beccatini 2003)
    • but see Bianchi 2006 on dangers of mythologising small enterprise spatial systems
  • General issue of statistical data based on admin. units versus reality of innovation processes, that do not match regional and national boundaries
  • Should not make the choice between studying regions on nations on a priori grounds and across the board - function of regions very different in different countries as in Italy compared to UK for example

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Italy as a challenging and exemplary case

  • To what extent and at which levels is innovation-systemness indicated?
  • Can regions carry the function of regional innovation organisers?
  • How much innovation-systemness is generated at various spatial levels?
  • Is this innovation systemness distributed across regions or specialised in specific regions?
  • Synergy measure enables questions to be addressed empirically
  • If test regional innovation systems using the generation of redundancy as an indicator of synergy, it is not optimal to understand Italy as a set of regional innovation systems when synergy is measured by interactions (i) geographical distribution of firms, (ii) firm size and (iii) technological bases of firms (NACE codes)

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The region in Italy and uneven economic development

  • Devolution – regions as innovation policy-units since 2001
  • Autonomy meant sharp reduction in national budget for R&D and industry with the south most adversely affected
  • Financial crises also had harsher effect on the southern part of Italy
  • General decrease in number of firms in most regions (stagnation since 2007-9)
  • Retreat of national policy only partially offset by EU cohesion and structural funds.
  • Two innovation systems in Italy – core and small firm network (Malerba 1993)
  • Weak national innovation system – triple helix elements of universities and industry non-existent/ineffective/unorganised
  • Instead – innovation regions “glocal systems” – which makes them vulnerable

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Methods

  • Historical and evolutionary dynamics are coupled in events
  • The question of systemness can be made empirical and amenable to measurement: when the generation of redundancy prevails over the generation of uncertainty “ innovation systemness” is indicated.
  • Relevant dimensions are geographical, technological and organisational (no. of employees) (TH dimensions previously used)
    • (data do not cover agric. Fish and forestry, nor public admin and non-profits)

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Results

  • 20 regions’ contribution to national synergy in 2015 – very similar to 2008 and 2011 – and as a basis for measurement leaves 45% of national synergy unexplained (very high compared to other countries)
    • Tuscany not part of central region in this data
    • TH synergy increased in all but one region (Sardegna)
    • Strongest regions e.g. Lombardy became even stronger in contribution to national synergy
    • 8 regions in Northern Italy are well developed as innovation systems (one third of national synergy) but 47% when considered as one region

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Synergy measured

  • Data demonstrate reduction of synergy generated above national level over time consistent with progressive withdrawal of innovation policy at national level and growing importance of the region
  • but only 55% of synergy is realised at the regional level – rest – across N/S divide or Italy as a national system
  • Medium high-tech and services are distributed proportionally across Italy (services tend to uncouple from a specific location leading to negative local synergies)
  • Southern region as a subsystem – stronger national synergy effect
  • Synergy enhanced by focusing on high and medium-tech manufacturing,
  • Two metropolitan centres of innovation systems (Rome and Milan) followed by Florence and Venice

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Policy issues

  • Analytical (academic) and policy agenda – regions as appropriate scale for delivering innovation policy (EU and OECD incentives)
  • Debates about policy agenda are positioned within the need to understand boundaries – municipal, provincial, regional, national and supra-national, by sector, and by combinations of types of analyses and indicators

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Conclusions

  • Analysis is historically informed
  • Selection and selectivity are explained.
  • TH and synergies are illustrated
  • Data deficiencies may affect results