New programming period 2014--2020 (cohesion funds, Horizon 2020, etc.:synergies and complementarities of funds and integration of policies and instruments.
(I) SWOT Analysis R&d&i 14 Strengths Availability of broadband coverage throughout the territory (universal service).
Computer equipment and Internet access; digital natives; use of mobile devices. Existence of facilities and centers of reference in ICT.
Extensive use of electronic means, especially in the relation with Public Administration, and within it (e--health, e--education).
New technologies (satellite, mobile broadband) instead of infrastructures. New trends: social networks, mobility and geolocation; telework; Cloud computing, pay--peruse models;
Open Data, demand for contents, more usable technologies closer to citizens, etc. Growing possibilities for use of ICT in the public sector (energy saving, education, health, social care.
New models of public--private cooperation that reduces costs (synergies. Building the evidence base for RIS3 (II) SWOT Analysis Knowledge Digital Society 17 Threats Low prokitability for operators in rural areas;
sustainability of infrastructures. Complexity of the regulatory framework on ICT. Low conkidence in digital environment.
Components & Equipment Agro--food Health & Quality of life Energy & Environment Habitat Tourism, Heritage & Spanish language 1. Encourage the deployment of telecommunications networks
and services to ensure digital connectivity. 2. To develop the digital economy for the growth and competitiveness of enterprises. 3. To improve the effectiveness,
sensors, embedded systems, data mining, etc. Robotics Intelligent infrastructures (roads, logistics: sensors, monitoring, etc. Bio--fuels: sunalower, bio--forest waste, etc.
We use scare quotes around the term‘school'to suggest a‘scholarly alignment of concerns and outlooks,
'‘new global protest movements'and in developing practices around social media. It is also being brought to bear in recognised policy domains,
http://www. weforum. org/content/global-agenda-council-social-innovation-2013 6 http://www. eiseverywhere. com/ehome/index. php?
brokering services and trading sites aimed at SMES (Gann and Dodgson (2007: 12). Notions such as user innovation (Von Hippel, 2005) and‘user-led innovation'highlight the source from
Co-creation has been boosted as a result of the growth of social media (OECD, 2007. There is now an extensive and growing literature on the impact that internet and social media tools (such Facebook, Twitter and Instagram,
often supported by mobile technologies) are having on patterns of business and social interaction. Radical claims are being made for social media technologies
and the empowering effect they are having in elevating the role of the consumer in the innovation process, both with firms and with each other in terms of new peer-to-peer relationships.
Google, for example, tested Gmail, Google Circles and Google+in this way. Summarizing a decade of innovation research around the impact of digital technologies,
WP2 Embracing Social Innovation Page 15 Notions such as‘co-creation',‘crowdsourcing',‘prosumers'(Toffler, 1980) 10 and‘mass collaboration'(Tapscott and Williams, 2008;‘
and local government levels in adopting social media tools (GOSS Interactive, 2013). The main objectives of investment were improving web site presence and greater and richer interaction with customers.
and by the perceived‘read-write'characteristics associated with Web 2. 0 and social media (Chadwick, 2009).
A number of initiatives are emerging at local government level12 in Europe in terms of interactive webs, wikis,
crowdsourcing, utilising big data; but much of this is still in experimental mode13 and European cities tend to lag those in the US14.
Although mainly restricted to information technology innovation activities, these initiatives are now spreading to other domains.
and gather information, through open data gathering techniques, crowdsourcing and so on. The potential importance of digital dialogue, including for Smart Specialisation for Regional Innovation:
constraints on internally generated funds are compounded by the fact that the sector does not register on the radar screens of conventional banks
The societal challenge perspective will also be an important feature of Cohesion Policy in the 2014-2020 programming period.
and synergies to be exploited by better integrating social challenges at the core of innovation activities.
a region is more likely to be a node in a European or global network. Smart Specialisation for Regional Innovation:
are prepared increasingly to experiment with social network technologies-from simple systems like Skype to other more sophisticated tele-presence systems
this concluding section is structured to reflect the four core themes of WP2. 6. 1 Conceptual linkages between S3
The concept of the mundane economy embraces sectors that loom large in meeting core human needs-such as health education, food, water, housing, energy, social care and the like
This socio-ecological critique challenges the conceptual core of the S3 concept-which is need that regions to differentiate themselves,
Pioneering private sector firms like Google and Dyson demonstrate an enlightened sense of self-interest when they give talented employees
housing, food etc), supported by a set of common catalysts (eg ICT and public procurement).
Our core argument here basically consisted of two warnings to policy-makers and practitioners alike:(i) that the social enterprise sector was too heterogeneous to justify generalisations about its contribution to either S3
because the core argument of this reflections paper is that social innovation is too amorphous and heterogenous a concept,
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How Information technology is Reshaping the Economy. Cambridge, Mass: MIT Calzada, I. 2013) Knowledge building and organizational behavior:
Edward Elgar Castells, M. 2001) The Internet Galaxy. Oxford: Oxford university Press Smart Specialisation for Regional Innovation:
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research in the European union Approaches, findings and future directions policy review Chadwick, A. and Howard, P. N. 2009) New directions in internet politics research, in Chadwick, A. and Howard
, P. N. 2009 (eds) The Routledge Handbook of Internet Politics. Abingdon, Oxon: Routledge Charles, D.,Gross, F. and Batchler, J. 2012) Smart Specialisation and Cohesion Policy A strategy for all regions?
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http://www. tepsie. eu/index. php/publications Last accessed 15.12.13 Davies, A, Simon, J, Patrick, R and Norman, W. 2012)‘ Mapping citizen engagement
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) Public sector digital engagement and social media. Plymouth, UK: GOSS. Retrieved from: http://www. gossinteractive. com. Haddock, S v. 2013) Introduction:
http://www. innovationfutures. org/sites/default/files/INFU%20final%20report%20march%202012 0. pdf Lévesque, B. 2013) Social innovation in governance and public
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Information technology, Innovation and Creativity. Report to the National Research Council. Washington D c: The National Academies Press Smart Specialisation for Regional Innovation:
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New approaches to transforming public services http://www. nesta. org. uk/sites/default/files/social innovation policy brief cover. pdf Noya A. ed.)(2009) The Changing Boundaries of Social Enterprises.
OECD (2007) Participative Web and User Created Content: Web 2. 0, Wikis and Social networking. Paris:
OECD. Available for download at: http://www. oecd. org/fr/sti/ieconomie/participativewebandusercreatedcontentweb20wikisandsocialnetworking. htm OECD (2008b)‘ Shaping Policies for the Future of the internet economy'.
'Prepared for the OECD Ministerial Meeting on the Future of the Internet Economy, Seoul, Korea, 17-18 june 2008.
OECD (2010) SMES, Entrepreneurship and Innovation. Paris: OECD OECD (2011) Fostering Innovation to Address Social Challenges, Workshop Proceedings, http://www. oecd. org/sti/inno/47861327. pdf Oeij, P
. R. A.,Dhondt, S.,Korver, Ton. 2011) Workplace Innovation, Social Innovation, and Social Quality International Journal of Social Quality, 1, 2, 31-49 (19) Oosterlynck, S. 2013)‘ Introduction:
how social media changes the way we live and do business, Hoboken, NJ: John Wiley and Sons RESINDEX (2013) A regional index to measure social innovation.
The Report of the High-level Panel of Eminent Persons on the Post-2015 Development Agenda.
Regional Innovation Monitor, Thematic Paper 6. Prepared for DG Enterprise and Industry. Available at http://ec. europa. eu/enterprise/policies/innovationpolicy/regionalinnovation/monitor/index. cfm?
Incases wherethisinformationwasnotavailablefromcurrentcompanies'websites, orifthecompanies'websiteswerenolongeractive, the Internetarchive'swaybackmachinewasusedtovisitthepast websites (Yadavetal. 2007). ) Dataon firms'inventiveportfolios wascollectedusingpatstat.
finished productsmadefromfabricsandsimilarmaterials2350. 9193.28 Agricultural production 0140.7394.01 Heavyconstructionotherthanbuildingconstructioncontractors1640. 7394.74 Textilemillproducts 22 40.7395.46 Food andkindredproducts 20 30.5496.01 Printing, publishing, andalliedindustries 2730.5496.5515.0095.00 Building
gas, andsanitaryservices 49 30.5497.64 Leather andleatherproducts 3120.3698.00 Oil andgasextraction 1320.3698.3715.00100.0 Building materials, hardware, gardensupply, andmobilehomedealers5220. 3698.73 Mining andquarryingofnonmetallicminerals, exceptfuels1410. 1898.91 Construction specialtradecontractors
<http://www. wipo. int/export/sites/www/freepublications/en/licen sing/903/wipo pub 903. pdf>.Wooldridge, J. M.,2002.
download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and multimedia products in your own documents, presentations, blogs,
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and Antonella Noya (Chapter 5). Further written inputs were provided by Stefano Menghinello, National Statistical Institute, Italy (the spatial clustering analysis and annexes in Chapter 3) and Andrea
This book presents the relevant data and policy information from 40 economies around the world,
In addition to presenting the data, the report also explores the policy imperatives in three major yet insufficiently recognised action areas that are new to much of the policy world.
How can we upgrade capabilities within the SME workforce? What skills are needed to start firms that will innovate?
providing up-to-date data and highlighting current policy issues of greatest concern. It draws in particular on the expertise and analysis of the OECD's Working Party on SMES and Entrepreneurship and the Directing Committee of the Local Economic and Employment Development Programme.
To download the matching Excel spreadsheet, just type the link into your Internet browser, starting with the http://dx. doi. org prefix.
and your PC is connected to the Internet, simply click on the link. You'll find Statlinks appearing in more OECD books.
Notes on the country data...128 Chapter 3. Knowledge Flows...131 Introduction...132 How knowledge affects entrepreneurship...
134 The geographical clustering of knowledge-intensive activities...136 The role of local knowledge flows for spatial agglomerations and local innovation systems...
The ORBIS Database...158 Annex 3. A2. The LISA Methodology...161 Chapter 4. Entrepreneurship Skills...
Presents a set of country-level data on SMES, entrepreneurship and innovation performance, and a review of major policies and new policy developments in the field.
The data also show substantial EXECUTIVE SUMMARY SMES, ENTREPRENEURSHIP AND INNOVATION OECD 2010 17 shares of total activity accounted for by each of the sub-categories of micro,
The data suggest that SMES innovate less than large firms across a range of categories including product innovation, process innovation, non-technological innovation, new-tomarket product innovations and collaboration in innovation activities.
There is strong spatial clustering in knowledge-driven sectors, i e. those where R&d intensity, basic university research and highly-skilled workers are most important.
such as in research and development, legal, information technology, marketing and other knowledge-intensive activities. Their advice and joint work with SME workforces upgrades skills, increasing the ability of SMES to develop,
absorb and apply knowledge in their broader innovation processes. Yet despite the capacity to support learning in this way,
Learning processes are at the core of entrepreneurship and SME innovation. Yet many emerging and potential business creators are lacking entrepreneurship skills such as in risk assessment,
2009). 2 The Global Entrepreneurship Monitor survey in 53 countries suggests that only 6. 5%of new entrepreneurs are highexpectation entrepreneurs,
New technologies such as computer-numerically-controlled production tools have made it possible for small firms in many industries to produce small batches as efficiently as large firms once produced large batches.
and data is not commonly available for non-technological innovation as a proportion of firm employment or turnover.
or contestability of their markets, may force incumbents to upgrade. Empirical evidence across 24 countries confirms the relationship between productivity growth
representing revolutions in technologies and markets (e g. the assembly line, the integrated circuit, the personal computer). Incremental innovations are the opposite:
The ordinary SME has a more important role in this mode, making incremental innovations that upgrade traditional sectors (Asheim, 2009.
Chapter 2 provides data on SME innovation performance and constraints across 40 economies and examines the major and new policies that have been introduced.
Definitions Supporting Frameworks for Data Collection, OECD Statistics Working papers, 2008/1, OECD Publishing, Paris, doi: 10.1787/243164686763.1.
Autio, E. 2007) Global Entrepreneurship Monitor 2007 Global Report on High-Growth Entrepreneurship, Babson college, Massachusetts.
New Evidence from Micro Data, Ch. 1, pp. 15-82, University of chicago Press, Chicago. Baumol, W. 2002), The Free-Market Innovation Machine:
Volume II Proceedings of the Brasilia Conference, OECD, Paris. OECD (2008), Open Innovation in Global networks, OECD:
Possibilities for Prosperity, Basic books, New york. Potter, J. 2005), Local Innovation Systems and SME Innovation Policy, in OECD SME and Entrepreneurship Outlook, OECD, Paris, pp
Each Country Note is accompanied by structural data on the SME sector and selected indicators showing SME innovation performance, perceived barriers to innovative activities
When available, data are presented also for accession countries (Chile, Estonia, Israel, Russia and Slovenia) and enhanced engagement countries (Brazil, China, India, Indonesia and South africa.
Box 2. 1. Basic methodological references Data presented in the chapter come from three main sources:
OECD Structural and Demographic Business Statistics Database; Innovation Surveys (e g. the Community Innovation Surveys; national innovation surveys;
Structural indicators of the enterprise population Data are drawn from the OECD dataset Business Statistics by Size Class,
which is part of the OECD Structural and Demographic Business Statistics Database. The dataset comprises five dimensions:
This includes significant improvements in technical specifications, components and materials, incorporated software, user-friendliness or other functional characteristics.
This includes significant changes in techniques, equipment and/or software. Marketing innovation: The implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing.
The PMR database comprises three broad sets of indicators on: state control, barriers to entrepreneurship,
significantly enhance their web facilities, and engage in e-business capabilities to help reduce their costs
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812706506652 B. Innovation performance of SMES and large firms, 2007-081
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812710434422 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812733856326 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812772716231 B. Innovation performance of SMES and large firms, 2002-041
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812823002327 B. Innovation performance of SMES and large firms, 2004-061
In order to create national coherence and synergies between the centres, a common webpage, telephone number, user evaluation system, intranet, competencies development programme,
and customer relationship management system (CRM) have been established for all five existing centres. Basic funding for the Regional Centres of Growth amounts to DKK 92.8 million a year (including administrative costs.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812824001404 B. Innovation performance of SMES and large firms, 2004-061
At each stage, the funding decision involves external panel evaluation, and only 10-20 businesses per year are expected to reach the third phase of financing.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/812888716138 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813015740451 B. Innovation performance of SMES and large firms, 2004-061
Deutsche telekom and Siemens to initiate the High-tech Gründerfonds. The amount of capital provided by the fund's investors totalled EUR 272 million.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813110872302 B. Innovation performance of SMES and large firms, 2004-061
Creation Support to New Innovative Enterprises In the 2000-07 programming period the General Secretariat for Research and Technology of the Ministry of Development launched programmes such as ELEFTHO (business incubators
on the other hand, aim to support SMES in the manufacturing sector and software industry, in buying innovative consulting services and know-how from so-called innovation agents,
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813116208667 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813126285000 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813138862470 B. Innovation performance of SMES and large firms, 2002-041
Current CSETS are in pharma-biology, digital enterprise, nanotechnology, regenerative medicine, telecommunications, software engineering, biomedical diagnostics,
next-generation localisation and sensor webs. ii) Technology Transfer Offices (TTOS) A fund of EUR 30 million has been made available to improve the knowledge flow between higher education and the enterprise sector.
most of the projects focus on software engineering, services and food. iv) Innovation Vouchers The voucher initiative offers businesses with limited experience of R&d the chance to collaborate with any of the 22 higher education institutes,
1. Data only reflect enterprises with 3 or more persons engaged. 2. As%of all firms within size class. 3. 2002-04.4.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813224252704 B. Innovation performance of SMES and large firms, 2004-062
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813326326305 B. Innovation performance of SMES and large firms, 2004-061
seeks to contribute to the manufacturing capabilities of Japanese industry by creating networks between SME companies that possess core basic technologies with downstream normal industry,
1. For manufacturing, data only reflect enterprises with 4 or more persons engaged. 2. As%of SMES with new product sales. 3. Index scale of 0-6 from least to most restrictive.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813327663628 B. Innovation performance of SMES and large firms, 2002-04
1. For manufacturing, data only reflect enterprises with 5 or more persons engaged. 2. As%of all firms within size class. 3. As%of total turnover. 4. Index scale of 0-6 from least to most restrictive.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813331118285 B. Innovation performance of SMES and large firms, 2002-042
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813367102180 B. Innovation performance of SMES and large firms, 2004-061
The Last Mile programme supported mainly information technology (IT) firms (36), %followed by advanced materials (13)
%The Entrepreneurs Fund also supported mainly the creation of IT firms (35%)followed by electronics and telecommunication (25%.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813468327202 B. Source of finance of SMES and large firms, 2002-04
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813475131677 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813487217851 B. Innovation performance of SMES and large firms, 2005-071
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813517714027 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813521857686 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813540502857 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813544660727 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813612045268 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813624112502 B. Innovation performance of SMES and large firms, 2004-061
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813727458672 B. Type of innovation by SMES, 20071 C. SMES'reasons
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813835033115 B. Innovation performance of SMES and large firms, 2004-061
and regional level) into a series of 30 core products that will share a common brand.
A number of innovation-related products are included also in the range of core business support products,
1. As%of panel respondents. 2. As%of innovating firms. 3. Index scale of 0-6 from least to most restrictive.
OECD, Product Market Regulation Database. statlink2 http://dx. doi. org/10.1787/813847876385 B. Innovation performance of SMES and large firms, 20071 C
university science parks, incubators and software parks across China. At the national level alone, by 2008 53 high-technology development zones, 62 university science parks, about 200 business incubators and 35 software parks had been developed through governmental support.
In the period 1992-2005, the revenue, industrial value added and profit of the enterprises operating in the 53 development zones grew at an average annual rate of 47.0%,30.5%and 38.2%,respectively.
Information technology (IT) The development of the IT industry in India is lauded greatly by decision makers and researchers alike.
which was followed in the year 2000 by the Information technology Act; combined, they provided legal recognition to transactions carried out by electronic data interchange.
Several other actions, including the establishment of Cyber Laws, the setting up of the Cyber Regulations Appellate Tribunal,
which include data relating to the Golan heights, East Jerusalem and Israeli settlements in the West bank. 1. Czech republic, Hungary, Korea, Mexico, Poland, Slovak Republic, Turkey. 2. Austria, Belgium, Finland
OECD, PMR Database; OECD Economic Surveys: Israel 2009. statlink2 http://dx. doi. org/10.1787/813271727207 A. Barriers to entrepreneurship, 2008 Index scale of 0-6 from least to most restrictive B. Administrative
AN OVERVIEW BY COUNTRY SMES, E 128 NTREPRENEURSHIP AND INNOVATION OECD 2010 ANNEX 2. A1 Notes on the Country Data The structural data on businesses presented in the chapter
Most data presented refer to the nonfinancial business economy, i e. ISIC Rev. 3/NACE Sections C to I and K and is subdivided into Industry (Sections C, D,
The following text gives details on the completeness of the data for each country. Australia:
but instead requires a web of relationships among firms, research organisations and governments. Knowledge flows are the quintessence of an innovation system,
thereby underscoring the importance of social networks. Adragna and Lusardi (2008), on the other hand, single out gender and age as the key determinants of entrepreneurship;
The geographical clustering of knowledge-intensive activities Activities can cluster for different reasons, such as availability of intermediate suppliers and skilled labour
These findings underline the importance of knowledge-driven clustering in knowledge-intensive industries. They are reflected also in the results of a recent OECD study of seven internationally-reputed clusters including Grenoble in France and Medicon Valley in Scandinavia.
Given the limits of official data sources for local-level analysis, we turn to firm-level information from the commercial ORBIS database on the location, nature and performance of local innovation clusters.
The ORBIS database provides insights about the spatial pattern of business demography and performance and is based on a highly disaggregated territorial breakdown that is not easily available from national statistical offices.
The use of ORBIS location information (based on company zip code or municipality of residence) and business demographic information (based on the company year of incorporation and persistence in time as an active company) has enabled development
Selected clusters are compared then using data on business demography and business performance. These findings represent some of the first outputs of an OECD project to map clusters
structural and selection biases in the original data source. 3 3. KNOWLEDGE FLOWS SMES, ENTREPRENEURSHIP AND INNOVATION OECD 2010 137 European union The first two maps show the agglomeration of HTM
and United kingdom. Given problems of comparability between the NUTS classification and the location information included in the original data source, countries such as Denmark, Luxembourg, The netherlands,
OECD elaboration based on ORBIS database available from Bureau Van dijk. Low LQ Medium-Low LQ 3. KNOWLEDGE FLOWS SMES, E 138 NTREPRENEURSHIP
which might also infer a bias in the original data sources. Secondly, KISA firms often tend to Figure 3. 2. Distribution of KISA firms in the European union (Quantiles based on LQS) Source:
OECD elaboration based on ORBIS database available from Bureau Van dijk. Low LQ Medium-Low LQ Medium-High LQ High LQ 3. KNOWLEDGE
and telecommunications has made it possible for firms to separate production from management, with the former being relocated to areas with same-sector specialisation
the second type is built from a statistical algorithm for analysis of spatial agglomeration named LISA (i e.
Figure 3. 5 points out the location of KISA firms in the United states using the same data source,
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software. 1st range (0) 2nd range (891) 3rd range (516) 4th range (493) 5th range (488) Figure 3. 4. Agglomerations of HTM firms in the United states LISA methodology Source:
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software. High-High low-Low Low-High High-low 3. KNOWLEDGE FLOWS SMES, ENTREPRENEURSHIP AND INNOVATION OECD 2010 141 Figure 3. 6, based on the same methodology
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software. 1st range (0) 2nd range (790) 3rd range (400) 4th range (401) 5th range (399) 6th range (398) Figure 3. 6. Agglomerations of KISA firms in the United states
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software. High-High low-Low Low-High High-low 3. KNOWLEDGE FLOWS SMES, E 142 NTREPRENEURSHIP AND INNOVATION OECD 2010 Cluster rankings:
A preliminary exploration The combination of different indicators of business demography and business performance at the local level calculated experimentally from the ORBIS database can lead to an international analysis of the strength of clusters based on a composite indicator.
In the case of the US clusters, given data source constraints for this country, the composite indicator is limited to the first three variables in the list.
OECD elaboration based on ORBIS database available from Bureau Van dijk. statlink2 http://dx. doi. org/10.1787/814040554856 Name of business cluster Country New
OECD elaboration based on ORBIS database available from Bureau Van dijk. Ranking Name of business cluster Country of residence 1 Boston (Route 128) United states 2
OECD elaboration based on ORBIS database available from Bureau Van dijk. statlink 2 http://dx. doi. org/10.1787/814047837382 Name of business cluster Country
OECD elaboration based on ORBIS database available from Bureau Van dijk. Ranking Name of business cluster Country of residence 1 Silicon valley United states 2 Austin ITC
E 144 NTREPRENEURSHIP AND INNOVATION OECD 2010 The role of local knowledge flows for spatial agglomerations and local innovation systems The above section illustrated the phenomenon of spatial clustering of economic activity
briefly summarised here, suggests that local knowledge transfers are important to this clustering process. This literature stresses the fact that knowledge does not spill over long distance
Knowledge spillovers decay with distance Unlike information that can be exchanged easily through the Internet, the knowledge that drives long-term growth is technical, detailed and context-specific (Auerswald, 2007).
%A relationship therefore exists between knowledge spillovers, spatial clustering and innovative output (Giuliani, 2005. This is especially true for knowledge-driven sectors,
Examples include transitions from telephone handset production to mobile Internet system design or from vehicle production to GPS, road sensing and safety equipment (OECD, 2007b.
Despite the increasing importance of university-industry knowledge transfers and of public schemes that try to bolster such transfers, it is difficult to produce reliable and comparable data on this phenomenon.
In addition, data collection is regular in some countries but sporadic in others. 3. KNOWLEDGE FLOWS SMES,
Data show that KTOS have a much longer tradition in the United states than in Europe.
Finally, data on university spin-offs in the two different contexts diverge much more slightly, with nearly 2 spin-offs per KTO a year in Europe and nearly 3 in the United states. University-industry knowledge transfers are also of increasing importance in Asia;
Data, however, show that knowledge transfer is still incipient in China. Universities have a great number of patents (126 per KTO),
ICT, electronics and telecommunications), companies tend to look for partners to keep up with new developments within the same sector and in related industries.
Tolerance and access to social networks appear to be key factors in attracting skilled, entrepreneurial and career-minded people.
Based on these core messages the following key policy recommendations are formulated. Key policy recommendations Design advice and training programmes for start-up entrepreneurs who have strong technological knowledge
about 200 business incubators and 35 software parks (see China's Country Note). Cooperatives and business consortia can also support small-firm upgrading through, for example, joint technology purchase.
computers and office machinery (30; electronics-communications (32; scientific instruments (33. KISA comprises: post and telecommunications (64;
computer and related activities (72; research and development (73). 3. An overview on the ORBIS database is given in Annex 3. A1. 4. Patent protection can be sought abroad
but the applicant must apply within one year of the date of the application first filed inside his/her country.
These patent applications may link to the earlier filing date of the original application. This is known as priority patent application. 5. Based on international rules,
Evidence from European Patent Data, European Economic Review, Vol. 47, pp. 687-710. Cantner U.,M. Goethner and A. Meder (2007), Prior Knowledge and Entrepreneurial Innovative Success, Jena Economic Research Paper, No. 2007-052.
Christensen, C. 1993), The Rigid Disk drive Industry: A History of Commercial and Technological Turbulence, Business History Review, Winter, No. 67, pp. 531-588.
and Economic Development, OECD, Paris. OECD (2005), SME and Entrepreneurship Outlook, OECD, Paris. OECD (2007a), Competitive Regional Clusters:
KNOWLEDGE FLOWS SMES, E 158 NTREPRENEURSHIP AND INNOVATION OECD 2010 ANNEX 3. A1 The ORBIS Database The scope of ORBIS for territorial analysis The ORBIS database, developed
is a source of business micro data. The database includes around 40 million companies, has a geographical coverage of up to 200 countries,
and can consider all sectors of economic activity. There are no exclusion thresholds in terms of enterprise size, unless national limitations reduce the coverage of administrative data sources.
Given national data source constraints there is plenty of information at the firm level about sector, legal status, ownership and an array of financial and economic variables.
The target population consists of firms with a corporate legal status, which means that micro firms with less than ten employees may be excluded largely from this database.
The value of the ORBIS database for territorial analysis rests on the possibility to rearrange firm-level data according to detailed company location.
The information on company location relates to the complete address, which includes street, city and postal code.
A wide range of entrepreneurship, economic performance and financial indicators can be calculated at the local level from the ORBIS database:
Business demographic indicators, e g. business birth rate; survival rate; distribution of firms by age, etc. Economic performance indicators, e g. labour productivity;
While economic performance and profitability indicators can be calculated from the ORBIS database at different levels of industry
Limited information available in the ORBIS database on complex business demography events, such as mergers and acquisitions, makes the definition of a company profile over time incomplete, with spurious effects on the calculation
Moreover, ORBIS naturally tends to overestimate real entry rates compared to real exit rates, as it is a continuously expanding database in terms of both international and national coverage.
information regarding the company's incorporation year is essential to disentangling real entry from increasing coverage effects.
In synthesis, the two different types of demographic information included in the ORBIS database i e. the date of company incorporation and the entry of a new company in the open panel dataset tend respectively to anticipate
and to postdate the real birth of a company. Potential biases of territorial data calculated from commercial databases The key territorial information included in a commercial database with firm-level data is the company's complete postal address.
Since this information is provided at the maximum available territorial detail, it can be rearranged easily according to various administrative and functional territorial classification schemes.
Two different sources of location bias can be associated with the use of this information to produce territorial data.
As already outlined in the previous section, the attribution of all company activities to a single location leads to incoherent territorial data in the case of multi-plant companies.
or legal headquarters may diverge from the place where it carries out its core economic activities.
other characteristics of commercial databases can indirectly alter the consistency of territorial data calculated from this sort of source.
Coverage restrictions concern the under-coverage of the set of companies extracted from the database with respect to the relevant target population,
Under-coverage is induced generally by threshold effects in which firms under a certain size are included not in the original data sets
or by additional restrictions on revealing information on small areas imposed by the database provider.
A structural bias is a systematic deviation from the target population in the sample distribution of key economic variables (number of firms
Structural biases may be induced by a number of factors such as restrictions in the database and poor data quality consistency across industries, regions,
A selection bias can be generated by the presence of selectivity criteria in the database, for instance the exclusion of all companies with some specific legal status.
E 160 NTREPRENEURSHIP AND INNOVATION OECD 2010 The extent to which statistical biases affect indicators Territorial data in the form of absolute values are affected by coverage restrictions, structural bias and selection bias.
This is because simple aggregations of micro data by relevant territorial units completely mirror the characteristics of input data.
may mitigate the negative impact of coverage restrictions and structural bias. If coverage restrictions or a structural bias homogeneously affect the spatial distribution of the sample e g.
SMES are underrepresented in the same direction and with the same magnitude in all territorial areas the standard location quotient (LQ) tends to neutralise these sources of bias in the input data Dynamic territorial indicators, such as employment or labour productivity
growth rates in a given period, present particular characteristics in terms of potential sources of bias as compared to static territorial indicators.
While the consistency of static territorial indicators is altered by an uneven spatial distribution of the sample of micro data as compared to the target population,
since commercial databases are upgraded sometimes in terms of coverage and data quality. This database upgrading may induce a structural break that can alter the spatial distribution of companies by increasing
or decreasing the magnitude of a static territorial bias. Spatial) econometric modelling may also represent a possible way to deal with different types of territorial bias in the data.
In particular, if model regressors absorb some sources of bias, this econometric approach may provide interesting and unbiased results.
This discussion balances the unquestionable informative relevance of commercial databases to carry out nonstandard territorial analysis with an insight into the methodological problems that may affect the consistency of these territorial data.
In the case of uneven spatial clustering global spatial indicators, such as Moran'S i, are found to be less useful and local indicators of spatial association (LISA) have been developed (Anselin, 1995.
Moran'S i and LISA differ in data employed and analytical scope. Moran'S i is a global measure of spatial autocorrelation.
and the overall pattern in the data is summarised in a single statistic. In contrast, LISA calculates a local version of Moran'S i for each areal unit in the data.
In particular, LISA shows statistically significant groupings of neighbouring areas with high and low values around each region in the study area.
However, the scope of these indicators should be limited to exploratory data analysis. In the absence of a well-defined spatial modelling framework,
E 164 NTREPRENEURSHIP AND INNOVATION OECD 2010 The importance of entrepreneurship skills for SMES and start-ups Learning processes are at the core of entrepreneurship and SME development.
data confirm the existence of a skills and training problem holding back innovation. Across OECD countries, employees of SMES participate in formal training activities to only half the extent that staff in large firms do (OECD, 2010b, forthcoming.
Green Specific skills to modify products, services or operations due to climate change adjustments, requirements or regulations (e g. water purification and site remediation planning/engineering in mining, solar panels
Box 4. 1. Core characteristics of entrepreneurs Knowledge. An entrepreneur is able to identify and extract knowledge that is relevant.
because they require the integration of several other skills, with both a horizontal understanding of business development and a vertical specialisation in one or more fields related to core competitive advantage.
Teachers are pressed hard to deliver on their core programmes the basis for recruitment and promotion and those not working on core activities can find it difficult to justify strong investments in what may be seen by their hierarchies and peers as side projects, whatever the expressed interest of the students.
Teaching approaches must also evolve to accommodate how entrepreneurship skills are learned best rather than be tethered to traditional classroom forms.
and people working in micro businesses, for example plumbers, painters, electricians and information technology specialists. Other people go on to work in larger SMES
1) Successful learners are skilled in generic processes and activities such as core skills; appreciate the relevance of what they are learning;
Across the EU-15 countries, data from the Eurostat Continuing vocational training Survey show that employees in enterprises with less than 50 employees receive significantly less in-company training than employees in larger firms.
At the heart of this are knowledge intensive service activities (KISAS) such as electronic commerce, information technology, market research,
Examples from this group include the provision of management skills for integrating e-commerce into the core business.
Small firms must rely on training skills available locally, on the way the ecosystem upgrades these skills, and on the way the services are offered (Hall and Lansbury, 2006).
Governments have a critical role to play as catalysts here, providing an appropriate policy context and support for the resources,
2006), Knowledge Intensive Service Activities (KISA) in Software Innovation, International Journal of Services Technology and Management, IJSTM Special Issue, Vol. 7, No. 2, pp
Martinez-Fernandez, C.,C. Soosay, V. V. Krishna, T. Turpin, M. Bjorkli (2005b), Knowledge Intensive Service Activities (KISA) in Innovation of the Software
OECD (2002), Management training in SMES, OECD, Paris. OECD (2003), OECD Employment Outlook, OECD, Paris. OECD (2005), SME and Entrepreneurship Outlook, OECD, Paris
The Social Entrepreneurship Monitor is a special report of the Global Entrepreneurship Monitor (GEM) UK project to estimate the percentage of social entrepreneurs in UK society using population survey data.
recent UK data released by the Third Sector in July 2009 (www. cabinetoffice. gov. uk/media/231495/factoids. pdf) refer to an estimated average (2005-07) of 61
8 in July 2009) out of 515 organisations that applied (data elaborated for OECD by the Korea Labor Institute and the Research Institute of Social Enterprise.
The study can be downloaded at www. socialeconomy. eu. org/spip. php? article420. In the United states, the Johns Hopkins Nonprofit Economic Data Project (NED) is generating information on the dynamics of the nonprofit sector by analysing diverse datasets on nonprofit organisations,
including data on nonprofit finances, employment and wages, and volunteering. The website of the project (www. ccss. jhu. edu/index. php?
section=content&view=9&sub=10 accessed on 28 october 2009) reports that: Nonprofit employment is much larger than expected and much more widely dispersed,
outdistancing many major industries in its contribution to state employment and payrolls; Nonprofit employment is dynamic,
therefore, at pursuing both radical and incremental social changes. 5. Is social entrepreneurship a local phenomenon or a global one?
7 in this particular case the core mission is to provide health services, but in conjunction with preventing illness through a wider approach to the different factors influencing illness (poor housing and diet).
5. SOCIAL ENTREPRENEURSHIP AND SOCIAL INNOVATION SMES, ENTREPRENEURSHIP AND INNOVATION OECD 2010 193 Health-related problems are at the core of the initiative of pharmaceutical scientist Victoria G. Hale,
p. 1). Social networks based on Information and Communication Technologies (ICT) are also gaining importance both as social innovation in themselves and as producers of social change (De Biase, 2009),
Social innovation can be driven by governments (new models of public health), the private sector (open source software) or civil society (fair trade)( Mulgan et al.
five-year IDA pilot project with 13 competitively selected community partner sites operating 14 programmes in a mix of urban and rural locations across the country.
Supported by the Brazilian National Secretariat for Economic Solidarity, partner of several Brazilian traditional banks, supported by global networks of social economy organisations;
www. iledefrance. fr. 5. SOCIAL ENTREPRENEURSHIP AND SOCIAL INNOVATION SMES, E 202 NTREPRENEURSHIP AND INNOVATION OECD 2010 The following provides an outstanding example of how social media
and social networks can contribute to connect people and good causes. In this case a web based platform has opened up the boundaries of donation mechanisms to support among others also social enterprises and socially innovative initiatives.
Box 5. 10. Social Impact Bonds (United kingdom) Social Finance was created from the Commission on Unclaimed Assets,
www. socialfinance. org. uk/downloads/SIB REPORT WEB. pdf. Box 5. 11. ammado: A global platform harnessing social media for social goods ammado is a global platform
which connects nonprofit organisations, sociallyresponsible companies and engaged individuals in a unique environment of shared interests.
and power of Web 2. 0. It was founded as a mission-based, for-profit enterprise, in Dublin in 2005 by a serial entrepreneur, Peter Conlon,
and challenges in harnessing social media for social good. After four years of building the ammado platform the site was launched in June 2008
and is currently available in 12 languages (Dutch, English, French, German, Italian, Japanese, Korean, Polish, Portuguese, Spanish, traditional and simplified Chinese) connecting individuals from 130 countries
A global platform harnessing social media for social goods (cont. nonprofits to promote their cause (s)
The integration of company profiles, vast and various web tools and a secure donation interface called the Giving Circle make ammado a one-stop shop. ammado facilitates charitable contributions from everyone, worldwide,
A wave of response from Italians and others around the world wanting to send immediate relief was being thwarted by a series of difficulties on the IRC site,
from language (many 2nd 3rd generation Italians do not have command enough of the language to navigate an Italian-language site) to payment methods accepted (to date,
many Italian npo sites require a bank transfer or Italian credit card, limiting international donations. As a stopgap, The irish Red cross and American Red cross accepted donations through ammado and spread the word about their initiative.
In addition to online donation capabilities, ammado offers giving vouchers and interactivity with other social networks like Facebook and Twitter.
Nonprofits can add the Donate Now box to their Facebook Fan Pages. The ammado donations widget is one of the platform's latest features.
The cutting-edge micro-donations software is a compact vibrant space, the same size as an iphone screen
and can sit on any website, blog or social network profile that can accept embeddable HTML.
It has a welcoming image which invites visitors to donate. By clicking donate they are brought through the donation process then
and there without navigating away from the site/blog. In 2008, Edelman Goodpurpose released a study on Mutually beneficial marketing:
Why business and brands need a good purpose, which stated that, New findings...reveal that nearly seven in 10 (68%)consumers would remain loyal to a brand during a recession
if it supports a good cause. That same study stated that 76%of consumers globally like to buy from brands that make a donation to worthy causes.
In June 2009 ammado was honoured as Laureate of The Computerworld Honors Program for its achievement in the application of information technology to promote positive social, economic,
it displays various degrees of innovation and change; it is constrained by the external environment (p. 10.
Harding, R. 2006), Social Entrepreneurship Monitor: United kingdom 2006, Foundation for Entrepreneurial Management, London Business school, full paper available at www. london. edu/assets/documents/PDF/Gem soc ent web. pdf. Harris, M
and this requires the display of innovativeness, proactiveness and risk management behaviour. This behaviour is constrained by the desire to achieve the social mission
very wide boundaries from gay partnerships to new ways of using mobile phone texting, and from new lifestyles to new products and services.
and technology, including aerospace, pharmaceuticals, computers and office machinery, electronicscommunications, and scientific instruments. Incremental innovation An improvement on existing products or processes that is achieved through internal R&d,
Knowledge-intensive service activities (KISA) These are sources and carriers of knowledge in sectors such as research and development, legal services, computing and information technology and marketing.
post and telecommunications; computer and related activities; research and development. Learning failure A type of systemic failure occurring
when firms in an innovation system have not developed sufficient absorptive capacity to codify and introduce new knowledge in their business operations.
In addition, country notes present statistics and policy data on SMES, entrepreneurship and innovation for 40 economies, including OECD countries, Brazil, China, Estonia, Indonesia, Israel, the Russian Federation
www. sourceoecd. org/9789264080317 Sourceoecd is the OECD online library of books, periodicals and statistical databases.
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