programming  period  2014- †2020  (cohesion  funds  Horizon
•†Computer  equipment  and  Internet  access  digital  natives
 use  of  mobile  devices  •†Existence  of  facilities
 Computing  pay- †per- †use  models  Open  Data
 demand  for  contents  more  usable  technologies  closer  to
 telecommunications  networks  and  services  to  ensure  digital  connectivity
 data  mining  etc   •†Robotics   •†Intelligent
display a lower proï tability though, due to the imperfections inherent in invention market transactions and
fax: Ã 44 20 7040 8328 2 Tel.:Ã 351 217 214270; fax: Ã 351 217 270250
Technovation 41-42 (2015) 38†50 require ï rms to incur the private costs related to search and ne
-erlying the inventions often displays tacit components in addition to codiï ed components (Arora, 1996; Winter, 1987.
examining the software secu -rity industry, found thatmft raise the value of marketing capabilities in
3. 1. Sample and data We used a cross-sectional dataset of Europe-based SMES across all
choice of employing a cross-sectional dataset instead of a panel dataset is motivated by the concern for the reliability of yearly data
on invention commercialization strategies, provided that our sample is composed by SMES. Indeed, forming a panel dataset would require
the collection of yearly data on ï rms'invention commercialization strategies (i e. yearly data on whether each ï rm had sold or licensed
its inventions to other ï rms or had embodied its inventions into products). ) Having conducted an accurate and extensive pilot search
on multiple data sources (including Business & Industry, Factiva Zephyr and Securities Data Corporation databases as well as com
-pany web sites and specialized websites) we discovered that collect -ing yearly data for small private companies was problematic since
these ï rms do not receive systematic media coverage. Therefore it is not possible to ï nd each licensing agreement or each product
launched by each of these companies in each single year reported on public sources However, our pilot search supported the idea that expanding our
cross-sectional analysis to a time window of six years would lead to a reliable assessment of ï rms'strategies.
announced on a website or in a corporate report is quite high. Sim -ilarly, if a company has launched products based on its inventions
this information is likely to appear at least once on the materials we collected on the company in the six years window of reference
only a way to bypass the reliability problem that a panel approach would cause, but also a more appropriate approach from the stand
-point of yearly data variability. The choice of using a cross-sectional dataset is in fact in line with other studies in the ï eld such as Arora
Company names identiï ed from the patent database have been matched with company names from the Amadeus database (Bureau
Van dijk; hence both listed and non-listed companies were incl -uded in our sample. Checks for misspelling of company names were
employed to collect the data that we used in this study. Data on ï rms'vertical integration and invention trade were collected and
triangulated through an extensive search of press releases, including Business & Industry, Factiva, Zephyr and the Securities Data Corpora
-tion (SDC) databases as well as from company web sites. In cases where this information was not available from current companies
'websites, or if the companies'websites were no longer active, the Internet Archive's Wayback Machine was used to visit the past
websites (Yadav et al. 2007). ) Data on ï rms'inventive portfolios was collected using Patstat. Data on ï rms'age were obtained from
company websites and Internet archives. Amadeus was employed to collect data on ï rms'proï tability and size across the whole time
-frame covered by this study. Finally, to obtain data on the strength of the appropriability regime across the different European countries
included in this study sample, this paper referred to publications by Park (2008) and Ginarte and Park (1997
The ï nal sample included 551 ï rms, of which 20 were technology specialists. Basic characteristics of industry afï liation and country of
origins of the ï rms included in our sample are displayed in Tables 1 and 2
Table 1 reports the industry afï liation for all ï rms in the sample on the basis of US SIC codes.
The table is organized to allow for an immediate comparison between the distribution across industries of the overall sample and the distribution across industries of the
31.4%,Industrial and Commercial Machinery and Computer Equip -ment), SIC 34 (11.98%,Fabricated Metal Products, Except Machinery
%Industrial and commercial machinery and computer equipment 35 173 31.40 31.40 Fabricated metal products, except machinery and transportation equipment 34 66 11.98 43.38 2 10.00 10.00
Electronic and other electrical equipment and components, except computer equipment 36 43 7. 80 60.25
Building materials, hardware, garden supply, and mobile home dealers 52 2 0. 36 98.73 Mining and quarrying of nonmetallic minerals, except fuels 14 1 0. 18 98.91
Amadeus database having been granted at least 1 patent that had been applied at the EPO ofï ce in 1996†2001,
-tive performance, we refer to patent data. However, patents substan -tially vary in their economic and technological value (Griliches, 1984
Industry, Factiva, Zephyr and the Securities Data Corporation (SDC databases as well as company websites and specialized websites) to
identify announcements and reports mentioning the name of the ï rm. We used the Internet Archive's Wayback Machine to visit the
version of the websites published in the period 1996†2001 (Yadav et al. 2007). ) We read the full text of all announcements.
To assess whether the company had engaged in licensing activity we referred to the content of the announcement.
-iï ed their strategy on their website or in their reports. When this information was not available,
we searched the company website to check whether any products were advertised. We also searched news
i e. whether (1) the data are representative of the overall populations of technology specialists in Europe in the time period considered;(
limited data are available publicly on the population of SMES who are technology specialists. Hence, we believe that the selected sample is
also regard other players, like large ï rms or users. Future research should therefore investigate to what extent
However, we acknowledge that the panel data on technology commercialization strategies of small private ï rms
since these data are not available on public or commercial dataset. Future research may consider the possi
whilst the use of secondary data allows conducting such investigation only to a very limited extent, the use of surveys or in
Available at www. oecd. org/cfe/smes/2090740. pdf Park, W. G.,2008. International patent protection:
WIPO, 2014. âoe http://www. wipo. int/export/sites/www/freepublications/en/licen sing/903/wipo pub 903. pdfâoe
Econometric Analysis of Cross-section and Panel Data. The MIT Press, Cambridge, Massachussets Yadav, M. S.,Prabhu, J. C.,Chandy, R. K.,2007.
Sample and data Variables Dependent variables Independent variable Control variables Results Discussion Implications to practice Implications to theory
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
Sourceoecd is the OECD online library of books, periodicals and statistical databases For more information about this award-winning service and free trials ask your librarian,
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Italy (the spatial clustering analysis and annexes in Chapter 3) and Andrea Piccaluga, Scuola Superiore Sant†Anna, Pisa, Italy,
data and policy information from 40 economies around the world, and so provides an insight into the
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?
data and highlighting current policy issues of greatest concern. It draws in particular on the expertise
To download the matching Excelâ spreadsheet, just type the link into your Internet browser starting with the http://dx. doi. org prefix
If you†re reading the PDF e-book edition, and your PC is connected to the Internet, simply
click on the link. You†ll find Statlinks appearing in more OECD books TABLE OF CONTENTS Table of contents
Notes on the country data...128 Chapter 3. Knowledge Flows...131 Introduction...132 How knowledge affects entrepreneurship...
The geographical clustering of knowledge-intensive activities...136 The role of local knowledge flows for spatial agglomerations
The â€oeorbis†Database...158 Annex 3. A2. The LISA Methodology...161 Chapter 4. Entrepreneurship Skills...
â 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 SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 201016 EXECUTIVE SUMMARY shares of total activity accounted for by each of the sub-categories of micro, small-and
The data suggest that SMES innovate less than large firms across a range of categories including product innovation, process innovation, non-technological innovation, new to
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.
areas, 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.
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
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
source is the consumer or user. Users and consumers are playing a growing role in
innovation, for example in helping to test new products. New ICT in particular helps users and consumers to input into decision making about product design
The key consequences are increased the importance of collaboration and the opening of innovation to SMES.
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
circuit, the personal computer. Incremental innovations are the opposite: small improvements on existing products and processes.
The DUI mode, on the other hand, is driven a user approach that relies on experienced -based know-how and informal processes of adaptive learning.
with users of products and services outside the organisation. The result is innovation with localised usability in addressing problems faced by the firm.
more important role in this mode, making incremental innovations that upgrade traditional sectors (Asheim, 2009 While the two modes of innovation are not mutually exclusive and both firms and
Chapter 2 provides data on SME innovation performance and constraints across 40 economies and examines the major and new policies that have been introduced.
Frameworks for Data Collectionâ€, OECD Statistics Working papers, 2008/1, OECD Publishing, Paris doi: 10.1787/243164686763 SMES, ENTREPRENEURSHIP AND INNOVATION  OECD 2010 41
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
OECD (2008), Open Innovation in Global networks, OECD: Paris OECD (2008b), â€oeentrepreneurship and Local Innovation Systems:
Entrepreneurship Outlook, OECD, Paris, pp. 127-142 Potter, J. ed.)(2008), Entrepreneurship and Higher education, OECD, Paris
by structural data on the SME sector and selected indicators showing SME innovation performance, perceived barriers to innovative activities, and financing
available, data are presented also for accession countries (Chile, Estonia, Israel, Russia and Slovenia) and enhanced engagement countries (Brazil, China, India, Indonesia and South
Data presented in the chapter come from three main sources â OECD Structural and Demographic Business Statistics Database
â Innovation Surveys (e g. the Community Innovation Surveys; national innovation surveys â OECD Product Market Regulation Indicators
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: country, industry, year, size class and variable. The variables presented in this chapter are:
components and materials, incorporated software, user-friendliness or other functional characteristics â Process innovation: The implementation of a new or significantly improved production or delivery meth
This includes significant changes in techniques, equipment and/or software â Marketing innovation: The implementation of a new marketing method involving significant changes
The PMR database comprises three broad sets of indicators state control, barriers to entrepreneurship, and barriers to trade and investment.
0, 3343, en 2649 34323 2367297 1 1 1 1, 00. html Micro Small Medium SME Large EU countries, Iceland, Norway, and Switzerland 1-9 10-49 50-249 1-249 250
enhance their web facilities, and engage in e-business capabilities to help reduce their costs and improve their
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812706506652 B. Innovation performance of SMES and large firms, 2007-081
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812710434422 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812733856326 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812772716231 B. Innovation performance of SMES and large firms, 2002-041
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812823002327 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
of Growth and Programme for User-driven Innovation are two of the Strategy†s initiatives
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
Programme for user-driven innovation The Programme for user-driven innovation has a yearly budget of DKK 100 million and runs for 2007-09
By strengthening the diffusion of methods for user-driven innovation in the private and public sector, the
programme aims to help increase growth in the participating companies and increase user contentedness and/or efficiency in participating public institutions.
The programme should also result in the development of new products, services and concepts, as well as in an increase of the qualifications of the
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/812824001404 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
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 statlink 2 http://dx. doi. org/10.1787/812888716138 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813015740451 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-064
corporations BASF, Deutsche telekom and Siemens to initiate the High-tech Grã nderfonds. The amount of capital provided by the fund†s investors totalled EUR 272 million.
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813110872302 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2002-043
In the 2000-07 programming period the General Secretariat for Research and Technology of the
manufacturing sector and software industry, in buying innovative consulting services and know-how from so-called â€oeinnovation agentsâ€,
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813116208667 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813126285000 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813138862470 B. Innovation performance of SMES and large firms, 2002-041 C. Types of innovation co-operation, 2002-043
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. The aim is to ensure
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
1. Data only reflect enterprises with 3 or more persons engaged. 2. As%of all firms within size class
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813224252704 B. Innovation performance of SMES and large firms, 2004-062 C. Types of innovation co-operation, 2004-065
and final users such as public entities, associations and so on (the latter participating on voluntary basis, without grants) that stipulate cooperative agreements
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813326326305 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2002-044
by creating networks between SME companies that possess core basic technologies with downstream normal industry, to link technological seeds with market needs.
1. For manufacturing, data only reflect enterprises with 4 or more persons engaged. 2. As%of SMES with new product sales
OECD, Product Market Regulation Database statlink 2 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
Regulation Database statlink 2 http://dx. doi. org/10.1787/813331118285 B. Innovation performance of SMES and large firms, 2002-042 C. Administrative burdens on start-ups4
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813367102180 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
The Last Mile programme supported mainly information technology (IT) firms (36), %followed by advanced materials (13%)and design
mainly the creation of IT firms (35%)followed by electronics and telecommunication (25%.%Both programmes mostly backed firms in Mexico city (50),
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813468327202 B. Source of finance of SMES and large firms, 2002-04 C. Administrative burdens on start-ups1
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813475131677 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813487217851 B. Innovation performance of SMES and large firms, 2005-071
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813517714027 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813521857686 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813540502857 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813544660727 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-064
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813612045268 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-064
Database statlink 2 http://dx. doi. org/10.1787/813624112502 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2002-044
Furthermore, 80%of users interviewed corroborated that the offerings were of value SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 2010100
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813727458672 B. Type of innovation by SMES, 20071
os ts too hi gh Rig hts no t en for ce ab le Ins
OECD, Product Market Regulation Database statlink 2 http://dx. doi. org/10.1787/813835033115 B. Innovation performance of SMES and large firms, 2004-061 C. Types of innovation co-operation, 2004-063
a series of 30 core â€oeproducts†that will share a common brand Advisory and capability support for SMES continues to be offered through the Business Links service in
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 statlink 2 http://dx. doi. org/10.1787/813847876385 B. Innovation performance of SMES and large firms, 20071 C. Types of innovation co-operation, 2004-062
high-technology development zones, university science parks, incubators and software parks across China. At the national level alone, by 2008 53 high-technology development zones, 62 university science
and 35 software parks had been developed through governmental support. In the period 1992-2005, the revenue, industrial value added
Information technology (IT The development of the IT industry in India is lauded greatly by decision makers and researchers alike
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
OECD, PMR Database; OECD Economic Surveys: Israel 2009 statlink 2 http://dx. doi. org/10.1787/813271727207
http://www. oecd. org/dataoecd/59/53/46211243. pdf Russian Federation A. Definition of SMES Size Employees Annual turnover
Notes on the Country Data The structural data on businesses presented in the chapter follow the International
Standard Industrial Classification (ISIC) Rev. 3, based on the following nomenclature A. Agriculture, hunting and forestry
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, E and F) and Services
The following text gives details on the completeness of the data for each country Australia:
instead requires a web of relationships among firms, research organisations and governments. Knowledge flows are the quintessence of an innovation system
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
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
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
Selected clusters are compared then using data on business demography and business performance. These findings represent some of the
and selection biases in the original data source. 3 SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 2010136
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 SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 2010 137
which might also infer a bias in the original data sources. Secondly, KISA firms often tend to
OECD elaboration based on ORBIS database available from Bureau Van dijk Low LQ Medium-Low LQ Medium-High LQ High LQ
progress in transport and telecommunications has made it possible for firms to separate production from management, with the former being relocated to areas with same-sector
the second type is built from a statistical algorithm for analysis of spatial agglomeration named LISA (i e.
data source, territorial grid and methodology adopted for Figure 3. 3. This map provides empirical evidence on the uneven distribution of US firms in knowledge-intensive services
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
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software High-High low-Low Low-High High-low
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software 1st range (0) 2nd range (790) 3rd range (400
OECD elaboration based on ORBIS database available from Bureau Van dijk (Geoda software High-High low-Low Low-High High-low
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
the case of the US clusters, given data source constraints for this country, the composite
OECD elaboration based on ORBIS database available from Bureau Van dijk statlink 2 http://dx. doi. org/10.1787/814040554856
OECD elaboration based on ORBIS database available from Bureau Van dijk Ranking Name of business cluster Country of residence
OECD elaboration based on ORBIS database available from Bureau Van dijk statlink 2 http://dx. doi. org/10.1787/814047837382
OECD elaboration based on ORBIS database available from Bureau Van dijk Ranking Name of business cluster Country of residence
The above section illustrated the phenomenon of spatial clustering of economic activity in knowledge intensive sectors.
suggests that local knowledge transfers are important to this clustering process. This literature stresses the fact that knowledge does not spill over long distance †which means
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
interaction process between customers and suppliers or between users and producers which explains why proximity is so important for knowledge spillovers to happen
exists between knowledge spillovers, spatial clustering and innovative output (Giuliani 2005). ) This is especially true for knowledge-driven sectors,
and radio and TV communications are all highly concentrated in the three states of Massachusetts, California and New york (Audretsch and
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 Knowledge spillovers benefit new and small firms New and small firms can benefit substantially from knowledge spillovers.
comparable data on this phenomenon. Patents and numbers of spin-off companies are relatively easy to count,
In addition, data collection is regular in some countries but sporadic in others SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 2010 145
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
Data, however, show that knowledge transfer is still incipient in China. Universities have a great number of patents (126 per KTO),
providers and users of technology carry out technology transfer activities; coordinate R&d financial tools; support technology
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 â Design advice and training programmes for start-up entrepreneurs who have strong technological
zones, 62 university science parks, about 200 business incubators and 35 software parks (see China†s Country Note.
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
Christensen, C. 1993), â€oethe Rigid Disk drive Industry: A History of Commercial and Technological Turbulenceâ€, Business History Review, Winter, No. 67, pp. 531-588
OECD (2005), SME and Entrepreneurship Outlook, OECD, Paris OECD (2007a), Competitive Regional Clusters: National Policy Approaches, OECD, Paris
The â€oeorbis†Database The scope of ORBIS for territorial analysis The ORBIS database, developed and maintained by Bureau Van dijk (BVD),
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
â Business demographic indicators, e g. business birth rate; survival rate; distribution of firms by age, etc
ORBIS database at different levels of industry or geographical breakdown using standard formulas, the calculation of business demographic indicators raises methodological
Limited information available in the ORBIS database on complex business demography events, such as mergers and acquisitions, makes the definition of a company
real exit rates, as it is a continuously expanding database in terms of both international and national coverage. In this respect, information regarding the company†s incorporation
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
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
territorial data. The first concerns use of the company instead of the local unit as the
company activities to a single location leads to incoherent territorial data in the case of
its core economic activities Besides location bias, 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, where the latter is
conventionally assumed to include all active enterprises resident in a given country 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, turnover, employees, value added
by classification variables (economic activity, firm size and location. Such a deviation potentially generates biased economic indicators.
number of factors such as restrictions in the database and poor data quality consistency across industries, regions,
database, for instance the exclusion of all companies with some specific legal status. It occurs when the selection effect is correlated significantly with variables of interest for
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
Normalised territorial indicators, of which location quotients (LQ) are the most relevant example, may mitigate the negative impact of coverage restrictions and structural
neutralise these sources of bias in the input data Dynamic territorial indicators, such as employment or labour productivity growth
indicators is altered by an uneven spatial distribution of the sample of micro data as compared to the target population,
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
databases to carry out nonstandard territorial analysis with an insight into the methodological problems that may affect the consistency of these territorial data.
The conclusion is that normalised static territorial indicators and dynamic territorial indicators are more robust with respect to different sources of territorial bias.
In the case of uneven spatial clustering global spatial indicators, such as Moran†S i, are found to be less useful and local indicators
Moran†S i and LISA differ in data employed and analytical scope. Moran†S i is a global
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.
suggest clustering of similar values (positive spatial correlation), whereas the HL and LH locations indicate spatial outliers (negative spatial correlation
indicators should be limited to exploratory data analysis. In the absence of a well-defined spatial modelling framework,
Learning processes are at the core of entrepreneurship and SME development. They are essential for the formation of a new business, its survival and growth as well as for the
Also in the case of workers in existing SMES, data confirm the existence of a skills and training problem holding back innovation.
at work such as managing people, computing, collaborating, dealing with risk and uncertainty or developing a new product or service (Tether et al.
Generic General IT user skills, oral communication, written communication, numeracy and literacy, office administration skills Routine Repetitive, more basic, low knowledge-intensive skills (e g. packing chocolates in boxes in a factory
requirements or regulations (e g. water purification and site remediation planning/engineering in mining, solar panels installation, wind turbines design, green management, carbon capture and
Box 4. 1. Core characteristics of entrepreneurs Knowledge. An entrepreneur is able to identify and extract knowledge that is relevant.
development and a vertical specialisation in one or more fields related to core competitive advantage. One of the definitional difficulties is that these skills are relevant not just to
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
businesses, for example plumbers, painters, electricians and information technology specialists. Other people go on to work in larger SMES
â are skilled in generic processes and activities such as core skills â 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
KISAS) such as electronic commerce, information technology, market research, and industry development advice KISA projects can be undertaken by SMES with outsiders such as business
management skills for integrating e-commerce into the core business. They may also include legal advice to a firm/organisation on the design of new business structures to support
upgrades these skills, and on the way the services are offered (Hall and Lansbury, 2006 The concept of skill ecosystems directs attention to the interdependency of multiple
catalysts here, providing an appropriate policy context and support for the resources infrastructure and institutional framework to establish
KISA) in Software Innovationâ€, International Journal of Services Technology and Management, IJSTM Special Issue, Vol. 7, No. 2, pp. 109-173
Activities (KISA) in Innovation of the Software Industry in Australia, University of Western Sydney Sydney
OECD (2003), OECD Employment Outlook, OECD, Paris OECD (2005), SME and Entrepreneurship Outlook, OECD, Paris
OECD (2006), The Role of Knowledge Intensive Activities (KISA) in Innovation, OECD, Paris OECD (2008), Enhancing the Role of SMES in Global Value Chains, OECD, Paris
Monitor (GEM) UK project to estimate the percentage of social entrepreneurs in UK society using population survey data.
The GEM report found that 1. 2 million people, which corresponds to 3. 2%of the working-age UK population,
entrepreneurship, 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 61 800 social enterprises in England. In 2005 social enterprises had a turnover of
serving 5 million users and with an economic turnover of EUR 10 billion In Korea from 2007 to 2009, the Korean Ministry of Labor has certified 251 organisations
515 organisations that applied (data elaborated for OECD by the Korea Labor Institute and the Research Institute of Social Enterprise
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 â€oenonprofit 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,
5. Is social entrepreneurship a local phenomenon or a global one? While many initiatives happen at the local level,
7 in this particular case the core mission is to provide health services, but in conjunction with preventing illness through a
Health-related problems are at the core of the initiative of pharmaceutical scientist Victoria G. Hale, founder of the Institute For one World Health (Box 5. 4). There the concern is to
courses to gain essential skills in mathematics and English, are provided. There is a charge for courses,
Social networks based on Information and Communication Technologies (ICT) are also gaining importance both as social innovation in themselves and as producers of social
open source software) or civil society (fair trade)( Mulgan et al. 2007). ) It can also start in
13 competitively selected community partner sites operating 14 programmes in a mix of urban and rural locations across the country.
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
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, socially -responsible companies and engaged individuals in a unique environment of shared
receiving and giving donations, embracing the breadth and power of Web 2. 0 It was founded as a mission-based, for-profit enterprise, in Dublin in 2005 by a serial
harnessing social media for social good â 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
social media for social goods (cont â nonprofits to promote their cause (s) and solicit donations
â The integration of company profiles, vast and various web tools and a secure donation
thwarted by a series of difficulties on the IRC site, from language (many 2nd â€
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
interactivity with other social networks like Facebook and Twitter. Nonprofits can add the â€oedonate 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 â€oedonate†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 â€oemutually beneficial marketing:
Why business and brands need a good purposeâ€, which stated that, â€oenew findings...reveal that
nearly seven in 10 (68%)consumers would remain loyal to a brand during a recession if it
supports a good causeâ€. That same study stated that â€oe76%of consumers globally like to buy
for its achievement in the application of information technology to promote positive social, economic, and educational change.
it displays various degrees of innovation and change; it is constrained by the external environment (p. 10
sociales), www. crises. uqam. ca/cahiers/ET0314. pdf Cochran, P. L. 2007), â€oethe Evolution of Corporate Social Responsibilityâ€, Business Horizons, Vol. 50
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 D. Albury (2009), The Innovation Imperative: Why Radical Innovation Is needed to Reinvent
Entrepreneurs, www. socialent. org/pdfs/GLOSSARY. pdf SMES, ENTREPRENEURSHIP AND INNOVATION Â OECD 2010 209
NESTA (2007), Innovation in Response to Social Challenges, www. nesta. org. uk/assets/Uploads/pdf
/Policybriefing/innovation in response to social challenges policy briefing nesta. pdf NESTA (2008a), Transformers. How Local Areas Innovate to Address Changing Social Needs, www. nesta. org. uk
/assets/Uploads/pdf/Research-Report/transformers report nesta. pdf NESTA (2008b), Social Innovation: New Approaches to Transforming Public services, Policy Briefing, January
www. cabinetoffice. gov. uk/media/cabinetoffice/third sector/assets/innovation social enterprise. pdf Zhara, S.,E. Gedajlovic, D. Neubaum and J. Shulman (2006), â€oesocial Entrepreneurship:
and this requires the display of innovativeness, proactiveness and risk management behaviour. This behaviour is constrained by the desire to achieve the social mission
ways of using mobile phone texting, and from new lifestyles to new products and services. We have
outside of public services and can be developed by the public, private or third sector, users and
They include general IT user skills, oral and written communication, clerical competencies, etc Breakthrough innovation A discontinuous innovation representing breaks with previous technologies and
including aerospace, pharmaceuticals, computers and office machinery, electronics -communications, and scientific instruments Incremental innovation An improvement on existing products or processes that is achieved through internal
development, legal services, computing and information technology and marketing. The engagement of SMES with providers of KISAS supports their learning and innovation
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
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
Sourceoecd is the OECD online library of books, periodicals and statistical databases For more information about this award-winning service and free trials ask your librarian,
Programme for user-driven innovation Finland Funding for Young Innovative Enterprises and Start-up Accelerator France
Information technology (IT Biotechnology Technopreneur Promotion Programme Indonesia Innovation Centre for Micro, Small and Medium Enterprises
Notes on the Country Data Chapter 3. Knowledge Flows Introduction How knowledge affects entrepreneurship The systemic approach to innovation
The geographical clustering of knowledge-intensive activities European union Figure 3. 1. Distribution of HTM firms in the European union (Quantiles based on LQS
The â€oeorbis†Database Annex 3. A2 The LISA Methodology Chapter 4 Entrepreneurship Skills The importance of entrepreneurship skills for SMES and start-ups
Box 4. 1. Core characteristics of entrepreneurs How are acquired entrepreneurship skills Universities and higher education institutions Box 4. 2. Entrepreneurship support in universities:
A global platform harnessing social media for social goods Preliminary recommendations Social entrepreneurship Social innovation Notes
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