Synopsis: Ict: Data: Data:

The current strategy is based on data in the Diagnosis Analysis †Report on communication services in broadband (Roland Berger 2006) and on those supplied by the National Authority in

rapid transmission of a huge volume of data, so that the access to a wide range of

Thus, taking into consideration the data in the table above and the fact that there

distributed, access to specific applications and large data traffic generators. At the same time it supposes the existence of broadband communication infrastructure as

Thus, we can develop data basis (e-Tourism, e-Culture that favor the development of the digital content of cultural type, including in tourism

administrative tax payment, of transmitting data and answering in electronic format as well as of giving useful info as regards certifications and authorizations (e

services by setting up data basis nationally concerning health of patients in hospitals and at the level of medical clinics (e-Health) and developing telemedicine services

Statistical data concerning electronic communication market in Romania in the first half of 2008, reported by providers to the National Authority for

According to data reported by internet providers, in June 2008, in Romania, there were approximately 2, 27 million broadband access

Data published by the European commission show that, despite the diminishing of economic growth perspectives in general, broadband internet development

According to data provided by ANC for the next period companies and institutions intend to purchase a broadband connection at high speed transfer, this

Long distance data transportation networks are developed well ï¿The purchase cost terminals (PCS, laptops, mobile phones, mobile

-to collect and centralize statistical data related to the process of equipping the population with reception devices

Recent data (April 2010) provided by ANCOM show a 12.4%increase in the number of fixed broadband connections at the end of 2009 versus the same period

These preliminary data indicate a penetration rate of broadband fixed connections at 13.1%of the population and

•Facilitate obtaining data, information and real-time reports •Application of general indicators regarding the development of Information

processing data, information and updated documents B. Streamline relations with public institutions •Increased access to electronic public services

•Reassessment of host status for data •Increased competitiveness and development of economic operators through

1 Data available in December 2012. This table presents the available data for each indicator in the

latest update of each source Population and territory The Autonomous Community of the Balearic Islands is located in the Mediterranean sea along

October 2012 data The unemployment rate in Balearic islands in 2011 (21,96%)is well above the European average (9, 70%)and the OECD countries

 data  access  markets  and  market  roles  as  well

 data  safety  industry  development  research  The  key  ongoing

 data  collection  by  utility  personnel  to  gain  a

 data  handling  customer  contact  or  local  congestion Â

 data  safety, 16  industry  development  (mainly  ICT  electrical

 data  pro- †tection  for  consumers  (3  establishing

 data  han- †dling  The  challenges  of  distributed

 data  handling  and  communication  Differ- †ent  smart

http://www. tdeurope. eu/data/TD%20europe%20position%20paper%20on%20infrastructures%20and%20smar t%20grids%20010212. pdf

 data  of  the  customers  Will  there  be  distribution- †level

 data  gathering  data  handling  data  security  and  discussions

 on  data  privacy  On  the  other  hand  it

 might  as  advocates  sustain  allow  for  more  demand

 response  reliability  and  shorter  reaction  times  The  two

 data   Moreover  in  a  perspective  where  consumption

energieanbieter. de/data/uploads/20111010 bne positionspapier smart grids. pdf   Brandstã¤tt  C  Brunekreeft  G

APPROACH DATA METHOD Quantitative Statistical data from Spanish National Statistics Institute (INE) on number of establishments, GDP

employment and Input-Output regional economic accounts (www. ine. es Specialisation pattern mapping following Del

Qualitative data: all the regional RIS3 in Spain available from the Spanish Ministry of Finance and Public Administration (MINHAP

follow-up and improve the strategy, a data set of policies (some of which could be developed jointly by different regions), the open economy dimension

Key socio economic data Aragã n is proud of its geostrategic location in the northern part of Spain between the Atlantic and Mediterranean

data facilitated by IDEPA. After that general introduction, we will discuss position in the last Regional

According to the latest population data, for the advancement of the Municipal Register to January 1 2011, Asturias has 1,

according to the latest data provided by the National Statistics Institute in Central Business Directory. This is a decrease from the previous year of 1. 3%.If

data, 2009 and 2010 The productive structure presents great weight of the industrial sector with 21.78%of the total

In view of the above data the main features of the Asturian economy and more specifically of its

With due caution with the data presented in Expert Assessment of RIS3 strategy for the region of Asturias, Spain †Miquel Barcelã 6

details in annex 5. 1. For every institution visited some basic data, functions and available figures are

Data Sede W3c 80 personas Presupuesto 2011: 4 Mâ Pieza clave de una futura estrategia del sector TIC

ï The strategy has been iniciated by IDEPA with the preparation of some data based on enquiries and information already available, that will be completed by thematic

ï By indirect data, like companies participating in Neotec programs (CDTI loans to based technology), EIBT certification by ANCES (National Association of CEEI€ s) or by

Economic data ï¿The (Gross domestic product) GDP of Cantabria was 13.289,89 millions of â in 2011

Economic data ï¿GDP distribution ï¿Services 61 %ï¿Industry and energy 17 %ï¿Construction:

Economic data ï¿Industry GDP distribution ï¿34.72%Metal processing ï¿12.51%Food, beverages and

%Economic data ï¿Services GDP distribution ï¿26,87%Business services ï¿13,76%Tourism and hospitality

%Economic data ï¿The main export destinations ï¿France ï¿Germany ï¿Italy ï¿U k

is a significant increase in the R&d activity of the enterprises as compared with the data of one decade ago, in

%Figure 5. Main data of †HAMHIT€ Companies in Castilla y Leã n Source: INE

%According to the data published by EUROSTAT, Castilla y Leã n has reduced in 17.8 percentage points the gap in GDP with the European union since the incorporation of

•Based on objective data and including solid supervision and evaluation systems 1. 2 METHODOLOGY The elaboration of the Castilla y Leã n RIS3 has followed the six-step methodology

The latest available data assigns economic returns for Castilla y Leã n participation in national R&d programmes

) Concerning Internet access technology, data for the first quarter of 2013 in Castilla y Leã n are very positive,

Additional noteworthy data is the positive evolution of technology by the youngest part of the population, especially in the 10

independent contractors), where usage data and ICT availability continue to be low with minor annual economic growth.

Usage data from companies using the Castilla y Leã n Online Government is better than the usage of these services by citizens:

Open Data; new models for collaboration with other companies Citizens •Existence of constantly increasingly

1 Latest data available from 2010 2 National Statistics Institute 3 Scopus Database, Elsevier 4 Application of historical data queried from the Spanish Foreign

Trade Institute. Ministry of Economy and Competitiveness 5 European Statistics Office 6 Secretariat of State for Telecommunications and Information

7 Data corresponding to the first six months of 2013 8 At least once a week during the last three months

9 Data corresponding to 2013 ME 035 10 FINANCIAL PLAN The development of Strategy will involve both public and private resources.

 Data  demand  for  contents  more  usable  technologies  closer

 data  mining  etc   •†Robotics   •†Intelligent

3. 1. Sample and data We used a cross-sectional dataset of Europe-based SMES across all

dataset is motivated by the concern for the reliability of yearly data on invention commercialization strategies, provided that our sample

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

-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

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

) 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

-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

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

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

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

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.

data and highlighting current policy issues of greatest concern. It draws in particular on the expertise

Notes on the country data...128 Chapter 3. Knowledge Flows...131 Introduction...132 How knowledge affects entrepreneurship...

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

and data is not commonly available for non-technological innovation as a proportion of firm employment or turnover.

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

New Evidence from Micro Data, Ch. 1, pp. 15-82, University of Chicago Press, Chicago

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

Data are drawn from the OECD dataset Business Statistics by Size Class, which is part of the OECD Structural and Demographic Business Statistics Database.

1. Data only reflect enterprises with 3 or more persons engaged. 2. As%of all firms within size class

1. For manufacturing, data only reflect enterprises with 4 or more persons engaged. 2. As%of SMES with new product sales

1. For manufacturing, data only reflect enterprises with 5 or more persons engaged. 2. As%of all firms within size class

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

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:

Given the limits of official data sources for local-level analysis, we turn to firm-level

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,

which might also infer a bias in the original data sources. Secondly, KISA firms often tend to

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

the case of the US clusters, given data source constraints for this country, the composite

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),

of business micro data. The database includes around 40 million companies, has a geographical coverage of up to 200 countries,

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,

rearrange firm-level data according to detailed company location. The information on company location relates to the complete address,

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

alter the consistency of territorial data calculated from this sort of source Coverage restrictions concern the under-coverage of the set of companies extracted

size are included not in the original data sets or by additional restrictions on revealing information on small areas imposed by the database provider

number of factors such as restrictions in the database and poor data quality consistency across industries, regions,

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

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

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

methodological problems that may affect the consistency of these territorial data. The conclusion is that normalised static territorial indicators and dynamic territorial 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.

Also in the case of workers in existing SMES, data confirm the existence of a skills and training problem holding back innovation.

Across the EU-15 countries, data from the Eurostat Continuing vocational training Survey show that employees in enterprises with less than 50 employees receive

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

515 organisations that applied (data elaborated for OECD by the Korea Labor Institute and the Research Institute of Social Enterprise

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

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

Notes on the Country Data Chapter 3. Knowledge Flows Introduction How knowledge affects entrepreneurship The systemic approach to innovation

Open Data movements and innovative/transparent forms of governance go hand in hand (http://data gov. uk) with these new forms of coproduction.

The Open Data movement lobbies government institutions, international organizations and the private sector to make private

and public databases available to application developers. Therefore, the new technology co-creation community ethos of the Web 2. 0 social media dialog questions not only the

Data is an important resource and output of these social media innovations. Opening up government data silos to developers and communities is

therefore potentially one way to support this growing social-digital economy. Yet to be of any use, the new superfluity of data needs to

be structured, analyzed and interpreted (Wilson et al. 2013. This is an increasingly pressing challenge, deeply imbued by often overlooked issues of provenance and trust

Data Is the Solution! What was the Question Again? Public Money & Management 33 (3:

collecting and correlating social network data (e g. degree, density, etc.)for innovation success •Providing a framework for timely communication and distribution of experiences, contextual information

and displaying data and is used as the front-end tool for the application in conjunction with Oracle 9i database as the backend.

Through data-driven tables of contents, Oracle Forms provides users with an easy interface to the information that is required.

The Entity Relationship diagram (ERD) in Figure 6 represents the data modeling of I3. The figure represents the organization of data into entities and the relationships between the entities in I3

Although the actual system includes both user modules and administrator modules, only the administrator modules

the data in the system is updated and true at all times, the main menu also provides administrators with tools to enter

and manage all meta-data and other pre-conditional data required for the system. These include metadata pertaining

to user, company, resource or request management like Education level, Occupation list, Ethnic group, Expertise areas, NAICS code, Nonprofit type, Occupation type, Session type, Milestone, Counties, zipcodes, regions, contact

registration and profiles are created through an initial registration process and data (e g.,, occupation, education information, college teaching, highest education level, privacy level, etc.

manages the †who knows who†data collated from a survey deployed during the registration process and information

Similar data is collected and managed for all resource types. Each resource is tagged to its owner (a registered user) and is

and to improve usability, all data entry fields are enabled with smart tips to provide information (e g.,

or meanings of data) or helpful tips when a user moves mouse over a field,

for all data fields Figure 12: Resource Management †Smart tips enables Figure 13: Viewing Related Messages

with many reports to give the administrator a different direction for analyzing data. The graphs can be accessed from

implementing social networks but analyzing the data and building a knowledge base would help build a stronger

Knows Who Data Presents the user†s social connectedness in the network and can help

the fields of data/text mining, business process simulation, software agent applications, and demand forecasting especially in a supply-chain environment

This demographic data implies a shift in healthcare spending and policy reform †the two main areas that will impacted he hugely by this trend

do today using interconnected sensors and data analytics; Health, Wellness and Wellbeing is bringing mind, body and soul to the centre of connected

intelligence, internet of everything and data analytics in buildings, homes grids, water networks, hospitals, cities, factories and transport systems

with secondary research across a host of both external and internal data sources, Frost & Sullivan deployed its unique, bottom-up approach to

& Sullivan then employed its rigorous, data-driven approach to market quantification and forecasting through triangulated data inputs to derive

its initial quantification of the global market potential represented by Social Innovation Social Innovation to answer Society†s Challenges

To evaluate the South Tipperary County Hub Data and consider its rolling out throughout the region

Baseline Data and Analysis: Southeast Region, n d..An overview of the region based on an analysis of quantitative and qualitative indicators across a range of competitiveness factors

A summary comparing Southeast key data with the State average is featured in Regional Competitiveness Agendas:

%Table 1. Summary of key data-2008/2009 Source: Regional Competitiveness Agendas: Overview, Findings and Actions, 2010

Better data will be available from both ETBS and SOLAS in terms of initiatives which work best for which learners

In drawing up this Map, economic data such as unemployment and Gross domestic product for all counties will be analysed afresh

An interesting initiative in this regard is South Tipperary County Council†s County Data Hub (southtipperaryinfo. ie),

and analyse county data and statistics to assist decision making and service delivery Its aim is to provide a central portal for information, data, maps and statistics, relevant to South Tipperary and designed in an easy to use format

The agencies subscribing to the initiative recognise the benefits of sharing data and making it more accessible and in delivering information that is relevant to the services they provide throughout the county

An evaluation of the site†s operation should be undertaken with consideration given to expanding its scope as a one-stop-shop and rolling out this initiative across the region

To evaluate the South Tipperary County Hub Data and consider its rolling out throughout the region

Data on construction employment was obtained by DKM Economic Consultants for Q1 2010, based on the total number employed at that time (130,600).

There are no separate data published for unemployment in construction but with construction accounting for 57%of all job losses,

In the most recent twelve month period, for which data is available, almost 60%of males who emigrated were Irish.

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