63 Ecommerce Europeassociation data at a glance 2014 European Reports Reports include country profiles, trends & Infographics.
and their individual research partners for providing us with the required data and information. We would also like to thank all participating company members, business partners and stakeholders for their involvement.
Gfk turns big data into smart data, enabling its clients to improve their competitive edge and enrich consumers'experiences and choices.
More than 160 companies in 40 countries use Richrelevance to turn data into actionable insight, which delivers the most relevant experience for consumers as they shop across web, store and mobile.
INFA) is the world's number one independent provider of data integration software. Organizations around the world rely on Informatica to realize their information potential and drive top business imperatives.
Informatica Vibe, the industry's first and only embeddable virtual data machine (VDM), powers the unique Map Once.
With regard to information technology, Informatica helps wherever possible by delivering the right data in the right way to the right users.
and reduce abandonment is going to come from a clear interpretation of the insights to be derived from the data that exist.
Huge volumes of data need to be analyzed in order to identify issues and The year of SEPA?
By applying analytics and visualization to payments data, merchants can track and compare performance per country, per payment method or per time period,
and the projected growth of (B2c) e-commerce. 645,250 websites According to data received from national e-commerce associations,
which will be published in the fall of 2014.2013 Key B2c E-commerce Data of Goods and Services at a Glance Top 10 e-commerce countries in turnover (EUR billion) USA € 315.4 China € 247.3*UK € 107.1 Japan €
Market of Goods & Services www. ecommerce-europe. eu B2c E-commerce in Europe 2013 Key B2c E-commerce Data of Goods and Services at a Glance;
Data of Goods and Services at a Glance The netherlands Belgium France United kingdom Ireland 1 United kingdom € 107,157 2 France € 51,100 3 The netherlands € 10,583 4 Ireland
bn 1 2 3 Ranking Central europe in turnover (EUR million) 2013 Key B2c E-commerce Data of Goods and Services at a Glance 1 Germany € 63
) 2013 Key B2c E-commerce Data of Goods and Services at a Glance Italy Spain Greece 1 Spain € 14,414 2 Italy € 11
) 2013 Key B2c E-commerce Data of Goods and Services at a glance 1. Sweden € 8, 622 2. Denmark € 8, 367 3. Norway
Key B2c E-commerce Data of Goods and Services at a Glance Ukraine Romania 1 Russia € 15,500 2 Ukraine € 1, 850 3 Romania € 1,
Technological competitiveness and the links between KETS and industrial sectors are explored through patent data. The rationale for this choice is given below
patent data seem to be the most European Competitiveness in KETS ZEW and TNO EN 24error!
Although comparability of patent data is limited due to different economic values a patent may represent, different degrees of technological novelty and different degrees of actual applicability,
patent data are nevertheless a widely used source to analyse dynamics in certain fields of technology
Figures based on data from AT, BE, CY, CZ, EE, ES, FR, GR, HR, HU, LT, LU, NL, PL, PT, RO, SK, TR.
which statistical data would be available) since the cross-sectional nature of KETS implies that firms from different industries develop
Consequently, traditional concepts of analysing competitiveness based on industry data such as market shares, trade performance, productivity and growth in value added cannot be applied to analyse competitiveness in emerging KETS.
patent data seem to be the most relevant source. Patent applications refer to technical inventions that have reached a certain state of feasibility
Although comparability of patent data is limited due to different economic values a patent may represent different degrees of technological novelty and different regulations of national patent offices, patent data are
nevertheless a useful source to analyse dynamics in certain fields of technology and identify the regional distribution of new knowledge generation,
) Patent data have widely been used to analyse technological performance particularly for KETS, such as nanotechnology (see Palmberg et al.,
patent data are more closely related to innovations and product markets. Chapter 2 Methodological Issues EN 33error!
EN Patent Data as Technology Indicators Using patent data as empirical base for analysing technological competitiveness of KETS has several advantages:
Patent data contain information on the technological area (s) a certain patent is related to, based on an internationally standardised classification system (International Patent Classification-IPC.
Patent data also contain text information of the technical content of a patent (patent abstracts)
Patent data allow to determining the"market share"of the EU in the total production of new technical knowledge in each KET in the past two decades or so
Patent data also enable to differentiating by country of applicant and thus to pattern technological competitiveness in each KET by EU member state.
Patent data contain information on the applicants which can be linked to other data in order to identify the institutional background of an applicant (higher education institution, public sector research institution, private firm, individuals) or the sector affiliation.
Sector affiliation of applicants is important information to evaluate the role of each KET for different sectors.
Patent data allow to some degree an analysis of technological links between certain fields of technology
However, patent data also have a number of limitations (see Griliches, 1990; Moed et al. 2004) that limit their applicability as technology indicators and that complicate their analysis:
As a result, any count of patent data, whether weighted by a"relevance factor "or not, is problematic as it is likely to compare entities of completely different values.
Patent data applied at different patent authorities are difficult to compare because of different patent national laws, different practices at patent offices and different application procedures.
As a consequence want cannot simply add up patent data applied at different patent offices. Applying for patent protection at a specific patent office is linked to the applicant's strategy for commercialising this invention,
Patent data are available only with a considerable time lag after the underlying invention has been made. First
We try to tackle some of these shortcomings of patent data in the following way:
By doing this, we reduce the incidence of double-counting of one and the same invention in patent data.
Identifying KETS in Patent Data There are two approaches to assign patents to technology areas. One is to identify key words (and combination of these) that characterise a certain technology and to search in patent abstracts for the occurrence of these key words.
when it comes to combining key words and searching across patent data from various patent authorities.
At the same time, relying on applicant countries enlarges the analytical potential of patent data since patents only applied at USPTO
We do so, on the basis of secondary data: scientific and vocational cluster publications, and publically available information.
Electronics-silicon electronics-nanoscaled transistors-polymer electronics-CNT field emission displays-MRAM memories-phase-change memory-MEMS memory-CNT data memory-CNT
'34 30 http://www. mext. go. jp/english/org/struct/029. htm 31 http://www. meti. go. jp/english/aboutmeti/data/aorganizatione
since enterprise R&d surveys rarely collect data on R&d expenditure devoted to nanotechnology. Figure 3-25:
In 2008, the OECD reports a moderate growth of the semiconductor industry, the most recent data available, of 2. 2 percent to $260 billion in current prices (OECD
2007). 43 The most recent R&d data of the OECD Technology Outlook 2008 does not go beyond 2006.
Industry Links and Market Potentials 5. 2. 1. Technological Competitiveness Analysing technological competitiveness in industrial biotechnology based on patent data using patent classification systems is challenging.
Photonics enables the processing, the storage, the transport and the visualisation of the huge masses of data.
It is optical transmission networks that are enabling all of this, giving data accessibility to anyone, anywhere (Photonics21, 2006.
) However, this data is based on a survey from 2002. Others in the meantime (2007) speak of 69 Since 2005 the photonics clusters in Berlin-Brandenburg, Tucson, Arizona,
EN 7. 2 Technological Competitiveness, Industry Links and Market Potentials 7. 2. 1. Technological Competitiveness Analysing technological competitiveness in advanced materials based on patent data
which in the ECO data is listed 4th in the chemical clusters category with high level of innovativeness.
but solely focus on quantitative analyses based on patent data. This decision reflects the specific nature of this KET (see the following section for more detail) which implies different mode of generating and diffusing technologies and less significance of clusters for technological advance in this KET.
We analyse technological competitiveness of advanced manufacturing technologies (AMT) based on patent data. AMT patents are identified through a combination of IPC classes (see section 2. 2). Measured in terms of patents applied at EPO or through the PCT procedure (EPO/PCT patents
For quantitative analysis, patent data were employed. Qualitative analysis of success factors, barriers and market and system failures rest on detailed analysis of ten selected clusters (five from Europe, five from overseas.
Arvanitis, S.,H. Hollenstein (1997), Evaluating the Promotion of Advanced Manufacturing Technologies (AMT) by The swiss Government Using Micro-Level Survey Data:
An Empirical Analysis Based on Firm-level Data for Swiss Manufacturing, Zurich (mimeo. Arvanitis, S.,H. Hollenstein, S. Lenz (1998), Are Swiss Government Programmes of Promotion of Advanced Manufacturing Technologies (AMT) Effective?
An Economic Analysis Based on Microlevel Survey Data, Paper Presented at the International Conference on The Economic Evaluation of Technological Change, Georgetown University Conference center, Washington, D c.,June 15 16.
A Firm-Level Analysis Using Comparable Micro-Data from Four European countries, NBER Working Paper No. 14216.
More information on the European union is available on the Internet (http://europa. eu). Cataloguing data can be found at the end of this publication.
It presents the latest data on the process of global technology development and future prospects based on strategic knowledge assets.
Data: Eurostat, OECD, Unesco, Science Metrix/Scopus (Elsevier. Notes:( (1) Tertiary graduates in science and engineering:(
i) Data is not available for China;(2) GERD: Shares were calculated from values in current PPS€.
when compiling the data. 36.1 28.833.1 31.8 26.6 22.9 21.9 23.028.3 28.8 39.8 25.5 41.1 32.3 38.6 29.8 25.7 21.415.2 13.2 10.6 22.0
the data shows that the EU is still the main destination in the world, representing 1/4 of FDI inflows worldwide, twice the level of the US or China.
The most recent data (2011) is consistent with the overall finding of FDI data, namely of the EU's slightly falling but persisting world lead.
Stehrer, in the upcoming Innovation Union Competitiveness report 2013) EU (1)( 2) China United states India Japan Data:
2008 2010 2004 2006 2008 2010 EU-27 inward flows by partner bn EUR Data:
Foreign Direct Investments of European firms outside the EU Extra-EU FDI Outflows Data: OECD, Eurostat.
The service sector is excluded due to missing data. The size of the pie chart for each country indicates the total amount of R&d expenditure of foreign-owned firms in this country
The data presented illustrates the pre-crisis period. 6 As for the investments in research and innovation,
Extra-FDI Outflows Data: OECD, Eurostat. Source: DG Research and Innovation Economic Analysis Unit. 2004 2005 2006 2007 2008 2009 2010 2011 20%40%60%80%100%0
However, Chinese data is incomplete and has some methodological issues, which makes a comparison with data from OECD countries difficult.
The R&d expenditure of wholly foreign-owned companies in China was € 2. 4 billion in 2007.
Data: OECD, Eurostat, National statistical offices, DG RTD study calculations. Notes: 1) Firms from the European union spent € 774 million on R&d in Switzerland in 2007;
Swiss firms spent € 2. 47 billion on R&d in the EU-27 in 2007.2) Swiss data also includes the service sector;
data for China is estimated based on national sources and US and Japanese outward data. Figure 7:
Breakdown of Foreign Direct Investments by sector%of all extra-EU NACE sectors Data: OECD, Eurostat.
The numerator is based on firm-level data by headquarter and the denominator on national data (firms operating in the country independently of the location of their headquarter).
8 When a country has several large multinational corporations investing in R&d worldwide (in the country and abroad),
these investments can be larger than the sum of R&d investments financed by the businesses registered in the country (BERD data).
Data: Eurostat, OECD, EU R&d industrial scoreboard. notes:(1) EU average does not include Croatia. 8 For a more extensive methodological note,
and Industrial Scoreboard datasets, see Azagra-Caro, J. and Grablowitz, A.,2008.12 Europe's compet it ive technology prof i l e in the global ised knowledge economy between the two data sets,
The data for the United kingdom is particularly interesting, since the overall R&d intensity in the country is much lower than in other EU Member States.
PCT data. Technology-intensive countries in North america and Asia are more strategic than the EU,
Data: WIPO PCT applications; data processed by the University of Bocconi, Italy. 14 Europe's compet it ive technology prof
i l e in the global ised knowledge economy Economic transformation addressing societal challenges may come from Asia Figures 10 and 11 below highlight the accelerating progress of Asia in transformative technologies linked to major societal
Data: Eurostat, DG ECFIN, OECD. Source: DG Research and Innovation Economic Analysis Unit. Notes:(1) Patent applications under the PCT (Patent Cooperation Treaty), at international phase, designating the EPO by country of residence of the inventor (s).(2) The estimation for the period 2011-14 is based on the annual
Data: WIPO PCT applications; data processed by the University of Bocconi, Italy. Data: Eurostat, DG ECFIN, OECD. Source:
DG Research and Innovation Economic Analysis Unit. Notes:(1) Patent applications under the PCT (Patent Cooperation Treaty), at international phase, designating the EPO by country of residence of the inventor (s).(2) The estimation for the period 2011-14 is based on the annual
average growth rate calculated for the period 2005-10. Figure 11: PCT patent applications addressing societal challenges Environment Environment-related technologies PCT patent applications (1) per billion GDP (PPS€), 2000-14 (2) 0. 2
Data: WIPO PCT applications; data processed by the University of Bocconi, Italy. 17 3. Potential of European cooperation in converging technologies for emerging growth markets Technology development is an important part of the supply side of innovation potential.
A more strategic focus of supply measures for technology relevant for growth markets has strong potential to foster high-growth innovative enterprises
Conclusions 24 Europe's compet it ive technology prof i l e in the global ised knowledge economy Azagra-Caro, J. and Grablowitz, A. 2008)‘ Exploring data on business R&d:
and secondary data from existing studies enable us to probe the research gaps that we suspect exist.
Plenty of published data describes size, growth rates, specialisms, successful cluster companies, and many other features but this doesn't necessarily equate with defining cluster performance.
Various credible sources have offered data and insights as we have referred to in this paper but we confidently speculate there remains unconfirmed relationships between aspects of cluster operation and economic outcomes.
and bibliometric data 62. Generally speaking, such studies have detected most of the factors and mechanisms influencing the effectiveness of systems.
the analysis of patent data, Res. Policy 21 (1)( 1992) 79 93.75 A. Arora, A. Fosfuri, A. Gambardella, Markets for Technology:
data analytics and mobile are rapidly emerging as disruptive forces for businesses across all industries, from retailers and banks through to carmakers and energy companies.
and transfer the data onto a smart phone to send to a health care provider. This is an example of how technology contributes to generate new revenues for our firm,
The rise of the digital business A core set of digital technologies mobile, social, the cloud and data, among others are transforming companies at both an operational and a strategic level.
as the CTO or chief data officer? In many respects, this depends on CIOS themselves, argues Bob Sydow, Americas IT Advisory Leader at EY,
the amount of automation and data-driven information that they use in their daily business is magnitudes bigger than just a couple of years ago,
the amount of automation and data-driven information that they use in their daily business is magnitudes bigger than just a couple of years ago.
and uncovering new data-driven insights. My job is to find interesting new ideas and innovations,
The single biggest trend for marketing is to be oriented very data, he says. Of course, this raises specific challenges in the interface between marketing,
whether it's data consumption, acquisition or analytics, people expect answers immediately. To deal with this, IT
and mining of data captured, to gain greater customer insights and design more effective sales campaigns.
As a result, the executive management team has tasked now her with applying data analytics to generate new customer insights
whether it's data consumption, acquisition or analytics, people expect answers immediately. To deal with this, IT
like the aerospace CIO who explains convincingly the impact of harnessing in flight sensor data to transform their business model,
These CIOS clearly know their industry business processes, the value of collecting data from their products,
the business around monetizing that data, and creating value-added services. They know how to explain these new business models,
across both functions and companies Be willing to take risks Widen your resume Tasks at a personal level Set up the right architectures for growth Get control of your data Set out the relevant standards Understand strategic alignment with the rest of the business Take a fast,
so you need a foundational architecture for mobile, cloud, data, applications, and so on. If you don't,
CIOS have been focused largely on application and infrastructure delivery, ahead of data. But a shift into the cloud reduces the emphasis on the application front,
and makes data far more important again. Digital transformation requires to radically simplify the business and to change the mindset around product development.
to add additional context to our data and findings. We focused on those sectors independently identified as being the most IT-intensive,
Norway (16,3%),Island (13,7%),Switzerland (11,5%),USA (10,1%)and Denmark (2, 2%).The data confirms a much tied connection between the work tax
The changing nature of sectors, high data volumes and information intensity, the increased use of graphics and video, interactive websites,
Fexco (Tralee) and Quinn (Cavan) 25 Internet data transfer capacities are growing at a fast rate.
For ease of comparison across regions, data tables are provided in the Appendix. Border The Border region,
Key Data and Statistics Border Border State Average Dublin Unemployment (Q1 2009) 11.7%10.2%8. 9%Employment Growth 1998-2008 38%33
and services used in its production latest available data is for 2006 FORFÁS REGIONAL COMPETITIVENESS AGENDAS:
Key Data and Statistics-West West State Average Dublin Unemployment (Q4 2009) 11%10.2%8. 9%Employment Growth 1998-2008 37%33
Key Statistics and Data-Midlands Midlands State Average Dublin Unemployment (Q4 2009) 11.7 10.2%8. 9%Employment Growth 1998-2008 45%33
Key Data and Statistics Southwest Southwest State Average Dublin Unemployment (Q4 2009) 9. 9%10.2%8. 9%Employment Growth 1998-2008 32
and other Services, Food and Tourism Key Data and Statistics Midwest Midwest State Average Dublin Unemployment (Q1 2009) 11.4%10.2%8. 9%Employment
Key Data and Statistics Southeast Southeast State Average Dublin Unemployment (Q4 2009) 11.4%10.2%8. 9%Employment Growth 1998-2008 40%33
Key Data and Statistics-East Dublin Mideast State Average Unemployment (Q1 2009) 8. 9%9. 2%10.2%Employment Growth 1998-2008 22
Baseline Data and Analysis: Southeast Region which provides an overview of the region today based on an analysis of quantitative and qualitative indicators across a range of competitiveness factors;
Baseline Data and Analysis for the region. Figure 1: Factors of Competitiveness Overview Population and Growth Comprising of counties Carlow, Kilkenny, South Tipperary, Waterford and Wexford,
The IDA is developing a limited number of larger scale strategic sites that are intended to service utility intensive enterprise activity (e g. bio/pharma manufacturing, data intensive services.
2011 (Preliminary Results) See data in Appendix 1 SOUTH EAST EMPLOYMENT ACTION PLAN FORFÁS Map 1:
EN 0063509 Ordnance Survey Ireland/Government of Ireland-Data Source: CSO Census of Population 2011 (Preliminary Results.
CSO, Census of Population 2002 & 2006 and estimates based on preliminary data for 2011 The effect of the dispersed urban structure in the region is evident in the quite limited extent of Waterford City's commuter catchment area,
EN 0063509 Ordnance Survey Ireland/Government of Ireland-Data Source: CSO POWCAR data for 2006.
Not to be reproduced without permission from AIRO. The age profile of the South East diverges only slightly from that of the State as a whole.
A positive is that in 2006 (latest available data) the region had a higher proportion of its population aged under 15 (Appendix 1). SOUTH EAST EMPLOYMENT ACTION PLAN FORFÁS Economic Development
Trend data over the period 2006 to 2009 shows that the number of small enterprises
and at a faster rate than the decline nationally (Appendix 1). 7 Based on Forfás analysis of CSO Business Demography data.
The GEM 2008 findings are reflected in EI data with respect to the emergence of high potential start-ups from the region.
FAS SLMRU/CSO QNHS Data Early school leaving: Recent Department of education data on education retention at secondary level indicates that regional performance on educational attainment is likely to 8%6%15%13%25%26%16%12
%16%16%18%24%3%3%0%10%20%30%40%50%60%70%80%90%100%South East State
and Machine Operative occupations in the South East(-31 percent since 2008) relative to the State(-22 9 Refer to data tables in Appendix 3 22 percent).
however, a key challenge for the airport is 11 This is based on the 2006 Census data as 2011 data is not yet available by town.
and updated to take account of more recent sectoral data and trends through Forfás ongoing sectoral research and policy development 20 Teagasc (2008) Towards 2030:
and Infrastructure-such as NGNS, data hosting, etc. The broad sector displays strong growth prospects; driven by changing consumer behaviour/preferences in the sector, the increasing power of mobility & devices,
Data includes consumer spending on console (incl. handheld), PC games, online games and wireless/mobile games and video games advertising.
and Investment 9 Places Bachelor of science (Level 7) Information technology 17 Places 42 Refer to Appendix X for data tables 46 Table 5. 1 Education Providers
Data on the level of enrolments are not yet available. Courses are available across a range of NFQ levels
and engage. 43 See data in Appendix 3 SOUTH EAST EMPLOYMENT ACTION PLAN FORFÁS In addition,
KPO services include activities such as business research services, data analytics, patent research services etc. The increasing complexity of activities being outsourced often goes hand in hand with increased sensitivity of the related data
which may impact on a company's location decisions. 50 The corporate shared services activities are evolving in much the same way requiring a strategic partnership approach by The irish based subsidiary in terms of its relationship with affiliates and quality
Latest available regional data is for 2006 86 metric for a number of reasons, particularly because‘transfer pricing'by multinational corporations can exaggerate the value of activity taking place at a given location72.
100 sat the leaving certificate by 2010.73 The table below shows the available data on the South East counties compared to the national average. 73 The Department of education produce a final adjusted rate of 87. 7percent to take account of students that emigrated
FAS SLMRU/CSO QNHS Data 92 Figure A 15 Employment Permits issued in the South East 2004-2010 The number of new employment permits issued in recent times
Business Processes Transaction processing Data entry/conversion or indexing services to various verticals including e g.
Clinical data management Supply Chain/Procurement services Managing supply chain activities including Order to Cash,
or elements of IT services including e g. data hosting, Software as a service, Infrastructure as a service, Platform as a service etc. 102 Appendix 7 Business Process Outsourcing An Evolving Sector From Business Process Outsourcing to Knowledge Process Outsourcing Characteristics BPO Professional Services/KPO Business
The AR content embedded into the magazine includes a variety of 3d data-driven visualizations
Moreover, learning analytics based on such data are increasingly being incorporated across digital learning environments. Mobile devices such as smartphones or tablets can be used easily as well as clicker apps
Narrative science transforms data into stories and insights through its proprietary artificial intelligence authoring system. The algorithms the system uses are highly effective
measuring performance required data that were unavailable from suitable secondary data sources. Hence, we used subjective measures of performance provided by the respondent managers to capture firms'relative profitability
The model fits the data strongly (c2=123.40, df=81, p<.05; CFI=0. 99;
see The Global Competitiveness Report 2012 2013 with detailed profiles of all 144 economies as well as an interactive data platform are available at www. weforum. org/gcr.
the data suggest a slight downward trend of its performance in higher education (ranking 8th place on higher education
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