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.
and optimize their businesses through aggressive fraud management and the application of big data analytics. Mobile first strategy In 2014
Big data to monitor risks and identify opportunities Another big trend that is further maturing in 2014 is the application of big data analytics and visualization to the domain of online payments.
E-commerce leaders such as Amazon have been applying big data for years now with the objective of building sophisticated profiles of their consumers for Conversion Rate Optimization (CRO.
And with good reason. Cross-border payments can quickly become very complex and hard to manage.
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,
He studied Business Administration at Radboud University Nijmegen and he has a great interest in the international (digital economy and e-commerce.
Cluster analysis...74 European Competitiveness in KETS ZEW and TNO EN 4 Error! Unknown document property name.
Cluster analysis...125 4. 3. 1. Micro-and Nanoelectronics Europe: The Grenoble cluster...126 4. 3. 2. Micro-and Nanoelectronics Canada:
Cluster analysis...173 5. 3. 1. Industrial biotechnology cluster Europe: Cambridge (United kingdom...174 5. 3. 2. Technology cluster Non-Europe:
Cluster analysis...218 6. 3. 1. Photonics Europe: The Optical Technologies Berlin-Brandenburg cluster (Optecbb...219 6. 3. 2. Photonics Non-Europe:
Cluster analysis...269 7. 3. 1. Advanced Materials Europe: Wallonia's Plastiwin cluster...269 7. 3. 2. Technology cluster non-Europe:
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.
such as digital data processing (the first computer was invented in the 1940s) or cellular telephone communication (the technological principles have been discovered in the 1920s).
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.
All patent analysis rest on the Patstat database generated by the EPO. We use the September 2009 edition of Patstat.
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
All this complicates to foresee future market development and results in low accuracy of forecasts.
which further limits the accuracy of market forecasts. Chapter 2 Methodological Issues EN 41error! Unknown document property name.
Fourthly, establishing the accuracy of past market forecasts is complicated by either a lack of clear definitions of the technologies and products for
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
-OLED-2d photonic crystals-EUV lithography optics-quantum-dot lasers-3d photonic crystals-all-optical computing-optical metamaterials-data transmission through surface plasmons
) The tagging exercise was undertaken retroactively resulting in a full coverage of all patents related to nanotechnology.
Cluster analysis Nanotechnology has the potential to impact and shape many other industries through its multiple application possibilities.
'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:
While regional or national clustering has certainly its merits and can be an important driver for advance in nanotechnology,
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
Cluster analysis Clustering can be viewed from three angles: production locations, research activity and investments indicating future (production) location.
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.
Cluster analysis The geographical distribution of industrial biotechnology clusters can be summarised in four regions: West-and North Europe, American West coast, American East coast, and East asia.
Optical networks have opened the way to almost unlimited digital communication, building the very foundations of our Information Society.
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.
Cluster analysis On a global level, production is located (increasingly in low-cost countries, predominantly in Asia. In 2005 Japan represented 32 percent, Europe 19 percent North america 15 percent, Korea 12 percent and Taiwan 11 percent of world production.
but also to local and national governmental initiatives that promote regional clustering activities (Sydow et al.,2007).
) 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,
The financial resources are used to finance three FTE at Optecbb as well as to keep the internal database up to date,
First, it represents the activities of cluster firms to the outside world through a website, database, press releases but also coordinated events at industry fairs globally.
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
, photoresist chemicals, wet chemicals BCC (2006 Compound semiconductor materials 14.44 2006 33.7 2012 15 wireless electronic devices, optical data storage, fiber optics communications, illumination
Cluster analysis Advanced materials clusters can be found all over the globe, but mainly in North america, Europe, Japan, Australia,
which in the ECO data is listed 4th in the chemical clusters category with high level of innovativeness.
and its geography is spread across all the five Walloon provinces with an extended coverage to the Brussels region (see figure below).
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.
EN firm databases to increase transparency of the actors present in the cluster, provide intermediary services etc.
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.
and technology field analysis based on USPTO patent database, Journal of Nanoparticle Research 6. Hullmann, A. 2006), The economic development of nanotechnology-An indicators based analysis, Brussels:
Nordicity Group (2006), Regional/local industrial clustering: Lessons from abroad, Ottawa: National Research Council Canada.
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€.
4) Patent applications under the PCT (Patent Cooperation Treaty), at international phase, designating the EPO by country of residence of the inventor (s).(5) The coverage of the Rest of the World is not uniform for all indicators.
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:
Key words cluster, convergent, creative, digital, IT, ICT, information technology, start-up, SME, district, transformation, innovation, digital economy, media, co--working, Introduction Based on findings from the Tech
and secondary data from existing studies enable us to probe the research gaps that we suspect exist.
Historical Evolution of Creative Clusters‘Clustering'is a term that can be applied to a variety of human, animal, biological and scientific states.
Within this clustering the university and business enterprise may be supplemented by an incubation partner, typically separate from the main university campus and on the outskirts of the university town or city.
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.
Primary References Economist, 21st Sept 2013, p 30 Tech Nation‘Powering the Digital economy'www. TECHCITYUK. COM https//www. gov. uk/government/news
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.
For example, these individuals have a close focus on the front office and innovation: 65%are engaged highly in helping develop new products
the cloud and big data are transforming the way companies and their customers interact. At the same time these technologies are releasing a wave of IT-led innovation,
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.
to others selling its digital data In many cases, digital has moved technology toward becoming the front end of the spear rather than the tail feathers,
as the CTO or chief data officer? In many respects, this depends on CIOS themselves, argues Bob Sydow, Americas IT Advisory Leader at EY,
and systems of engagement (revenue-generating and firmly in the front office). Exceptional CIOS can play both of these roles,
He's now more closely engaged with the front office of the business, acts as the link between the firm's global IT strategy and its local implementation,
digital transformation 51%Discussing business performance with the executive management team 53%17%Seat at top table Involvement in innovation 50%Relationships to succeed Focus on front office IT-intensive industry CIO
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,
respectively The americas CIO and global CMO at SAP, believe their functions have changed so fundamentally with the advent of digital technologies such as big data, mobile,
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
The CIO of a major Chinese insurance company explains how her firm is working closely with the front office to give them the mobile tools they need to boost sales.
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
and making sure the front office understands what's possible. They also need to think differently in terms of integrating digital activities into their analog activities.
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,
but the real spending is being redirected into platforms, around analytics, big data, mobility and the cloud or whichever area has the highest benefit for your company,
however, will require you to build tight relationships across the front office starting with the CMO
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,
The digitisation of everything: how organisations must adapt to changing consumer behaviour, EY, 2011.4.5 Facts about Chief Digital Officers, by Dave Aron, Gartner, 6 november 2013.5.
Digital data opportunities: using insight to drive relevance in the digital world, EY, 2011. Predictive analytics:
The digitisation of everything: how organisations must adapt to changing consumer behaviour, EY, 2011. Born to be digital 41 EY Assurance Tax Transactions Advisory About EY EY is a global leader in assurance, tax, transaction and advisory services.
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