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SIBISIST– 2000-26276

Statistical Indicators Benchmarking the Information Society

Benchmarking Work, Employment andSkills in the Information Society in Europeand the US

by

March 2003

Benchmarking Work, Employment and Skills in the Information Society

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This publication has been prepared by empirica Gesellschaft fü r Kommunikations-und Technologieforschung mbH, Bonn (Germany) in the context of the IST-26276-SIBIS project (“SIBIS Statistical Indicators Benchmarking the Information Society”) inco-operation with the other partners in the project.All publications of the SIBIS project – including this report – are available in electronicformat on the internet at:www.sibis-eu.org

Neither the European Commission nor any person acting on behalf of theCommission is responsible for the use which might be made of the followinginformation. The views expressed are those of the authors and do not necessarilyreflect those of the European Commission. Nothing in this report implies orexpresses a warranty of any kind. Results from this report should only be used asguidelines as part of an overall strategy.

For further information, contact:empirica GmbHOxfordstr. 2D-53111 BonnE-mail: [email protected]

A great deal of additional information on the European Union is available on theInternet. It can be accessed though the Europa server: http://europa.eu.int

© SIBIS project and European Communities, 2003Reproduction is authorised provided the source is acknowledged.Printed in Germany.

http://www.sibis-eu.org

mailto:[email protected]

http://europa.eu.int


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Table of Contents

1 Executive Summary............................................................................................................9

2 Introduction .......................................................................................................................15

2.1 Topic Area Definition ................................................................................................... 152.2 Overview of the Report................................................................................................18

3 Identification of the Indicator Framework and Hierarchy ..................................................20

3.1 Skills ............................................................................................................................203.2 Work organisation ....................................................................................................... 243.3 Structure and outcomes of employment ..................................................................... 283.4 Suggestions for compound indicators .........................................................................30

4 Analysis of Data ................................................................................................................32

4.1 Skills ............................................................................................................................324.2 Work organisation ....................................................................................................... 424.3 Structure and outcomes of employment ..................................................................... 664.4 Preliminary results of compound indicator calculation ................................................71

5 Further developments ....................................................................................................... 73

5.1 Skills ............................................................................................................................735.2 Work and work organisation........................................................................................745.3 Structure and outcomes of employment ..................................................................... 75

6 Conclusions.......................................................................................................................77

7 ANNEXES.........................................................................................................................81

7.1 Annex I: Additional Tables...........................................................................................817.2 Annex IV: Explanation of Indices.................................................................................83

8 Bibliography ......................................................................................................................88

9 Methodology of the survey................................................................................................91

9.1 General Population Survey (GPS) ..............................................................................919.2 Decision Maker Survey (DMS)....................................................................................989.3 Questionnaires ..........................................................................................................104


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TablesTable 3-1: Indicators on skills from SIBIS and other relevant sources .................................... 24Table 3-2: Types of increases in flexibility of work organisation and role of ICTs ...................25Table 3-3: Indicators on work organisation from SIBIS and other relevant sources................27Table 3-4: Indicators on outcomes of employment from SIBIS and other relevant sources.... 29Table 3-5: Indicators for measuring worker-centred flexibility of work arrangements .............31Table 3-6: Indicators for measuring company-centred flexibility..............................................31Table 4-1: Participation in work-related training in last 4 weeks (in %) ................................... 33Table 4-2: Participation in work-related training in last 4 weeks (in %, EU15) ........................33Table 4-3: Self-directed learning in last 4 weeks (in %)...........................................................34Table 4-4: Participation in self-directed learning in last 4 weeks (in %, EU15) .......................35Table 4-5: Any work-related learning in last 4 weeks (in %)....................................................36Table 4-6: Use of e-Learning technologies for work-related training (in %, EU15) .................37Table 4-7: Use of eLearning for work-related training (in %) ...................................................38Table 4-8: Use of online eLearning for work-related training (in %) ........................................ 38Table 4-9: Women’s and Men’s use of e-Learning for work-related training (in %, EU15)...... 39Table 4-10: Enterprises offering training (CVTS data, as % of all enterprises) .......................40Table 4-11: Establishments giving the majority of their staff access to ICTs ..........................41Table 4-12: Establishments giving the majority of their staff access to ICTs (share among all

user establishments).........................................................................................................41Table 4-13: Employee participation in decision making on issues relating to changes in work

organisation (ESCWs data, in %) .....................................................................................43Table 4-14: Management by Objectives (ESCWs data, in %) .................................................44Table 4-15: Adaptability of daily starting and finishing times (in %).........................................45Table 4-16: Adaptability of number of working hours (in %) ....................................................46Table 4-17: Voluntary and involuntary part-time work (Community LFS, 2000 data)..............47Table 4-18: Home-based teleworking (in %, EU15)................................................................. 50Table 4-19: Interest in telework among persons employed (in %)...........................................52Table 4-20: Interest in telework among the unemployed and other persons looking for work (in

%)...................................................................................................................................... 53Table 4-21: Feasibility of home-based telework (in %, EU15).................................................53Table 4-22: Financing of teleworking equipment (in %)...........................................................54Table 4-23: Churn in home-based teleworking (in %, EU15) ..................................................54Table 4-24: Home-based telework and teleworker churn (in %)..............................................55Table 4-25: Mobile teleworking (in %, EU15)...........................................................................56Table 4-26: Tele-cooperation (in %, EU15) .............................................................................57Table 4-27: Tele-cooperation (in %).........................................................................................58Table 4-28: Self-employed teleworkers in SOHOs (in %, EU15).............................................59Table 4-29: Types of telework (in %) .......................................................................................60Table 4-30: Development of telework in the EU 1999 - 2002..................................................60Table 4-31: Outcomes of home-based telework (in %, EU15) ................................................62Table 4-32: Outcomes of home-based telework (in %, USA) ..................................................62Table 4-33: “e-Lancing” (in %, EU15) ......................................................................................64Table 4-34: Types of “e-lancing” (in %)....................................................................................65Table 4-35: Use of the Internet for job search (in %) ...............................................................66Table 4-36: Employment in IT occupations (in % of total employment)................................... 67Table 4-37: Employment in IT sectors (in % of total employment) ..........................................68Table 4-38: Sustainability of work and family life (in %, EU 15) ..............................................69Table 4-39: Job quality (in %, EU 15) ......................................................................................69Table 4-40: Overall job satisfaction (in %) ...............................................................................70Table 4-41: Results - Index on worker-centred flexibility .........................................................71Table 4-42: Results values - Index on company-centred flexibility..........................................72Table 7-1: Lifelong learning – Eurostat indicator based on Member States’ LFS (in %) .........81Table 7-2: Participation in any work-related learning in last 4 weeks (in %, EU15) ................81Table 7-3: Use of online eLearning for work-related training (in %) ........................................ 82


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Table 7-4: Sustainability of work and family life according to job position (in %, EU 15) ........ 82Table 7-5: Job quality according to job position (in %, EU 15) ................................................83Table 7-6: Indicators for measuring worker-centred flexibility of work arrangements .............83Table 7-7: Indicators for measuring company-centred flexibility..............................................86


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Foreword

For some years now statistical indicators on Information Society have been central inthe policy making process. This has been best demonstrated through thebenchmarking exercise of eEurope 2002 Action Plan, and its further inclusion as akey activity in eEurope 2005. Having recognised this need and driven by thedifficulties in obtaining reliable and appropriate statistics, the IST programmesupported a pan-European research effort during Framework Programme 5. Theprime objective has been to develop and make available methodologies, tools andnew statistical indicators which can help remedy the deficit in this field.

It is in this context that the SIBIS project was launched (IST-26276, StatisticalIndicators Benchmarking the Information Society”, www.sibis-eu.org). This documentpresents some of the project’s main findings so far.

There are at least two main reasons that make this document interesting. First, it isone of the few original attempts to have a coherent and comprehensive approach inmeasuring the Information Society. As such it is expected to stimulate further debateand research among the professional statistical community, leading to an improvedstatistical competence in Europe. Second, it provides a unique single source of dataon real time which supports many of the new IST research areas, at the launch ofFramework Programme 6.

Building on the original SIBIS research, in particular on the results of the indicatorsurveys, the project has produced 9 reports, selected from those addressed by e-Europe.

The SIBIS work attracts further interest since it also supports the e-Europe 2005initiative. SIBIS is carrying out an evaluation and a benchmarking of the eEurope2005 initiative for the 15 EC Member States and the 10 Accession countries whichwill become available later in 2003. Both the reports and benchmarking results canbe obtained from the SIBIS web site.

The publication of the SIBIS project results is a timely and direct contribution tobenchmark progress on key issues of the information society in general and the e-Europe initiative in particular.

Thanassis Chrissafis

[email protected]

DG INFSO-C6




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Preface

This report represents one of the main deliverables of the SIBIS project (Statistical IndicatorsBenchmarking the Information Society) (www.sibis-eu.org), funded by the EuropeanCommission under the “Information Society Technology” Programme (1998-2002). Theoverall goal of SIBIS is to develop and pilot indicators for monitoring progress towards theInformation Society, taking account of the “e-Europe action lines”. On this basis SIBISfocuses on nine topics of interest, i.e. Telecommunications and Access, Internet for R&D,Security and Trust, Education, Work, Employment and Skills, Social Inclusion, e-Commerce,e-Government and e- Health.

Within the SIBIS project two surveys (a General Population Survey (GPS) and a DecisionMaker Survey (DMS) of businesses) were conducted on the nine eEurope topics betweenMarch and May 2002. This report describes the outcomes with respect to the topic of “Work,Employment and Skills”. The document has two main objectives: to report on the results ofindicator testing and data gathering on the topic of “Work, Employment and Skills” in theSIBIS GPS and DMS surveys including compound indicator development and benchmarkingof the “Work, Employment and Skills” domain and on the basis of this and other relevantavailable indicators, specifying needs for further research into indicators in this field. Thereport has been peer-reviewed internally and by external experts.

The report is organised in number chapters and number annexes. The first three chapters aredesigned to give the reader an idea of the main outcomes (Executive Summary), the context(Introduction) and the indicators developed (Identification of the Indicator Framework andHierarchy). The core of the report is the analysis of indicators and a presentation of theresults of this analysis, provided in chapter 4. It discusses methodological issues such asreliability and validity of the data produced, presents preliminary results and containssuggestions for two compound indicators (indices). Chapter 5 spells out the need for furtherresearch into indicators in this field and chapter 6 presents the conclusions. The annexesprovide some additional tables, figures and the bibliography.

The main audience should be policy makers, statistical offices at all levels (national, e.g. CBS,Statistisches Bundesamt, Statistics Finland etc., and supranational, e.g. Eurostat, OECD),industry leaders and researchers in the domain and those involved and interested inbenchmarking the domain throughout Europe and the world.

Within SIBIS, another report for each of the nine topics has been developed during 2001.That report was aimed at setting the scene on the topic, defining the gaps in the statisticalcoverage and suggesting innovative indicators to be developed through the subsequentsurvey. The current report, although a self-standing document, is an interim report, since afinal version will be produced by April 2003.

SIBIS is led by Empirica (Bonn, Germany), and includes the following project partners: RandEurope (Leiden, The Netherlands), Technopolis Ltd. (Brighton, UK), Databank Consulting(Milan, Italy), Danish Technological Institute (Taastrup, Denmark), Work Research Centre Ltd.(Dublin, Ireland), Fachhochschule Solothurn Nordwestschweiz (Olten, Switzerland).

empirica Gesellschaft fuer Kommunikations- und Technologieforschung mbH (empirica) is awell established research and consultancy organisation in Germany with a strong track recordin European RTD and consultancy projects in the area of new and innovative concepts andapplications of information and communication technologies as well as benchmarkingdevelopments in the area of IST. empirica led the European-wide ECATT projectbenchmarking progress on new ways of work and electronic commerce in Europe by meansof a series of surveys of the population and establishments, and was responsible for theSeniorWatch project, the key European technology foresight and monitoring project in thearea of social care for the elderly and disabled people. Further projects with a strongrelevance and relationship to SIBIS include the IST project BISER (Benchmarking theInformation Society in European Regions) and the project E-Biz (e-Business Marketwatch), aservice contract for DG ENTR.



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For more information about empirica or this document, please contact:

Karsten Gareis ([email protected])Werner B. Korte ([email protected])Alexander Mentrup ([email protected])

empirica Gesellschaft fuer Kommunikations- und Technologieforschung mbHOxfordstr. 253111 Bonn - GermanyTel.: +49 228 98530-0Fax: +49 228 98530-12E-mail: [email protected]: www.empirica.com

www.sibis-eu.org

Acknowledgement

We thank Dr. Juha Antila (University of Helsinki, Ministry of Labour), Tiina Hanhike (FinishMinistry of Labour), Timo Kauppinen (European Foundation for the Improvement of Living andWorking Conditions), Ulrich Klotz (Industriegewerkschaft Metall), Dr. Jack Nilles (JALAInternational, Inc.), Dr. Juhani Pekkola (Finnish Ministry of Labour) and Dr. Pekka Ylostalo(University of Helsinki, Ministry of Labour) and our SIBIS partners for commenting on previousversions of this report. Of course, the authors are fully responsible for all remaininginsufficiencies and errors.





http://www.empirica.com



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1 Executive Summary

ICTs have led to profound changes to the organisation of work at micro level as well as labourmarkets at macro level over the last two decades. The ability of individuals, companies andgovernment to adapt to these changes appears to largely determine their success in theInformation Society. This is being reflected by EU policy making such as the eEurope initiativeand the European Employment Strategy, and has led to increasing demand for timely data onInformation Society related issues such as ICT-enabled new ways of working, telework, work-related IT skills, employment in IT sectors and occupations and many others more.

Indicators and data on these issues from existing sources are scarce, and often not suitablefor the task of informing policy-making. As a consequence there is still a lot of uncertainty andconfusion about the direction and intensity of developments regarding ICT-enabled new waysof working. SIBIS research on work, employment and skills intends to shed light on some ofthe related issues, for which one method is the development and piloting of an own set ofindicators through a general population survey conducted in the EU, Switzerland and theUSA, and a supplementary establishment survey conducted in selected EU countries.

For areas have been identified by SIBIS where statistics are in high demand and where theproject can make a valuable contribution to ongoing attempts of the European StatisticalSystem to develop new indicators: The acquisition of work-related skills, the organisation ofwork at the workplace level, and structure and outcomes of IT-related employment andflexible ways of working.

In the field of skills in the Information Society, the issues Lifelong learning and IT-relatededucation and training are the most pressing issues for which indicators are required. Theacquisition of skills increasingly takes place throughout the working life as opposed to thetraditional model in which it precedes the entry in the labour market. The more training andlearning takes place in non-formal and informal settings, the harder it is to measure. Eurostatprovides data on basic indicators such as participation in training activities which is based ondata from the Community Labour Force Survey (LFS). However, the results appear to be notentirely valid as the survey instruments used by the NSI’s for this survey use widely divergingconcepts and terminology, in spite of EU regulation which set down common guidelines.Results from the SIBIS pilot survey in which the EU labour force was asked whether they

participated in work-relatedtraining provided by theiremployer or anotherorganisation, or practisedself-directed learning whichwas related to their work,suggest that the extent towhich lifelong learning ispractised is underestimatedby the LFS data. Moreover,comparison betweencountries arrives at adifferent result with regard torelative performance ofMember States if comparedto the LFS data.

The SIBIS data suggests that the skills gap between the current workforce and theunemployed is going to widen because of the extent to which persons in employment areengaged in company-provided training, learning by doing and also self-directed learning. Itseems that the training provided by the state to the unemployed cannot make up for theprovision of learning opportunities companies supply to their staff.

Further research on indicators is necessary to develop tools for measuring the intensity ofnon-formal and informal learning activities. This is likely to require in-depth surveys such astime-use studies.

Participation in work-related training (in %)Base: Labour force

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The fast-moving universe ofICT applications presentsone reason why the labourforce, and people in general,need to learn continuously.But ICTs also provide one ofthe possible tools with whichto face this challenge, asthey can make the provisionof learning content andlearning environmentseasier. These so-calledeLearning technologiescomprise offline applicationssuch as learning

programmes on CD-ROMs as well as online applications usually transferred via the Internetor company/university-internal computer networks. About 15% of the EU labour force aremaking use of eLearning for work-related training, two third of which already use onlineapplications.

ICT user skills can beprovided via more or lessformal training measures butexperience shows that in anycase, user experience isneeded. This is usually beingacquired through regularworking with theseapplications as a workingtool. An important indicator,therefore, is the share of theworkforce which has accessto ICTs at their working place.SIBIS data shows thatbetween 40% (Greece) and

91% (Finland) of EU employment is in companies which grant their staff free access to theInternet. The commitment with which Finnish companies let their employees use e-mail andsurf the Net can be assumed to be one reason for the success of the country in the Europeaninformation economy.

The provision of IT skills (“digital literacy”) on the labour market is difficult to measurebecause direct assessment (which could deliver the best results) is extremely expensive andtime-consuming. Self-assessment is another possibility, but it requires careful testing of theinstruments used. The results of piloting the SIBIS module on self-assessed digital literacyare discussed elsewhere (see SIBIS report “Education”).

The demand for IT skills is comprised of demand for IT specialists and demand for IT skills ofnon-specialists. The main work to be done in this area is harmonisation of existing conceptsand terminologies which are being used in national studies on the issue, which would preparefor the required pan-European survey on IT skill requirements. Such a survey is needed tosupport EU policy-makers in their search for the right strategy on IT skills provision.

Just as the conditions for skill acquisition, supply and demand have changed as a result ofICT-related change, ICTs have also strongly affected the way work is organised in time andspace and with regard to content and contractual basis. These changes are of a more generalnature which means that indicators for measuring work organisation in the InformationSociety cannot restrict themselves to directly ICT-based ways of working, but should coverthe broader developments towards more flexibility in work settings which have been at thecentre of analysis of labour market research in recent years.

Use of eLearning (in %)Base: Labour force

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Establishments giving their staff access to ICTsBase: All establishments, weighted by employment

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e-mailInternetIntranet


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Among these, the flattening oforganisational hierarchiescombined with the shift frommanagement by eyeball tomanagement by objectivesare two hypotheticaldevelopments which are ofcentral importance. Adequateindicators for these includeparticipation in decision-making and discretion overthe order of tasks, methods ofwork and speed or rate ofwork. Comparing EUcountries using data from the

European Survey on Working Conditions shows that a larger than expected share of theworkforce may already be described as being managed by objectives, even in less developedEU countries such as Greece (33%) and Portugal (39%).

There are bigger variations between European countries with regard to working hours. UsingCommunity Labour Force Survey data reveals that not only do some countries have a muchhigher share of part-time workers than others (the Netherlands have 41%, Greece only 5%),there are also huge differences in the ratio of voluntary to involuntary part-time employment.Whereas in the Netherlands almost all part-time employment is voluntary, in Finland forexample one third of part-timing takes place involuntarily. This findings indicates that part-timeemployment should not be understood per se as flexible employment, at least not from theworker’s point of view as it might just be a poor substitute for full time jobs.

For measuring flexibility, voluntary part-time work seems to be the more appropriate indicatorfour our purposes. Another important indicator is the degree to which employees can adaptworking times to individual preferences and schedules (inside of working contracts with agiven number of working hours per week). The latter indicator has been piloted as part of theSIBIS GPS. According to this data, 49% of the EU workforce can adapt their daily starting andfinishing times to their own preferences, while 40% can adapt the number of weekly workinghours.

Telework and tele-cooperation have been identified as areas in which existing indicators(such as those which were used for the eEurope 2002 benchmarking exercise) are notadequately representing the nature of ICT-enabled changes to working locations. SIBISdeveloped a questionnaire module for measuring telework and tele-cooperation whichaddresses the short-comings of previous cross-country comparisons.

The results clearly show thattelework has many differentfaces (see figure on the right), ofwhich traditional teleworkers whospend a major share of theirworking time at home representonly one, and maybe not eventhe most significant, facet. 7% ofthe EU workforce are practisinghome-based telework. Thereseems to be evidence thatbecause of this the share of EUpopulation participating in thelabour force is higher than itwould be without the possibilityfor telework. This is an important contribution to the European Employment Policy’s goal ofincreasing labour market participation throughout the EU.

Management by objective (in %)Base: Total employment

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• working at home with PC

• using ICT to transfer work results

• permanent, alternating or supplementary

self-employedin SOHOs

home-based

• working away from main place of work

• using online-connections during business trips or in the field

• e-mail, Internet or remote access

• home is the main place of work or the base for trips into the field


• SOHO = small office, home office

mobile


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The most important effect oftelework, however, seems tobe to make workers moreefficient and effective bygranting them greaterflexibility in how to organisetheir work. Most teleworkersuse their home not forworking full days (only 2% ofall persons employed spendat least one full working dayper week at home), but forsupplementary teleworking.This means that they workonly some hours per day at

home, but still commute to a more traditional working environment for the brunt of their work.The home becomes a touch-down office, which is equipped for giving online access tocompany resources whenever needed, but it is in most cases not being used for full workingdays.

Preliminary results from a comparison with data from the 1999 ECATT survey even suggestthat the share of the EU workforce which practises permanent or alternating telework withmore than one full day per week spentat home is actually stagnating while thenumber of supplementary teleworkersis growing fast. This finding indicatesthat more and more people make useof the locational flexibility offered byICTs and spend some working time athome, but only comparatively few staywhole days at home. The number oftele-workplaces (in the technical senseof a networked workplace installedpermanently or temporarily in thehome) is increasing at a rapid rate, butthe number of persons working at home at any given point in time remains modest. Thelocation of work becomes more footloose, but there is no general shift of work from the officeinto the home.

The reasons for this are only partly extractable from the data, but the perceived need for face-to-face interaction with colleagues, customers or other persons certainly plays a key role. Still,about one quarter of all jobs are considered feasible for alternating home-based teleworkingby their holders, more than 10 times the number of actual people teleworking in this way.Together with the high degree of interest expressed by the labour force in telework, thesefigures suggest that the demand for telework is much higher than the supply provided byemploying organisations. More and more companies prove willing to give their staff remoteaccess to their computer network, but the acceptability of staff working from home whole daysseems to be limited.

This trend is complemented by the strong increase in mobile teleworking, i.e. the use of onlineconnections for work purposes during business trips. Here again, the technology is being putin place and increasingly used. The share of mobile teleworkers has grown from 1.5% to 4%in the course of only three years. This is likely to benefit employers, as the efficiency ofbusiness process increases because of more continuous communication flows. Self-employed teleworkers in SOHOs, many of which are freelancers, are also becoming muchmore numerous as tele-mediated communication with clients and work partners opens upnew possibilities for improving business performance. While the share of SOHO-basedteleworkers in the EU was only 1% in 1999, it is more than 3% in 2002 as a result of annualgrowth averaging more than 50%.

Spread of Telework in EU15

13.0%6.1%all types

3.4%0.9%self-employed in SOHOs

4.0%1.6%mobile telework

5.3%2.0%home-based telework < 1 day per week

2.1%2.0%home-based telework >= 1 day per week

20021999

Spread of Telework in EU15

13.0%6.1%all types

3.4%0.9%self-employed in SOHOs

4.0%1.6%mobile telework

5.3%2.0%home-based telework < 1 day per week

2.1%2.0%home-based telework >= 1 day per week

20021999

Home-based telework (in %)Base: Total employment

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From these observations wecan follow that most teleworktoday takes place in flexiblesettings, with the home actingas only one of a biggernumber of options for worklocations. Consequently, thenumber of mobile teleworkersis likely to outnumber home-based teleworkers soon.These trends should bereason enough to rethinksome of the originalassumptions about teleworkand how it will affect society.

Telework seems to be part of a general move towards greater variability and flexibility of theway work is organised, and is being implemented in ways that are believed to maximise theeffectiveness and efficiency of the work process. With regard to home-based telework, thehighest return seems to be believed to come from equipping workers with tele-workplaces,but keeping them at the central office location for most of their working time.

Telework is usually singledout as the most significantICT-related development withregard to working locationsbut tele-cooperation, i.e. theuse of the data transfer, e-mail and the Internet forcontacts between workplacesat geographically distantlocations, is bound to play abigger role in shaping the waythe majority work, as it affectsalready more than two third(38%) of the EU workforce.We can understand tele-

cooperation as making use of ICTs to enable new configurations of labour without actuallyhaving to move workers from one place to the other. Its attractiveness stems from the factthat labour is well-known to be geographically very immobile (in comparison to capital as theother major factor of production), so every new possibility to transmit products of workbetween locations of production without moving workers themselves is welcomed by industry.Indicators which explore tele-cooperation in more depth will have to be developed in thefuture.

SIBIS research on work, employment and skill also included an assessment of the degree towhich the self-employed make use of so-called e-lancing practises to conduct their business.In the narrow sense of the term, e-lancers are freelancers who “work on the Net”, i.e. carryout all communication with others (supplier, work partners and associates, clients andcustomers) through the Internet or other computer networks. For survey research, and basedon the assumption that e-lancing in the narrow sense of the term is still extremely seldom,SIBIS defined three different degrees of e-lancing using the variables a) attracting newbusiness online b) delivering work results online and c) communicating exclusively viaelectronic means. 9% of the self-employed in the EU communicate at least sometimesexclusively via electronic means with their clients, thus may be called (occasional) e-lancers.The share is much higher in the U.K. (18%) and the USA (14%) which appear to be headingthe freelancer movement onto the Internet according to the results from the pilot survey.

The effect of telework and other new ways of working on dependent variables on outcomesof employment such as job quality, job satisfaction and the balance between work and familyhas until recently almost exclusively been explored via case-study based research. Thismeans that the degree to which research results are representative for the entirety of atypicalworkers is unknown. There are many reasons to assume that the choice of workers for case

Mobile telework (in %)Base: Total employment

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Tele-cooperation (in %)Base: Total employment

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studies is highly selective. Representative studies which are based on representativeprobability samples of the entire adult population (such as the SIBIS pilot GPS) are thereforeneeded. After finishing multi-variate analysis of the survey data (which is currently ongoing), anumber of indicators which compare work outcomes at the personal level between traditionaland new ways of working will be operationalised in detail.

The structure of IT-relatedemployment can beenmeasured using data from theCommunity Labour ForceSurvey which follows theNACE and ISCO-88 classifi-cations. The share of employ-ment in IT occupations (ISCO213, 312, 313) in the EU liesbetween 0.6% (Greece) and3.2% (Nether-lands), withdata for Ireland missing.Employment in IT sectors ishighest in Ireland with 2.9%of the total workforce.

In order to aggregate the findings from a large number of indicators (some of which havebeen presented in this report) it may be advisable to construct compound indicators whichadequately represent complex constructs. SIBIS research on work has developed two suchindices based on data from a number of sources, namely the index on worker-centredflexibility and the index on company-centred flexibility. They rest on a conceptual frameworkwhich stresses the need to distinguish between on the one hand flexibility for workers toadapt ways of working to personal requirements and preferences and on the other handflexibility for companies to deploy labour according to business objectives. The selection ofcomponent indicators was not derived using statistical methods, but through consensus-building involving policy-makers at the EU and nation state level, and was informed by thecurrent objectives of the European Employment Policy. While data availability from time-series sources is still a major problem for such index-building, the results of the exercise pointtowards significant differences in the distribution of flexibility between both supply anddemand side of the labour market.

Employment in IT Occupations (in %)Base: Total employment

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n.a


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2 Introduction

2.1 Topic Area Definition

2.1.1 Problem description

Of all the impacts of information and communication technologies (ICTs), arguably it has beenthe effect on labour markets and on the way work is organised which has had the most far-reaching repercussions on the societies of EU Member States, and the rest of the developedworld. The adaptation of statistical systems to these changes is an enormous task, which – itmay be argued – has only just begun. However policy makers urgently need adequate dataon the direction and nature of change, since they have to be able to devise the necessarymeasures in order to make society adapt in a way that maximises benefits for all.

ICTs have led to profound changes to the organisation of work at micro level as well as labourmarkets at macro level over the last two decades. The ability of individual companies as wellas regional, national and supranational labour markets to adapt to these changes appears tolargely determine their success in securing medium and long-term economic development.This is being reflected by EU policy making such as the eEurope initiative and the EuropeanEmployment Strategy.

At the same time, ICTs are also providing solutions for these requirements, as applications ofICT in education and training such as computer-supported training programmes open up newpossibilities for making acquisition of skills easier. In this context the issue of “e-learning” hasattracted particular attention, since remote learning technologies may remove one importantbarrier to the provision of knowledge to people, namely distance. E-learning, too, featureshigh on the EU agenda, as the Commission’s “eLearning Action Plan” proves.

2.1.2 Framework for assessing the area

For the purpose of indicator development, SIBIS has structured the Topic area broadly intothree subsections: skills, work organisation, and structure and outcomes of employment.

Skills are defined as the "learned power of doing something competently". In the context ofwork and employment, skill is the ability to fulfil tasks which are part of a gainful occupation.More precise: Skills are the ability to conduct a certain activity with particular means and at acertain speed. Skills are the main “goods” demanded and supplied on the labour market.They constitute the necessary input for the productive deployment of individuals in theproduction process. ICTs have a very decisive influence on the way skills are acquired and onthe type of skills offered and requested on the labour market. These technologies most of allhave changed the speed with which specific skills must be produced and become outdatedagain. This again considerably affects the required structures for education and training whichhave to be provided to support skill production. The supply side, namely the acquisition andprovision of skills, are at the centre of SIBIS research, as the need to apply knowledge andskills efficiently and effectively has been identified as an imperative of the information society(OECD 1996: 32). Today these requirements focus on general skills needed to make use ofICTs, as well as the specialised, technical knowledge needed to compete in increasinglyknowledge-intensive work environments.

Work is defined here as aimed productive activity. Work is the process of making use ofhuman capabilities, i.e. skills, in the production process. There is a complex relationshipbetween technology and work organisation, both impacting on each other in a way thatpropels change. In SIBIS, only productive activity for remuneration is considered, in otherwords gainful occupation. Self-work and societal work, two other main types of work, are notrelevant here. Mostly, gainful occupation takes place in a private sector company or a publicsector organisation. There, individual work is embedded in a larger context and is subject to acertain kind of work organisation. Organisational aspects of work, that is to say the co-


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ordination of employees in the course of the division of labour, are at the centre of theresearch on "work" in SIBIS.

The structure of employment refers in particular to the sectoral and occupational distributionof employment, as well as unemployment and labour force participation. The sectoral andoccupational structure of the workforce is in a process of constant change, which again isenabled or even propelled by advances in technology. While these are certainly areas wherenew statistics and new indicator systems are in high demand, they are not an area where theSIBIS project has developed new indicators since the main work to be done in that arearelates to the design of new classifications and taxonomies of sectors and occupations ratherthan the development of new measures. This report will refer to existing data from thirdsources.

The analysis of outcomes of employment should distinguish between outcomes from thecompany perspective (such as gross value added, wages, social costs, and productivity whichrelates value added to inputs) and outcomes from the worker perspective which can bemeasured using diverse indicators such as payment levels, perceived job quality and jobsatisfaction. The emphasis in this report is on indicators measuring outcomes from the workerperspective.

SIBIS research in this area has by necessity to be focused as the breadth and sheer numberof available indicators and also “wish lists” for new indicators are very large. SIBISconcentrates on social indicators for which data can be collected using surveys of thegeneral population (including the labour force) and/or decision makers in companies.

2.1.3 Identification of stakeholders and their interactions

The main stakeholders in this Topic area can be further broken down as follows:

ü Workers: On the labour market, workers supply the human capital which is the mostimportant factor of production skills in an increasing share of sectors. As far as the labourmarket allows, workers will try to find jobs which they deem most likely to meet theirindividual preferences, and provide the highest remuneration. Workers may use ICTs forall parts of the job matching process (locating job offers, communicating with recruitersetc.) as well as in the work process itself. ICT-driven sectoral and occupational changewill also alter the type of jobs which are available on the labour market.

ü Employers: Employing organisations form the demand side in the labour market. As such,they translate their labour deployment requirements into demand for types of skills. Dueto the relative immobility of the factor labour in comparison to capital, companies tend tolocate their operations where they find the right mix of workers. ICTs have greatlyimpacted production systems and the scale and pattern of value chains, and of coursehave also enabled the invention of new products. All of these developments lead tochanges in the labour requirements of companies, and the organisation of work.

ü Intermediaries in the labour market: This includes the Public Employment Services butalso private companies that derive revenues from supporting matching between supplyand demand of labour. These intermediaries are important as users and providers of ICT-based matching services that may increase the efficiency and performance of the overallmatching process (Gareis and Mentrup 2001a).

ü The unemployed and the hidden labour reserve: Individuals who are either unemployedor who have decided not to take part in the labour market but would be willing to workunder altered circumstances represent the labour force reserve. The size of this group ismainly influenced by the regulatory framework, the business cycle, and a number ofstructural parameters (Fuchs and Schmidt 2000). In the face of a scarcity of IT skills onthe market, IT skills in the labour reserve play an important role.

ü Government: The state takes a central role in the labour market by creating theframework in which labour can be traded between workers and employers. Manyobserves think that state intervention is to a large extent responsible for the differences inthe performance of labour markets between the Member States of the EU, and beyond.This applies, in particular, to the speed and nature of the diffusion of modern new ways ofworking, including ICT-enabled work forms (EC 1999stat). Government (at the national,


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country, regional and/or local level) also regulates the field of education. Providing ITskills by means of continuous education is, for this reason, partly a task of the state whichcan act by creating a regulatory environment that is conducive for self-directed andcompany-provided learning and training activities.

ü Social partners and other non-government regulators: Traditionally, social partners play amajor role in national employment policies in the EU. The results of the collectivebargaining process have far-reaching implications for work organisation. In particular,attitudes towards the application of ICTs and new ways of working influence decisionstaken on the company level and thereby can significantly affect the diffusion process.

ü Former educational system: This is the most visible provider of educational services1 andmade up to the largest part by public educational institutions such as schools anduniversities. The role of IT skills in the curricula is among the determinants whichinfluence how well prepared school leavers and graduates are for meeting therequirements of the labour market. The former educational system is dealt with in aseparate report.

ü Non-formal educational system: This comprises the providers of further education whichmay be educational institutions run by the state or by private bodies such as unions andprofessional associations, but also includes companies who run schemes for providingskills to their workers. The services are paid for by the state, employers and/or therecipients. The non-formal educational system is likely to bear the brunt of supplying the“new” skills demanded for in the Information Society, and of up-dating existing skills inorder to catch up with fast-changing, often ICT-driven skill requirements.

ü Actors providing informal training: This kind of training is mainly provided by companies (itincludes “learning by doing” which takes place at the workplace), as well as by workersthemselves. Almost by definition, informal training activities are the hardest to pin down,and to supply data on. Work-relevant IT skills are more likely to be taught informally thantraditional skills since the world of ICT changes so fast that formal training schemes oftentake too long to establish before they become outdated.

ü Providers of technology: Education technologies, workplace and other productiontechnologies are at the very core of Information Society-related developments in work,employment and skills. Using ICTs for education offers huge potentials. Workplacetechnology has strongly supported the increase in locational flexibility which companiesas well as employers make use of today. Data on IT as production technology is collectedin Europe by the European Information Technology Observatory (EITO).

The figure demonstrates the type of interrelations which exist between the different groups ofstakeholders, as outlined above.

1 The OECD (Drymoussis 2000: 4) distinguishes between three basic categories of purposeful learning activity: (a)

Formal education – It refers to learning taking place in education and training institutions leading to recogniseddiplomas and qualifications. According to the Glossary of the ISCED97 classification formal education refers to"...the system of schools, colleges, universities and other formal educational institutions that normally constitutesa continuous ’ladder’ of full-time education for children and young people, generally beginning at age five toseven and continuing up to 20 or 25 years old." In some countries, however, these age limits need to beextended. (b) Non-formal learning/ education – It refers to learning taking place within or outside educationalinstitutions, including the workplace and does not typically lead to formalised certificates. According to ISCED97,non-formal education comprises "any organised and sustained educational activities that do not correspondexactly to the above definition of formal education. Non-formal education may therefore take place both withinand outside educational institutions, and cater to persons of all ages." (c) Informal learning – It consists of allintended learning activities and/or situations that cannot be classified as formal or non-formal education andtraining (i.e. self-directed training or in-groups at the workplace or within the family). These activities arecharacterised by relatively low level of organisation.


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Figure 2-1: Stakeholder groups in the Topic area “ Work, employment and skills”

LABOUR MARKET

EDUCATION

REGULATION

workers employers

socialpartners government

otherregulating

bodies

intermediaries

formaleducational

system

non-formaleducational

system

actors providinginformal training

unemployed &hidden labour

reserve

PRO

VID

ERS

OF

TEC

HN

OLO

GY

educ

atio

nte

chno

logi

es

wor

kpla

ce &

prod

uctio

nte

chno

logi

es

Each of these groups represent subjects on which data needs to be collected, but alsoproviders of data. For example, the unemployed are a group whose size and nature needs tobe measured using statistical indicators (as it is done in the Eurostat Benchmark EmploymentSeries), but they also act as respondents in social research on factors determiningunemployment, and social outcomes of this (such as in the Community Labour Force Survey).

2.2 Overview of the Report

In the following chapters, development of indicators for the Topic area “work, employment andskills” is briefly outlined before first results of indicator piloting undertaken as part of SIBIS arediscussed.

Chapter 3 explains the hierarchical tree developed for structuring indicators for work,employment and skills. The chapter also includes a tabular presentation of level-1 indicators.Supplementary level-2 indicators can be found in the an earlier SIBIS report (if relevant thyare referred to in this document). Level-1 indicators are called those survey-derived indicatorswhich are most relevant in terms of lack of current data availability and/or value forbenchmarking the progress of EU Member States in the Information Society. Data sources forlevel-1 indicators are either dedicated surveys of the general population or establishments(pilot versions of which are part of the SIBIS project), or other sources, depending on theappropriateness of the methodology for the data requirements involved. It should bementioned here that, because of budgetary constraints, not all Level-1 indicators can bepiloted through SIBIS surveys. Level-2 indicators are those which are collected additionally inorder to gather data on contextual indicators which are needed to support interpretation oflevel-1 indicators, or in order to validate the new indicators against data from other sources.Level-2 indicators might also be those which are of interest only to a comparatively smallgroup of specialised interests (e.g. ICT manufacturers). The tables in chapter 3 specify level 1indicators piloted in the SIBIS survey, as well as those which are not included in SIBISsurveys but are suggested either to be taken up by other organisations involved in EU-widedata collection, or to be calculated from readily available data from third sources.

Chapter 4 contains first results of the SIBIS surveys in which selected level-1 and level-2indicators have been piloted. It discusses methodological issues such as reliability and validityof the data produced, and also presents some preliminary statistics.


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Chapter 4 also contains two suggestions for compound indicators (indices), one intended torepresent worker-centred flexibility of work arrangements, the other to represent company-centred flexibility of work arrangements. By theory-led combination of indicators from a varietyof sources, these indices allow to rank countries such as EU Member States according to theoverall performance in comparison with each other. Although indices of this type have to beapproached with care because of the necessary high level of aggregation of data, theynevertheless prove to be of high value for communication of the results of statistical analysisto policy makers and the wider public.

Chapter 5 spells out the need for further research into indicators in this field. It focuses, inparticular, on indicators which have been defined in SIBIS but which could not be piloted forreasons to be discussed. It also highlights where the results from the pilot surveys indicatethat different indicators than those developed in SIBIS may be needed to obtain a moreadequate picture.

Chapter 6 presents the conclusions of the SIBIS research into indicators on “work,employment and skills in the Information Society”. The annexes provide some additionaltables, figures and the bibliography.


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3 Identification of the Indicator Framework and Hierarchy

As outlined above, SIBIS structures the Topic into the domains

ü skills,ü work organisation andü structure and outcomes of employment.

For each of these domains, available indicators have been identified and analysed accordingto their suitability for mapping Information Society developments (see the earlier SIBISreport). In addition, indicators which are in development, i.e. have been piloted in one-offstudies or in one or a small number of EU Member States, have been collected. Data sourcesfor these indicators range from administrative data collections by supranational statisticalbodies such as Eurostat, ILO and the OECD, and by national statistical offices, to regularsurveys conducted by research organisations.

Indicator identification as well as development have taken place using the above structure,which is further specified in the figure on the next page.

3.1 Skills

The aggregated skills of workers constitute the supply side in the labour force. New skills areconstantly added to the open labour market by new entrants who have just finished theireducation, by influx of foreign workers, by training measures through which unemployed aretaught skills that are in demand, and by self-learning activities of job-seekers. People in workgain skills informally through their everyday working experience, and/or formally throughemployer-supplied training or training measures provided by third parties.

New skill requirements follow from the concept of the Information Society for a number ofreasons (Davidow and Malone 1992; Stock et al. 1998; Datamonitor 2000; Ducatel andBurgelman 2000; Millar 2001; OECD 2001wb; ILO 2001):

ü Size of ICT industry: The technology that underlies the information society, namely ICTssuch as the Internet, itself forms an industry of considerable size; companies that operatein this industry depend on the availability of skills that are in line with the dynamicrequirements of the market. As in other industries that rely to a great extent on innovationas their main driving force, specific skills that have been acquired in the past are indanger of becoming obsolete extremely fast; they are constantly being replaced by newskill requirements.

ü ICT effects the whole economy: The nature of ICT-related innovation implies that ICT is abasic technology that affects the foundations of the whole economy in one way oranother. It impacts on all economic sectors, as ICTs are applied throughout the economyto increase productivity and enable innovation. Consequently, ICT-related skills are indemand in all companies, either as specialist skills for the operation and maintenance ofICT equipment, or as user skills for applying the technology to support the aims of theorganisation.

ü Widespread private ICT use: People (as citizens or consumers) need skills in using ICTsfor them to be in the individual as well as public interest. These skills are not directlyrelated to the competitiveness of companies, but the reality shows that companies benefitfrom domestic markets in which they can test their products in. The more advanced apopulation is with respect to the availability of ICT user skills, the better the conditions forcompanies that sell innovative ICT-related products.


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BWork organisation

B2 Time B4 ContractB3 PlaceB1 Content

/Appliedskills

C Structureand Outcomes of

Employment

ASkills

C2 Employ-ment

Structure

C3 Outputof Employ-

ment

C1 Employ-ment

Benefits

A1 Skillacquisition

A2 Skillprovision

A3 Skillrequire-ments

A1-1 Formaleducation

A1-2 Non-formallearning/education

A1-3 Informallearning

A2-1 Educationalattainment

A2-2 General ICTskills

A2-3 Life skills

A3-1 Demand forICT-related skills

A3-2 Suitability ofICT-related skills

B1-1 Working tools

B1-2 Workingmethods

B1-3 Function indivision of labour

B1-4 Self-determination

B2-1 Worker-centred time

flexibility

B2-2 Company-centred time

flexibility

B3-1 Telework

B3-2Tele-cooperation

B4-1General

B4-2Self-employment

B4-4 Duration ofcontract

B4-3 Labourmarket flexibility

B4-5Compensation

C1-1 Materialbenefits

C1-2 Immaterialbenefits

C2-1 Overallemployment

C2-2 Sectors andoccupations

C2-3Unemployment

C3-1 Labourproductivity

C3-2 Unit labourcosts


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ü Shortened skill lifecycles: The application of ICTs has also affected the demand for skillsthat are not related to ICTs themselves. These indirect effects result, in particular, fromthe shortening of product life cycles that is being enabled by technology. The intensity ofresearch and development associated with creating new products has steadily increased.Competitive forces are bound to lead to a further acceleration of the process of translatinginnovation into marketable products and processes. As new products and processes areassociated with new skill requirements, skill life cycles, too, have shortened and willdecrease further in the future.

For the purpose of identification and classification of existent and to be developed indicators,SIBIS suggests to distinguish between

ü indicators measuring the acquisition of skills (this includes educational attainment, etc.),ü indicators measuring the provision of skills (i.e. the skill supply on the labour market) andü indicators measuring skill requirements (i.e. the demand for skills on the labour market).

The acquisition of skills takes place either in the formal education system (mainlycomprised of elementary and secondary schools as well as third level institutions such asuniversities), as non-formal learning/education (which includes further training measuresprovided by the state, mostly to the unemployed, as well as apprenticeship schemes andother certificated training schemes which often are provided by companies) or as informallearning, e.g. self-directed learning, “training on the job” etc.

The main theme running through all discussions related to the Information Society is the issueof Lifelong Learning. The need to make people engage in learning for their whole lifetimeimpacts, if taken seriously, on all parts of the education system (formal, non-formal, informal),but of course it affects especially the relative importance of non-formal and informal trainingand learning vis-à -vis the training provided by the established, formal education system.Because of their elusive character and problems concerning the definition of “learning”against other human activities, it is informal learning activities which are, in particular, not wellrepresented in available statistics, but non-formal training, too, is not covered sufficiently byindicators yet which is mainly due to the variety of schemes on offer and the resultingdifficulties of comparability.

The Eurostat Taskforce on Measuring Lifelong Learning has investigated existing indicatorsand suggested new ones for remedying the current lack of data (EC and Eurostat 2001).These suggestions have been the starting point for developing the SIBIS indicators in thisfield. The document asks for the EC and Member States to "develop data relating to [thedocument’s] six key messages and to define appropriate quantitative and qualitativeindicators on lifelong learning" (EC 2000memo: 20-21). Many of the themes discussed in thedocument would require a “complete survey on education and informal learning” (Skaliotis2000), but SIBIS has developed more specific indicators which can be used as stand-alonevariables in surveys.

ICTs are not only a major cause for new skill requirements, but they also provide solutions formeeting them. For example, the training may make use of the Internet to substitute orsupplement traditional training. Such a case is distance learning or eLearning, where trainingthat traditionally would have occurred in a classroom takes place via an ICT link (Urdan 2000;OECD 2001e-l). eLearning is defined in the European Commission’s “eLearning Action Plan”(2001: 2) as

the use of new multimedia technologies and the Internet to improve the quality oflearning by facilitating access to resources and services as well as remoteexchanges and collaboration.

eLearning can help meeting the challenge posed by the Information Society: “A requirementthat cuts across all education settings is the need to significantly improve the efficiency of thelearning process and thereby control the cost of an exploding demand for education andtraining” (do.: 2). Moreover, new organisational models for the provision of training servicesare needed which take advantage of ICTs as well as traditional methods of teaching (Hanna1998).


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Hardly any indicators are available on e-learning yet. New indicators are needed for mappingdevelopments in the supply as well as in the application of eLearning technologies (reach,frequency and intensity of use) and their outcomes. As a first step SIBIS suggests a moduleon e-learning to be included in population surveys.

The provision of skills (i.e. the supply of skills on the labour market) has been at the centreof a public debate on the shortcomings of today's education systems. Data on educationalattainment, e.g. on the intensity of certain professions in the graduate output, are readilyavailable (although comparability between countries suffers from national differences ineducation systems and curricula). However, data on IT-skills in not directly ICT-relatedprofessions (non-specialist ICT skills of students) is scarce. This applies also to thepopulation in general. In principal, there are three ways to measure skills:

ü (a) counting certificates which have been granted to all citizens who have mastered adefined sets of skills in some sort of examination. This option is only available if acommon assessment scheme is available across countries, and widely used by citizens.With regard to ICT skills, such a scheme is not available, although the EuropeanComputer Driving License (ECDL) initiative is working on this goal.

ü (b) directly measure skills through some sort of testing. This is extremely time-and cost-intensive, as the experience with the International Adult Literacy Survey (IALS) hasshown. It has to be doubted if a large-scale survey of the size of the IALS will ever beable to adequately provide data on IT-related skills because of problems of timeliness, asIT-related skill requirements change much faster than the sort of basic literacy skillsincluded in the IALS concept.

ü (c) asking people to self-assess their skill-levels. This requires much less resources, butof course brings up questions of the reliability of the data. A module for doing this waspiloted in SIBIS. The validity and reliability of the data gathered is discussed in theseparate report on education in the Information Society.

With regard to skill requirements, only very few indicators are available yet, most of themdeveloped ad hoc for specific policy problems (such as the proprietary data provided by ITconsultancies such as IDC), because data available from NSIs are limited to vacanciesunfilled statistics provided by Public Employment Services (PES), which are not compatiblebetween EU Member States. They also do not allow for an exact assessment of skillrequirements, as data is only provided along occupational categories that do not adequatelyreflect the variety of IT-related skills to be found in reality.

SIBIS recommends indicators on the ICT skill requirements recruiting companies haveregarding non-ICT staff, and on the suitability of ICT skills of job applicants/ new recruits. Bothrequire a special survey targeted at HR managers in companies.

The table below shows the indicators developed in SIBIS, distinguishing between indicatorsthat could be piloted in SIBIS surveys, and those which could not, but are recommended tothe be taken up by the European Statistical System. This is discussed in more detail insection 5 of this report.


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Table 3-1: Indicators on skills from SIBIS and other relevant sources

Thematic Domain &No. Indicator Name

Existingindicator ofrelevancefor SIBIS

New SIBISindicator

Skill acquisition (sa1) Participation in work-related training XSkill acquisition (sa2) Spread of self-directed learning XSkill acquisition (sa3) Participation in work-related training and learning XSkill acquisition (sa4) Use of e-learning for work-related training/learning

by workers (offline/online) X

Skill acquisition (sa5) Use of e-learning for study-related training/learningby students (offline/online) X

Skill acquisition (sa6) Enterprises offering training (CVTS) XSkill acquisition (sa8) Companies supporting self-directed training by their

staff R

Skill acquisition (sa9) Share of establishments giving staff access to ICTs XSkill acquisition (sa10) Use of PIAPs by the population2 XSkill provision (sp1) ICT skills in the labour force (self-assessed)3 XSkill provision (sp2) ICT skills in the labour reserve (self-assessed) 4 XSkill requirements (sr1) Employers' ICT skill requirements of non-

professionals R

Skill requirements (sr2) Perceived suitability of ICT skills of job applicants/new recruits R

R = SIBIS has not collected data on this indicator, but has operationalised the indicator which is recommended to bepiloted as part of an existing regular EU survey

3.2 Work organisation

The concept and idea of new ways of working has been described as a new paradigm. It isnecessary to conceptualise this paradigm shift in sufficient detail so that the underlyingdevelopments can be mapped using existent, and newly developed indicators.

In general, the transition which could be observed in the last years is characterised bydevelopments toward greater flexibility of labour deployment (Toffler 1980). A changingeconomic environment together with shifts in social attitudes and the widespread applicationof ICTs are believed to have resulted in greater spatial, contractual and temporal flexibility,shifts towards more self-provided social security provision, the need for multi-tasking andsignificantly more dynamic (social) skill developments (Bü ssing and Glaser 1998; Klotz 2000).ICTs are enablers of change but they do not predetermine outcomes. They do not e.g. pushlabour markets towards specific configurations, but open up new possibilities for organisingwork. The way ICTs are applied to change the organisation of work is to a great extentdependent on the bargaining power of employers vis-à -vis workers (Stanworth 1998;Valenduc et al. 2000) and on regulation by the state (ILO 2001). For this reason it is useful todistinguish between worker-centred and company-centred flexibility (see table below).

When looking at flexibility developments, the dimensions considered are working time, theplace of work, the type of contract and the work content, i.e. the skills that are applied in theproduction process (see figure). There are numerous interrelations between each of thesedimensions; for example, a change to the contractual underpinning of the work relationshipusually also results in (or is driven by the need for) a more flexible use of working time andplace. All major parameters of the change in the organisation of work can be captured usingthis framework. 2 This indicator is reported on in a separate report (Telecommunications & Access)3 This indicator is reported on in a separate report (Education)4 This indicator is reported on in a separate report (Education)


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TIME- average per day, week,

month etc.- distribution- variability

PLACE- location of workplace(s)- co-operation between

locations- variability

CONTENT- skills applied

- working methods- working tools

- decision-making- variability

CONTRACT- contract of employment- "informal contract" and

responsibility- payment- variability

The figure below outlines the role of ICTs in changes to the flexibility of work organisationfrom the viewpoints of workers (left hand side) and companies (right hand side).

Table 3-2: Types of increases in flexibility of work organisation and role of ICTs

Dimension: ContentWorker-centred:Aim: Broader and constantly updated skillendowment to make it possible to work in greatervariety of work contexts.Job enrichment and job enlargement.Participation in decision making, in particular withregard to change management.Role of ICTs:Rapid development in application of ICTs speedsup the skill life cycle, making continuous learningmore important than ever.e-learning makes access to learning material andtraining offers easier.

Company-centred:Aim: Broader and constantly updated skills mix instaff to be able to adapt quickly and accurately tovariations in demand that follows from business.Handing responsibility over the achievement of worktargets to workers (Management by objectives).Role of ICTs:e-learning technologies make training workers easierand cheaper.HR management systems make managing skills inthe staff easier.Workflow systems make management by objectiveseasier.

Dimension: TimeWorker-centred:Aim: More freedom to choose working timesattuned to personal preferences and familyrequirements.Role of ICTs:Coordination between co-workers made easier viapowerful asynchronous communication media andcomputer-supported collaborative worktechnologies.

Company-centred:Aim: Bringing supply of human capital in line with thetemporal requirements following from business, e.g.times of customer demand, machine running times,optimal utilisation of capital invested.Role of ICTs:See left-hand side.Utilisation of work products being produced in othertime zones made possible using computer networks.


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Dimension: PlaceWorker-centred:Aim: More freedom to choose work location(s)attuned to personal preferences and familyrequirements.Role of ICTs:Computer networks enable collaborationregardless of distance.Digitisation of work inputs and outputs enablethese to be transferred via ICTs instead ofphysical transport.

Company-centred:Aim: More easily changeable configurations of humancapital without actually moving people from one placeto the other.Bringing workers closer to the market (customers)without shutting them out from company-internalcommunication flows.Role of ICTs:Same as left-hand side.

Dimension: ContractWorker-centred:Aim: Greater choice in available job options,including option to stay at the current employer(job security).Being able to choose different types of workcontracts (e.g. employed work, self-employment)without the choice affecting social securityprovision and other main benefits fromemployment.Role of ICTs:Establishment of electronic markets make work asfree-lancer technically easier.Enabling “e-lancing”.Maintaining contact with clients and collaboratorsin spite of geographical distance made easier.

Company-centred:Aim: More freedom in adapting human capitalresources to the requirements following frombusiness, in particular fluctuations (quantitative) andchanges (qualitative) in demand; changes in theregulatory environment, etc.More freedom to sack unwanted staff and morepossibilities to find the skills needed on the labourmarket.Role of ICTs:Integration of freelancers and outsourcing madeeasier through computer-supported collaborativework and telework.Improvement in the efficiency of the recruitmentprocess through electronic work exchanges.

Looking at available indicators, work content has until now mostly been covered by lookingto the use of basic ICTs such as computers and the Internet at the workplace. Changes inworking methods that have been enabled by the use of ICTs have attracted much lessattention. This is unfortunate, as the focus on IT tools may cover up large differences in theway these new technologies are used, and in impacts on employee's control over their workcontents (which is a determinant of job quality). The data from the SIBIS surveys allows tocalculate indicators that measure differences in participation in decision-making betweentraditional workers and workers with flexible work arrangements (such as telework, flexitime,etc.). This is related to the often-mentioned concepts worker empowerment and jobenrichment.

Changes to the time-related organisation of work are fairly well covered by availablestatistics. However, data that allows for differentiating between worker-centred and company-centred flexibility is hardly existent. These are in demand to put the debate on theflexibilisation of the labour market on a conceptually more satisfying grounding. The currentpolitical debate still suffers from a view of flexibility that is too general and not differentiatedenough. For a more accurate view on the options available on the way towards moreflexibility, and possible drawbacks of different types of flexibility, better data is needed. SIBIStherefore has piloted an indicator on working time adaptability.

With regard to the place of work, Most national statistical agencies (and also the LFS)traditionally collect data on home-based work, but this is a totally different group of workersthan those who are commonly referred to as "teleworkers". According to available evidence(see ECaTT 2000, Felstead and Jewson 2000), the main difference is that home workers tendto work at home for most or all of their working time (in the respective job), whereasteleworkers usually spend only a small part of their working time at home while still beingbased primarily in a traditional central office facility. Data on telework has been madeavailable sporadically from a number of sources, but definitions used diverge strongly, andare mostly found to be inadequate for the purpose. The SIBIS telework module presents themost advanced instrument to measure telework-related variables to date, and is arguably the


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first which adequately reflects the need for data that supports the European Commission andEU Member States in making sense of telework as a tool for reaching policy objectives.

In contrast to home-based telework, tele-cooperation is much less visible - this is the reasonwhy it is also called "in -situ telework". Consequently, data on ICT-based forms of cooperationbetween workers are very hard to obtain in a reliable way. Also here, a module has beendeveloped that can be included in surveys targeted at the labour force.

For both telework and tele-cooperation, data from company surveys have proven to be oflimited value because they usually face problems in assessing the intensity of usage.Examples for these problems can be studied in the DTI International Benchmarking Study,the ECaTT Decision Maker Survey, and in the EMERGENCE employer survey. Only dataabout uptake (i.e. whether a technology is used or not) can be reliably collected using thismethodology. A combination of company and population surveys seems to be best suited forthe challenge of mapping changes in the organisation of work in companies. Indicators formeasuring spatial flexibility of companies have been developed in SIBIS, but will not bepiloted because they would require a survey targeted at human resource managers, whichwill not be conducted in the scope of the project.

The contractual dimension of work organisation concerns, in particular, shifts betweendifferent types of employment, i.e. between self-employment and dependent employment andbetween temporary and open-ended work contracts. These refer to the formal contractbetween worker and employer/client. The data situation in this respect can be regarded asbeing good. However, to be able to point out the effect of ICTs on the contractual organisationof work requires that the 'self-employed' category is being explored further. There is, inparticular, a demand for an indicator that adequately represents the number of the so-called"new self-employed" and "e-workers" (Malone and Laubacher 1998). The results of testingone such indicator are described in the next chapter of this document.

Cross-country data on more flexible types of compensation, especially contracts whichinclude performance-related pay components, does not exist yet. To adequately cover thisissue would requires a more extensive module on monetary benefits derived from work.

Table 3-3: Indicators on work organisation from SIBIS and other relevant sources



New SIBISindicator

Work content (wc1) Employee participation in decision-making (ESCW) XWork content (wc2) Management by objectives (ESCW) XTime (wt1) Worker-centred adaptability of working times

(daily/weekly) X

Time (wt2) Voluntary part-time employment (LFS) XPlace of work (wp1) Share of home-based teleworkers according to

telework intensity (permanent, alternating,supplementary)

X

Place of work (wp2) Interest in telework (demand side) XPlace of work (wp3) Share of jobs which are perceived feasible for

telework X

Place of work (wp4) Teleworker churn XPlace of work (wp5) Perceived outcomes of home-based telework XPlace of work (wp6) Telework-enabled labour force participation XPlace of work (wp7) Share of mobile teleworkers XPlace of work (wp8) Establishments practising/interested in home-based

telework R

Place of work (wp9) Establishments practising mobile telework RPlace of work (wp10) Share of workforce practising tele-co-operation X


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Place of work (wp11) Share of self-employed teleworkers in SOHOs XWork contract (wc1) Spread of eLancing among self-employed XWork contract (wc2) Share of the labour force which use the Internet for

job seeking X

Work contract (wc3) Share of companies that use the Internet forrecruitment R

Work contract (wc4) Share of companies that use the Internet foradvertising vacancies R

Work contract (wc5) Perceived success of online recruitment RR = SIBIS has not collected data on this indicator, but has operationalised the indicator which is recommended to bepiloted as part of an existing regular EU survey

3.3 Structure and outcomes of employment

ICTs have played a significant role in the well-discussed development from the Fordist modelof labour markets, which was based on large shares being employed in the manufacturingsector, towards the post-Fordist model which is in general used to describe the situation today(Amin 1994). The post-Fordist model is characterised by production technologies andassociated labour systems that allow for shorter product and innovation cycles, therebymaking possible a more flexible response to fluctuations in market demand or changes in theregulatory environment. In addition (but not as a replacement, as it is often assumed, seeTommaney 1994) to economies of scale which have been at the centre of the Fordist model,today's production systems seek for economies of scope. Without resorting into technologicaldeterminism it is safe to say that economies of scope to the extent that they are beingachieved today would have been completely impossible without ICTs.

For analytical and practical reasons it is, however, necessary to disentangle the influence ofICTs as a Kondratiev type base technology (Perez 1986) that indirectly impacted upon allparts of the economy, from the direct effects of ICT applications, which are the immediatesubject of this report.

When direct impacts are concerned, the technology is mostly discussed in relation to thesupply and/or the demand side of ICTs.One possibility is to analyse employment in the ICT sector. There is a lack of a clear definitiondue to the inappropriateness of the statistical taxonomies which are used for this task (ISCO,ISIC/NACE). The OECD5 defines the ICT sector using the following criteria:

ü For manufacturing industries, the products of a candidate industry (a) must be intended tofulfil the function of information processing and communication including transmission anddisplay; (b) must use electronic processing to detect, measure and/or record physicalphenomena or to control a physical process.

ü For services industries, the products of a candidate industry must be intended to enablethe function of information processing and communication by electronic means.

Other definition may be used if the boundary is to be drawn wider to match what is called themultimedia (see Prognos 1995) or TIME sector (Seufert 2000) which usually also comprisesmedia incl. broadcasting, some business services such as advertising, and a number of othersectors not included in the ICT sector definition described above.

The problem with this approach is the statistical base which assigns each firm to one of theISIC branches without taking into account that each firm is involved in many differentactivities, some of which might not have to do much with the main field of activity as definedby ISIC. For this reason, an occupational approach which classifies employment not by theorganisation it takes place in, but by the occupational nature of the individual itself, may be

5 The OECD ICT sector definition was agreed at the April 1998 meeting of the Working Party on Indicators for the

Information Society (WPIIS) and subsequently endorsed and declassified at the September 1998 meeting of theCommittee for Information, Computer and Communications Policy.


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better able to reflect the change in labour markets (Weidig et al. 1998). This means looking atthe demand for ICTs as working tools rather than production of ICTs in the ICT sector.Occupational structures are changing even faster than sectors because innovations such asICT tend to affect occupations in existing sectors as much as they create/benefit new sectors.

In this respect, the subject of analysis is most often employment in the quartery or informationsector, i.e. employment in "information services" (OECD-ICCP 1981) or "informationoccupations", which are believed to be heavily dependent on information technology and assuch the main application field for ICTs. The original definition of employment in theinformation sector stems from Porat (1976) who differentiated between a primary and asecondary information sector, the former including all those industrial sectors that either pro-duce, process and transmit information or produce the technological means for it; thesecondary information sector, meanwhile, was suggested to include all the information labourin the remaining economic industrial sectors producing non-information products. In a recentpaper, Dostal (2000) applied an approach which is based on Porat's original classification toGermany, showing that today around half of all jobs in Germany fall in the category ofinformation occupations. For international comparisons, data on occupational structuresbased on the ISCO classification6 is required.

Such definitions of information occupations have been criticised as not being linked to anyspecific ICT (Seufert 2000), which means that they rather measure the potential forapplication of ICTs than actual use of these technologies as working tools. Very good data onthe use of ICTs as working tools at the workplace are available for some EU Member States(e.g. Troll 2000), but cross-country data on this subject are very scarce.

With regard to the outcomes of employment SIBIS distinguishes between two types ofindicators; those on outcomes from the company perspective (such as gross value added,wages, social costs, and productivity which relates value added to inputs) and those onoutcomes from the worker perspective. SIBIS focuses on outcomes at the personal level.

Job satisfaction, for example, is an outcome of work at the individual worker’s level that has tobe monitored to be able to assess the sustainability of working arrangements. Data that notonly maps the spread of flexible work practices, but also worker’s satisfaction with them andeffects on the quality of jobs, are needed if policy makers want to make sound decisionsabout which ways of working should be supported and which should be prevented (Clark1998). The same applies to telework which effect on, for instance, finding the right balancebetween family and work demands has until now only been explored at the case study level(FAMILIES 2002). Statistics which are representative for the whole labour force need to beprovided.

Another issue covered by SIBIS is the use of the Internet for matching on the labour market.The Internet opens up new possibilities to make job matching more efficient. PublicEmployment Services in the EU have begun to make use of the Internet to publish vacancies(Gareis and Mentrup 2001a). They face competition in private labour market intermediariesthat charge companies for job advertisements that are placed on websites with sophisticatedjob and candidate search engines. The literature tells almost nothing about the degree towhich these Internet-based services have made matching more efficient and more effective,and how job-seekers and recruiters use them in combination with traditional channels ofcommunication.

Table 3-4: Indicators on outcomes of employment from SIBIS and other relevantsources



New SIBISindicator

Employment structure(es1)

Employment in IT sectors (LFS) X

6 International Standard Classification of Occupations (ISCO-88) , the EU variant is called ISCO-88 (COM)


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Employment structure(es2)

Employment in IT occupations (LFS) X

Outcomes (eo1) Relative job satisfaction in flexible workarrangements

X

Outcomes (eo2) Job quality of jobs with flexible work arrangements XOutcomes (eo3) Perceived job security of workers with flexible work

arrangementsX

Outcomes (eo4) Perceived work-family balance in flexible workarrangements

X

R = SIBIS has not collected data on this indicator, but has operationalised the indicator which is recommended to bepiloted as part of an existing regular EU survey

3.4 Suggestions for compound indicators

It may be useful to aggregate some of the indicators developed (if appropriate, together withindicators already existing in official statistics) into topic indices. In this chapter twoapproaches for such compound measures are discussed, both designed to compare theflexibility or adaptability of work arrangements between EU Member States.

The most often used indicators on the flexibility of labour markets and regulatory regimes ofnational labour markets have been developed and calculated by the OECD. These aremeasures for the stringency of labour markets with regard to the effect of regulatory labourmarket regimes between countries. Main ingredients are sub-indicators measuring proceduralrequirements for laying off workers, notice and severance pay, prevailing standards of andpenalties for ‘unfair’ dismissals, and conditions for fixed-term contracts (Nicoletti et al. 2000).

With regard to this understanding of flexibility in labour market contexts, the EuropeanCommission (2000xa: n.p.) states that “the concept of flexibility in working life, firstestablished by the OECD, was opposed by the Trade Unions because it only referred to theneed of workers to adapt to changing economic conditions. By contrast, the EuropeanEmployment Strategy [...] was based on the wider concept of ‘adaptability’ which combinedflexibility and security”. Boeri et al. (2000: 1) define adaptability as the ability of the labourmarket to a) provide protection against uninsurable labour market risk b) ensure that labourskills continuously match demand as economic development and technological advance takeplace and as the international division of labour evolves, and c) maintain an efficient degree ofgeographical and sectoral mobility. Indicators of labour market adaptability have to becapable of presenting a picture of the EU labour market situation that is in line with theEuropean Employment Policy’s emphasis on socially sustainable new ways of working in theInformation Society.

Each index consists of a number of indicators which are aggregated. For the benefit ofcomparability original indicator values were converted into standardised values with thecountry showing the highest value being assigned the benchmark value of 100 (see Tables inthe next section). Each country can then be ranked according to its performance in eachindicator. The values for each of the suggested indices can then calculated as the mean ofthese ranks. Component indicators are not weighted as it is not suggested that one of them,or one of the four dimensions per index, is more important for overall flexibility than theothers.


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Table 3-5: Indicators for measuring worker-centred flexibility of work arrangements

Dimension Indicator Preliminary sourceTime Voluntary part-time working Community Labour Force Survey

(quarterly)

Time Temporal autonomy in job ECaTT (1999)

Place Home-based teleworking (excluding self-employed)

ECaTT (1999)

Place Teleworkability ECaTT (1999)

Contract Job security International Social Survey Programme(1997); Eurobarometer 44.3 (1996)7

Contract Average job tenure OECD (1999)

Content Share of population aged 25-64participating in training (lifelong learning)

Community Labour Force Survey(quarterly)

Content Participation in decision-makingconcerning changes at workplace

European Survey on Working Conditions(2000)

Table 3-6: Indicators for measuring company-centred flexibility

Dimension Indicator Preliminary sourceTime Part-time working Community Labour Force Survey

(quarterly)

Time Workers with atypical working times(evening, night, weekend work andworking long hours) (ESWCs)

European Survey on WorkingConditions (2000)

Place Tele-cooperation (ECaTT) ECaTT (1999)

Place Mobile teleworking (ECaTT) ECaTT (1999)

Contract Employment Protection LegislationIndicator (OECD)

OECD (1998)

Contract Workers with temporary work contracts(excluding voluntary and contracts fortraining) (LFS)


Content Employees who have had trainingprovided by employer (past 12 months)(ESWCs)


Content Management by objectives (ESWCs) European Survey on WorkingConditions (2000)

The component statistics listed in Table 3-5 and Table 3-6 were selected to construct anindex each for worker-centred flexibility and company-centred flexibility. For an explanation ofindividual indicators and the underlying concept of flexibility, see Annex Data sources arementioned as well. While these indices have the advantage of being based on data which isreadily available from publicly accessible sources, not all of them are updated annually, oreven on a regular basis. It would therefore be valuable to have a harmonised set of annuallyupdated indicators which are available from a single source (such as Eurostat) and whichcould feed indices of this type. No such single source is available yet.

7 Only satisfaction


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4 Analysis of Data8

4.1 Skills

4.1.1 Skill acquisition: Lifelong learning, self-directed learning, e-Learning

As skill requirements change more and more often due to the decreasing length of skill lifecycles in the Information Society, continuous learning of workers becomes a primedeterminant of a nation’s human capital wealth. As the Eurostat taskforce on LifelongLearning has pointed out, the measurement of continuous learning activities becomes themore difficult the less they take place in formal settings.

Eurostat derives an indicator on lifelong learning from the Community Labour Force Surveywhich should, according to the guidelines communicated to the National Statistical Institutes,comprise “all education or training whether or not relevant to the respondent's current orpossible future job. It should include initial education, further education, continuing or furthertraining, training within the company, apprenticeship, on-the-job training, seminars, distancelearning, evening classes, self-learning etc. It should also include courses followed for generalinterest and may cover all forms of education and training as language, data-processing,management, art/culture, health/medicine courses” (European Commission and Eurostat2001: 15). Results are presented in Table 7-1 in the annex.

However, analysis of the questionnaires used for national LFS showed that the hugedifferences in lifelong learning according to this data are likely to be caused by divergingquestion wording. For example, while the U.K. LFS instrument takes care to include all typesof training activities (Office for National Statistics 2001), the German questionnaire focusesexclusively on “Fortbildungsmaß nahmen” (further education measures), a term which isgenerally reserved for formal training courses provided by the state for the unemployed, andwhich lead to a certificate if finished successfully.

Comparison with other data, e.g. the results of the European Survey on Working Conditions(see Paoli and Merllié 2002) which in 2000 directly asked only for training provided by theemployer, shows that the Eurostat numbers are remarkably low for some countries includingGermany, which is understandable given the questionnaire design.

For this reason, SIBIS suggests to use a questionnaire module which directly asksrespondents whether they have participated in training, without listing individual trainingactivities. The module focuses on work-related training only, and was put to workers with acontract of employment as well as to the self-employed and the unemployed. Table 4-1shows results per country for the labour force including all the above groups, as well asdependently employed workers only.

8 For explanation of methodology applied and survey instruments used, see separate document. In the tables in

this chapter, only percentages based on at least 50 respondents (not weighted) are indicated. In other cases datacells are marked with an (*).


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Table 4-1: Participation in work-related training in last 4 weeks (in %)

Base: Labour force Base: Workers with contract ofemployment

yes no DK yes no DK totalAUSTRIA 25.1 73.3 1.6 28.2 70.9 0.8 100BELGIUM 21.9 77.1 1.0 23.3 76.4 0.3 100DENMARK 28.7 70.6 0.7 32.1 67.4 0.4 100FINLAND 37.2 62.8 - 42.0 58.0 - 100FRANCE 17.5 82.5 - 20.9 79.1 - 100GERMANY 24.9 74.8 0.4 27.7 72.1 0.2 100GREECE 13.7 86.3 - 18.7 81.3 - 100IRELAND 19.8 79.8 0.4 25.8 73.6 0.5 100ITALY 20.0 80.0 - 23.3 76.7 - 100LUXEMBOURG 21.3 78.4 0.3 21.9 77.8 0.3 100NETHERLANDS 29.5 70.5 - 36.1 63.9 - 100PORTUGAL 12.3 86.8 1.0 13.8 85.6 0.6 100SPAIN 20.0 80.0 - 27.0 73.0 - 100SWEDEN 30.3 69.6 0.2 36.0 64.0 - 100U.K. 25.7 74.3 - 30.6 69.4 - 100EU15 22.6 77.2 0.2 26.8 73.1 0.1 100CH 24.5 70.8 4.7 24.2 70.2 5.6 100USA 37.3 62.7 - 46.8 53.2 - 100Base: labour force (N=6,604)9 and workers with contract of employment (N=4,946); weighted. EUaverage weighted by EU15 population. Source: SIBIS 2002, GPS

Results show marked differences between countries (although much less pronounced thanthe national LFS data suggests), with the USA, Finland, and Sweden the only countries wheremore than 30% of the labour force where involved in work-related training provided either bytheir company or by some other organisation. The Netherlands and Denmark follow next,while in Portugal and Greece less than 15% of the labour force participate in this type oflifelong learning.

Table 4-2: Participation in work-related training in last 4 weeks (in %, EU15)

yes no DK totalParticipation in work-related training:

Labour force 22.6 77.2 0.2 100Worker with contract of employment 26.8 73.1 0.1 100

- part-time contract 19.7 80.2 0.1 100- full-time contract 28.4 71.4 0.2 100- temporary contract 21.2 78.6 0.2 100

Self-employed 11.7 88.1 0.2 100- working part-time 8.1 91.9 - 100- working full-time 11.9 87.9 0.2 100

Unemployed 9.4 90.0 0.6 100Base: labour force (N=5,723); workers with contract of employment (N=4,274); the self-employed(N=809); weighted by EU15 population. Source: SIBIS GPS

Comparison between values for the whole labour force on the one hand (23% participating)and employees with a contract of employment only on the other hand (27% participating)indicates that the latter group is more likely to participate in work-related training. 9 All figures for N in this document are non-weighted figures (number of observations).


34

A closer look at the figures broken down by type of employment (see Table 4-2) reveals thatparticipation is remarkably lower for workers with a part-time or temporary working contract,the self-employed (especially those working part-time), and the unemployed: Only 9% of allunemployed take part in training measures “with the aim of preparing them for a future job”.As the unemployed do not benefit from learning by doing at the workplace, this finding isworrying since it seems to indicate that the skills gap between the unemployed and theworkforce is becoming increasingly wider, thus diminishing the chances of the unemployed toregain high quality jobs on the labour market in the future. It seems that the training providedby the state to the unemployed cannot make up for the provision of learning opportunitiescompanies supply to their staff.

Training provided by others can, and in many cases should, be supplemented by self-directedlearning which can be better adapted to individual skill requirements, and time schedules.Both types of training might be supplementary in the sense that persons who do not find thetime to participate in training courses, or feel they do not deliver the kind of skills needed, canopt for self-directed learning activities. The SIBIS module explicitly only covered self-directedlearning which is related to the respondent’s work (for employed) or a future job (forunemployed) respectively. In most countries, a significantly higher share engage themselvesin work-related self-directed learning than in training provided by outside organisations (seeTable 4-3), most of all in Germany (52% of the labour force), and in Austria (48%),Luxembourg (45%), USA and Finland (both 44%).

Table 4-3: Self-directed learning in last 4 weeks (in %)


yes no DK yes no DK totalAUSTRIA 47.6 50.5 1.9 46.4 52.0 1.6 100BELGIUM 23.5 74.8 1.7 23.7 75.1 1.2 100DENMARK 30.4 68.5 1.1 32.0 67.7 0.4 100FINLAND 44.4 55.2 0.3 48.0 51.6 0.4 100FRANCE 13.2 86.8 - 14.0 86.0 - 100GERMANY 51.7 47.7 0.5 53.5 46.3 0.2 100GREECE 11.7 88.3 - 11.5 88.5 - 100IRELAND 26.3 73.3 0.4 28.3 71.2 0.5 100ITALY 29.4 70.4 0.2 27.8 71.9 0.2 100LUXEMBOURG 44.9 55.1 - 44.8 55.2 - 100NETHERLANDS 34.3 65.7 - 33.8 66.2 - 100PORTUGAL 20.3 78.9 0.8 21.3 78.3 0.4 100SPAIN 22.5 77.5 0.0 25.5 74.4 0.1 100SWEDEN 33.9 65.6 0.5 36.9 62.6 0.5 100U.K. 29.6 70.4 - 31.5 68.5 - 100EU 31.7 68.0 0.3 33.0 66.8 0.2 100CH 41.4 52.9 5.8 43.2 51.2 5.6 100USA 44.1 55.7 0.2 47.1 52.6 0.2 100Base: labour force (N=6,604) and workers with contract of employment (N=4,946); weighted. EUaverage weighted by EU15 population. Source: SIBIS 2002, GPS


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Table 4-4: Participation in self-directed learning in last 4 weeks (in %, EU15)



part-time contract 28.1 71.6 0.3 100full-time contract 34.1 65.8 0.2 100temporary contract 28.5 71.4 0.1 100

Self-employed 36.6 63.1 0.3 100working part-time 38.8 61.2 - 100working full-time 35.9 63.8 0.2 100


Breaking down the EU15 averages, again, by type of employment (see Table 4-4) gives thesame pattern as for organisation-provided training, albeit the scale of the gap betweenemployees, the self-employed and the unemployed is somewhat smaller here. The figure forunemployed persons practising self-directed learning (17%) is little more than half the figurefor workers with a contract of employment. Here, too, the findings suggest that more effortsare needed to integrate the unemployed in the continuous skill-rejuvenation process which isso important for the individual’s chances on the labour market, and the EU economy ingeneral.

It should be noted here that, because of its elusive nature, some self-directed learning mightnot be recognised as such, and therefore might not be reported in the context of a surveyinterview. If cultural setting in which self-directed learning takes place differ betweencountries, this is likely to have an effect on country comparisons. Only in-depth studies oflearning activities, based on direct observation or time-use surveys, can reveal the extent towhich such differences exist between the Member States. This is a task still left to be done.

Combining both self-directed learning and training provided by third parties results in the totalnumber of persons who take part in work-related learning activities. The high share of thelabour force participating in work-related lifelong learning, while not giving any information onthe type, intensity and field of these activities, shows that a high percentage of workers is inthe process of preparing for the adaptation of skills to the fast-changing requirements whichare a key feature of the Information Society. More than half of the labour force in Finland,Germany, the USA, Austria and Luxembourg have updated their work-related skills in the fourweeks preceding the survey. Even in the countries with the lowest spread of work-relatedlearning activities (Greece, Portugal and France), still between one fifth and a quarter takepart. Figures are usually slightly higher when looking only at workers with a contract ofemployment.

The results from the SIBIS pilot surveys suggest that the numbers derived from theCommunity Labour Force Survey let us underestimate the extent to which the workingpopulation practises lifelong learning, and supports the view that the LFS data does actuallynot confirm to the definition supplied by Eurostat for most EU countries. While this may be amethodological problem of harmonising data from 15 separately designed labour forcesurveys which also have to fulfil important tasks in the supply of data for national policymaking, it points towards the need to be careful in using data from NSI sources forbenchmarking purposes even if very large samples are used and supranational regulationasking for harmonisation is in place.


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Table 4-5: Any work-related learning in last 4 weeks (in %)


yes no DK yes no DK totalAUSTRIA 54.1 44.0 1.9 54.9 43.9 1.2 100BELGIUM 33.2 65.1 1.7 35.0 63.7 1.2 100DENMARK 45.2 53.3 1.5 49.1 50.1 0.8 100FINLAND 59.9 40.1 - 66.0 34.0 - 100FRANCE 23.9 76.1 - 27.0 73.0 - 100GERMANY 58.4 41.1 0.5 61.6 38.2 0.2 100GREECE 19.4 80.6 - 22.8 77.2 - 100IRELAND 35.0 64.6 0.4 39.5 60.0 0.5 100ITALY 37.5 62.3 0.2 38.3 61.5 0.2 100LUXEMBOURG 52.8 47.1 0.1 53.8 46.1 0.1 100NETHERLANDS 46.5 53.5 - 49.2 50.8 - 100PORTUGAL 23.9 74.8 1.3 25.8 73.1 1.0 100SPAIN 33.4 66.6 - 40.8 59.2 - 100SWEDEN 47.1 52.7 0.2 52.6 47.4 - 100U.K. 39.4 60.6 - 43.1 56.9 - 100EU 40.8 58.9 0.3 44.4 55.5 0.2 100CH 48.7 46.6 4.7 50.1 44.3 5.6 100USA 57.1 42.9 - 63.6 36.4 - 100Base: labour force (N=6,604) and workers with contract of employment (N=4,946); weighted. EUaverage weighted by EU15 population. Source: SIBIS 2002, GPS

Enabling people to practice lifelong learning means that learning content has to be provided inways which suit the target group with regard to

ü the total time available for learning,ü individual schedules, i.e. the distribution of available time over days, weeks and months;ü possible and preferred locations for learning activities;ü the tools available for learning (such as PC);ü lifestyles and personal preferences.

As a rule, persons in paid work are usually much more constrained regarding these factorsthan young people in the stage of initial education. Lifelong learning therefore puts greatdemands on learning systems and learning environments which have to enable efficientlearning and be geared towards the personal preferences of the respective target group.eLearning can play a decisive role in delivering learning systems which fulfil these demands.

For the working definition used for the survey, we can distinguish between two broad groupsof eLearning technologies: offline and online eLearning. The first category comprises multi-media learning material such as computer programmes on diskettes, video tapes and CD-ROMs, the second category is limited to learning content which is provided online through theInternet or the computer network of the employing organisation or the school/university,respectively.

Table 4-7 shows values for the EU15 labour force as well as for students (aged over 14).Among the latter group, the use of eLearning is already well advanced with 45% of allstudents using electronic learning material, and one third online learning material accessedvia the Internet or their education institution’s internal computer network10. The share of thelabour force that uses e-learning is 15% on average in the EU and 23% in the USA (seeTable 4-7), which means that a bit more than one third of all persons who have participated in 10 The sample size does not allow for break-downs of students by country.


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work-related training in the four weeks prior to the survey have used electronic learningmaterial (see Table 4-6). No European country sports a figure which is above 20% (see Table4-7, left hand). Finland, Germany and the Netherlands (each 19%) as well as Austria (18%)Denmark and the U.K. (each 17%) come closest to that number, while in France and Greecethe share is only 6%.

Table 4-6: Use of e-Learning technologies for work-related training (in %, EU15)

Base:Labour force

Base:Students

Participated in work-related learning last 4 weeks 40.8 100Thereof:Has used electronic learning material 35.4 44.5- offline 26.7 33.7- online 23.1 33.4Has not used electronic learning material 64.4 55.1DK 0.2 0.4

Has not participated in work-related learning in last 4 weeks 58.9 -DK 0.3 -Total 100 100 100 100Base: Labour force (N=5,723), weighted by EU15 population Source: SIBIS 2002, GPS

An alternative indicator would take as a base only those which have participated in work-related training (Table 4-7, right hand). This data shows that some countries with low absoluteshare of e-learners show impressive performance when taking lifelong learners as the basis,Spain and Portugal among them. The differences between countries are overall smaller thanmight be expected.

If the focus is shifted to the more limited understanding of eLearning which only includesonline transmission of learning content (Table 4-8), differences between EU states with a highshare of users and those with a low share come out even more pronounced. This is to beexpected as technologically simpler eLearning technologies such as training content on CD-ROMs is likely to diffuse ahead of online eLearning which requires not only access to theInternet, but also a fairly good connection speed to maintain user attention. Only 2% of theGreek labour force use online eLearning, against the EU average of 10% and maximumvalues as high as 17% for the USA and 16% for Finland. Indeed, looking at the ratio of onlineeLearning users to all eLearning users per country (see fifth column in Table 4-8), it mainly isthe countries with highest share of the labour force practising online eLearning which havethe highest ratios (Sweden, Finland, the U.K. and the USA), and vice versa for the countrieswith low diffusion rates.


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Table 4-7: Use of eLearning for work-related training (in %)

Base: Labour force Base: All who participated inwork-related training

yes no DK yes no DK totalAUSTRIA 17.7 82.3 - 32.1 67.9 - 100BELGIUM 11.6 87.3 1.1 34.9 61.7 3.4 100DENMARK 17.1 82.9 - 37.7 62.3 - 100FINLAND 19.3 80.7 - 32.3 67.7 - 100FRANCE 5.7 94.3 - 23.9 76.1 - 100GERMANY 18.9 81.1 - 32.3 67.7 - 100GREECE 5.7 94.3 - * * * 100IRELAND 14.3 85.7 - 40.9 59.1 - 100ITALY 14.7 85.1 0.2 39.2 60.4 0.5 100LUXEMBOURG 16.2 82.4 1.4 30.7 66.6 2.7 100NETHERLANDS 18.7 81.3 - 40.4 59.6 - 100PORTUGAL 8.3 91.7 - 34.8 65.2 - 100SPAIN 13.4 86.6 - 40.1 59.9 - 100SWEDEN 16.4 83.6 - 34.9 65.1 - 100U.K. 17.0 82.8 0.2 42.3 57.1 0.5 100EU 14.5 85.4 0.1 35.4 64.4 0.2 100CH 13.4 86.6 - 27.6 72.4 - 100USA 22.9 77.1 - 40.1 59.9 - 100Base: labour force (N=6,604); all participants in work-related training in last 4 weeks (N=2,677)weighted. EU average weighted by EU15 population. Source: SIBIS 2002, GPS

Table 4-8: Use of online eLearning for work-related training (in %)

Base: Labour force

yes no DK Online eLearners :all eLearners (ratio) total

AUSTRIA 10.3 89.2 0.6 0.58 100BELGIUM 6.6 92.3 1.1 0.57 100DENMARK 11.6 88.1 0.3 0.68 100FINLAND 15.9 84.1 - 0.83 100FRANCE 3.5 96.4 0.1 0.61 100GERMANY 13.4 86.4 0.2 0.71 100GREECE 1.7 98.3 - 0.30 100IRELAND 9.0 91.0 - 0.63 100ITALY 8.0 91.8 0.2 0.55 100LUXEMBOURG 9.5 89.1 1.4 0.58 100NETHERLANDS 9.1 90.7 0.2 0.49 100PORTUGAL 5.5 94.5 - 0.66 100SPAIN 7.3 92.5 0.2 0.54 100SWEDEN 14.3 85.7 - 0.87 100U.K. 12.7 87.1 0.2 0.75 100EU 9.5 90.3 0.2 100CH 9.6 90.4 - 0.71 100USA 17.0 82.9 0.1 0.74 100Base: labour force (N=6,604); all who participated in work-related training in last 4 weeks (N=2,677)weighted. EU average weighted by EU15 population. Source: SIBIS 2002, GPS


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While participation in work-related learning is more or less the same for women (39%) and formen (42%), there are pronounced differences between genders with regard to the use of e-learning, and online e-learning, in particular (see Table 4-9). Only 28% of female learners useeLearning technologies, against 41% of male participants in work-related learning. Thesedifferences are bigger than those relating to the uptake of PCs and the Internet, whichindicates that affinity to technology still plays a role for the uptake of e-learning.

Table 4-9: Women’s and Men’s use of e-Learning for work-related training (in %, EU15)

Base: Femalelabour force

Base: Malelabour force

Participated in learning in work-related last 4 weeks 38.9 42.3Thereof:Has used electronic learning material 27.6 41.3- offline 18.5 32.9- online 17.5 27.3Has not used electronic learning material 72.2 58.4DK 0.2 0.3

Has not participated in work-related learning in last 4 weeks 60.9 57.3DK 0.2 0.4Total 100 100 100 100Base: female labour force (N=2,736) and male labour force (N=2,987), weighted by EU15 population.

Source: SIBIS GPS---

The use of survey-derived data for measuring work-related learning activities is, as theEurostat taskforce on Lifelong Learning has pointed out, the most appropriate way of coveringthe diversity of learning activities people are engaged in. For a more complete picture,however, statistics on the number and structure of companies providing training is also of highrelevance. For this purpose, data from the EU-wide Continuing Vocational Training Survey(see Davis n.a., CTPS 1996) can be used. The CVTS was conducted twice until now, in 1993and 2000.

As Table 4-10 shows the share of enterprises (with 10 or more employees) offering training ismore than 70% in all EU Member States except for Greece, Portugal and Spain. In Denmarkwhich leads the rank table in the EU, only one in 25 enterprises does not offer training. Thedata also points towards an increase in the proportion offering training across all countrieswith the exception of Germany (where there has been no increase between 1993 and 2000)and Greece (however, this is probably due to a change in working definition).


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Table 4-10: Enterprises offering training (CVTS data, as % of all enterprises)

1993 2000training training

AUSTRIA n.a. 72.0BELGIUM 45.9 70.0DENMARK 86.8 96.0FINLAND n.a. 82.0FRANCE 62.4 76.0GERMANY 75.0 75.0GREECE 45.9 18.0IRELAND 76.8 79.0ITALY 15.0 n.a.LUXEMBOURG 60.3 71.0NETHERLANDS 56.1 88.0PORTUGAL 13.1 22.0SPAIN 26.5 36.0SWEDEN n.a. 91.0U.K. 81.6 87.0Base: All enterprises with 10 or more employees

Source: Eurostat 2002, Continuing Vocational Training Survey

Apart from more or less formal training schemes, the arguably most effective ways companiescan provide skills is by means of “learning by doing”, i.e. by providing their staff with workenvironments and involving them in tasks which lead to the acquisition of skills. This appliesespecially to innovative technology such as ICTs which require a lot of user experience to getaccustomed with. Much of the evidence available shows that people that got in contact withICTs at the workplace are more inclined to use them for private purposes as well, therebyleading to a virtuous circle of skills improvement. For older persons confrontation withcomputers and the Internet at the workplace is certainly the main way towards overcomingthe generation gap in computer user know-how (whereas young people entering theworkforce typically have obtained many of their computer skills through entertainment use).

However it is by no means self-evident that companies give their staff ready access to ICTs,as these technologies make control of staff harder. E-mail and the Internet can easily be usedfor private purposes as well (thereby undermining working morale) and are also prone tomisuse leading to virus infections etc. For this reason companies face a trade-off betweensupplying their staff with effective working tools which support the development of mediacompetence on the one hand, and cost control on the other hand. Anecdotal evidencesuggests that more conservatively managed companies tend to opt for cost control, whereascompanies with a progressive self-image, especially if they are in the knowledge economy,tend to opt for giving staff full access to ICTs.

SIBIS piloted a question which asked IT decision makers in establishments whether themajority of their office workers can access e-mail, the Intranet (if existent) and the Internet.Table 4-11 presents results with all establishments as the base, the figures in Table 4-12have the base all establishments that use this technology at all. Weighting by employment isbeing used.

The first (Table 4-11) is an indicator of the overall access of workers to ICT technologies atthe workplace. In Greece, 41% of workforce work in companies which offer the majority oftheir staff access to e-mail), in Spain and Germany the figure is around 70%, while Finlandhas the best access of workers to e-mail (as well as the Internet and Intranets) of thecountries surveyed with 94% (91% and 71%, respectively).

The second (Table 4-12) is an indicator that tells to what extent companies that have taken upan ICT already are giving their employees access to it. A low figure for the latter indicator


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might point out that establishments have reservations to give their staff access to ICTs – aproblematic attitude considering the increasing importance of knowledge and mediacompetence in all sectors of the economy. In France and Greece, only half of allestablishments which are connected to the Internet let the majority of their staff use it, whilethe figure for Finland is 93%. E-mail and the Intranet are somewhat more readily given accessto in all countries. These findings give strong support to the statement that Finnish workersare in a better position to continuously improve their ICT skills and digital literacy than, forexample, the Greek and the French labour force. This is likely to contribute to the widening ofgaps in ICT related human capital between the most “advanced” and the more “slow-moving”EU countries. Remedial action should try to support companies firstly to get access to ICTs (atask which has been fulfilled to a remarkable extent across the EU), and secondly to giveaccess to these technologies to their staff.

Table 4-11: Establishments giving the majority of their staff access to ICTs

in % of all establishmentse-mail Internet Intranet

FINLAND 93.9 90.6 71.3FRANCE 56.7 41.3 45.3GERMANY 73.0 65.0 48.5GREECE 40.5 39.8 19.5ITALY 60.0 56.7 39.7SPAIN 69.1 65.0 46.3U.K. 76.0 56.3 52.1Base: all establishments (N=3,139); weighted by employment Source: SIBIS 2002, DMS

Table 4-12: Establishments giving the majority of their staff access to ICTs (shareamong all user establishments)

in % of all establishments that use this technologye-mail Internet Intranet

FINLAND 97.1 93.2 96.9FRANCE 67.8 49.4 80.6GERMANY 80.4 70.2 85.1GREECE 58.6 52.2 57.2ITALY 70.2 65.8 74.1SPAIN 74.3 67.6 81.9U.K. 85.4 64.5 86.2Base: all user establishments: e-mail (N=2,734), Internet (N=2,785), Intranet (N=1,690); weighted byemployment Source: SIBIS 2002, DMS

In addition to these indicators for which data is available from SIBIS pilot surveys or theCVTS, SIBIS recommends to measure to what extent companies support self-directed IT-related learning. Types of support include handing out PCs and/or online accounts to staff forfree or a subsidised price, as it is being politically supported in Denmark and other countriesas well. Data for such an indicator would have to be collected through a survey targeted athuman resources managers in companies. Care has to be taken to design this indicator in away that makes it insensitive to distorting effects of country differences in business cycles.Time series over more than five years would therefore be preferable to one-off data collection.

4.1.2 Skill provision: ICT skills in the labour force

The provision of ICT-related skills on the labour market is today measured by looking into thesupply of graduates from ICT courses. However, ICT skills are by no means only relevant forthose (comparatively few) specialists whose primary activity revolves around thesetechnologies. Rather, ICTs are a transversal technology which impacts on business


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processes in all sectors and are being implemented as working tools for an ever increasingshare of the workforce. The provision of ICT skills in non-IT jobs has hardly been analysedyet, and data are not available even at the national scale. This is due to the fact thatmeasurement of non-certificated skills is a hugely complex task. Assessing skills directlywould mean to carry out tests such as they are being used in the International Adult LiteracySurvey or the students tests (such as the famous PISA study) both managed by the OECD.For timely data on fast-moving developments such as digital literacy, this approach is notfeasible. Another option, if somewhat more controversial methodologically, is self-assessment.

SIBIS has piloted a module on self-assessed digital literacy which is discussed in a separatereport on Education.

4.1.3 Skill requirements

There is no EU-wide time-series data on IT skill requirements available in the EU. Nationaldata on vacancies unfilled statistics provided by Public Employment Services are notcomparable between countries. For this reasons EU policy-makers until now have to rely onproprietary data provided by IT consultancies such as IDC (2001). This data has thedisadvantage of being based on undisclosed sources and methodologies which limits itsvalidity and usefulness considerably. There is an urgent need for a cross-country data sourceon IT skill requirements in the EU which would supply the adequate data.

A number of bodies at the national level have undertaken studies and surveys which mightact as an example on how the suggested EU survey should look like. One of these is “Stock,supply and demand of IT specialists” by the German public research organisations BIAT andBIBB (Petersen & Wehmeyer 2001). The priority of efforts at the European level should nowconcentrate on making the data gathering instruments used for such studies applicable for allEU Member States. This would require comparing concepts, terminologies and taxonomies(e.g. related to the differentiation of IT specialists in sub-groups) and arriving at a frameworkwhich is feasible to be applied across Europe. It would allow country comparisons as well asaggregation of national to EU-wide figures. Results of SIBIS research in this area will becomeavailable in the near future.

Additionally, data on the demand for IT-related non-specialist skills are missing. SIBISrecommends a module on this issue to be included in a survey of human resources managersin companies. It would include a qualitative and quantitative assessment of IT skill needs ofthe workforce (broken down by skill types, e.g. word processing, spreadsheet processing,database programming etc.) as well as a (subjective) assessment of the suitability of IT skillsof job applicants and new recruits, as perceived by companies.

4.2 Work organisation

4.2.1 Work content: Participation in decision-making and management byobjectives

There is growing consensus among experts and practitioners of human resourcemanagement that companies which want to succeed in the Information Economy must adapttheir management practices to derive maximum use from their staff’s skills. This has two maincomponents:

ü to involve staff in decision-making about the way work is organised in order to benefitfrom their know-how as the ones who actually do the work;

ü and to decentralise control over how business objectives are achieved while settingtargets/objectives of what outcomes have to be achieved.

Only management strategies involving these components are likely to lead to the highestreturns from qualified staff in most production settings (see e.g. Voß 1998). This is, in


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particular, because both participation in decision-making and management by objectives canact as boosts to employee morale, and thereby motivate workers to increase their productivityas they are given more self-responsibility and incentives to look for more efficient ways ofdoing their work (Clark 1998).

Table 4-13 shows the spread of worker-participation in decision-making. This practice is quitecommon already in most Member States of the EU, with more than three quarters of Dutch,Finnish and Danish workers claiming they can discuss changes to the organisation of theirwork with their superiors, but only 44% in Spain and less than 40% in Greece and Portugal.The countries with a high degree of worker participation appear to be those which have a longtradition in attempts to involve workers in company decisions (which has often been anexplicit policy goal of these countries’ unions), and those which have a higher than averageshare of the labour force in the services sector.

Table 4-13: Employee participation in decision making on issues relating tochanges in work organisation (ESCWs data, in %)

Participating indecision making

Not participating indecision making DK Total

AUSTRIA 59.9 31.8 8.3 100BELGIUM 64.3 23.4 12.3 100DENMARK 77.5 16.0 6.5 100FINLAND 76.3 14.9 8.8 100FRANCE 63.4 27.7 8.8 100GERMANY 59.4 30.5 10.2 100GREECE 37.4 35.2 27.4 100IRELAND 59.8 26.2 14.0 100ITALY 52.9 31.1 16.1 100LUXEMBOURG 61.5 22.4 16.2 100NETHERLANDS 79.0 12.9 8.1 100PORTUGAL 35.3 54.3 10.4 100SPAIN 44.1 38.1 17.7 100SWEDEN 69.9 22.0 8.0 100U.K. 67.7 25.1 7.2 100Base: all persons employed (n=21,703); weighted by country weights

Source: ESWCs 2000

“Management by objectives”, the second purported trend in human resources management,refers to the need to refrain from the traditional “management by eyeball”, meaning thatworkers are made responsible for reaching certain targets, without being given detailedinstructions how to reach them (and without being exposed to direct control of behaviour bytheir superiors). In theory, instead of process-specific instructions (which relates to the classicTaylorist organisation of work) supervisors are now asked to support their staff in developingthe right skills for tackling tasks, by means of continuous training (coaching).

As a working definition which enables us to use data from the European Survey on WorkingConditions (a five-yearly survey conducted by the European Foundation for the Improvementof Working and Living Conditions), SIBIS operationalises workers which are “managed byobjectives” as those who state that they generally

ü have to access themselves the quality of their work, andü have to solve unforeseen problems on their own, andü are able to choose or change their order of tasks, methods of work and speed or rate of

work.


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Table 4-14 shows the results for all Member States. According to this indicator, between onethird (Luxembourg, Greece, Germany) and more than half (Netherlands and Denmark) of allpersons employed are being managed by objectives.

Table 4-14: Management by Objectives (ESCWs data, in %)

"Managed byobjectives"

Not "managed byobjectives" DK Total

AUSTRIA 39.1 60.7 0.2 100BELGIUM 42.3 57.7 - 100DENMARK 55.7 44.3 0.0 100FINLAND 37.6 62.4 0.1 100FRANCE 41.2 58.8 - 100GERMANY 35.5 64.5 - 100GREECE 32.8 67.1 0.2 100IRELAND 37.5 62.1 0.3 100ITALY 37.8 62.2 - 100LUXEMBOURG 30.2 69.2 0.6 100NETHERLANDS 57.1 42.9 - 100PORTUGAL 38.5 61.5 - 100SPAIN 37.8 62.1 0.1 100SWEDEN 45.4 54.4 0.2 100U.K. 43.0 56.9 0.0 100Base: total economically active population (n=21,703); weighted by country weights

Source: European Foundation (ESWCs) 2000, SIBIS calculations

SIBIS was not able to influence the questions asked in the ESWCs which means that thethree criteria for management by objectives have been selected for their availability in thesurvey instrument. A module developed from scratch with the intention of measuringmanagement by objectives would possibly include more or different criteria, such as thequestions whether worker performance is measured by the extent to which predefined targetsor objectives have been met. A disadvantage of the ESCWs questions for the purpose ofconstructing the indicator are the limited answer categories which are yes and no. It may beargued that there is, e.g., no discrete dividing line between people who have to solveunforeseen problems in their work alone and those who have not, but that this is rather aquestion of the extent to which problem-solving is the duty of the worker or their superior orany other colleague. This means that a dichotomous scale for answer categories might try toexplain the reality in too simple terms. The SIBIS modules generally use 3-point scales forunipolar answer categories and 5-point scales of bipolar answer scales.

4.2.2 Time: Adaptability of working times

Working time flexibility is an important element of strategies to give workers more discretionover the organisation of work wherever this can be combined with the requirements of thebusiness, or even supports business objectives (such as operating hours being extended intothe early morning and late hours, or even to 24h service). Working time flexibility is stronglysupported, and in many cases only made possible, by ICTs which enable efficientasynchronous communication. As has been outlined in section 3.2, the two main types ofworking time flexibilisation are

ü flexibility to choose the beginning and end of the workday as it suits own preferences andprivate schedules, and

ü flexibility to choose the number of working hours per week, i.e. choose to work part-timewith a set or self-selected number of hours to be worked per week.


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As part of the SIBIS GPS module on the outcomes and conditions of work (see also chapter4.3.1), questions about these two characteristics were piloted:

ü In your current work arrangement, do you agree with the following statements about yourjob? ...- “I can adapt my starting & finishing times to my personal preferences”- “I can adapt the number of weekly working hours to my personal preferences”

In order to allow respondents to distinguish between different degrees of flexibility, a three-point-scale “strongly agree”, “somewhat agree” and “disagree” was chosen rather than bipolaryes-no answer categories. The questions were targeted at employed persons excluding theself-employed only, since the latter are almost by definition able to chose their working timesas it befits them (although the reality may sometimes be different, particularly in case of theseemingly unemployed, but assessing this issue would require a number of more in-depthquestions and a considerably larger sample for piloting).

Table 4-15: Adaptability of daily starting and finishing times (in %)

(1)strongly

agree

(2)somewhat

agree(1)+(2)agree disagree DK total

AUSTRIA 23.3 18.5 41.8 57.7 0.5 100BELGIUM 25.5 20.6 46.1 53.9 - 100DENMARK 21.7 23.4 45.2 53.5 1.3 100FINLAND 23.4 30.7 54.1 45.9 - 100FRANCE 18.2 26.7 44.9 54.8 0.3 100GERMANY 30.8 22.0 52.8 46.9 0.2 100GREECE 17.5 27.4 44.9 55.1 - 100IRELAND 19.1 19.7 38.9 61.1 - 100ITALY 25.0 27.8 52.8 46.7 0.5 100LUXEMBOURG 23.6 17.3 40.9 59.1 - 100NETHERLANDS 35.6 15.7 51.3 48.7 - 100PORTUGAL 14.3 20.1 34.4 65.6 - 100SPAIN 16.3 16.2 32.5 67.5 - 100SWEDEN 21.2 36.5 57.7 42.1 0.2 100U.K. 22.9 31.7 54.6 45.2 0.1 100EU 24.1 24.8 48.9 50.9 0.2 100CH 36.7 24.7 61.4 33.5 5.1 100USA 25.3 35.0 60.3 39.5 0.2 100Base: All employed excluding self-employed (N=4,966); weighted. EU average weighted by EU15population. Source: SIBIS 2002, GPS

The results are presented in Table 4-15 and Table 4-16. Near to 50% of all persons employedin the EU agree to the statement that they can adapt their starting and finishing times topersonal preferences, half of which agree “somewhat”, the other half “strongly”. Even inPortugal and Spain, the countries with the lowest overall figures, more than one third benefitfrom this kind of flexibility according to their reply to the question. The distribution of answersacross the three-point scale is fairly even when compared between countries, which leavesno reasons to believe that the use of this scale gives distorted results when translated intoother languages and transferred into other cultural settings.

About 40% of European employees agree to the statement “I can adapt the number of weeklyworking hours to my personal preferences”, only 17% agree strongly. These figures are onlyslightly lower than the ones mentioned above for daily working times. Therefore, a very highnumber of the EU workforce have the possibility to adapt their hours of work to their individualpreferences and requirements. It is striking that it is not necessarily the countries with thehighest share of part-time employment which lead the country ranking. The Netherlands


46

which according to the latest available data from the Community LFS (see Table 4-17) haveby far the highest rate of part-time employment (especially when considering voluntary part-time working, see fourth column) have a significantly smaller share of employed personsreporting they can adapt the number of working hours to personal references than Sweden,Italy and Germany – all of which countries with a much lower part-time employment rate.Quite obviously there are different ways towards achieving working time flexibility, part-timecontracts being one of them, but variability of weekly working hours inside of full-time workingcontracts another one.

Table 4-16: Adaptability of number of working hours (in %)

(1)strongly

agree

(2)somewhat

agree(1)+(2)agree disagree DK total

AUSTRIA 21.1 21.7 42.8 56.3 0.8 100BELGIUM 21.1 18.9 40.0 59.7 0.3 100DENMARK 15.7 21.1 36.7 61.3 2.0 100FINLAND 15.2 26.5 41.6 58.4 - 100FRANCE 15.9 19.4 35.3 64.0 0.6 100GERMANY 19.9 24.8 44.7 55.1 0.2 100GREECE 13.6 21.9 35.5 64.5 - 100IRELAND 15.9 19.5 35.5 64.5 - 100ITALY 21.2 23.7 45.0 54.3 0.7 100LUXEMBOURG 17.6 22.8 40.4 59.6 - 100NETHERLANDS 20.9 19.6 40.6 59.4 - 100PORTUGAL 11.6 13.6 25.1 74.9 - 100SPAIN 12.7 10.2 22.9 76.5 0.7 100SWEDEN 14.2 35.2 49.4 50.3 0.2 100U.K. 17.2 32.4 41.3 49.8 0.5 100EU 16.7 22.9 39.6 60.0 0.4 100CH 27.7 24.2 51.9 43.0 5.1 100USA 10.9 30.4 49.7 58.5 0.2 100Base: All employed excluding self-employed (N=4,966); weighted. EU average weighted by EU15population. Source: SIBIS 2002, GPS

Having time-series data on these indicators would be of considerable value, not the leastbecause it can be expected that the business cycle has an effect on the bargaining power ofemployees with regard to demanding working hours from their employers that suit theirindividual needs. Moreover although the data from the Community LFS clearly shows that theshare of the labour force working part-time is increasing all over Europe (with the exception ofDenmark and Sweden where the government has initiated measures to turn part-time into full-time jobs), there is no consistent evidence yet whether discretion of working times asdiscussed here is increasing.


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Table 4-17: Voluntary and involuntary part-time work (Community LFS, 2000 data)

Part-time workers as % oftotal employment

Share of involuntary as %of all part-time workers

Voluntary part-timeworkers as % of total

employmentAUSTRIA 17.0 10.7 15.2BELGIUM 20.7 22.2 16.1DENMARK 21.7 13.6 18.7FINLAND 12.2 34.7 8.0FRANCE 16.9 26.8 12.4GERMANY 19.4 12.0 17.1GREECE 4.6 43.7 2.6IRELAND 16.8 16.2 14.1ITALY 8.8 35.6 5.7LUXEMBOURG 11.3 7.2 10.5NETHERLANDS 41.2 3.5 39.8PORTUGAL 10.7 23.5 8.2SPAIN 8.2 22.8 6.3SWEDEN 22.8 23.2 17.5U.K. 24.9 9.7 22.5Base: All persons employed Source: Eurostat 2001, Labour Force Survey 2000, SIBIS calculations

4.2.3 Place: Telework and tele-cooperation

In almost every European country national surveys have been conducted and statistics on thenumber of teleworkers published (see www.eto.org.uk for an overview). In some countries likethe United Kingdom, the official labour force survey now includes a module on teleworkingfrom home. Unfortunately, it is mostly impossible to compare the results of these nationalstudies because of strong differences in definitions, composition of samples and projectionmethods used. Some cross-country statistics have also been produced, but in such studiesthe conceptual grasp of telework as an ICT-based way of making work more spatially flexibleis mostly limited. This leads to not fully adequate questions being asked in surveys, such asdemonstrated by the questions on telework included in the early 2000 Eurobarometer.

For almost all studies published yet, a clear-cut definition was used of what characteristicsconstitute a teleworker. A typical example is the Eurobarometer study which uses thefollowing definition: "telework occurs when paid workers carry out all, or part, of their workaway from their normal places of activity, usually from home, using information andcommunication technologies" and then asks: "Do you telework, or not?" and, if answered yes,"Regularly or occasionally?" It becomes obvious that the authors of the Eurobarometerquestionnaire tried to draw a clear line between teleworkers and non-teleworkers, althoughthe definition they give is somewhat blurred (what does "usually from home" mean?) andarguably not very suitable for the task.

Often studies like this take for granted that respondents already know whether they dotelework or not. SIBIS research involving a team of experts from all language areas present inthe EU, however, has shown that the term “telework” and its equivalents are commonlyunderstood in all EU languages as including only home-based telework where a change ofworkplace from the central office to the home has taken place. Many forms of telework as it isbeing discussed by the research community today are "invisible" to the workers involvedwhich means that these might not be able to tell whether they are teleworking or not, becausethey do not realise themselves. This applies especially to mobile telework and telework by theself-employed. If these are to be covered by statistics, new methods for gathering data haveto be developed.

The fact that the results from the Eurobarometer survey on telework were used forbenchmarking EU Member States as part of the assessment of eEurope 2002 (see EC 2002)

http://www.eto.org.uk


48

makes clear that there is a strong need for better indicators to become available for use in thefuture. SIBIS provides a template for this purpose.

Types of telework

Indicators developed in SIBIS address these questions. SIBIS suggests to approach thetelework phenomenon from three different angles, taking into consideration the ability ofrespondents to answer questions about their working behaviour: home-based telework,mobile telework and telework by self-employed. All of them have a number of characteristicsin common: work being carried out at a distance to where it is put to use; use of a personalcomputer in the course of the work; and use of telecommunications links for electronicallytransferring work results to colleagues, superiors or externals such as clients.

ü Home-based telework implies a relocation of the workplace, for part or whole of theworking time, from the establishment site to the home of the worker. This type of teleworkalso implies, in most cases, more flexibility with regard to time and content of work. Theseare natural outcomes of changes to the extent of control which can be exerted on workerswho are not present on-site. SIBIS distinguishes between intensity of teleworkingpractice: Supplementary teleworkers work at home for less than one daay per week,alternating teleworkers spend at least one full working day at home, and permanentteleworkers are those who spent almost all of their working time at their own place.

ü Mobile telework is the outcome of ICTs being used to either increase the locationalflexibility (where and - by implication - when to work) or enhance the productivity of mobileworkers (e.g. accessing corporate data during stays in the field to improve services tocustomers). Mobile teleworkers use online connections, especially e-mail, while travelling,allowing them to continue co-operating with members of staff at the central site (as wellas external business partners) and stay closely integrated in the production process.Communication does not have to literally take place "on the move" (e.g. in a train), butcan also occur at a hotel, on the customer's premises or at some other (stationary) place.

ü Self-employed teleworkers in SOHOs are freelancers and other self-employed personswho work from a so-called small office, home office (i.e. their workplace is at the samelocation as their home) and transfer work inputs and outputs by electronic means. ICTsare being used for interaction with clients, collaborators and suppliers. Many of these arein fields which have always had a large share of workers based at home (e.g. journalists)but are now transformed by tele-mediated communication practices.

There are a number of interrelations between the types of telework mentioned above, namelyhome-based, mobile and SOHO-based self-employed telework (see Figure 4-1). Basically,home-based teleworkers can also spend a considerable share of their time on business trips,such as is the case for many salesmen. The same applies to self-employed teleworkers inSOHOs. For this reason, the number of teleworkers per type cannot simply be added up toarrive at the total share of teleworkers, but overlaps between types have to be taken intoaccount.

So-called centre-based telework is not discussed under this phrase here, but as part of theexploration of tele-cooperation at the workplace (see below). It has proven conceptuallyimpossible to differentiate between centre-based telework taking place in so-called teleworkcentres, tele-centres, tele-cottages etc. on the one hand and other types of co-located typesof work which are heavily relying on ICTs for the transmission of work outputs on the otherhand in a way that is sufficient for survey research (see Gareis 1999). One exception isquestions which deal with demand-side interest in different types of telework, such as whichwas included in the SIBIS pilot survey and is discussed below.


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Figure 4-1: Interrelation between types of telework

• working at home with PC


• permanent, alternating or supplementary

self-employedin SOHOs

home-based

• working away from main place of work

• using online-connections during business trips or in the field

• e-mail, Internet or remote access

• home is the main place of work or the base for trips into the field


• SOHO = small office, home office

mobile

Indicators on home-based telework

Home-based telework is the most widely recognised type of remote work. The design of thequestionnaire module on home-based telework is demonstrated in the figure in the annex.

For some research questions it may be necessary to distinguish persons spending aconsiderable share of their working time teleworking from those only spending a few hoursper week at home (so-called supplementary teleworkers). Ideally, the survey design ensuresthat it is possible to set thresholds for analytical reasons without building the threshold into thequestion itself, as this would determine to some extent what analyses are possible. Forexample, a study looking into the effects of telework on traffic volumes might only beinterested in teleworkers who spend at least one whole working day per week at home,thereby reducing the number of commuting trips. Another research, however, that isinterested in the effects of teleworking on family life might want data on all kinds of work beingcarried out at home, no matter if commuting is reduced or not. The SIBIS module allows forsuch flexibility by collecting data on the intensity of teleworking, i.e. the number of workinghours spent at home.

Table 4-18 shows the results with respect to home-based teleworking. 7.4% of allrespondents in paid work indicated they are teleworking from home presently, at least part oftheir working time (see below for country comparisons). This is a somewhat higher share thanthose who stated they were teleworking in the 2000 Eurobarometer survey (5.6%), whichused a seemingly similar question (see above). This might either indicate that the spread oftelework has increased considerably in the course of the last two years, but may also be dueto the fact that the share of respondents who declare themselves to be teleworkers is highlysensitive to differences in the question wording. A point of particular importance seems to bewhether the self-employed who use ICTs for transferring work results regard themselves asteleworkers or not11. Analysis of the SIBIS data showed that only half of all self-employedworkers who work from home (or with home as a base) and transfer work results via ICTsanswer “yes” to the question whether they telework from home.

11 The SIBIS definition of home-based teleworkers includes self-employed only then when these do not usually

work from home, in the same grounds or buildings as their home, or in different places using home as a base.This group should e.g comprise owner managers of SMEs. Other self-employed persons who declare themselvesas teleworkers are assigned to the group “self-employed teleworkers in SOHOs” (see below) and typicallycomprise all kinds of freelancers who have their office in or adjacent to their home.


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Table 4-18: Home-based teleworking (in %, EU15)

Teleworking from home 7.4thereof:Teleworking at least one full working day/week (Alternatingteleworkers)

28.1

Teleworking less than one full working day/week (Supplementaryteleworkers)

71.9

Teleworking at least one full working day/week: DK -

thereof:Teleworking <10% of total working time 31.0Teleworking 10% to <25% of total working time 34.8Teleworking 25% to <50% of total working time 16.9Teleworking 50% to <75% of total working time 2.4Teleworking >=75% of total working time 3.1Teleworking hours per week: DK 11.8

Not teleworking from home 92.4Teleworking from home: DK 0.2Total 100

Base: all persons employed (N=5,100), weighted by EU15 population Source: SIBIS 2002, GPS

We follow from this that many self-employed persons to whom the definition of teleworkapplies do not regard themselves as teleworkers. For this reason, self-employed individualsworking from home in a so-called small office, home office (SOHO) have to be measuredseparately (see below) in order to avoid statistical under-representation of self-employedtelework. Trying to use one question to catch home-based, mobile and self-employedtelework, as has been tried in the Eurobarometer survey, does not seem to be likely toproduce valid results.

Figure 4-2: Home-based telework – share of total working time

Home-based telework: Intensity Share of total working time (absolute numbers)

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80 90 100Share of total working time (in %)

Num

ber o

f obs

erva

tions

(wei

ghte

d)

Base: all persons teleworking from home (N=401), weighted by EU15 population.Source: SIBIS 2002, GPS

SIBIS GPS respondents who stated they are teleworking regularly were then asked about thenumber of working hours spent at home, on average. 28% of all home-based teleworkersindicate that they telework for more than one full working day per week (= alternating plus


51

permanent teleworkers). This group may also be called tele-commuters, since they (and onlythey) are likely to reduce their commuting trips via staying whole days at home teleworking.The fact that only little over one quarter of all teleworkers spend more than one full dayworking from home seems to confirm recent research findings (see ECATT 2000) accordingto which most teleworkers still spend the majority of their working hours at a traditional worklocation; the home is being used as one additional location for work while still maintaining thecentral office as the main working environment. As Figure 4-2 shows, by far the mostteleworkers spend less than 30% of their total working time at home. Supplementary teleworkis the most wide-spread form of home-based telework.

At the other end of the spectrum, only a very small minority of teleworkers stay at home fulltime: 3% of all teleworkers are at least 75% of their working time at home, a number so smallthat country breakdowns inside of the EU are not possible with the SIBIS GPS pilot sample.These so-called permanent teleworkers continue to be the big exception among teleworkers(ECATT 2000).

Preliminary results from a comparison with data from the 1999 ECATT survey (which is –after data harmonisation is applied – well comparable regarding some of the SIBIS teleworkindicators) even suggest that the share of the EU workforce which practises permanent oralternating telework with more than one full day per week spent at home is actually stagnatingwhile the number of supplementary teleworkers is growing fast (see below, Table 4-30). Thisfinding indicates that more and more people make use of the locational flexibility offered byICTs and spend some working time at home, but only comparatively few stay whole days athome. The number of tele-workplaces (in the technical sense of a networked workplaceinstalled permanently or temporarily in the home), but the number of persons working at homeat any given point in time remains modest. The location of work becomes more footloose, butthere is no general shift of work from the office into the home. Since many of the advantagestraditionally ascribed to telework (such as reduced commuting) only apply if teleworkersspend full days at home, the data suggests that a new approach towards telework and how itshould be supported politically is needed.

How does this relate to the interest of persons employed, and of the unemployed and otherpeople looking for work, show in the different types of telework? The SIBIS GPS discussedthree telework options:

ü doing almost all work teleworking from home;ü telework where not all the working time, but at least one full working day per week is

spent at home; andü work in an office provided near your home which would allow to reduce commuting (this

refers to centre-based telework)

and presented respondents with a three-point scale for answer categories (very interested,somewhat interested and not interested). Table 4-19 presents the results with all personsemployed as the base. The degree of interest is considerable: 40% of the EU workforceexpress interest in permanent telework, 52% in alternating telework and even 55% in centre-based telework (see below). Nearly two thirds are interested in at least one of these forms oftelework.


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Table 4-19: Interest in telework among persons employed (in %)

Interested inpermanent home-

based telework

Interested inalternating home-

based teleworkInterested in centre-

based teleworkInterested in any of

these types of telework

AUSTRIA 45.2 59.8 53.9 70.3BELGIUM 43.7 53.0 68.8 77.1DENMARK 39.1 54.1 66.2 78.6FINLAND 44.4 66.0 56.6 75.4FRANCE 28.7 37.1 43.0 54.4GERMANY 41.8 58.1 61.1 75.5GREECE 35.7 40.5 50.0 53.7IRELAND 50.8 57.7 54.7 68.9ITALY 45.4 50.2 59.2 69.0LUXEMBOURG 40.6 56.1 64.7 74.7NETHERLANDS 44.2 68.5 64.1 74.7PORTUGAL 22.9 24.8 34.7 39.8SPAIN 41.7 45.6 46.1 59.6SWEDEN 43.3 60.6 45.6 67.3U.K. 41.5 55.7 54.9 65.3EU 40.1 51.5 54.5 66.5CH 34.8 44.8 51.2 63.5USA 50.5 61.7 61.6 73.3Note: Figures for “interested” includes answers “very interested” and “somewhat interested”. Base: Allpersons employed (N=5,901); weighted; EU averages weighted by EU15 population.

Source: SIBIS 2002, GPS

While interest in alternating telework is somewhat higher, the number of workers interested inpermanent telework is still remarkable given the low actual spread of this method of work. Wemay follow from this that there are either much less employers willing to let staff workpermanently at home, or much less jobs feasible for permanent telework than it would requireto meet the general demand in this work form. These figures for interest have, however, to betreated with care as the expression of interest does not imply that any real commitment wouldexist if actually faced with the option to telework. According to anecdotal evidence from casestudy and pilot projects the interest of employees in telework is often very undifferentiated inthe initial stage of being confronted with the concept of teleworking from home, but thenbecomes more differentiated after contemplating the pros and cons of actually starting totelework themselves. This hypothesis is confirmed by the data as the difference in interestbetween permanent and alternating telework is bigger in countries with a high share ofteleworkers (which arguably also means stronger public discussion about the subject) such asFinland, Denmark and the Netherlands than in countries with low telework penetration (i.e.only scarce confrontation with the subject in public life) such as Italy, Spain, Portugal andGreece.

Nevertheless, even if these factors are taken into account the data still seems to express thathome-based telework with a large share of the total working time spent at home presentssomething of an ideal for many people in the labour force, while in reality it is very flexibleconfigurations with the highest share of working time still spent in traditional work settingswhich are supported by employers.

As to be expected, levels of interest in telework are higher among the unemployed and otherpersons looking for paid work. Three quarters of this group express interest in at least onetype of telework. Since unemployment tends to be highest in the peripheral and remoteregions of the European Community, these regions can be described as having a greatermismatch between telework demand and supply than the more central regions. As otherstudies have pointed out before, telework has until now not lead to a better supply of remote


53

regions with (knowledge economy) jobs in spite of its technical potential to deliver just that(Millard 2002).

Table 4-20: Interest in telework among the unemployed and other persons looking forwork (in %)

Interested inpermanent home-

based telework

Interested inalternating home-

based teleworkInterested in centre-

based teleworkInterested in any of

these types of telework

AUSTRIA 47.1 63.5 58.6 70.6BELGIUM 37.8 50.8 72.9 75.1DENMARK 45.8 44.9 61.8 68.9FINLAND 58.3 64.7 67.2 78.0FRANCE 49.7 59.3 64.5 73.4GERMANY 51.5 60.8 68.4 73.5GREECE 52.0 52.1 55.7 61.1IRELAND 72.2 77.9 75.4 86.4ITALY 63.8 68.5 74.2 83.4LUXEMBOURG 63.4 54.4 75.8 84.3NETHERLANDS * * * *PORTUGAL 37.6 43.8 46.1 52.3SPAIN 57.6 62.8 70.1 78.5SWEDEN * * * *U.K. 61.3 69.3 71.6 77.0EU 55.3 62.9 68.1 75.6CH 42.0 49.8 55.2 68.4USA 61.3 65.2 65.3 77.7Note: Figures for “interested” includes answers “very interested” and “somewhat interested”.Base: Unemployed and other persons looking for work (N=1,458), weighted; EU averages weighted byEU15 population. Source: SIBIS 2002, GPS

Table 4-21: Feasibility of home-based telework (in %, EU15)

Teleworking already (at least one full working day per week) 2.1Not teleworking already (or less than one full working day per week) or DK 97.9

thereof:Job is feasible for telework 28.0Job is not feasible for telework 67.3

thereof: Main reason (multiple answers)*Company does not permit telework 13.6Superior does not approve of telework 5.3Job requires face-to-face contact with customers, colleagues or otherpersons 64.8

Job requires access to machines or other things which cannot be accessedfrom home 47.7

Other reasons 8.0Reasons: DK 1.3

Feasibility: DK, missing data 4.7Total 100 100Base: all persons employed (N=5,100), weighted by EU15 population; * Base: all persons (excludingself-employed) which state that their job is not feasible for telework (N=2,854), weighted by EU15population Source: SIBIS 2002, GPS

Current practice and interest in telework need to be compared with perceived feasibility ofcurrent jobs for teleworking. The SIBIS GPS asked respondents whether they perceive their


54

current job feasible for telework under the assumption that they would have to spend at leastone full working day per week at home (see Table 4-21). 28% of all non-teleworkers regardtheir job as feasible for this type of alternating telework, more than 10 times the number ofworkers who already telework for at least one day per week. This indicates that the principalinterest expressed in telework is to a considerable extent not being translated into actualtelework practice yet although jobs are regarded as being feasible for telework.

Of those who declare that their job is not feasible for telework (67% of all non-teleworkers),roughly two third state the need for face-to-face contacts with customers, colleagues or otherpersons as one reason; half of all mention access to machines or other things which cannotbe accessed from home; but only 14% and 5% respectively state as a reason that thecompany does not permit or that superiors do not approve of telework. Management-sideopposition against telework seems, therefore, to play not as big a role than cold be expected.

Table 4-22: Financing of teleworking equipment (in %)

EU15 USAMainly paid for by employer 41.4 34.2Partly paid for by employer 15.5 20.0Not at all paid for by employer 41.6 45.7Financing: DK 1.4 -Total 100 100Base: all persons teleworking from home excl. self-employed (N=458), weighted. EU 15 averageweighted by EU15 population. Source: SIBIS 2002, GPS

The question of who finances the tele-workplace is of importance since national teleworkframework agreements seek to ensure that the implementation of telework should not burdenemployees with additional costs. On the other hand, anecdotal evidence suggests that manyemployees happily accept contributing to the cost of telework in exchange for the increase inflexibility they derive from it. The picture from the SIBIS GPS data is mixed: 41% of EUteleworkers with a contract of employment indicate that their employers paid for theteleworking equipment, while 42% stated that they had to bear all costs. Only 16% state thatcosts are shared between both parties. As it is often stated that telework is organised in verydifferent ways in the USA and the EU, Table 4-22 also gives the numbers for the USA.However, only slightly more US employees have to bear all the costs for their tele-workplacein comparison to the EU15 average.

Table 4-23: Churn in home-based teleworking (in %, EU15)

Teleworking from home 7.4Not teleworking from home currently and ...... has teleworked from home regularly in last 5 years with at least one fullworking day per week spent at home

0.8

... has teleworked from home regularly in last 5 years with less than one fullworking day per week spent at home

1.7

... has not teleworked from home regularly in last 5 years 90.0Teleworking from home currently or previously: DK 0.1Total 100Base: all persons employed (N=5,100), weighted by EU15 population Source: SIBIS 2002, GPS

One aspect of telework which has attracted scant attention so far apart from case-studybased research is teleworker churn, i.e. the possibility that teleworking only takes place in aspecific stage of the working life, followed by a stage which sees full-time working at a centraloffice again. There is some anecdotal evidence that indeed telework is more suited to specificfamiliar and career settings than others to the effect that telework loses attractiveness once anew stage in the life cycle has been reached (see FAMILIES 2002). In the SIBIS GPS,respondents that indicated they are not teleworking from home were asked whether they haveteleworked before in the last 5 years, and whether they have done so for at least one fullworking day per week (see Table 4-24). The share is 2.5% of all non-teleworkers in the EU for


55

the former, and close to 1% for the latter. This means that for every three persons who areteleworking currently in the EU there is one who has teleworked on a regular basis before butstopped doing so.

Table 4-24: Home-based telework and teleworker churn (in %)

Home-basedteleworkers –alternating or

permanent

Home-basedteleworkers -

supplementary

(1)Current home-based

teleworkers – all

(2)Previous home-based

teleworkers - all

AUSTRIA * * 6.7 3.2BELGIUM 2.2 5.3 7.5 3.1DENMARK 2.6 15.1 17.7 5.9FINLAND 4.7 11.0 15.7 2.4FRANCE * * 4.4 2.8GERMANY 1.6 6.3 7.9 2.5GREECE * * 6.0 2.7IRELAND * * 6.0 2.8ITALY * * 2.5 1.4LUXEMBOURG * * 3.3 3.8NETHERLANDS 9.0 11.6 20.6 4.5PORTUGAL * * 1.6 1.3SPAIN * * 2.3 1.9SWEDEN * * 14.9 4.1U.K. 2.4 8.5 10.9 2.3EU 2.1 5.3 7.4 2.5CH * * 11.4 3.0USA 5.1 12.2 17.3 7.3Base: All persons employed (N=5,901), weighted by EU15 population. Source: SIBIS 2002, GPS

While all of the above data stems from the SIBIS general population survey, supplementarydata is required to be provided through company surveys. SIBIS has developed a module ontelework practice and interest to be used in surveys targeted at human resources managersin organisations. Interest is broken down into the same three categories used for the GPS(see above) plus a fourth one which asks for interest in supplying staff with remote accessfrom home without employees spending regular working time (or alternatively not spendingwhole days) at home. An early version of this module was piloted in the 1999 ECATT survey(see Figures in annex).

Indicators on mobile telework

As the term "telework" is commonly understood to indicate working at home, measuringmobile telework in surveys should avoid to use the term. SIBIS defines mobile teleworkers asthose who spend 10 hours per week or more away from their home and their main place ofwork, e.g. on business trips, travelling or on customer's premises, and make use of onlineconnections while doing so. The GPS survey design allows other thresholds to be used aswell. Table 4-25 presents some results, according to which 15% of the EU workforce can bedescribed as “mobile workers” (spending more than 10 working hours per week away fromhome and their main place of work) and 4% as mobile teleworkers.


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Table 4-25: Mobile teleworking (in %, EU15)

Mobile teleworkers (use computer connections when travelling) 4.0thereof (multiple response): Purposefor accessing the Internet 73.4for sending or reading e-mails 92.4for connecting to their company’s internal computer system 72.4----------------------------------------------------------------- ------------- -------------thereof (multiple response): Locationhotel, conference site or similar location 68.7another company’s premises 52.0Internet café or commercial teleservice centre 5.4on the move using mobile device for data transfer 37.0

Other mobile workers (have spent at least 10 hours away from home andmain place of work, but not teleworking) 11.4

Not spent at least 10 hours per week away from home and main place ofwork 81.8

Mobile telework: DK 2.8Total 100

Base: All persons employed (N=5,100); weighted by EU15 population. Source: SIBIS 2002, GPS

The main purposes of mobile teleworkers to use online connections is sending and reading e-mail (92%), but three quarters each also browse the Internet and connect to their company’sinternal computer system.

Understanding mobile telework implies that the means by which workers connect to electroniccommunication channels are assessed. Therefore, the SIBIS module in mobile work containsquestions on type of activity and access points for mobile use of online data connections. Onepotential access point are teleservice centres which offer travellers a temporary workplaceequipped with PC, Internet access, printer, fax etc. Such service providers are emerging atthe nodes of international traffic networks, i.e. at central locations in large cities as well asairports. They may contribute to making mobile work attractive for more and more travellers.However currently only 5% of all mobile teleworkers make use of telework centres, whereasmost choose the hotel room or conference site, another company’s premises a similarlocation for going online. More than a third use truly mobile technology, that is data transfervia mobile devices, for the purpose.

Indicators on tele-cooperation

Tele-cooperation is closely related to telework and has indeed sometimes been called ‘in situtelework’ because, although the majority of white-collar workers today appear to be co-located in central office buildings, in fact they are often working closely together with valuechain and project partners at far away locations. Evidence suggests that tele-cooperation hasboosted worker productivity and innovative performance throughout the EU economy byallowing flexible configurations of human capital without actually moving people from oneplace to the other (Reichwald et al. 1998).

Tele-cooperation was operationalised for the SIBIS GPS as communicating with externalbusiness contacts via e-mail, video-conferencing or electronic data transfer. As anexplanation external persons were described as “customers, clients, suppliers, other businesscontacts, but also colleagues working at other locations of the same company”.

Tele-cooperation is already widely in use in Europe (see Table 4-26) with an average ofalmost 38% of EU workers practising it at least “sometimes”. For each of the three ICTsmentioned, the intensity of usage was assessed. E-mail and electronic data transfer are usedat least once a day by more than three quarters and more than half of all people tele-cooperating, respectively. The number of users of video-conferencing, and the frequency ofusage are much lower.


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Table 4-26: Tele-cooperation (in %, EU15)

Tele-cooperating = Persons using e-mail, video-conferencing orelectronic data transfer when communicating with external contacts 37.8

thereof (multiple response):Using e-mail 96.5

Thereof10 or more times a day 34.0less, but at least once a day 39.0less, at least once a week 15.4less often than once a week 8.0never 2.8DK 0.7Total 100

Using video-conferencing 19.3Thereof10 or more times a day 0.4less, but at least once a day 0.6less, at least once a week 4.7less often than once a week 13.6never 80.0DK 0.6Total 100

Using electronic data transfer 81.9Thereof10 or more times a day 20.0less, but at least once a day 33.9less, at least once a week 19.3less often than once a week 8.7never 17.1DK 1.1Total 100

Not tele-cooperating 62.0Tele-coopeeration: DK 0.2Total (all employed) 100

Base: All persons employed (N=5,100); weighted by EU15 population. Source: SIBIS 2002, GPS

It becomes obvious from comparing the share of workers involved in telework and in tele-cooperation (as defined above) that tele-mediated work practices are affecting many morepeople than only those who actually work from a remote place. It has often been observedthat ICTs enable work to be brought to the worker (telework) instead of transporting workersto work (commuting). But work inputs and outputs are also increasingly transmitted betweentraditional workplaces via ICTs. This is a process which involves all parts of the economy and,as the SIBIS pilot data show, already more than a third of the EU workforce.


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Table 4-27: Tele-cooperation (in %)

yes no DKAUSTRIA 36.1 61.5 2.4BELGIUM 37.5 62.2 0.3DENMARK 56.0 42.5 1.5FINLAND 55.4 44.6 -FRANCE 25.8 74.1 0.1GERMANY 45.7 54.3 -GREECE 12.6 87.4 -IRELAND 37.1 62.9 -ITALY 35.2 64.8 -LUXEMBOURG 42.4 57.6 -NETHERLANDS 45.0 54.7 0.2PORTUGAL 9.8 89.7 0.5SPAIN 21.1 78.3 0.5SWEDEN 52.2 47.1 0.7U.K. 49.1 50.9 -EU 37.8 62.0 0.2CH 48.0 48.5 3.5USA 52.8 47.0 0.2Base: All persons employed (N=5,901), weighted by EU15 population. Source: SIBIS 2002, GPS

In the future further steps will become necessary to gather data on the nature of tele-mediated cooperation. This is likely to require special surveys which analyse workingprocesses in much detail. Existing surveys such as Germany’s “Qualification and EmploymentSituation Survey” (BIBB/IAB) can act as bases for this.


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Indicators on telework by self-employed

The questionnaire module on tele-cooperation described above is also used to single out self-employed workers who use online ICTs for interaction with clients, collaborators andsuppliers. These are called “self-employed teleworkers in SOHOs12” if they work from home,on the same grounds as their home or with their home as their base. According to the GPSdata, 3.4% of EU employment are self-employed teleworkers in SOHOs (see Table 4-28)which equals 21% off all self-employed. Another 0.5% (3%) are self-employed teleworkers,but they do not work from home or the same ground or building as their home, which meansthey are assigned to the category of traditional home-based teleworkers (see above).

Table 4-28: Self-employed teleworkers in SOHOs (in %, EU15)

Base: allemployed

Base: self-employed

Teleworking in SOHO 3.4 20.8thereof:Using e-mail 99.1Using video-conferencing 16.9Using electronic data transfer 85.1

Self-employed teleworker, but not from SOHO 0.5 3.3Not teleworking 12.3 75.9Not self-employed 83.4 -DK 0.4 -Total 100 100Base: All persons employed (N=5,100), all self-employed (N=809); weighted by EU15 population.


If tele-cooperation becomes the basic mode of interacting with external contacts we canspeak of e-lancers, i.e. freelancers who (more or less) exclusively use the Internet to get intouch with clients via the Internet, work as teleworkers, and transfer work results via ICTs(see below).

Summary: Types of telework

Table 4-29 gives an overview of the spread of telework in the EU broken down by country, asfar as sample sizes per country allow. The number of home-based teleworkers is highest inthe Netherlands where more than every fifth worker spends some time at home teleworking.Other countries with very high shares are Denmark (18%), the USA (17%), Finland (16%) andSweden (15%). The share of EU employment practising some form of telework is 13%(against 25% in the USA), 7% (17%) of which are teleworking from home, 4% (6%) aremobile teleworkers and 3% (6%) are self-employed teleworkers working in SOHOs. The EUaverage, therefore, still lags behind the USA considerably, although the Netherlands and theScandinavian countries sport figures that are sometimes as high (or even higher) than in theUSA.

Comparing the figures on diffusion between different types of telework that the largestcategory is that of home-based teleworkers, but the figures for mobile and SOHO-basedtelework are almost as high, and indeed rising fast. Only 2 percentage points of the overallfigure of 13% teleworkers in the EU workforce belong to the category of alternating andpermanent teleworkers (compare Table 4-24) – the category which comes closest to thetraditional cliché of the teleworker spending full days or even their whole working time athome. Most telework today takes place in more flexible settings, with the home acting as onlyone of a bigger number of options for work locations.

12 “Small office, home office”, meaning self-employed who work from a home base, usually own-account self-

employed (without employees) which are often referred to as freelencers.


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Table 4-29: Types of telework (in %)

Home-basedteleworkers Mobile teleworkers Self-employed

teleworkers in SOHOsAll teleworkers

(exclusing overlaps)AUSTRIA 6.7 * * *BELGIUM 7.5 * * *DENMARK 17.7 2.7 * *FINLAND 15.7 6.2 * *FRANCE 4.4 2.1 * *GERMANY 7.9 5.7 5.2 16.6GREECE 6.0 * * *IRELAND 6.0 4.2 * *ITALY 2.5 5.5 * *LUXEMBOURG 3.3 * * *NETHERLANDS 20.6 4.1 * *PORTUGAL 1.6 * * *SPAIN 2.3 * * *SWEDEN 14.9 4.9 * *U.K. 10.9 4.7 4.5 17.3EU 7.4 4.0 3.4 13.0CH 11.4 7.6 * *USA 17.3 5.9 6.3 24.6Base: All persons employed (N=5,901), weighted by EU15 population. Source: SIBIS 2002, GPS

Meanwhile the figures for mobile and SOHO-based telework are rising fast, as a tentativecomparison between the 2002 SIBIS data and 1999 ECATT data shows (see Table 4-30) .The share of mobile teleworkers has been rising at a rate of 38% per year since 1999, whilethe self-employed in SOHOs have experienced a growth rate of 54%. In both cases,technological progress which has resulted in more powerful and easier to use ICTs becomingavailable to a larger share of the workforce, have been instrumental in changing the wayworkers interact with internal and external work partners at their workplace and on business

Table 4-30: Development of telework in the EU 1999 - 2002

in % of all persons employed4.2.4 Type1999 2002

average annualgrowth (in %)

Alternating andpermanent home-basedtelework

2.0 2.1 2

Supplementary home-based telework 2.0 5.3 39

Mobile telework 1.5 4.0 38Self-employed teleworkin SOHOs 0.9 3.4 54

All telework (excludingoverlaps) 6.0 13.0 29

Base 1999: All persons employed; base 2002: All persons employed (N=5,100); both weighted by EU15population. Source: ECATT 1999, GPS; SIBIS 2002, GPS

What is most striking about the 1999-2002 comparison is the difference in developmentbetween alternating and permanent home-based telework on the one hand, andsupplementary home-based telework on the other hand. The latter is growing fast, with amore than two and a half bigger number of supplementary teleworkers today than in 1999.The number of teleworkers who spend at least one full working day at home, however, hasnot grown much at all in the last three years. There seems to be a shift of home-basedteleworkers towards less time spent at home. Obviously, the progress in the availability of


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cheap and powerful remote access technology has not led to workers spending more andmore time working at home, but rather to more and more workers spending only a fraction oftheir weekly working time at home. This points towards a greater flexibility in the use ofindividual working locations, but at the expense of some of the traditional advantagesascribed to telework such as savings on commuting.

Outcomes of telework

Until now the discussion about telework has been dominated by misconceptions and myths.For example it has for a long time been assumed that the teleworking workforce consistsprimarily of women, as telework seems to offer interesting possibilities to combine traditionallyfemale home-bound roles (bringing up children) with work careers. The ECATT (2000) studyhas shown that in reality, the large majority of teleworkers are male. This suggests that thedriving forces behind the implementation of telework are still not understood in their entirety.

The main reason for this is that most scientific evidence on telework is being collected incase-study based research which means that the degree to which research results arerepresentative for the entirety of teleworkers is unknown. Case studies often involve teleworkpractice in companies which run trials or schemes that are publicly announced. According toall evidence available, however, most telework takes place outside of formal schemes. Thereare many reasons to assume that telework inside and outside of formal schemes differsignificantly with regard to characteristics and outcomes of this way of working.Representative studies which are based on representative probability samples of the entireadult population (such as the SIBIS pilot GPS) are therefore needed.

Measuring outcomes by using representative surveys can be done in two ways: Either byquestioning teleworkers (i.e. asking for a self-assessment of outcomes by the personsinvolved) or by the analysis of correlations between intensity of telework and outcomevariables (e.g. work satisfaction).

With regard to the former, the SIBIS telework modules include a hypothetical question on theimpacts not being allowed to work at home would have for persons identified as practisinghome-based teleworking. From focus group discussions and pre-tests we follow that this kindof question will produce reliable results in spite of the general problems associated withhypothetical questions in surveys. As most home-based workers today are (still) very muchaware of the fact that working at home is something extraordinary, they prove to be able tocompare their own working conditions with the situation in more traditional, e.g. central office-based work settings. A hypothetical question has been preferred against a more directquestion asking for the effects of starting to telework, as it cannot be assumed anymore thattoday’s teleworkers have recently (or ever) worked in a traditional work setting. Only workerswho have changed their work location, e.g. from central office-based to the home, would beable to answer a question such as “What effect has telework had on your workperformance?”.

It has to be taken into account, however, that if telework is ever to become a mainstream wayof working, the ability of respondents to give reliable answer even to a hypothetical questionsuch as piloted in SIBIS would likely decrease13. According to available data this will still takesome time.

The results (see Table 4-31) show clearly that telework is perceived to have a beneficial effecton work performance (with 23% of all teleworkers agreeing completely to the statement thatwithout telework they would not doing their job as well, and another 28% agreeingsomewhat). Quite obviously telework is not only being pursued for private reasons, but alsofor making work more efficient and effective.

The question is designed to enable estimates on the quantitative effects of telework on labourmarket parameters such as labour market participation. 9% of all home-based teleworkersstate that they could not be in paid work at all without the possibility to telework from home 13 To illustrate this point we might think about a question such as “How would it affect you if you did not have a

telephone?”. Because the telephone has become so much part of everyday life (and most of us have never livedwithout it), most people would not be able to give sensible answers in a survey interview.


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(“agree completely”) and another 8.5% agree “somewhat” to this statement. The effect oftelework on EU labour market participation can thus be estimated: between 0.7% and 1.3% ofall jobs the EU are held by persons who could not participate in the labour force withouttelework, according to their own assessment14. This does not include self-employedteleworkers in SOHOs.

Table 4-31: Outcomes of home-based telework (in %, EU15)

Without telework I ... agreecompletely

agreesomewhat do not agree DK Total

(a) ... could not be in paid work atall 8.8 8.5 78.9 3.9 100

(b) ... could not do my job as wellas with telework 23.3 28.4 45.4 2.9 100

(c) ... would have to look foranother job which is located closerto my home

9.9 7.4 79.4 3.4 100

(d) ... would have to reduce myworking hours per week 14.5 12.2 69.6 3.6 100

Questions: Most working people are not allowed to work from home. Please consider you would not beallowed to telework from home, for whatever reasons. What would that mean for your ability to do yourjob? Base: all persons teleworking from home (N=401), weighted by EU15 population.


Additionally, between 15% (agree completely) and 27% (agree at least somewhat) of allhome-based teleworkers think that they would have to work less hours if telework was notavailable. Finally , telework is likely to contribute to (geographical) job mobility: Between 10%(agree completely) and 17% (agree at least somewhat) of all teleworkers would have,according to their own assessment, to look for another job which is located closer to theirhome if they could not telework from home.

Table 4-32: Outcomes of home-based telework (in %, USA)

Without telework I ... agreecompletely

agreesomewhat do not agree DK Total

(a) ... could not be in paid work atall 7.1 11.4 80.3 1.2 100

(b) ... could not do your job as wellas with telework 26.2 18.8 52.8 2.2 100

(c) ... would have to look foranother job which is located closerto your home

8.9 10.7 78.2 2.2 100

(d) ... would have to reduce yourworking hours per week 17.6 15.5 64.7 2.2 100

Questions: Most working people are not allowed to work from home. Please consider you would not beallowed to telework from home, for whatever reasons. What would that mean for your ability to do yourjob? Base: all persons teleworking from home (N=88), weighted. Source: SIBIS 2002, GPS

Outcomes cannot been investigated for other types such as mobile telework and self-employed telework in SOHOs in the same way. This is due to the fact that for these types oftelework, it is mainly the technology which has changed and allowed for improved businessprocesses, rather than the location of work. These changes are of a more gradual nature,often resulting not from conscious decisions by the persons affected but creeping into dailyworking life just as any other modification of work processes. As a consequence focus groupdiscussions have shown that these types of teleworkers are less able to reflect on the motivesfor taking up this way of working, and of outcomes. If these are to be assessed they wouldhave to focus on individual technologies (such as the mobile phone, PDAs etc.).

14 Share of employment teleworking from home: 7.4%; share of teleworkers who could not be in paid work without

the possibility to telework from home: between 8.8% (agree completely) and 17.2% (agree at least somewhat).


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4.2.5 Contract: e-Lancing and online labour markets

There is on ongoing discussion whether ICTs together with broad changes in labour marketregulation and attitudes towards entrepreneurial activities can be made responsible for whatis often called the rise in “new self-employment”, which seems to mark the end of the trend offalling rates of self-employed workers that could be observed for the longest part of the lastcentury. More important, there is also no consensus whether the increase in self-employmentthat seems to have taken hold in the 1990s in most EU Member States as well as the UnitedStates will gain speed or even continue in the coming years. According to the proponents ofan ICT-propelled shift towards entrepreneurs at the cost of “regular employmentrelationships”, it is falling transaction costs on the labour market which has been one of themain reasons for a rising willingness and ability of workers to “go it alone”. The Internet hasbeen very effective in decreasing transaction costs because it makes it easier for the supplyand the demand side on the labour market to match. Screening and comparing job offers,tenders and CVs of applicants is now possible at the click of a mouse on the Internet whereasit was causing very much effort in the offline world (Gareis and Mentrup 2001a).

In principle, therefore, new self-employment should have received a significant push by theInternet. It is now conceivable that freelancers can work exclusively “on the net”, which meansthat they carry out all major communication processes they need to get and stay in contactwith clients, suppliers and business contacts through the Internet. For this, initially onlyhypothetical phenomenon, the term "e-lancing" was invented by Malone and Laubacher(1998). It describes self-employed workers who have the following features (Gareis 2001: 9):

ü For all main stages of the work process (identifying and approaching potential clients,exchanging information during the work period, delivering results), e-lancers use ICTseither predominantly (wide definition) or exclusively (narrow definition).

ü Working life is organised in a sequence of projects which might last only a few hours up toseveral months (or even years).

ü Marketing of services is done on the open market via electronic marketplaces that areestablished e.g. on the Internet.

ü For complex tasks, groups of e-lancers put their skills together to temporarily act like atraditional firm, i.e. create virtual organisations. These networks disband as soon as thetask has been fulfilled.

ü e-lancers work where it suits them and their tasks best, most likely spending most of theirworking time in their own SOHO.

The concept of the e-lancer, therefore, goes beyond that of the teleworker as it describesworkers who are - at least in theory - totally detached from the need to be located in proximityto their clients, but instead work "on the Net".

Data on this phenomenon is scarce, which can not surprise given the elusive (and futuristic)nature of the concept. The originators of the e-lancing concept most often make use of dataon own-account self-employed (outside of the farming sector) to indicate the potential of e-lancers. Others make use of data on so-called “free agents” which they regard as apreliminary stage in the development towards eLancing (Laubacher and Malone 2000). Theseare believed to account for 30% of the US labour force (Kelly Services 1999), but mostlythese numbers are derived by simply counting all those that work in atypical forms ofemployment. Similarly Pink (1997) adds up the self-employed, the independent contractorsand temporary workers and arrives at a number of 25 million free agents, 16% of the USworkforce. It hardly seems appropriate to assume that all of these can be regarded as futuree-lancers (Gareis 2001). A more realistic view of the e-lancing phenomenon is clearly indemand, given the degree to which the public debate has been focussing on e-lancers asspearheading a general trend towards self-employment becoming the common contractualmode of working.


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The SIBIS GPS instrument contained a number of questions intended to measure the extentto which the self-employed carry out communication with clients and other business contactsvia the Internet. It asks whether the respondent sometimes

ü attracts new business through the Internet or via e-mailü delivers work results to clients/customers through the Internet or via e-mailü communicates with clients/customers exclusively by electronic means, i.e. via Internet, e-

mail, phone or fax, but without meeting face-to-face.

These questions allow to single out self-employed persons who have started to use practiceswhich are at the heart of the e-lancing concept. In order to distinguish between differentdegrees of e-lancing activity, three groups can be created:

ü e-lancing starters are self-employed workers who either attract new business through theInternet or via e-mail or deliver work results to clients/customers through the Internet orvia e-mail

ü advanced e-lancing users are self-employed workers who attract new business throughthe Internet or via e-mail and deliver work results to clients/customers through the Internetor via e-mail

ü (occasional) e-lancers are self-employed workers who communicate withclients/customers exclusively by electronic means, i.e. via Internet, e-mail, phone or fax,but without meeting face-to-face.

As Table 4-33 and Table 4-34 show, the share of the self-employed who use e-lancing is stillmodest on average, with 9% who can be described as (occasional) e-lancers, an additional5% of advanced users of e-lancing and 18% of e-lancing beginners. The highest share of(occasional) e-lancers is to be found in the U.K. where 18% of the self-employed belong tothis category. In the USA the corresponding figure is 14%.

Table 4-33: “ e-Lancing” (in %, EU15)

Self-employed 7.8thereof:Not using the Internet regularly (in last 4 weeks) 44.7Using the Internet regularly (in last 4 weeks) 55.3

thereof: (multiple answers)*(a) Attracts business through the Internet 34.7(b) Delivers work results through the Internet 47.4(c) Sometimes communicates exclusively by electronic meanswith clients/customers 15.9

thereof: e-lancing typology 31.9- Type “e-lancing starters” (either a or b but not c)- Type “advanced users of e-lancing” (both a and b but not c) 9.1- Type “e-lancers” (c) 15.9- none of these 42.8- DK 0.2

Total 100 100Base: all self-employed (N=809), weighted by EU15 population Source: SIBIS 2002, GPS

These figures indicate that e-lancing does not play a significant role yet for the very largemajority of self-employed workers in the European Union (even in the countries where the useof the Internet is most advanced). It seems necessary that the expectations for major jobgrowth resulting from the opportunities the Internet affords with respect to making business inthe “virtual domain” have to be scaled down somewhat, although attributes of the e-lancingconcept such as the bigger reliance on electronic communication at the expense of face-to-face interaction are certainly beginning to gain ground.


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Table 4-34: Types of “ e-lancing” (in %)

e-lancingstarters

advancedusers of e-

lancinge-lancers non-users of

e-lancing DK non-users ofthe Internet Total

AUSTRIA * * * * * * *BELGIUM * * * * * * *DENMARK * * * * * * *FINLAND * * * * * * *FRANCE * * * * * * *GERMANY 25.7 8.4 11.5 35.3 0.4 18.7 100GREECE 3.8 2.7 5.1 16.8 - 71.5 100IRELAND 10.2 2.4 4.0 14.1 - 69.3 100ITALY 18.6 6.1 9.8 15.9 - 49.6 100LUXEMBOURG * * * * * * *NETHERLANDS * * * * * * *PORTUGAL 7.2 - - 13.3 - 79.5 100SPAIN 9.2 1.3 0.7 14.6 - 74.2 100SWEDEN * * * * * * *U.K. 24.1 3.5 18.4 30.3 - 23.7 100EU 17.7 5.1 8.8 23.7 0.1 44.7 100CH * * * * * * *USA 24.3 3.6 13.8 32.1 - 26.3 100Base: All self-employed (N=935), weighted; EU average weighted by EU employment.

Source: SIBIS 2002, GPS.

Things look different when it comes to online labour markets which are supposed by manyexperts to develop rapidly in the field of matching supply of and demand for job offers, withpotentially significant effects on the efficiency of the recruitment process. The SIBIS GPSmodule on “e-commerce and other uses of the Internet” includes a question on this topic:

ü For your private purposes, have you used the Internet in the last 12 months to ... look fora job (plus four other items referring to e-commerce and online health information)

12% of the EU labour force (including persons interested in work but not registered asunemployed) use the Internet for job-related searches per year, more than half of which atleast once a month. The figure is almost twice as high for the USA (21% users, of which 13%are checking the Web regularly for job offers). EU countries with the highest number of onlinejob-searchers are Denmark (26% incl. occasional users), the U.K. (21%), followed by theNetherlands (17%), Finland and Ireland (16% each).

These figures are, of course, influenced by the general extent to which the labour force isengaged in job searching. In the USA, for example, comparatively low job tenure and high jobturnover may result in a high share of the workforce looking for a job although currently inemployment, while in countries with longer job tenure job searching might in general be lesscommon. These country differences are not controlled for in this indicator. It is thereforeproperly interpreted as a measure of online job search activity, but not as a measure of howmuch of existing job search activity is being transferred to the Internet. As such the indicatoris of high relevance for the assessment of (potential) labour mobility since lack of knowledgeof employment alternatives is believed to be one of the main constraints to (priorilygeographical) labour mobility.


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Table 4-35: Use of the Internet for job search (in %)

regular users ofjob search (last 4

weeks)

occasional usersof job search (last

12 months)non-users of job

search DK total

AUSTRIA 5.7 4.3 90.0 - 100BELGIUM 6.2 6.6 86.3 0.8 100DENMARK 13.0 12.6 74.4 - 100FINLAND 7.9 8.5 83.5 0.1 100FRANCE 6.1 2.8 90.6 0.5 100GERMANY 6.0 5.4 88.7 - 100GREECE 3.0 3.4 93.6 - 100IRELAND 8.3 7.6 84.0 - 100ITALY 3.9 3.5 92.3 0.3 100LUXEMBOURG 4.8 2.0 93.2 - 100NETHERLANDS 6.8 10.7 82.6 - 100PORTUGAL 2.7 2.4 94.9 - 100SPAIN 4.4 2.4 93.3 - 100SWEDEN 7.0 8.4 84.5 - 100U.K. 11.8 9.2 79.0 - 100EU 6.5 5.4 88.0 0.1 100CH 5.5 4.1 90.3 - 100USA 12.9 8.0 79.1 - 100Base: Total labour force and persons looking for work (N=7,359), weighted; EU average weighted by EUemployment. Source: SIBIS 2002, GPS

This indicator should be supplemented by data on the use and perceived success of onlinerecruitment for which a survey of human resources managers in organisations would be thebest data source. SIBIS has developed a module to be used for this purpose. It wouldproduce data for the following indicators:

ü share of companies that use the Internet for recruitmentü share of companies that


4.3.1 Structure of employment: Employment in ITCE occupations and ITsectors

The EMERGENCE project (Huws et al. 2001: 14-21) selected the following occupations for adefinition of information technology workers based on the International StandardClassification of Occupations (ISCO 88(COM)):

ü ISCO 213 (computing professionals)- 2131 Computing systems designers, analysts and programmers- 2139 Computing professionals not elsewhere classified

ü ISCO 312 (computer and associate professionals)- 3121 Computer assistants- 3122 Computer equipment operators- 3123 Industrial robot controllers

ü ISCO 313 (optical and electronic equipment operators)- 3131 Photographers and image and sound recording equipment operators- 3132 Broadcasting and telecommunications equipment operators


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- 3133 Medical equipment operators- 3139 Optical and electronic equipment operators not elsewhere mentioned.

Table 4-36: Employment in IT occupations (in % of total employment)

Computerprofessionals

(ISCO 213)

Computerassociate

professionals(ISCO 312)

Optical and electr.equipmentoperators(ISCO 313)

IT workers(ISCO 213 + 312 +

313)

AUSTRIA 0.3 1.1 0.2 1.6BELGIUM 1.5 0.1 0.3 1.9DENMARK 1.3 0.7 0.2 2.2FINLAND 1.6 0.5 0.2 2.3FRANCE 1.0 0.5 0.1 1.7GERMANY 0.7 0.6 0.2 1.5GREECE 0.1 0.2 0.3 0.6IRELAND n.a. n.a. n.a. n.a.ITALY 0.1 0.8 0.2 1.1LUXEMBOURG 1.2 0.6 n.a. 2.1NETHERLANDS 1.5 1.3 0.4 3.2PORTUGAL n.a. 0.5 0.2 0.9SPAIN 0.5 0.4 0.2 1.1SWEDEN 1.9 0.6 0.3 2.8U.K. 1.4 0.3 0.1 1.8Base: Total employment per country

Source: EMERGENCE 2001 based on Eurostat (LFS) data

The following sectors (at the two-digit level of NACE) make up the information technologysectors according to EMERGENCE:

ü NACE 30 (Manufacture of office machinery and computers)ü NACE 72 (Computer and related activities

These were identified by analysing the share of information technology workers (see above)of the total employment in the sector across the whole EU, but excluding the U.K. and Irelandbecause of missing data. The results (Table 4-37) show Ireland leading the field with almost3% of employment in IT sectors followed by Sweden and the U.K. (1.9%) and Denmark(1.8%). In Greece and Portugal which are at the end of the rank the share (0.3%) is 10 timessmaller than in leading country Ireland.


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Table 4-37: Employment in IT sectors (in % of total employment)

NACE 30 NACE 72 NACE 30 + NACE 72AUSTRIA 0.3 0.7 1.0BELGIUM 0.2 0.7 0.9DENMARK n.a. 1.8 1.8FINLAND n.a. 1.3 1.4FRANCE 0.2 1.1 1.3GERMANY 0.3 0.8 1.2GREECE n.a. 0.3 0.3IRELAND 1.0 1.9 2.9ITALY 0.2 0.9 1.1LUXEMBOURG n.a. (0.8) (0.8)NETHERLANDS 0.2 1.5 1.7PORTUGAL n.a. (0.3) 0.3SPAIN 0.2 0.6 0.8SWEDEN n.a. 1.8 1.9U.K. 0.5 1.4 1.9Base: Total employment per country, () “treat estimate with caution”

Source: EMERGENCE 2001 based on Eurostat (LFS) data

This analysis is, of course, hampered by the limited usefulness of the NACE classification formapping Information Society developments. This issue is discussed elsewhere.

4.3.2 Benefits from employment: job satisfaction, job security and job-familybalance

ICT-supported flexible ways of working can be assumed to be sustainable if they result in ahigh degree of job satisfaction, and a level of job security and job-family balance which areperceived as being good in comparison to more traditional types of work. Measuring theseimplies choosing a point of reference. This might be the previous job/work arrangement, orthe current work arrangement of other persons. The former option is only possible in caseswhere an easily recognisable shift from one way of working (= “traditional”) to an other (=”flexible”) has taken place. In cases where the person has always worked in the non-traditional work arrangement, or where the change has been so gradual that is has hardlybeen perceivable, it will not be possible to compare the current with the previous workarrangement. In these cases, then, it is more feasible to compare groups of workers with eachother according to work characteristics and their satisfaction with their job. As SIBIS isdeveloping indicators with the intention to make them applicable for an as long period in thefuture as possible, the project chose the latter option.

As a measure of the sustainability of the job with respect to the balance between job andfamily life, the SIBIS GPS included a module originally conceived for the Eurobarometer 44.3and also used for the FAMILIES project (2002) on the effects on flexible ways of working onthe family (this project used a non-probability sample). This allows us to compare results tothese studies, but it also enables building new indicators since the SIBIS pilot allows forbreak-downs by types of work (although statements based on such calculation have to beinterpreted with much care due to the limited size of the pilot sample).


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Table 4-38: Sustainability of work and family life (in %, EU 15)

How often do you... often some-times never doesn’t

apply DK total

... find your work stressful 31.9 49.5 18.3 0.2 0.2 100

... come home from work exhausted 31.7 50.4 17.4 0.3 0.2 100

... find your job prevents you from giving thetime you want to your partner or family 23.1 35.2 40.4 1.0 0.4 100

... feel to tired after work to enjoy the thingsyou would like to do at home 23.8 43.1 32.5 0.4 0.2 100

... find your partner/family gets fed up withthe pressure of your job 10.9 32.7 53.7 2.1 0.6 100

Base: All persons employed (N=5,100), weighted by EU15 population. Source: SIBIS 2002, GPS

Work stress is widespread in the EU with 32% of all employed stating they find their workstressful “often”, and an additional 50% doing so “sometimes”. The same shares of theworking population state that the come home from work exhausted. About one quarter eachindicate that they “often” find their job prevents them from giving the time they want to theirpartner or family, and that they often feel too tired after work to enjoy the things they wouldlike to do at home. 11% state that they find their partner/family often gets fed up with thepressure of their job.

Other dependent variables available for comparisons between types of workers include jobquality (Table 4-39) and overall job satisfaction (Table 4-40). These variables can now beused for comparing groups of persons according e.g. to work arrangement. shows such acomparison between workers with a full-time, open-ended contract of employment andworkers with other contracts of employment (part-time, temporary, etc.). However, asteleworkers and workers with flexible working arrangements are not evenly distributed acrossgender, position in employment, qualification etc, third factors influencing the comparisonhave to be taken into account (see e.g. Table 7-4 in annex).

Table 4-39: Job quality (in %, EU 15)

stronglyagree

somewhatagree disagree DK total

I have a lot of say over what happens in my job 34.5 43.7 20.9 0.9 100I have concerns about whether my job is secure 18.0 21.5 60.0 0.5 100I have a high income 9.7 33.3 55.4 1.6 100Base: All persons employed (N=5,100), weighted by EU15 population. Source: SIBIS 2002, GPS


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Table 4-40: Overall job satisfaction (in %)

very somewhat somewhat verysatisfied

neithernor dissatisfied

DK total

1 2 3 4 5 mean SDAUSTRIA 43.5 45.1 7.3 2.0 2.0 - 100 1.74 0.84BELGIUM 41.6 44.3 6.5 5.8 1.1 0.7 100 1.80 0.88DENMARK 64.1 22.8 6.1 4.4 1.8 0.7 100 1.56 0.93FINLAND 25.5 60.8 8.9 4.6 0.2 - 100 1.93 0.74FRANCE 25.9 56.6 9.2 4.5 2.7 1.2 100 2.00 0.88GERMANY 31.1 52.3 11.4 4.2 0.6 0.4 100 1.90 0.80GREECE 22.1 48.3 23.9 3.4 1.5 0.8 100 2.13 0.85IRELAND 33.2 49.1 6.2 8.1 3.4 - 100 2.00 1.01ITALY 28.2 52.6 11.7 4.7 2.9 - 100 2.02 0.92LUXEMBOURG 38.4 45.2 8.5 7.3 0.6 - 100 1.86 0.89NETHERLANDS 51.3 39.6 6.2 2.3 0.6 - 100 1.61 0.76PORTUGAL 27.0 47.1 19.1 6.1 0.8 - 100 2.06 0.88SPAIN 36.1 45.4 12.5 4.9 1.2 - 100 1.90 0.88SWEDEN 37.3 56.8 2.3 3.0 - 0.5 100 1.71 0.66U.K. 34.0 44.2 8.9 9.1 3.9 - 100 2.05 1.07EU 32.7 49.5 10.4 5.2 1.9 0.3 100 1.94 0.90CH 53.2 36.1 4.3 1.0 0.5 4.9 100 1.52 0.69USA 46.2 36.7 5.7 9.3 1.9 0.2 100 1.84 1.02Base: All persons employed (N=5,901), weighted; EU averages weighted by EU15 population.


As a consequence, a multivariate analysis is required to single out the factors that influencework-family balance, job quality and job satisfaction. This analysis will use the followingvariables:

Dependent variables No. Independent variables No.Work stress h1_a Home-based teleworkExhausting work h1_b Mobile teleworkWork and family life h1_c, h1_d Discretion over working time h2_e, h2_fWork pressure h1_e Atypical employment atypicalSustainability of work and family h1_a to h1_e Lifelong learningPerceived high pay h2_d Check variables No.

Participation in decision-making h2_a Demography (age, gender,country) age, z21

Perceived job security h2_c Sector in19Job quality h2_a, h2_c, h2_d Social grade (esomar) esomarJob satisfaction h3 Household type


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4.4 Preliminary results of compound indicator calculation

4.4.1 Results of preliminary calculation

The statistical variables outlined in section 3.4 were used to calculate a ranking of countriesalong each indicator. For the benefit of comparability original indicator values were convertedinto standardised values with the country showing the highest value being assigned thebenchmark value of 100 (see Tables below). Each country was ranked according to itsperformance in each indicator. The values for each of the two indices were then calculated asthe mean of these ranks, resulting in two index values, one representing worker-centredflexibility and the other company-centred flexibility. In this first approach, single indicatorswere not weighted.

The country coverage was restricted to the 10 EU Member States for which data along allindicators could be made available (Denmark, Finland, France, Germany, Ireland, Italy,Netherlands, Spain, Sweden, United Kingdom).

The approach described, while being very tentative, has the advantage of being based ondata which is already available, and will be updated in regular intervals in the future. Resultscan necessarily only be preliminary, but we think that this effort is the best availablecompound measure on the development of ICT-related increases in labour market flexibilityyet.

Table 4-41 ranks countries according to their mean ranking in the eight variables representingworker-centred flexibility. The Netherlands, the benchmark with regard to voluntary part-timeworking and participation in decision-making, come out first, followed by the Nordic countriesSweden (the benchmark for lifelong learning), Denmark (the benchmark for job security) andFinland (the benchmark for discretion over working hours and home-based teleworking).Germany, Italy (the benchmark for teleworkability and job tenure) and the U.K. constitute themidfield, while Ireland, France and Spain clearly lag behind.

Table 4-41: Results - Index on worker-centred flexibility

Dimension TIME PLACE CONTRACT CONTENT

Indicator

Volu

ntar

y pa

rt-ti

me

wor

king

Dis

cret

ion

over

wor

king

tim

e

Hom

e-ba

sed

tele

wor

king

Tele

wor

kabi

lity

Job

secu

rity

Job

tenu

re

Part

icip

atio

n in

deci

sion

mak

ing

Life

long

lear

ning

Wor

ker-

cent

red

Flex

ibili

ty In

dex15

Cou

ntry

rank

Netherlands 100 77 60 99 94 79 100 72 6.63 1Sweden 44 75 79 76 87 95 88 100 6.13 2Denmark 46 82 67 73 100 70 98 96 5.88 3Finland 20 100 100 83 87 83 97 91 5.88 3Germany 44 82 22 93 88 85 75 24 5.13 5Italy 13 81 24 100 86 100 67 24 4.63 6U.K. 59 74 36 92 84 69 86 97 4.50 7Ireland 39 75 15 75 84 78 76 24 2.50 8France 33 63 18 85 77 93 80 13 2.38 9Spain 16 70 19 87 83 83 56 23 2.00 10

Table 4-42 ranks countries according to their mean ranking in the eight variables representingcompany-centred flexibility. Here, the country sequence is somewhat different. The U.K.

15 Inverse average rank of 8 benchmarked variables


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ranks best together with the Netherlands, followed by the Nordic countries. Italy and theGermany perform much worse compared to the worker-centred index.

Table 4-42: Results values - Index on company-centred flexibility

Dimension TIME PLACE CONTRACT CONTENT

Indicator

Part

-tim

e w

orki

ng

Aty

pica

l wor

king

hour

s

Mob

ile te

lew

orki

ng

Tele

-Coo

pera

tion

Empl

oym

ent

Prot

ectio

n in

Legi

slat

ion

Invo

lunt

ary

tem

pora

ryw

orke

rs

Man

agem

ent b

yO

bjec

tives

Empl

oyee

trai

ning

prov

ided

by

com

pany

Com

pany

-cen

tred

Flex

ibili

ty In

dex16

Cou

ntry

rank

U.K. 57 86 49 85 100 14 85 96 6.63 1Netherlands 100 72 100 90 58 39 96 84 6.63 1Finland 20 84 60 100 64 37 69 100 6.00 3Denmark 47 70 49 63 78 14 100 89 5.13 4Sweden 44 73 53 75 58 37 56 80 4.63 5Ireland 35 85 7 75 89 6 69 67 4.00 6France 31 83 19 53 42 43 71 47 3.50 7Germany 43 75 35 64 49 21 56 56 3.38 8Spain 16 100 12 48 40 100 67 36 3.00 9Italy 14 93 33 54 38 21 65 42 2.38 10

Comparing the results for both indices, we can distinguish between three groups of countries(in columns readers find the difference between both index values, where a positive valuemeans that the country ranks higher in average with regard to worker-centred flexibility, and anegative value indicates that it performs better with regard to company-centred flexibility):

ü The first group consists of countries that perform well in both indices: In particular theNetherlands (0.00) which are at the top of the rank in both indices, and also Finland (-0.12) and Denmark (+0.75). These EU Member States come closest to reaching the aimsof the European Employment Policy.

ü A second group is made up by countries who perform weak in both indices and includesFrance (-1.12) and Spain (-1.00). These are countries which still have a long way to gobefore they reach at least EU average levels of labour market adaptability.

ü A third groups contains countries that score high on the worker-centred index, but muchlower on the company-centred index: Italy (+2.25), Germany (+1.75) and Sweden (+1.50).In these EU Member States, flexibility on labour markets is distributed in favour ofworkers, while companies are in need of a more flexible regulatory environment.

ü The last group is made up by countries that score high on the company-centred index, butlow on the worker-centred index, and includes the U.K. (-2.13) and Ireland (-1.50). Inthese EU Member States, flexibility on labour markets benefits mainly employers.

16 Inverse average rank of 8 benchmarked variables


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5 Further developments

Indicator research in SIBIS focuses on indicators for which data can be obtained throughsurveys of the population and/or decision-makers in companies. Against this background, theproject has developed and piloted a number of indicators. First results with regard tofeasibility of the methodological approach chosen and the validity and reliability of the datahave been presented in this report. Conclusions of this work in terms of recommendations formodifications or application in existing regular surveys undertaken e.g. by the NSIs willbecome available from SIBIS in due time.

A number of indicators which were developed in SIBIS and described in D2.2 could not bepiloted for one or more of the following reasons:

ü The decision-maker survey was targeted, in larger establishments, at heads of ITdepartment or senior managers in IT departments17. Only questions which thisstakeholder group was likely to be able to answer could be put to them. For many labourissues, however, human resources managers would have been the only group able toanswer questions reliably.

ü Sample sizes in the pilot surveys were too small to allow for small subgroups of thepopulation be asked certain specific questions.

ü The number of questions which could be included in the survey had to be limited, whichresulted in the need to drop some issue from the questionnaires. Reasons for this were tobe found in aspects of overall questionnaire design including the risk of respondentfatigue in case of too long interviews. Of course, budget limitations also plaid a role.

In the following some of the gaps will be outlined which have not been covered by SIBISsurvey work, to draw attention to where further research outside of SIBIS is needed.

5.1 Skills

With regard to the acquisition of skills, formal education structures and concepts are in theprocess of being revised in the face of new requirements in the Information Society. Thisissue is dealt with in a separate report (“Education”). With regard to indicators on non-formaleducation and training (which are among the subjects of this report) there is a lack ofcommonly agreed concepts and appropriate standards. Indicators in this field must be able toencompass the whole variety of existing training environments to be found in present-dayreality. Moreover, the shifts away from state-provided towards company- and self-providedtraining, and from full-time education towards continuous supplementary education, have notbeen adequately represented in available indicators. SIBIS has piloted better a measure ofinformal learning, but to properly account for the shift from formal, full-time education settingstowards more informal learning environments, an in-depth survey only on this topic is needed,possibly making use of diary techniques.

The Eurostat Taskforce on Lifelong Learning stresses that there is an urgent need forindicators measuring intangible investments in training activities by companies. Ultimately,though, the data derived from company surveys and the like will only be truly comparablewhen a classification of learning activities (including informal learning) has been agreed upon.Data on intangible investments by companies "may provide the link for measuring return toinvestment in learning by enterprises” (14). This relates to message 4 of the Memorandum onLifelong Learning which asks for significant improvements "in the ways in which learningparticipation and outcomes are understood and appreciated, particularly non-formal andinformal learning". Data will have to come from surveys of HR managers in companies.

ICT-related learning, e.g. acquiring the skills to master ICTs for certain purposes, has alsobeen undergone a transformation. Younger generations receive most of their skills in using

17 This decision was taken in order to maximise the number of issues for which data could be gathered in each

establishment, without having to change the respondent which is usually to be avoided for feasibility reasons.


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ICTs from every-day usage and learning-by-doing, while older generations tend to need moreformal training. Therefore, it has become harder in general to distinguish ICT-related learningactivities from other learning, as ICTs penetrate every sphere of our lives. Indicators in ICT-related learning may therefore only be useful for a limited number of years, after which alllearning will have a string ICT component.

Time use surveys seem to be an interesting proposition for measuring informal as well asformal learning activities, but have the disadvantage of being very expensive. It could beuseful, however, to integrate features of time use surveys into general population surveys togather data on these issues.

A simple indicator on e-Learning has been piloted in SIBIS. Following on from this, a morecomprehensive analysis of the use of ICTs for learning and training purposes should beundertaken.

Although the individual is maybe the best source of information on the acquisition of skills, asthe Eurostat Taskforce on Lifelong Learning suggests, additionally subgroups of the generalpopulation such as individuals in institutions (employees in companies, teachers/trainers ineducation organisations) should be addressed by specialised surveys, too.

The provision of skills (i.e. the supply of skills on the labour market) has been at the centreof a public debate on the shortcomings of today's education systems. Data on educationalattainment, e.g. on the intensity of certain professions in the graduate output, are readilyavailable (although comparability between countries suffers from national differences ineducation systems and curricula). However, data on IT-skills in not directly ICT-relatedprofessions (non-specialist ICT skills of students) is scarce. A survey specifically targeted atstudents may help out here.

With regard to skill requirements, EU policy-makers until now have to rely on proprietarydata provided by IT consultancies such as IDC, as other available data are limited tovacancies unfilled statistics provided by Public Employment Services (PES), and nationalsurveys of companies. PES data are not available for cross-country comparisons because ofdifferences in employment regulation. They also do not allow for an exact assessment of skillrequirements, as data is only provided along occupational categories that do not adequatelyreflect the variety of IT-related skills to be found in reality. An EU-wide survey on skillrequirements seems all the more pressing since Europe is competing with other trade areason the global market for scarce IT skills, whereas national markets for high-qualifiedpersonnel gradually lose relevance.

5.2 Work and work organisation

With regard to work content, changes in working methods that have been enabled by theuse of ICTs have attracted much less attention. This is unfortunate, as the focus on IT toolsmay cover up large differences in the way these new technologies are used, and in impactson employee's control over their work contents. Another area which is not properlyrepresented in statistics are changes in the division of labour, which are related to the often-mentioned concepts worker empowerment and job enrichment.

In comparison, changes to the time-related organisation of work are much better coveredby available statistics. There is the danger that, in the middle term, some of these indicatorswilll have to be redesigned if currently still common terms such as 'full-time' and 'part-time'loose their relevance in favour of a continuum of contractually fixed working hours per week,or variable numbers of working hours according to the needs of the worker or the employer.For the collection of time-series it is therefore advisable to use intensity indicators which use acommon measure (e.g. average hours worked per week) and do not rely (as for example theEuropean Labour Force Survey (LFS) still does) on the subjective judgement of therespondent.

Data on the location or place of work becomes harder to obtain because of the increasingvariability of working locations, and the speed with which “anytime-anywhere” technologies


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are spreading through the economy. Telework definitions need therefore to be adaptedcontinuously if the phrase is not to loose any relevance. Moreover, the intensity approachdeveloped in SIBIS for measuring home-based teleworking needs to be extended to otherICT-based new ways of working such as mobile telework.

The contractual dimension of work organisation concerns, in particular, shifts betweendifferent types of employment, i.e. between self-employment and dependent employment andbetween temporary and open-ended work contracts. These refer to the formal contractbetween worker and employer/client. The data situation in this respect can be regarded asbeing good, although there are problems associated with the statistical representation ofseemingly self-employed workers. Moreover, the category 'self-employed' encompasses alarge variety of own-account workers as well as business owners which have not much morein common than the fact that they are not formally working for somebody else. Existingindicators have also not been able to fully explain the reasons for differences in thedevelopment of self-employment between countries.

Also missing are reliable, cross-country data on more flexible types of compensation,especially contracts which include performance-related pay components.


The third domain (structure and outcomes of employment) encompasses two distincttypes of indicators; on the one hand indicators that measure macro-economic constructs suchas unemployment, employment in different economic sectors, developments in productivityetc.; on the other hand indicators on the personal benefits (and detriments) from employment.

For a better statistical representation of employment in IT-related sectors and occupations,further development of the relevant classifications NACE and ISCO are required. Many of thecategories in these classifications do not anymore adequately reflect the structure ofeconomic activity in reality.

Quality in work is traditionally measured based exclusively on pay, and maybe hours of work,as reflected in the European Community's structural indicators. However, research based onpersonal experiences of workers themselves has shown that pay is by far not considered tobe the most important aspect of a job (Clark 1998). Rather, job security, an interesting job,and promotion opportunities are ranked highest. Therefore, an assessment of quality in workin the EU has to acknowledge these aspects, too.

As "concerns about job quality are [...] strongly related to concerns about labour marketsegmentation and social exclusion" (EC2001emp: 66), data on work quality must includeindicators that measure disparities between groups of workers in countries, e.g. by breakingdown data according to the skill level of jobs.

Data on the immaterial benefits of employment, as well as detriments such as negativehealth effects, are available on a time-series basis, mainly from the International SocialSurvey Programme (ISSP) and a survey on employment options of the future conducted bythe European Foundation. Recently, supplements to the regular twice-yearly Eurobarometersurveys have also delivered data on this issue. It would be highly welcome if time-series dataon a short interval basis would become available through these sources soon. The next stepshould be to break down the data on these variables to account for differences betweenvarious types of work and, in particular, between people engaged in new ways of working andtraditional workers. The same applies to material benefits of employment, i.e. payments andother compensations. For this, large enough samples will be needed.

Measuring satisfaction is very difficult because results show a strong dependence on theinterview context (e.g. type of interview, preceding questions, interviewer characteristics). Itrequires advanced control over the interview situation. This has to be taken account whenassessing existing indicators, e.g. on job satisfaction of different types of workers, anddesigning new surveys. For this reason, time-series data on satisfaction indicators has to beapproached with care.


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Indicators measuring outcomes at the aggregate level, i.e. the level and structure ofemployment, are plenty. Researchers that want to calculate correlations between changes inthe fabric of the EU economy and labour market effects have many indicators at theirdisposal. Problems with regard to the ability to map Information Society developments withthese data stem mainly from the lack of appropriate sectoral and occupational standards.Both data on sectors and occupations are still heavily biased towards the status quo of theindustrial age. Service sectors are underrepresented in statistics; likewise, serviceoccupations. This poses the danger that changes in the sectoral structure of the economy arenot recognised early enough, or are misinterpreted.

With regard to indicators on employment and unemployment, information on the compositionof the labour reserve need improvement. The European Union will not be able to reach itsambitious goals regarding the increase of employment levels, especially among women, if itdoes not exploit all opportunities for tapping the labour reserve. This requires better indicatorson the characteristics of the not working population, especially skills and personalpreferences. The European Foundation's survey on work options of the future can act as agood example in this respect, but it is not expected to be repeated, i.e. no time-series data willbe available. Additionally, the problems facing EU Member States with regard to the scarcityof IT-related skills requires to take advantage of unused skills in the labour force, to bettermatch demand and supply of skills. Underemployment indicators are, therefore, of highrelevance to EU decision making. Existing underemployment indicators have only begun toreflect the issue. More advanced indicators need to be developed.


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6 Conclusions

A number of conclusions can be drawn from the results of the SIBIS pilot survey and from theother data analysed for this report. There is still a lot of uncertainty and confusion about thedirection and intensity of developments with regard to ICT-enabled new ways of working. Thisis partly caused by inadequate indicators being used for analysis, or by the lack of availabledata on the present situation (not to speak of time-series data). SIBIS research on work,employment and skills intends to shed light on some of the related issues, for which onemethod is the development and piloting of an own set of indicators.

In the field of skills in the Information Society, the issues Lifelong learning and IT-relatededucation and training are the most pressing issues for which indicators are required. Theacquisition of skills increasingly takes place throughout the working life as opposed to thetraditional model in which it precedes the entry in the labour market. The more training andlearning takes place in non-formal and informal settings, the harder it is to measure. Eurostatprovides data on basic indicators such as participation in training activities which is based ondata from the Community Labour Force Survey (LFS). However, the results appear to be notentirely valid as the survey instruments used by the NSI’s for this survey use widely divergingconcepts and terminology, in spite of EU regulation which set down common guidelines.Results from the SIBIS pilot survey in which the EU labour force was asked whether theyparticipated in work-related training provided by their employer or another organisation, orpractised self-directed learning which was related to their work, suggest that the extent towhich lifelong learning is practised is underestimated by the LFS data. Moreover, comparisonbetween countries arrives at a different result with regard to relative performance of MemberStates if compared to the LFS data.

The SIBIS data suggests that the skills gap between the current workforce and theunemployed is going to widen because of the extent to which persons in employment areengaged in company-provided training, learning by doing and also self-directed learning. Itseems that the training provided by the state to the unemployed cannot make up for theprovision of learning opportunities companies supply to their staff.

Further research on indicators is necessary to develop tools for measuring the intensity ofnon-formal and informal learning activities. This is likely to require in-depth surveys such astime-use studies.

The fast-moving universe of ICT applications presents one reason why the labour force, andpeople in general, need to learn continuously. But ICTs also provide one of the possible toolswith which to face this challenge, as they can make the provision of learning content andlearning environments easier. These so-called eLearning technologies comprise offlineapplications such as learning programmes on CD-ROMs as well as online applicationsusually transferred via the Internet or company/university-internal computer networks. About15% of the EU labour force are making use of eLearning for work-related training, two third ofwhich already use online applications.

ICT user skills can be provided via more or less formal training measures but experienceshows that in any case, user experience is needed. This is usually being acquired throughregular working with these applications as a working tool. An important indicator, therefore, isthe share of the workforce which has access to ICTs at their working place. SIBIS data showsthat between 40% (Greece) and 91% (Finland) of EU employment is in companies whichgrant their staff free access to the Internet. The commitment with which Finnish companies lettheir employees use e-mail and surf the Net can be assumed to be one reason for thesuccess of the country in the European information economy.

The provision of IT skills (“digital literacy”) on the labour market is difficult to measurebecause direct assessment (which could deliver the best results) is extremely expensive andtime-consuming. Self-assessment is another possibility, but it requires careful testing of theinstruments used. The results of piloting the SIBIS module on self-assessed digital literacyare discussed elsewhere (see SIBIS report “Education”).


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The demand for IT skills is comprised of demand for IT specialists and demand for IT skills ofnon-specialists. The main work to be done in this area is harmonisation of existing conceptsand terminologies which are being used in national studies on the issue, which would preparefor the required pan-European survey on IT skill requirements. Such a survey is needed tosupport EU policy-makers in their search for the right strategy on IT skills provision.

Just as the conditions for skill acquisition, supply and demand have changed as a result ofICT-related change, ICTs have also strongly affected the way work is organised in time andspace and with regard to content and contractual basis. These changes are of a more generalnature which means that indicators for measuring work organisation in the InformationSociety cannot restrict themselves to directly ICT-based ways of working, but should coverthe broader developments towards more flexibility in work settings which have been at thecentre of analysis of labour market research in recent years.

Among these, the flattening of organisational hierarchies combined with the shift frommanagement by eyeball to management by objectives are two hypothetical developmentswhich are of central importance. Adequate indicators for these include participation indecision-making and discretion over the order of tasks, methods of work and speed or rate ofwork. Comparing EU countries using data from the European Survey on Working Conditionsshows that a larger than expected share of the workforce may already be described as beingmanaged by objectives, even in less developed EU countries such as Greece (33%) andPortugal (39%).

There are bigger variations between European countries with regard to working hours. UsingCommunity Labour Force Survey data reveals that not only do some countries have a muchhigher share of part-time workers than others (the Netherlands have 41%, Greece only 5%),there are also huge differences in the ratio of voluntary to involuntary part-time employment.Whereas in the Netherlands almost all part-time employment is voluntary, in Finland forexample one third of part-timing takes place involuntarily. This findings indicates that part-timeemployment should not be understood per se as flexible employment, at least not from theworker’s point of view as it might just be a poor substitute for full time jobs.

For measuring flexibility, voluntary part-time work seems to be the more appropriate indicatorfour our purposes. Another important indicator is the degree to which employees can adaptworking times to individual preferences and schedules (inside of working contracts with agiven number of working hours per week). The latter indicator has been piloted as part of theSIBIS GPS. According to this data, 49% of the EU workforce can adapt their daily starting andfinishing times to their own preferences, while 40% can adapt the number of weekly workinghours.

Telework and tele-cooperation have been identified as areas in which existing indicators(such as those which were used for the eEurope 2002 benchmarking exercise) are notadequately representing the nature of ICT-enabled changes to working locations. SIBISdeveloped a questionnaire module for measuring telework and tele-cooperation whichaddresses the short-comings of previous cross-country comparisons.

The results clearly show that telework has many different faces, of which traditionalteleworkers who spend a major share of their working time at home represent only one, andmaybe not even the most significant, facet. 7% of the EU workforce are practising home-based telework. This indicates that the share of EU population participating in the labour forceis considerably higher than it would be without the possibility for telework – an importantcontribution to the European Employment Policy’s goal of increasing labour marketparticipation throughout the EU.

The most important effect of telework, however, seems to be to make workers more efficientand effective by granting them greater flexibility in how to organise their work. Mostteleworkers use their home not for working full days (only 2% of all persons employed spendat least one full working day per week at home), but for supplementary teleworking. Thismeans that they work only some hours per day at home, but still commute to a moretraditional working environment for the brunt of their work. The home becomes a touch-downoffice, which is equipped for giving online access to company resources whenever needed,but it is in most cases not being used for full working days.


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Preliminary results from a comparison with data from the 1999 ECATT survey even suggestthat the share of the EU workforce which practises permanent or alternating telework withmore than one full day per week spent at home is actually stagnating while the number ofsupplementary teleworkers is growing fast. This finding indicates that more and more peoplemake use of the locational flexibility offered by ICTs and spend some working time at home,but only comparatively few stay whole days at home. The number of tele-workplaces (in thetechnical sense of a networked workplace installed permanently or temporarily in the home) isincreasing at a rapid rate, but the number of persons working at home at any given point intime remains modest. The location of work becomes more footloose, but there is no generalshift of work from the office into the home.

The reasons for this are only partly extractable from the data, but the perceived need for face-to-face interaction with colleagues, customers or other persons certainly plays a key role. Still,about one quarter of all jobs are considered feasible for alternating home-based teleworkingby their holders, more than 10 times the number of actual people teleworking in this way.Together with the high degree of interest expressed by the labour force in telework, thesefigures suggest that the demand for telework is much higher than the supply provided byemploying organisations. More and more companies prove willing to give their staff remoteaccess to their computer network, but the acceptability of staff working from home whole daysseems to be limited.

This trend is complemented by the strong increase in mobile teleworking, i.e. the use of onlineconnections for work purposes during business trips. Here again, the technology is being putin place and increasingly used. The share of mobile teleworkers has grown from 1.5% to 4%in the course of only three years. This is likely to benefit employers, as the efficiency ofbusiness process increases because of more continuous communication flows. Self-employed teleworkers in SOHOs, many of which are freelancers, are also becoming muchmore numerous as tele-mediated communication with clients and work partners opens upnew possibilities for improving business performance. While the share of SOHO-basedteleworkers in the EU was only 1% in 1999, it is more than 3% in 2002 as a result of annualgrowth averaging more than 50%.

From these observations we can follow that most telework today takes place in flexiblesettings, with the home acting as only one of a bigger number of options for work locations.Consequently, the number of mobile teleworkers is likely to outnumber home-basedteleworkers soon. These trends should be reason enough to rethink some of the originalassumptions about telework and how it will affect society. Telework seems to be part of ageneral move towards greater variability and flexibility of the way work is organised, and isbeing implemented in ways that are believed to maximise the effectiveness and efficiency ofthe work process. With regard to home-based telework, the highest return seems to bebelieved to come from equipping workers with tele-workplaces, but keeping them at thecentral office location for most of their working time.

Telework is usually singled out as the most significant ICT-related development with regard toworking locations but tele-cooperation, i.e. the use of the data transfer, e-mail and the Internetfor contacts between workplaces at geographically distant locations, is bound to play a biggerrole in shaping the way the majority work, as it affects already more than two third (38%) ofthe EU workforce. We can understand tele-cooperation as making use of ICTs to enable newconfigurations of labour without actually having to move workers from one place to the other.Its attractiveness stems from the fact that labour is well-known to be geographically veryimmobile (in comparison to capital as the other major factor of production), so every newpossibility to transmit products of work between locations of production without movingworkers themselves is welcomed by industry. Indicators which explore tele-cooperation inmore depth will have to be developed in the future.

SIBIS research on work, employment and skill also included an assessment of the degree towhich the self-employed make use of so-called e-lancing practises to conduct their business.In the narrow sense of the term, e-lancers are freelancers who “work on the Net”, i.e. carryout all communication with others (supplier, work partners and associates, clients andcustomers) through the Internet or other computer networks. For survey research, and basedon the assumption that e-lancing in the narrow sense of the term is still extremely seldom,


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SIBIS defined three different degrees of e-lancing using the variables a) attracting newbusiness online b) delivering work results online and c) communicating exclusively viaelectronic means. 9% of the self-employed in the EU communicate at least sometimesexcusively via electronic means with their clients, thus may be called (occasional) e-lancers.The share is much higher in the U.K. (18%) and the USA (14%) which appear to be headingthe freelancer movement onto the Internet according to the results from the pilot survey.

The structure of IT-related employment can been measured using data from the CommunityLabour Force Survey which follows the NACE and ISCO-88 classifications. According tocalculations from the EMERGENCE project, the share of employment in IT occupations(ISCO 213, 312, 313) in the EU lies between 0.6% (Greece) and 3.2% (Netherlands), withdata for Ireland missing. Employment in IT sectors is highest in Ireland with 2.9% of the totalworkforce.

The effect of telework and other new ways of working on dependent variables on outcomesof employment such as job quality, job satisfaction and the balance between work and familyhas until recently almost exclusively been explored via case-study based research. Thismeans that the degree to which research results are representative for the entirety of atypicalworkers is unknown. There are many reasons to assume that the choice of workers for casestudies is highly selective. Representative studies which are based on representativeprobability samples of the entire adult population (such as the SIBIS pilot GPS) are thereforeneeded. After finishing multi-variate analysis of the survey data (which is currently ongoing), anumber of indicators which compare work outcomes at the personal level between traditionaland new ways of working will be operationalised in detail.

In order to aggregate the findings from a large number of indicators (some of which havebeen presented in this report) it may be advisable to construct compound indicators whichadequately represent complex constructs. SIBIS research on work has developed two suchindices based on data from a number of sources, namely the index on worker-centredflexibility and the index on company-centred flexibility. They rest on a conceptual frameworkwhich stresses the need to distinguish between on the one hand flexibility for workers toadapt ways of working to personal requirements and preferences and on the other handflexibility for companies to deploy labour according to business objectives. The selection ofcomponent indicators was not derived using statistical methods, but through consensus-building involving policy-makers at the EU and nation state level, and was informed by thecurrent objectives of the European Employment Policy. While data availability from time-series sources is still a major problem for such index-building, the results of the exercise pointtowards significant differences in the distribution of flexibility between both supply anddemand side of the labour market.


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7 ANNEXES

7.1 Annex I: Additional Tables

Table 7-1: Lifelong learning – Eurostat indicator based on Member States’ LFS (in %)

1995 1996 1997 1998 1999 2000 2001AUSTRIA 7.7 7.9 7.8 n.a. n.a. n.a. n.a.BELGIUM 2.8 2.9 3.0 4.4 6.9 6.8 7.3DENMARK 16.8 18.0 18.9 19.8 19.8 20.8 17.8FINLAND n.a. 16.3 15.8 16.1 17.6 19.6 19.3FRANCE 2.9 2.7 2.9 2.7 2.6 2.8 2.7GERMANY n.a. 5.7 5.4 5.3 5.5 5.2 n.a.GREECE 0.9 0.9 0.9 1.0 1.2 1.1 1.4IRELAND 4.3 4.8 5.2 n.a. n.a. n.a. n.a.ITALY 4.0 4.4 4.9 4.8 5.5 5.5 5.1LUXEMBOURG 2.9 2.9 2.8 5.1 5.3 4.8 5.3NETHERLANDS 13.1 12.5 12.6 12.9 13.6 15.6 16.3PORTUGAL 3.3 3.4 3.5 3.0 3.2 3.3 3.3SPAIN 4.1 4.2 4.2 4.1 4.9 4.9 4.7SWEDEN n.a. 26.5 25.0 n.a. 25.8 21.6 n.a.U.K. n.a. n.a. n.a. n.a. 19.2 21.0 21.7EU n.a. 5.7 5.8 n.a. 8.2 8.4 8.4Base: Total population at working age Source: Eurostat 2002, Labour Force Survey

Table 7-2: Participation in any work-related learning in last 4 weeks (in %, EU15)



part-time contract 37.7 62.0 0.3 100full-time contract 45.9 53.9 0.2 100temporary contract 37.4 62.4 0.2 100

Self-employed 38.7 61.0 0.3 100working part-time 39.5 60.5 - 100working full-time 38.4 61.3 0.3 100



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Table 7-3: Use of online eLearning for work-related training (in %)

Base: Labour force Base: All who participated in work-related training

yes no DK yes no DK totalAUSTRIA 10.3 89.2 0.6 18.4 80.5 1.1 100BELGIUM 6.6 92.3 1.1 20.0 76.7 3.4 100DENMARK 11.6 88.1 0.3 25.7 73.7 0.6 100FINLAND 15.9 84.1 - 26.6 73.4 - 100FRANCE 3.5 96.4 0.1 14.6 85.1 0.2 100GERMANY 13.4 86.4 0.2 22.9 76.8 0.3 100GREECE 1.7 98.3 - * * * 100IRELAND 9.0 91.0 - 25.7 74.3 - 100ITALY 8.0 91.8 0.2 21.4 78.2 0.5 100LUXEMBOURG 9.5 89.1 1.4 17.9 79.4 2.7 100NETHERLANDS 9.1 90.7 0.2 19.6 79.9 0.5 100PORTUGAL 5.5 94.5 - 23.0 77.0 - 100SPAIN 7.3 92.5 0.2 21.8 77.6 0.6 100SWEDEN 14.3 85.7 - 30.4 69.6 - 100U.K. 12.7 87.1 0.2 31.4 68.1 0.5 100EU 9.5 90.3 0.2 23.1 76.5 0.5 100CH 9.6 90.4 - 19.7 80.3 - 100USA 17.0 82.9 0.1 29.9 69.9 0.2 100Base: labour force (N=6,604); all who participated in work-related training in last 4 weeks (N=2,677)weighted. EU average weighted by EU15 population. Source: SIBIS GPS

Table 7-4: Sustainability of work and family life according to job position (in %, EU 15)

Share stating “ often”How often do you... Employed

pro-fessional

Manage-ment

Othernon-

manualemployee

Manualworker All

... find your work stressful 40.2 35.6 28.9 31.6 31.9

... come home from work exhausted 37.2 34.5 28.4 33.0 31.6

... find your job prevents you from giving thetime you want to your partner or family 27.4 29.2 19.0 21.8 22.3

... feel to tired after work to enjoy the thingsyou would like to do at home 25.8 29.0 20.8 25.5 23.8

... find your partner/family gets fed up withthe pressure of your job 14.8 12.0 8.2 11.3 10.4

Base: All persons with a contract of employment (N=4,274), weighted by EU15 population.Source: SIBIS 2002, GPS


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Table 7-5: Job quality according to job position (in %, EU 15)

Share “ strongly agree”

Employedpro-

fessionalManage-

ment

Othernon-

manualemployee

Manualworker All

I have a lot of say over what happens in myjob 34.7 52.6 30.6 28.4 34.4I have concerns about whether my job issecure 21.0 14.0 16.1 23.1 18.0I have a high income 12.7 20.5 7.1 5.7 9.8Base: All persons with a contract of employment (N=4,274), weighted by EU15 population.


7.2 Annex IV: Explanation of Indices

In this section, the rationale for selecting indicators for the indices on worker-centred andcompany-centred flexibility listed in chapter 3.4 (see also Tables below) is presented.

Table 7-6: Indicators for measuring worker-centred flexibility of work arrangements

Dimension Indicator Preliminary sourceTime Voluntary part-time working Community Labour Force Survey

(quarterly)

Time Temporal autonomy in job ECaTT (1999)

Place Home-based teleworking (excluding self-employed)

ECaTT (1999)

Place Teleworkability ECaTT (1999)

Contract Job security International Social Survey Programme(1997); Eurobarometer 44.3 (1996)18

Contract Average job tenure OECD (1999)

Content Share of population aged 25-64participating in training (lifelong learning)


Content Participation in decision-makingconcerning changes at workplace

European Survey on Working Conditions(2000)

7.2.1.1 Dimension: Time

Flexitime, part-time work and credit time arrangements are only three examples of a declaredgeneral move away from stability in working times (the so-called 9-to-5 job) towards modelsthat are supposed to be more in line with the requirements of business in increasingly volatilemarkets, as well as the personal preferences of employees. Flexibility in this regard can takethe basic forms of:

ü more flexible choice of regular working time per day, month, year, etc.;ü more flexible choice of the distribution of working hours across daytime, week, months,

etc.;ü greater working time variability (which might be attuned to the demands of business, e.g.

shift work, or to the preferences of workers, e.g. flexitime).

18 Only satisfaction


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Part-time working is in general considered to be one of the most visible of developmentstowards greater flexibility in working arrangements (EC 2000EiE: 29-42). The specification ofthe hours worked may originate in preferences of the worker, the company, or both dependingon the overall labour market situation (e.g. unemployment rates) and business imperatives.Government such as in the Netherlands have developed a strategy of promoting part-timeworking with the attempt to reduce unemployment rates and offer work opportunities to thosenot able to work full-time (especially women). In contrast, some Nordic countries such asSweden and Denmark have explicitly sought to convert part-time jobs into full-time jobs as ameans of gender mainstreaming (Hoffmann and Walwei 2000).

This shows that, from a worker-centred point of view, caution should be taken beforeinterpreting high levels of part-time work as a sign of labour market adaptability as it can be asign for the incapability of an economy to provide enough full-time jobs. In fact, the majority ofEU workers consider the level of job security to be lower in part-time in comparison to full-timearrangements (Gasparini 2000). For this reason, a more accurate indicator of worker-centredflexibility would be the rate of voluntary part-time work.

The other major aspect of worker-centred time flexibility is temporal autonomy, i.e. the extentof discretion over working times. The most prominent model involves a core daily workingtime, around which individual working hours can be arranged according to individual orcompany requirements. More advanced models have shed the core working time altogether.Flexitime models, like part-time working, are supported by ICTs through improvements inmanagement and monitoring technology, and more powerful asynchronous communicationmedia such as e-mail and voice mail which have liberated routine communication andworkflow in organisations from the dependence on face-to-face interaction (and, byimplication, fixed working times). Discretion over start/finish of working day was selected asindicator because other models (such as freedom to choose days worked per week or monthsworked per year) are much less widespread.

7.2.1.2 Dimension: Place

The distance-bridging properties of ICTs increase the ‘spatial flexibility’ of companies as wellas workers: Technically it becomes possible to choose locations for work processes morefreely. The location of work becomes variable in the short term, whereas it was practicallyfixed in the short and medium term before. This makes them more adaptable to changes intheir environment. To varying degrees, companies have made use of this new freedom tochange the geography of work, while workers demand to work where they want to as theneed for co-location appears to be gradually diminishing. One practical outcome of increasedlocational flexibility at the level of the individual work arrangement is telework, which can takedifferent forms: home-based (in the home of the worker), mobile (on business trips or in thefield) or, much more seldom in practice, centre-based (in a centre which is located to savecommuting time).

Home-based telework is today implemented mostly in a worker-centred way (EC 2001stat), inparticular with the aim to improve the compatibility of work and family life and to keep highlyproductive knowledge workers happy. It is therefore selected here as an indicator for worker-centred flexibility. As telework is still not very widespread in the EU yet but believed toexperience considerable growth in the near future (Gareis and Kordey 2000), an additionalindicator included in this index is teleworkability which represents the share of the workforcewhich could, in principal, telework from home at least one day per week. The inclusion ofteleworkability ensures that not only the current state, but also the "technical" potential forfurther diffusion of home-based telework in a country is taken into account.


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7.2.1.3 Dimension: Contract

This dimension refers to the contract that underlies the relationship between worker and theorganisation that utilises the work products, e.g. a contract of employment or acontractor/client-relationship that is based on self-employment.

The worker-centred perspective on the flexibility of a working arrangement is almostdiametrically opposed to the company's view. While a permanent employment relationshipmight mean rigidity from the company's standpoint, it means - in the absence of forced labour- something completely different for the worker: the freedom to look out for an otherappointment while enjoying the security which comes from holding a job. A worker-centredflexibility index must, therefore, include measures on job security to take account of the factthat flexibility in working arrangements is only recognised as such by workers if it is combinedwith some provision of safety.

For this reason, SIBIS included two measures of job security in the worker-centred index.Unfortunately, data from the International Social Survey Programme on the share of theworkforce who claim that their job is secure is available only for a number of EU MemberStates, and not up-dated frequently enough. As an alternative SIBIS uses data fromEurobarometer which measures the satisfaction with job security of respondentsrepresentative of the EU labour force. The second indicator selected is the average jobtenure. In country comparisons, a higher average job tenure indicates that workers have ahigher likelihood of staying with the same employer than in other countries, which was foundto correlate positively with the perception of job security (Clark 1998).

7.2.1.4 Dimension: Content (applied skills)

The skills workers apply in the production process define the content of their work (and viceversa). Work content has been hugely affected, in particular, by the increasing‘informatisation’ of work and by technological progress related to ICTs.

Continuous learning affects workers as well as companies, with the difference that workersmust be concerned about their employability while companies must manage the skills in theirstaff to support the production process now and in future. The fact that skill requirementstoday change over shorter durations means that workers cannot rely on being able to markettheir skills once they have acquired them in their youth throughout their lifetime. Rather, theyhave to constantly adapt their skills to the demands of the labour market, i.e. practice ‘lifelonglearning’ even while they are holding a job. Life-long learning boosts employability andtherefore provides workers with the flexibility of choice on the labour market.

Available data on lifelong learning measures is scarce. For our purpose, the most adequateindicator is the share of the population of employable age (but excluding persons in initial full-time education) who take part in education and training (including self-directed learning). Forthis data is provided by the Community Labour Force Survey.

The last indicator that went into this index on worker-centred flexibility is participation indecision making, again derived from data collected through the ESWCs. Workers have aninterest in keeping some degree of control over changes to their working conditions;otherwise flexibility is something imposed on them, potentially to their disadvantage.Participation in decision making is therefore a vital ingredient in an index that tries to presentflexibility of working arrangements from the viewpoint of workers.


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7.2.2 Index on company-centred flexibility

Table 7-7: Indicators for measuring company-centred flexibilityDimension Indicator Preliminary sourceTime Part-time working Community Labour Force Survey

(quarterly)Time Workers with atypical working times

(evening, night, weekend work andworking long hours) (ESWCs)


Place Tele-cooperation (ECaTT) ECaTT (1999)Place Mobile teleworking (ECaTT) ECaTT (1999)

Contract Employment Protection LegislationIndicator (OECD)

OECD (1998)

Contract Workers with temporary work contracts(excluding voluntary and contracts fortraining) (LFS)


Content Employees who have had trainingprovided by employer (past 12 months)(ESWCs)


Content Management by objectives (ESWCs) European Survey on WorkingConditions (2000)

7.2.3 Dimension: TimeFrom the company-centred view, every part-time worker increases the supply of workerswilling to work flexible hours, so the appropriate indicator here is the share of all part-timeworkers in a national workforce.

Apart from part-time jobs, companies show much interest in non-typical working times to getworking hours in line with production and service schedules. While traditional shift-working inmanufacturing is declining (in absolute numbers) together with the decreasing workforceemployed in these sectors, it is being extended to sectors where it has been non-existentpreviously (Brewster et al. 1997). Workers who are deployed at the front-office, i.e. havedirect contact with customers, are the first to be exposed to the requirements resulting fromextended opening hours and 24 hours a day, 7 days a week customer service strategies. InSweden and Finland, which are among the EU Member States with the highest share ofemployment in the service sector, there are already more women than men engaged in shift-work. Indeed, workers with "atypical working times" (the indicator chosen for inclusion in theSIBIS index) constitute already the majority in all EU Member States.

7.2.3.1 Dimension: Place

Mobile telework, one major type of spatial flexibility, is mostly implemented on the initiative ofthe company with the aim to move workers closer to customers (Gareis and Kordey 1999).The increase in the number of mobile workers is due to sales staff (and other employees whotraditionally work in the field) being equipped with remote access technology, and also due torising numbers of office workers who spend a high share of their working time on businesstrips for the purpose of meeting co-operating partners.

Mobile telework is chosen here as an indicator for company-centred spatial flexibility, togetherwith tele-cooperation has become the common working mode for an increasing share ofworkers. Tele-cooperation is sometimes also called ‘in situ telework’, because, althoughworkers appear to be co-located in central office buildings, in fact they are often workingclosely together with project partners at far away locations. Evidence suggests that tele-cooperation has boosted worker productivity and innovative performance throughout the EUeconomy by allowing flexible configurations of human capital without actually moving people


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from one place to the other (Reichwald et al. 1998). Data for all of these variables comes fromthe 1999 ECaTT survey conducted in 10 EU Member States.

7.2.3.2 Dimension: Contract

This dimension refers to the contract that underlies the relationship between worker and theorganisation that utilises the work products, e.g. a contract of employment or acontractor/client-relationship that is based on self-employment. Differences in the duration ofemployment contracts affect average job tenure.

As the first indicator for the company-centred view of this dimension, SIBIS uses theEmployment Protection Legislation Indicator developed by the OECD. This indicator wasdeveloped to be able to compare the effect of regulatory labour market regimes betweencountries. Main ingredients are subindicators measuring procedural requirements for layingoff workers; notice and severance pay; prevailing standards of and penalties for ‘unfair’dismissals; ‘objective’ reasons under which a fixed-term contract could be offered; themaximum number of successive renewals of fixed-term contracts; and the maximumcumulated duration of a fixed-term contract (Nicoletti et al. 2000: 41). According to thisindicator, countries such as the United Kingdom and Ireland, but also Denmark, are thosewith lowest levels of employment protection regulation while France, Italy and Spain providethe most stringent regimes.

One way for companies to deal with stringent labour market regimes is to look for alternativework arrangements that are not subject to the same regulation as regular employmentrelationships, e.g. fixed-term contracts. For this reason SIBIS selected the share of workerswith temporary (fixed-term) work contracts as an additional indicator for measuring thecontract dimension in the SIBIS index. For meaningful comparison between countries, the rawfigures from the Community Labour Force Survey need to be adapted to account for so-calledvoluntary temporary workers, most of which are persons who hold contracts for training (e.g.apprenticeships, vocational training).

7.2.3.3 Dimension: Content (applied skills)

To identify adequate indicators for company-centred flexibility with regard to this dimension, alook at some trends in business theory and human resource management is helpful. The keymessage of many of these (e.g. business process re-engineering) is that companies have toabandon of activities that do not create any value for customers. As a consequence,successful companies have flattened organisational hierarchies so that more responsibilityand decision power can be decentralised and handed over to the (groups of) individuals whoare actually carrying out the work and who are much better acquainted with the needs ofcertain jobs. If such decentralisation is to be made to work, employees need to be trainedcontinuously. This is also a logical consequence of the impact of ICTs which have shortenedskill life cycles enormously. SIBIS chose "employees who have had training provided by theiremployer" as indicator representing the extent to which a country's company's have acceptedthis challenge.

Decentralisation also means that management styles change: from the traditional"management by eyeball" to "management by objectives" techniques that rest on themonitoring of results instead of behaviour. No indicator on the spread of management byobjectives in EU Member States is readily available. As a supplement, SIBIS constructed anindicator from variables included in the European Survey on Working Conditions (ESCWs) .


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8 Bibliography

Amin, A. (1994) 'Post-Fordism: Models, Fantasies and Phantoms of Transition' in: Amin, A.(ed) Post-Fordism - A Reader, Blackwell: Oxford and Cambridge, Mass, 1-39.

Bell, D. (1973) The Coming of the Post-Industrial Society - A Venture in Social Forecasting,New York.

Boeri, T. & Garibaldi, P. (2000) ‘The Concept and Measurement of European Labour MarketAdaptability’, Contribution to Workshop on ‘Concepts and Measurement of LabourMarkets Flexibility/Adaptability Indicators’, Brussels, 26-27 October 2000.

Brewster, C., Mayne, L. and Tregaskis, O. (1997) ‘Flexible Working in Europe: a Review ofthe Evidence’, Management International Review, 37(1): 85-103.

Bü ssing, A. and Glaser, j. (1998) ‘Arbeitszeit und neue Organisations- undBeschäftigungsformen. Zum Spannungsverhältnis von Flexibilität und Autonomie’,Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, 31 (3): 585-598.

Centre for Training Policy Studies (CTPS)(1996) ‘The Influence of the Size of the Enterpriseon Training Behaviour. A Report Based on the Results of the First Continuing VocationalTraining Survey (CVTS1), University of Sheffield, England.

Clark, A. E. (1998) 'Measures Of Job Satisfaction. What Makes A Good Job? Evidence FromOECD Countries’, Labour Market And Social Policy, Occasional Papers No. 34, OECD:Paris.

Cullen, K. et al. (2002) Work and Family in the eWork Era, Amsterdam et al.: IOS Press.Forthcoming.

Davis, N. (n.a.) ‘The Making of the Continuing Vocational Training Survey’, Working Paper,Brussels: European Commission, URL:http://europa.eu.int/comm/education/leonardo/leonardoold/stat/trainingstatis/reports/cvts1history.doc.

Davidow, W.H. and Malone, M.S. (1992) The Virtual Corporation – Structuring andRevitalizing the Corporation for the 21st Century, New York: HarperCollins.

Datamonitor (2000) ‘The Economic Impact of an IT Skills Gap in Western Europe’, WhitePaper prepared on behalf of Microsoft, London: Datamonitor.

Ducatel, K. and Burgelman, J.-C. (2000) ‘ICTs and Employment in Europe’, Proceedings ofthe 15th European Communications Policy Research Conference, March 25-27, Venice:423-443.

ECaTT (2000) ‘Benchmarking Progress on New Ways of Working and New Forms ofBusiness across Europe. Final Report’, Bruxelles: European Commission, DGInformation Society.

European Commission (1999stat) ‘Status Report on European Telework – New Methods ofWork 1999’, Brussels: European Commission, DG Information Society.

European Commission, Directorate-General for Employment, Industrial Relations and SocialAffairs (2000EiE) ‘Employment in Europe 2000’, Luxembourg: Office for OfficialPublications of the European Communities.

European Commission (2000memo) ‘A Memorandum on Lifelong Learning’, Community StaffWorking Paper, Bruxelles: EU.

European Commission (2001stat). eWork 2001 - Status Report on New Ways to Work in theKnowledge Society. Brussels: European Commission, Directorate C.

European Commission, Directorate-General for Employment, Industrial Relations and SocialAffairs (2001EiE) ‘Employment in Europe 2001’, Luxembourg: Office for OfficialPublications of the European Communities.

European Commission (2002) ‘eEurope Benchmarking Report’, Communication from theCommission to the Council, the European Parliament, the Economic and SocialCommittee and the Committee of the Regions, COM(2002)62 final, Brussels.

European Commission and Eurostat (2001) 'Labour Force Survey: Definition of the variablesspecified in Commission Regulation n.° 1575/2000; Revised Version', Brussels: Eurostat,Directorate E: Social and regional statistics and geographical information system.

http://europa.eu.int/comm/education/leonardo/leonardoold/stat/trainingstatis/reports/cvts1


89

FAMILIES Consortium (2002), Consolidated results of project, March 2002, URL:www.families-project.com.

Felstead, A. and Jewson, N. (2000) In Work, at Home: Towards an Understanding ofHomeworking, London: Routledge.

Finke, W.F. (2000) Lifelong Learning in the Information Age – Organizing Net-based Learningand Teaching Systems, Jena: Bueren.

Fuchs, J. and Schmidt, D. (2000) ‘The Hidden Labour Force in the United Kingdom - aContribution to the Quantification of Underemployment in International Comparisons’,IAB Labour Market Research Topics, Nr. 39, Nü rnberg: IAB: 1-23.

Gareis, K. (1999) ‘Benchmarking Progress on Telework and Other New Ways of Working inEurope’, Proceedings of the Fourth International Workshop on Telework, Tokio, August31st - September 3rd 1999, n.p.

Gareis, K. (2001) ‘The Electronic Freelancing Economy: Myth or Reality? An Overview ofEvidence’, STAR Issue Report No. 9, www.databank.it/star.

Gareis, K. and Kordey, N. (1999) 'Telework - an Overview of Likely Impacts on Traffic andSet-tlement Patterns', Netcom, 13 (3-4): 265-286.

Gareis, K. and Kordey, N. (2000) ‘The Spread of Telework in 2005’, in Stanford-Smith, B. andKidd, P.T. (eds.) E-business – Key Issues, Applications, Technologies, 83-90,Amsterdam et al.: IOS Press.

Gareis, K. and Mentrup, A. (2001a) ‘Virtualisation of Labour Market Transactions:Technological Potential and Status Quo’, STAR Issue Report No. 7,www.databank.it/star.

Gasparini, G. et al. (2000) ‘Full-time or Part-time Work: Realities and Options’, WorkingPaper, Dublin: European Foundation for the Improvement of Living and WorkingConditions.

Hanna, D.E. (1998) ‘Higher Education in an Era of Digital Competition: EmergingOrganizational Models’, Journal of Asynchronous Learning Networks, 2(1), URL:http://www.aln.org/alnweb/journal/vol2_issue1/hanna.htm [retrieved 04/07/2001, 10:00]

Hoffmann, E. and Walwei, U. (2000b) ‘Erosion oder Renaissance der Normalarbeit? -Ländervergleich Dänemark - Deutschland’ IAB Kurzbericht, No.16, Nü rnberg:Bundesanstalt fü r Arbeit.

Huws, U., Jagger, N. and Bates, P. (2001) ‘Where the Butterfly Alights: The Global Locationof eWork’, IES Report 378, Brighton: Institute for Employment Studies.

IDC (2001) ‘ICT Skills in Western Europe’, in in EITO (eds.) European InformationTechnology Observatory 2001, Frankfurt: EITO, pp. 22-95.

ILO (2001) Yearbook of Labour Statistics, Geneva: ILO.Kelly Services Inc. (1999) ‘The Free-Agent Workforce Has Grown to More than 24 Million

Workers’, Press Release, 15 March, Troy MI.Klotz, U. (1999) ‘Die Herausforderungen der Neuen Ö konomie’, Gewerkschaftliche

Monatshefte, 50(10): 590-608.Laubacher, R.J. and Malone, T.W. (2000) ‘Retreat of the Firm and the Rise of the Guilds: The

Employment Relationship in an Age of Virtual Business’, Working Paper No. 33, MITSloan School of Management, 21st Century Initiative, Cambridge.

Malone, T.W. and Laubacher, R.J. (1998) ‘The Dawn of the E-Lance Economy’, HarvardBusiness Review, 76(10): 145-152.

Millar, J. (2001) ‘ITEC Skills and Employment – Assessing the Supply and Demand: anEmpirical Analysis’, STAR Issue Report No. 11, URL: http://www.databank.it/star.

Millard, J. (2002) 'Summary of European Experience of Telework and Telecentres in theRegions - A Guide for Policy Makers', Flexwork Working Paper, URL www.flexwork-ei.org.

Nicoletti, G., Scarpetta, S. and Boylaud, O. (2000) 'Summary Indicators of Product MarketRegulation with an Extension to Employment Protection Legislation', Contribution toWorkshop on ‘Concepts and Measurement of Labour Markets Flexibility/AdaptabilityIndicators’, Brussels, 26-27 October 2000.

http://www.families-project.com

http://www.databank.it/star


http://www.aln.org/alnweb/journal/vol2_issue1/hanna.htm



90

OECD (1996) Lifelong Learning for All, Paris: OECD.OECD (2001e-l) E-Learning: The Partnership Challenge, Paris: OECD.OECD (2001wb) The Well-being of Nations: The Role of Human and Social Capital, Paris:

OECD.Office for National Statistics, U.K. (2001) 'The Labour Force Survey User Guide', Volumes 1-

10, London: Office for National Statistics.Paoli, Pascal and Merllié , Damien (2001) 'Third European survey on working conditions

2000', Dublin: European Foundation for the Improvement of Living and WorkingConditions.

Pink, D.H. (1997) ‘Free Agent Nation’, Fast Company, 12: 131-140.Reichwald, R., Möslein, K., Sachenbacher, H. Englberger, H. and Oldenburg, S. (1998)

Telekooperation. Verteilte Arbeits- und Organisationsformen, Berlin et al.: Springer.Skaliotis, M. (2000) ‘Lifelong Learning for Education Statistics’, Sigma, 3: 25-28.Stanworth, C. (1998) ‘Telework and the Information Age’, New Technology, Work and

Employment, 13(1): 51-62.Toffler, A. (1980) The Third Wave. New York: Bantam.Tommaney, J. (1994) A New Paradigm for Work Organization and Technology? In: Amin, A.

(ed) Post-Fordism - A Reader, Blackwell: Oxford and Cambridge, Mass, 157-194.Urdan, Trace D. (2000) ‘Corporate e-Learning: Exploring A New Frontier’, WR Hambrecht

Report, URL:http://www.wrhambrecht.com/research/coverage/elearning/ir/ir_explore.html.

http://www.wrhambrecht.com/research/coverage/elearning/ir/ir_explore.html


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9 Methodology of the survey

9.1 General Population Survey (GPS)

9.1.1 Outline of the studyThe survey was conducted in April-May 2002 in all 15 EU Member States plus Switzerlandand the USA, using computer-aided telephone interviews. The survey was co-ordinated andexecuted by INRA, Germany. The population for this study is all persons aged 15 and overliving in private households in the respective countries and speaking the respective nationallanguage(s). Subject discussed included ownership and use of ICT equipment, use of theInternet and e-commerce activities, competence in the use of new media, questions on healthand the Internet, the Internet and security concerns, e-government, telework, mobile work andother new ways of working, as well as further education and satisfaction with workingconditions. 11,832 interviews were successfully completed. The average interview length percountry varied between 10 and 20 minutes.

9.1.2 Methodology

Subject of study Topics of this survey were statements on interviewees’ ownershipand use of ICT equipment, use of the Internet and e-commerceactivities, competence in the use of new media, questions on healthand the Internet, the Internet and security concerns, e-government,telework, mobile work forms, as well as further education andsatisfaction with working conditions.

Study concept The study was conceived and executed as a cross national study.The co-ordination was carried out by INRA Deutschland GmbH,Mölln, on behalf of the client. The study consisted of two parts, atrial in Germany with a subsequent main survey in all participatingcountries.

Overallresponsibility andco-ordination

INRA Deutschland GmbH, Mölln

Countries andexecuting institutes

Belgium: INRA BelgiumKroonlaan 159-165 Avenue de la Couronne1050 Brussels

Denmark: Gallup A/SSundkrogsgade 102100 Copenhagen

Germany: INRA Germany GmbHPapenkamp 2-623879 Mölln

Finland: Taloustutkimus OyLemuntie 900510 Helsinki

France: BVAB.P. 5978222 Viroflay Cedex

Greece: MEMRB – K.E.M.E24 Ippodamou St.11635 Athens

Great Britain: BMRB InternationalSaunders House, 53 The Mall, EalingLondon W5 3TE

Ireland: Lansdowne Market Research Ltd.49 St. Stephens GreenDublin 2

Italy: INRA DemoskopeaVia Salaria, 290; Via Rubicone 4100199 Roma

Luxembourg: ILReS. S.A.46, Rue du Cimetière1338 Luxembourg / Bonnevoie

Netherlands: NIPO


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Grote Bickersstraat 741013 ks Amsterdam

Austria: SpectraBrucknerstr. 3-4/54020 Linz

Portugal: METRISAv. Eng. Arantes e Oliviera, No. 3-21900 Lisboa

Sweden: GfK Sverige ABBox 40122100 Lund

Switzerland: Link InstitutSpannortstrasse 7/96000 Luzern

Spain: INRA Españ a S.A.Calle Alberto Aguilera 7-5º28015 Madrid

USA: I.C.R605 West Street

Media, Pennsylvania 19063-2620

Survey methodology The study was carried out as a telephone survey (ComputerAssisted Telephone Interview – C.A.T.I) in all countries.

Population The population for this study is all persons aged 15 and over living inprivate households in the respective countries and speaking therespective national language(s).Switzerland: Here the survey was carried out in both the Germanand French speaking parts of Switzerland.USA: The population includes English speaking people in the 48continental federal states of the USA (excluding Alaska and Hawaii).Finland: Finnish speaking population.

Random samplingand selectionprocess

Belgium: 3-stage selection process based on the INFO BELtelephone directory. Addresses in 10-fold translation, randomsampling of households, selection of the target person via a birthdaykey.Denmark: Geographically stratified sample based on telephonedirectories. Telephone numbers are generated so as to also includeunlisted numbers. The selection of the target person results from abirthday key.Germany: Within the ADM telephone sampling system arepresentative, multistage random sample is drawn for each surveyarea. The selection data is based on the batch of all registered fixednetwork telephone numbers. Master numbers are formed bydetaching the two final digits. Through the generation of new finaldigits from 00 to 99 number blocks are produced which contain listedas well as non listed numbers. As far as possible, businessnumbers were removed from this sampling frame. All telephonenumbers were given an area code number, either the original oraccording to the known distribution in the number block. In this waynumbers can be sorted regionally, thus increasing the precision ofthe sample. By means of the relation between sample size anddistribution of households per regional cell an allocation table isproduced which determines the number of samples to be drawn foreach cell. Assuming a random starting point, all areas areprocessed with a fixed step width through set stages until thenumber to be selected from which areas for each cell has beendetermined. Subsequently the numbers are drawn randomly in asecond selection stage. The selection of the target person resultsfrom a birthday key.Finland: Geographically and socio-demographically stratifiedrandom sample based on information from official statistics. Theselection of target households takes place at random. The selectionof target persons results from a birthday key.


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France: Geographically and socio-demographically stratifiedrandom sample of 8000 starter addresses based on France Telecomdirectories. The selection of target persons results from a birthdaykey.Greece: Multistage stratified random sampling. The geographicalstratification takes place on the basis of NUTS 1, NUTS 2 andlocation size. The size of each unit is determined on the basis ofofficial statistics. The selection of the target person results from abirthday key.Great Britain: The sample is based on a draw data-file. Throughthe generation of new final digits a sample frame is establishedwhich contains listed and unlisted as well as so far non-existentnumbers. The selection of target households takes place at random.The selection of the target person is via quota.Ireland: Geographically sorted random sample based on the”Eircom” telephone directory. Additional telephone numbers are alsogenerated in order to include unlisted numbers. The selection of thetarget person results from a birthday key.Italy: Geographically and socio-demographically stratified randomsample. 705 sample points result from the stratification. Additionaltelephone numbers are generated in order to also include unlistednumbers. The selection of the household results from Random DigitDialling and the selection of the target person results from a birthdaykey.Luxembourg: The sample is based on a draw data-file. Throughthe generation of new final digits from 00 to 99 a sample frame isestablished which contains listed and unlisted as well as so far non-existent numbers. The selection of target households takes place atrandom. The selection of the target person results from a birthdaykey.Netherlands: Geographically stratified random sample. Thegeographical sorting is based on post code areas. Target personselection takes place through an algorithm which selects theinterviewee on the basis of age and gender of people living in thehousehold.Austria: Geographically stratified random sample. The selection ofthe target household takes place through RDD (Random DigitDialling). The selection of the target person results from a birthdaykey.Portugal: Geographically and socio-demographically stratifiedrandom sample. 200 sample points result from the stratification.The selection of households takes place via Random Digit Dialling,the selection of target persons via a birthday key.Sweden: Geographically and socio-demographically stratifiedrandom sample. 200 sample points result from the stratification.The selection of households takes place via Random Digit Dialling,the selection of target persons via a birthday key.Switzerland: Geographically stratified random sample based onpost codes. Each post code represents a sample cell. The selectionof households takes place via Random Digit Dialling and theselection of the target person via an algorithm which selects theinterviewee at random on the basis of a list of household members.Spain: Geographically stratified random sample based on NUTS2areas. 148 randomly selected sample points result from the sorting.Within these sample points addresses of target households arerandomly drawn. Selection of target persons results from a birthdaykey. After about two thirds of the fieldwork the screening wastargeted towards male members of the household due to adisproportionate number of female interviewees.


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USA: Geographically stratified random sample based on the MSG-Genesys sampling process. The selection of households takesplace via Random Digit Dialling and the selection of the targetpersons via a birthday key. After the 758th interview the screeningwas targeted towards male members of the household due to adisproportionate number of female interviewees.

Survey period The interviews were carried out in the following period:04.03.-18.05.2002

Interviewsundertaken

Total: 11,832

Belgium 16.0 min Luxembourg 16.2 minDenmark 18.1 min Netherlands 18.4 minGermany 17.5 min Austria 15.8 minFinland 17.3 min Portugal 12.1 minFrance 12.0 min Sweden 20.2 minGreece 10.2 min Switzerland 19.0 minGreat Britain 18.0 min Spain 12.5 minIreland 17.7 min USA 18.3 min

Average interviewlength

Italy 14.0 min

Interviewers used Total: 632

Additionalcomments to thedata set

Belgium: In order to improve the sample, an additional 85interviews were carried out in some cells.Finland: In order to improve the sample, an additional 169interviews were carried out in some cells.Netherlands: In order to improve the sample, an additional 30interviews were carried out in some cells.Switzerland: In Switzerland respondents were not asked to deducttax from income (Z19), as that is not the norm there.

Data supply One labelled SPSS data set of the main survey of all interviews.


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Field report and outcomesB DK D FIN F EL UK IRL I L NL AT P S CH E USA

Method C.A.T.I.

1 gross sample (utilised addresses) 4506 3154 9999 2621 7300 5022 11392 3890 12006 8764 3640 4669 1403 5177 2327 6494 18162

1.1. non-contacts – thereof: 311 242 1701 40 3401 2346 139 1111 4436 5023 803 193 91 455 638 1239 4192

1.1.1 unobtainable 0 235 1202 0 2342 2077 123 654 4436 3748 522 124 43 113 638 644 3656

1.1.2 engaged 3 7 436 0 57 206 1 316 0 705 164 8 32 55 0 5 536

1.1.3 answer phone, fax, modem 308 0 63 40 1002 63 15 141 0 570 117 61 16 287 0 590 0

1.1.4 other 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1.2 sample neutral non-response – thereof: 1874 1917 4492 984 511 1022 5088 1051 2659 1316 805 2322 410 2808 322 1095 8789

1.2.1 invalid telephone numbers 955 1516 3760 97 60 529 4308 498 1657 790 652 858 334 2297 230 398 5725

1.2.2 not in the population 472 202 41 782 374 176 119 405 364 0 153 1248 47 16 0 164 478

1.2.3 business numbers 300 82 285 12 27 220 437 0 340 455 0 75 15 193 0 434 1331

1.2.4 other 147 117 406 93 50 97 224 148 298 71 0 141 14 302 92 99 1255

2 net sample – thereof: 2321 995 3806 1597 3388 1654 6165 1728 4911 2425 2032 2154 902 1914 1367 4160 5181

2.1 refusal 1470 468 2451 912 2231 747 5012 1134 3592 1000 1248 1609 364 1246 529 2255 3198

2.2 termination 114 0 87 0 30 0 80 11 201 0 0 1 6 19 0 115 143

2.3 target person contacted but interviewimpossible – thereof: 152 26 267 16 127 402 73 83 118 925 254 44 32 146 316 775 836

2.3.1 possible appointment outside field time 0 23 14 1 23 9 26 14 106 763 208 7 6 30 80 321 156

2.3.2 appointments to continue interview outsidefield time 152 0 200 0 104 295 47 65 12 17 11 34 18 24 194 179 669

2.3.3 other 0 3 53 15 0 98 0 4 0 145 35 3 8 92 42 275 11

2.4 complete interviews 585 501 1001 669 1000 505 1000 500 1000 500 530 500 500 503 522 1015 1004

3 exhaustion rate (%) (2.4/(2.1+2.2+2.4)) 27.0% 51.7% 28.3% 42.3% 30.7% 40.3% 16.4% 30.4% 20.9% 33.3% 29.8% 23.7% 57.5% 28.5% 49.7% 30.0% 23.1%


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9.1.3 Weighting1. Transformation from household sample to person sample:As only one person per household is interviewed, the described sample procedure provides ahousehold sample, i.e. each household of the base population has the same likelihood ofbeing in the sample but not each person. With the weighting stage of the transformation theequal likelihood of households is replaced mathematically by the equal likelihood of theindividuals. To this end, each data set is multiplied by the amount of people in the householdaged 15 or over. This number is subsequently divided by the average household size in orderto obtain the actual case number.2. Adjustment of unweighted sample structure to the official statistic:Because random samples are not evenly distributed across all population strata, thedistribution of unweighted samples regularly and systematically deviate from the populationdistribution from official statistics. Through the mathematical weighting the sampledistribution is adjusted to the official statistics. The national weighting factor (P10) whichresults from the iterative weighting was included in the data material. To this end thefollowing criteria are used in the respective countries.Austria: age, gender, region; Belgium: age, gender, region, locality size; Denmark: age,gender, region; Germany: age, gender, region, locality size; Greece: age, gender, localitysize; Finland: age, gender, region; France: age, gender, region, locality size; Ireland: age,gender, region; Italy: age, gender, region, locality size; Luxembourg: age, gender, region,locality size; Netherlands: age, gender, region; Portugal: age, gender, region, locality size;Sweden: age, gender, region; Switzerland: age, gender, region; Spain: age, gender, region,locality size; UK: age, gender, region; USA: age, gender, region, locality size.3. Adjustment of weighted sample structure to the EU15-member states population:This weighting factor was necessary to calculate total figures according to the wholepopulation of the European Union member states. Furthermore it is useful to compare the EUwith the US. Population sizes of each member state are weighted to reduce the distortionbased on the sample sizes in each country. The different country-specific weighting factorsare the following:

Austria 0.44 Italy 1.63Belgium 0.48 Luxembourg 0.02Denmark 0.29 Netherlands 0.80Germany 2.29 Portugal 0.55Greece 0.59 Spain 1.09Finland 0.21 Sweden 0.48France 1.56 United Kingdom 1.57Ireland 0.20 Switzerland, USA none

9.1.4 Sample characteristics and effect of weightingTotal EU15

un-

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d

wei

ghte

d

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eigh

ted

%w

eigh

ted

un-

wei

ghte

d

wei

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eigh

ted

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eigh

ted

Total sample 11832 11832 100.0 100.0 11832 10306 100.0 100.0CountryAustria 500 500 4.2 4.2 - - - -Belgium 585 585 4.9 4.9 - - - -Denmark 501 501 4.2 4.2 - - - -Finland 669 669 5.7 5.7 - - - -France 1000 1000 8.5 8.5 - - - -Germany 1001 1001 8.5 8.5 - - - -Greece 505 505 4.3 4.3 - - - -Ireland 500 500 4.2 4.2 - - - -Italy 1000 1000 8.5 8.5 - - - -


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Luxembourg 500 500 4.2 4.2 - - - -Netherlands 530 530 4.5 4.5 - - - -Portugal 500 500 4.2 4.2 - - - -Spain 1015 1015 8.6 8.6 - - - -Sweden 500 500 4.2 4.2 - - - -Switzerland 522 522 4.4 4.4 - - - -UK 1000 1000 8.5 8.5 - - - -USA 1004 1004 8.5 8.5 - - - -EU15 - - - - 10306 10306 87.1 100.0Age groupsup to 24 1964 2019 16.6 17.1 1731 1651 16.8 16.025 to 49 5511 5309 46.6 44.9 4817 4593 46.7 44.650 to 64 2515 2495 21.3 21.1 2191 2209 21.3 21.465 and more 1833 2000 15.5 16.9 1558 1839 15.1 17.8don’t know 9 9 0.1 0.1 9 14 0.1 0.1Terminal education ageup to 13 695 717 5.9 6.1 693 728 6.7 7.114 715 742 6.0 6.3 701 881 6.8 8.515 to16 1794 1750 15.2 14.8 1641 1820 15.9 17.717 to 20 3587 3515 30.3 29.7 2997 2937 29.1 28.521 and more 3266 3275 27.6 27.7 2743 2495 26.5 24.2still studying 1687 1751 14.3 14.8 1463 1372 14.2 13.3don’t know 88 81 0.7 0.7 77 73 0.7 0.7Household typeone person household 2006 1611 17.0 13.6 1682 1408 16.3 13.7household with kids aged under 6 1723 1754 14.6 14.8 1451 1440 14.1 14.0household with kids aged 6+ 2970 3152 25.1 26.6 2653 2655 25.7 25.8two person household withoutkids 5063 5240 42.8 44.3 4467 4768 43.3 46.3

no answer on household size 70 75 0.6 0.6 53 35 0.5 0.3Household income (according to national household income quartiles by Eurobarometer)First quartile (lowest income) 1774 1580 15.0 13.4 1548 1299 15.0 12.6Second quartile 2132 2084 18.0 17.6 1878 1764 18.2 17.1Third quartile 2536 2521 21.4 21.3 2214 2087 21.5 20.3Fourth quartile (highest income) 2968 3102 25.1 26.2 2502 2725 24.3 26.4don’t know 1214 1295 10.3 10.9 993 995 9.6 9.7refusal 1208 1249 10.2 10.6 1171 1436 11.4 13.9Employment statuspaid employment 4966 4853 42.0 41.0 4291 4133 41.6 40.1self-employed 935 941 7.9 8.0 809 799 7.8 7.8unemployed/ temporarily notworking 701 683 5.9 5.8 621 631 6.0 6.1

in education 1687 1751 14.3 14.8 1463 1372 14.2 13.3retired or other not working 3441 3510 29.1 29.7 3034 3292 29.4 31.9don’t know 102 94 0.9 0.8 88 80 0.9 0.8Social grade (ESOMAR classification)unskilled manual workers andother less well educated workers/employees

1332 1318 11.3 11.1 1238 1323 12.0 12.8

skilled workers and non-manualemployees 1525 1445 12.9 12.2 1316 1287 12.8 12.5

well educated non-manual andskilled workers 1434 1402 12.1 11.8 1254 1121 12.2 10.9

managers and professionals 1577 1586 13.3 13.4 1265 1167 12.3 11.3not specified 5964 6081 50.4 51.4 5233 5408 50.8 52.5


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9.2 Decision Maker Survey (DMS)

9.2.1 Outline of the studyThe survey was conducted in March-May 2002 in seven EU Member States using computer-aided telephone interviews. The survey was co-ordinated and executed by INRA, Germany.The population for this study is defined as all establishments belonging to four aggregatedindustry sectors in the seven Member States. The interview was conducted with ITresponsible persons in companies across all sectors of the economy. Subjects discussedincluded ownership and use of ICT equipment, use of the Internet and e-commerce and e-business activities, e-business security, e-government, web-site accessibility and ICT inresearch and development. 3,139 interviews were successfully completed. The averageinterview length per country varied between 14 and 18 minutes.9.2.2 Methodology

Subject of study • Basic ICT: use of ICT and e-business technologies• e-commerce• e-business security• e-government• web-site accessibility• research and development• establishment demography

Study concept The study was conceived and executed as a cross national study.The co-ordination was carried out by INRA Deutschland GmbH. Thestudy consisted of 2 parts, a trial in Germany with a subsequentmain survey in all participating countries.

Overallresponsibility andco-ordination

INRA Deutschland GmbH, Mölln

Countries andexecuting institutes

Germany: INRA Germany GmbHPapenkamp 2-623879 Mölln

Finland: Taloustutkimus OyLemuntie 900510 Helsinki

France: BVA101 avenue du General Leclerc78222 Viroflay Cedex

Greece: MEMRB – K.E.M.E24 Ippodamou St.11635 Athens

Great Britain: Continental Research132-140 Goswell RoadEC1V 7DY London

Italy: INRA DemoskopeaVia Rubicone 4100199 Roma

Spain: INRA Españ a S.A.Calle Alberto Aguilera 7-5º28015 Madrid

Survey methodology The study was carried out as a telephone survey (ComputerAssisted Telephone Interview – C.A.T.I) in all countries.

Population The population for this study are establishments (in each respectivecountry) in the four sectors:• Manufacturing, Construction, Primary Sector• Distribution, Catering, Transport & Communication• Financial & Business Services• Public administration, education, health, other personal and

social services


99

Target person at the establishment was the person who isresponsible for or significantly involved in decisions in the area of IT/DP. In larger establishments/ organisations the head or anotherexecutive of the IT/ DP department. In smaller establishments/organisations also the owner/ proprietor or managing director/ boardmember.

Random samplingand selectionprocess

General: The sample was set up according to given industry andsize class quota. Accordingly a stratified random sample was drawnfrom the universe, allowing for the relevant industries within the fouraggregated sectors. Drawing the sample was organised locally bythe national executing institutes.Germany: The sample was drawn from the Heins und PartnerBusiness Pool. Heins und Partner have created a high qualitybusiness pool based on the available address inventories consistingof about 3.4 m data sets that have undergone comprehensivevalidation. For every enterprise comprehensive additionalinformation is available, including corporate structure and branchoffice structure (220,000 branch offices) and is continuously beingupdated. The sample was drawn from the establishment file, whichresults from the transformation of enterprises into establishmentsand appending branch offices to the headquarters.Finland: The sample was taken from the so called "Blue Book -Salesleads database" which is edited by Helsinki Media CompanyOy (Sanoma Magasines Finland). This data base contains of about170,000 data sets and is being updated every two months.France: The sample was drawn from the “INSEE Siren file” (thenational office of statistics). INSEE, as a public organisation, isresponsible for gathering all economic and social data in France.These data sets are being updated every two months.Greece: The sample was drawn from the address inventory of ICAP(major establishment data base for Greece and member of theEuropean Association of Directory and database Publishers). Thedata base is being updated every 18 months and also containspublic sector addresses. Additionally, public sector addresses weretaken from the national telephone inventory.Great Britain: The sample was drawn from "BT’s BusinessDatabase". This is a representative data base of all establishmentsin the UK having a telephone number (including addresses by BT,Mercury, cable and about 92 further telecom carriers). The database consists of about 1.6 m addresses and is being updated everytwo months.Italy: The sample was drawn from Dun & Bradstreet's data base.This data base is considered to be the most reliable source for Italy.Spain: The sample was drawn from Schober's data base. This database is the most voluminous record as regards number ofestablishments for Spain.

Survey period The interviews were carried out in the following period:21.03.-15.05.2002

Interviewsundertaken

Total: 3,139

Germany 16.0 min Great Britain 16.2 minFinland 16.4 min Italy 18.2 minFrance 14.1 min Spain 16.4 min

Average interviewlength

Greece 15.1 min

Interviewers used Total: 212

Quality control All interviewers were instructed about the questionnaire before the


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beginning of field work. Field work was permanently controlled bysupervisors. Because of computer aided realisation of interviewssystematic errors of data gathering can be excluded. Furthermorethe proper realisation of interviews was monitored according toinstitute standards. Following is the share of interviews monitored(by telephone):

Germany: 10%

Finland: 5%

France: 10%

Greece: 20%

Great Britain: 8%

Italy: 10%

Spain: 30%

Additionalcomments to thedata set

Question A8: Turnover indication in national currencies weretranslated in Euro except for UK.Some indications seem to be very high, others very low. Nationalinstitutes have re-examined and verified statements by calling therespondents again and reassured turnover answers were as stated.

Problemsencountered

In all countries fulfilling the quota for the largest establishments wasdifficult (mainly 500+ / partly also 200-499 employees). In theseestablishments on the one hand the availability of target persons issignificantly lower, on the other hand are these target persons "over-researched” (which in part results in a general interdiction to takepart in surveys).Due to this in France it was necessary to adapt the quota in order toachieve the number interviews aimed at (i.e. interviews - as far aspossible - carried out in establishments of the next smaller sizeclass).

Data supply One labelled SPSS-data set of the main survey of all interviews.

Field report and outcomesD FIN F EL UK I E

1 Sample (gross), i.e. number dialled at least once 4917 1923 8061 1728 8726 10846 84891.1 Telephone number does not exist 787 47 598 43 416 1160 8081.2 Not an establishment (i.e. private household, etc.) 46 15 0 2 0 0 2351.3 Fax machine/ Modem 81 0 152 31 0 0 5191.4 Quota completed, therefore address not used 0 849 1599 2 2659 848 13971.5 No target person in establishment 858 226 1261 35 1766 822 20431.6 Language problems 0 15 0 0 0 0 101.7 SUM (1.1+1.2+1.3+1.4+1.5+1.6) 1753 1152 3610 113 4841 2830 50122 Net sample (1 minus 1.7) 3164 771 4451 1615 3885 8016 3477

2.1 Nobody picks up phone (and max. contacts notyet exhausted) 325 2 326 229 32 804 18

2.2 Line busy, engaged 45 0 31 235 2 1852 92.3 Answering machine 111 4 82 15 0 0 482

2.4 Contact person refuses (i.e. refusal at reception,switchboard) 436 228 912 38 1354 1056 1022

2.5 Target person refuses 1044 204 1569 107 1672 1410 8962.6 no appointment during fieldwork period possible 33 14 356 36 176 680 2032.7 open appointment 604 4 642 644 52 1668 1112.8 target person is ill/ cannot follow the interview 1 3 18 0 0 0 182.9 Interview abandoned 53 1 14 4 97 34 1022.10 Interview error, cannot be used 0 5 0 6 0 0 109

2.11 SUM(2.1+2.2+2.3+2.4+2.5+2.6+2.7+2.8+2.9+2.10) 2652 465 3950 1314 3385 7504 2970

2.12 SUCCESSFUL INTERVIEWS 512 306 501 301 500 512 507

3 Completion Rate(2.12 / (2.11+2.12)), in % 16.18 39.69 11.25 18.63 12.87 6.38 14.58


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Target and actual numbers of interviewsF D I E UK FIN EL

Quota Group required - achieved - required - achieved - 1 - 9 30 33 30 34 33 32 18 18 17 10 - 49 35 36 36 37 35 35 21 21 22 50 - 199 35 38 37 40 35 35 21 21 25 200 - 499 40 44 41 43 41 40 24 28 22 500+ 15 9 14 13 15 15 9 9 6

IManufacturing,construction, primarysector

Sum 155 160 158 167 159 157 93 97 92 1 - 9 45 50 47 45 46 45 27 28 27 10 - 49 40 42 41 41 43 40 24 24 25 50 - 199 30 28 31 26 30 30 18 18 18 200 - 499 15 19 15 16 15 15 9 5 9 500+ 10 5 10 8 10 10 6 5 6

IIDistribution, catering,transport andcommunication

Sum 140 144 144 136 144 140 84 80 85 1 - 9 30 32 30 34 30 30 18 16 17 10 - 49 20 19 21 23 21 20 12 14 11 50 - 199 10 13 10 17 10 10 6 6 8 200 - 499 10 13 10 6 10 10 6 7 6 500+ 10 8 9 4 7 8 6 6 6

IIIFinancial and businessservices

Sum 80 85 80 84 78 78 48 49 48 1 - 9 20 20 24 19 20 20 12 13 13 10 - 49 25 29 25 26 25 25 15 16 16 50 - 199 30 22 30 34 30 30 18 18 18 200 - 499 35 32 35 31 35 35 21 23 20 500+ 15 9 16 15 16 15 9 10 9

IVPublic administration,education, health, otherpersonal and socialservices Sum 125 112 130 125 126 125 75 80 76

Total 500 501 512 512 507 500 300 306 301

9.2.3 WeightingFor the SIBIS DMS a sample stratified by sector/ size cells was used which ensured that ineach sector, establishments from all size classes were sampled. In order to be able to raisefigures to national level, some form of weighting is required which adequately reflects thestructure and distribution of establishments (or related variables) in the universe of therespective country (and, by implication, EU15). All presentation of SIBIS results indicatesclearly which of these weighting schemes was used.

9.2.3.1 Original weight

Within each country, the interviews were split according to a quota plan which guaranteedthat the sample is not dominated by micro and small companies. The quotas roughly reflectthe distribution of employment over sector and establishment size bands in the EU, andderive from research into establishment sampling frames undertaken for previous studies byInfratest and GfK in the course of ECaTT. They represent best estimates, but do not takeaccount of country differences.


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The quota scheme looks as follows:empirica SUGGESTED QUOTAS: Sectors (aggregated) X Size

1- 9 10 - 49 50 - 199 200 - 499 500+ Total % of total abs

% of total

% of total

% of total

% of total

% of total

Quota I 6% 30 7% 35 7% 35 8% 40 3% 15 31% 155

1 Mining, Energy2 Manufacturing3 Construction

Quota II 9% 45 8% 40 6% 30 3% 15 2% 10 28% 140

4 Distribution5 Hotels, Restaurants6 Transport, Communication

Quota III 6% 30 4% 20 2% 10 2% 10 2% 10 16% 80

7 Banking, Insurance8 Business Services

Quota IV 4% 20 5% 25 6% 30 7% 35 3% 15 25% 125

9 Public Administration10 Education11 Health and Social Work

12 Other personal or social services

Total 25% 125 24% 120 21% 105 20% 100 10% 50 100% 500

Financial & Business Servicesincludes:

Public administration, education, health, other personal & social servicesincludes:

Manufacturing, Construction, Primary Sector,includes:

Distribution, Catering, Transport & Communicationincludes:

(The absolute numbers refer to countries with n=500)

Weighting was used in cases where the quotas could not be reached exactly in line with thisquota plan (mostly due to the limited absolute number of establishments in the two biggestsize classes). Note that because of the use of a single quota plan for all countries, countrydifferences in the distribution of employment over establishment size bands which occur inreality are not reflected in the data. This is due the lack of available data on the distribution ofemployment across establishments size bands in almost all EU Member States, andconstitutes a considerable problem. This weight is therefore not used for presenting SIBISresults.

9.2.3.2 Weighting by employment

The data available on the distribution of employment over establishment size bands is verylimited for most EU Member States. SIBIS used data from a variety of sources, includingü BT database (United Kingdom)ü ISTAT Industry and Services Intermediate Census – latest available, 1996 (Italy)ü National Statistical Service of Greece - latest available, 1995 (Greece)ü SIREN (France)ü Tilstokeskus Official Statistics (Finland)ü Heins + Partner B-Pool (Germany)ü Schober Business Pool (Spain)and adjusted using data from the DG Enterprise/ Eurostat SME Database (latest available,1997), to estimate the establishment/ employment structure for each country in the sample.The table below shows the resulting establishment size structure per country.

CountryD E EL F FIN I UK EU7

1 to 9 23% 23% 59% 17% 13% 38% 14% 23%10 - 49 19% 28% 16% 22% 16% 22% 31% 24%50 - 199 21% 21% 8% 21% 19% 14% 26% 20%200 - 499 13% 9% 6% 14% 16% 7% 13% 12%

Esta

blis

hme

ntsi

ze b

and

500 and more 25% 18% 10% 25% 37% 19% 17% 21%Total Column % 100% 100% 100% 100% 100% 100% 100% 100%


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Using this weight, the weighted sample for each country therefore reflects employeedistribution between the five establishment size bands within that country. This means that adata reference of, for example, ”20% of all establishments in country A” should be understoodto mean ”establishments accounting for 20% of all employees in country A”.

9.2.3.3 Weighting by employment for EU7 averages

Additionally another weighting factor was created to calculate average figures for all countriesin the sample (which together represent roughly 82% percentage of total EU employment).Each country is represented in this weight according to its share in the total employment ofthe 7 EU countries in which the survey was conducted.

9.2.4 Sample characteristics and effect of weightingTotal

unweighted weighted byemployment* % unweighted % weighted by

employment*Total sample 3139 3139 100.0 100.0CountryFinland 306 306 9.7 9.7France 501 501 16.0 16.0Germany 512 512 16.3 16.3Greece 301 301 9.6 9.6Italy 512 512 16.3 16.3Spain 507 507 16.2 16.2UK 500 500 15.9 15.9

Total

unweightedweighted byemployment

(EU7)% unweighted

% weighted byemployment

(EU7)Number of staff at siteup to 9 803 713 25.6 22.710 to 49 769 746 24.5 23.850 to 199 668 648 21.3 20.6200 to 499 626 364 19.9 11.6500 and more 273 668 8.7 21.3Industry Sectorprimary: manufacturing, energy,mining, construction 990 989 31.5 31.5

secondary: distribution, catering,communication and transport 873 878 27.8 28.0

third: financial and businessservices 502 501 16.0 15.9

fourth: public administration,health, education, other social/personal

774 772 24.7 24.6

Type of organisationheadquarter of internationaloperating organisation 267 348 8.5 11.1

headquarter of organisation onlyoperating in country 607 536 19.3 17.1

division/ branch of internationaloperating organisation 256 290 8.2 9.2

division/ branch of organisationonly operating in the respectivecountry

309 312 9.8 9.9

other type 76 40 2.4 1.3only one establishment 1617 1608 51.5 51.2don’t know 7 6 0.2 0.2


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9.3 Questionnaires

9.3.1 Questionnaire for the General Population Survey (GPS)

Structure of the questionnaire:

Module IN: Introduction and screening

ü Ageü Educational attainmentü Employment statusü Occupationü Type of organisationü Main working place

Module A: Basic ICT equipment access and use

ü Use of computerü Use of e-mailü Internet access and useü Methods of Internet accessü Effects of Internet useü Barriers to using the Internetü Access to mobile phoneü Mobile data servicesü Effects of mobile phone use

Module B: E-commerce and other uses of the Internet

ü Online activitiesü Barriers to buying online

Module D: Skills

ü Internet user experience and know-how

Module L: e-Health

ü Use of online health informationü Perception regarding the trust placed in online health information providerü Rationale for health info search

Module J: Security

ü Security concernsü Reporting of security violationsü Security-related awareness and behaviour

Module K: e-Government

ü Preference for e-Government servicesü e-Government experienceü Barriers to e-Government


105

Module E: Telework

ü Home-based teleworkü Intensity of home-based teleworkingü Duration of telework:ü Financing of tele-workplaceü Interest in telework:ü Perceived feasibilityü Effects of telework

Module F: Mobile work

ü Mobile work (Intensity):ü Mobile telework

Module G: Tele-cooperation/Tele-collaboration

ü Co-operation with external contacts using ICTsü e-Lancing

Module H: Outcomes of work

ü Work-family balanceü Job qualityü Job satisfaction

Module C: Educational attainment and lifelong learning

ü Company-provided trainingü Training provided by other organisationsü Self-directed learningü Modes of training (use of eLearning)

Module Z: Standard demography

ü Household sizeü Disabilityü Income


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Question Answer categories

106

Module IN: Introduction and Screener questions GPSINTRO TEXTALL

Hello my name is ... calling for ...We are presently conducting a scientific survey for the European Unionin fifteen countries. I would like to talk to the person in your household,that is at least 15 years old, and whose birthday is up next.[INTERVIEWER: IF NECESSARY] To topic of this survey is theinternet and the work life.[INTERVIEWER: IF NECESSARY] Your answers will be held strictlyconfidential and will be used only for scientific purposes.[INTERVIEWER: IF NECESSARY] Your participation is very importantto us, because you have been selected through a statistical procedurethat will result in a typical selection of people in [COUNTRY][PROMPT: The interview will last about 15 minutes]

IN1ALL

Would you please tell me in which year you were born? |_1_|_9_|__|__|[DK]

PROGRAMMING: IF respondent born after 1986 END INTERVIEW!

IN2ALL

Have you finished your full-time education or are you still studying? (1) finished education already(2) Is still studying(3) DK

IN3IF IN2=1

At what age did you finish full-time education?[PROMPT: HOW OLD WHERE YOU WHEN YOU STOPPED FULL-TIME EDUCATION]

|__|__| years[DK]

Transition X1IF IN2=1

I would like to ask you a few questions regarding your employmentsituation.

IN4IF IN2=1

At present are you in paid work either as an employee, civil servant oras self-employed?

(1) yes(2) no(3) DK

IN5aIF IN4=1

Do you have one job or more than one job at present? (1) only one job(2) more than one job(3) DK

IN5bIF IN5a=2,3

How many hours per week do you normally work, including paidovertime and taking all your jobs together?

|__|__|__|[DK]

Transition X2IF IN5a=2

For answering the following questions, please consider only your mainjob, i.e. the job you spend most of your working time on.

IN6IF IN4=1

And are you ... [in your main job][INTERVIEWER: Read out answer categories]

(1) self-employed(2) in paid employment (including civil servants)(3) DK

IN7IF IN4=2,3

And are you ...[INTERVIEWER: Read out answer categories]

(1) temporarily not working, e.g. because ofunemployment, paternal leave or illness(2) retired(3) not working, because you are responsible forordinary shopping and looking after the home.(4) DK


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IN8IF IN6=1

What kind of work do you do? Are you a ...[INTERVIEWER: Read out answer categories]

(1) Professional (eg doctor, lawyer, accountant,architect)(2) Farmer, fisherman(3) Business proprietor, owner of company/shop,craftsmen, other self-employed person(4) DK

IN9IF IN8=3

How many employees do you have? |__|__|__|__|__|__|[DK]

IN10IF IN4=1

[In your main job,] Are you working full-time or part-time? (1) full-time(2) part-time(3) DK

IN11IF IN4=1

How many hours per week do you normally work in your main job,[PROGRAMMER: Skip the following if IN6=1] including paid overtime?

|__|__|__|[DK][PROGRAMMER: INCLUDE CHECK WITH IN5B]

IN12IF IN6=2,3

Are you employed ...[INTERVIEWER: Read out answer categories]

(1) on an unlimited permanent contract(2) on a fixed term contract(3) on a temporary employment agency contract(4) on apprenticeship or other training scheme(5) other(6) DK

IN13IF IN7=2,3,4

Would you like to be in paid work? (1) yes(2) no(3) DK

IN14IF IN8=3 or IN6=2

What kind of work do you do? Are you ...[INTERVIEWER: Read out answer categories]

(1) working mainly at a desk(2) not working at a desk, but travelling(salesmen, driver, ...),(3) not working at a desk, but in a service job(retail shop, restaurant, ...)(4) doing some other kind of work(5) DK

IN15IF IN6=2

What position do you hold? [INTERVIEWER: Read out answer categories]

(1) Employed professional (employed lawyer,medical practitioner, accountant, architect etc.),(2) Management(3) Other non-manual employee(4) Manual worker(5) DK

IN16IF IN15=2

And which of the following best describes your position?[INTERVIEWER: Read out answer categories]

(1) General management, director or topmanagement (managing directors, directorgeneral, other director)(2) Middle management, other management(department head, junior manager, teacher,technician)(3) DK

IN17IF IN15=4

And which of the following best describes your position?[INTERVIEWER: Read out answer categories]

(1) Supervisor(2) Skilled manual worker(3) Other (unskilled) manual worker, servant(4) DK

IN18IF IN15=2

How many employees you are responsible for? |__|__|__|__|__|__| [DK]


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IN19IF IN6=2

For what kind of organisation do you work?[INTERVIEWER: Read out answer categories]

(1) a private firm or business or a limitedcompany(2) in the public sector or in a charity, voluntaryorganisation or trust[PROMPT - DO NOT READ: (2) includes publiccompanies, local or central government, civilservice, armed forces, council, schools,universities or other grant funded educationestablishments, public authorities, charities,voluntary organisations](3) DK

IN20IF IN6=2

How many employees work in the company/organisation for which youwork?[INTERVIEWER: Read out answer categories]

(1) <10(2) 10-49(3) 50-249(4) 250 and more(5) DK

IN21IF IN4=1

Do you work mainly ...[INTERVIEWER: Read out answer categories]

(1) in your own home(2) in the same grounds or buildings as yourhome(3) in different places using home as a base (e.g.travelling salesman, free insurance agent etc.)(4) somewhere quite separate from home(5) DK

Module A: Basic ICT equipment access and use GPSTransition AALL

Now we would like to ask you a few questions about computers andthe Internet

A1ALL

Have you used a PC, Mac or any other computer, for work or for privatepurposes - in the last four weeks?

(1) yes(2) no(3) DK

A3IF A1=1

Have you sent or received any e-mail messages, for work or for privatepurposes, during the last four weeks?

(1) yes(2) no(3) DK

A4aIF A3=1

How many of your friends and relatives have their own email address?[INTERVIEWER: Read out answer categories]

(1) all or almost all(2) about three quarters(3) about half(4) about one quarter(5) only few or no-one(6) DK

A4bIF A4a<5

And with how many of your friends and relatives do you communicateregularly via email?[INTERVIEWER: Read out answer categories]


A5ALL

Do you have access to the Internet in your home? (1) yes(2) no(3) DK


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A6IF A5=2

Did you once have Internet access in your home? (1) yes(2) no(3) DK

A7ALL

Have you used the Internet at least once in the last four weeks, athome, at school or work or at any other place?

(1) yes(2) no(3) DK

A8IF A7=2,3

Have you used it in the last 12 months at least once? (1) yes(2) no(3) DK

A9FOR (a):IF A7=1 and A5=1FOR (b)-(f):IF A7=1

How much time do you spend in a typical week on using the Internet ...[item][INTERVIEWER: Read out answer categories for the first 2 items](a) at home?(b) at the workplace?(c) at school, university or another educational institution?(d) at a public place where Internet access is free?(e) at an Internet café or other place where you have to pay for access?(f) at another place not mentioned yet

FOR EACH(1) none(2) less than 1 hour(3) between 1 and 5 hours(4) between 6 and 10 hours(5) between 11 and 20 hours(6) more than 20 hours(7) DK

A10IF A7=1 or A8=1

When did you use the Internet for the first time?[INTERVIEWER: Read out answer categories]

(1) < 6 months ago(2) 6 - 12 months ago(3) 1 year - 2 years ago(4) 2 years + ago(5) DK

A11aIF A5=1

Do you know what technical method you use at home to connect to theInternet?

(1) yes(2) no(3) NA

A11bIF A11a=1,3

I will read to you a number of methods to access the Internet. Which ofthese do you use at home?[INTERVIEWER: Read out and code those that apply]

MULTIPLE ANSWERS(1) Dial-up with modem(2) Cable Modem(3) Leased line(4) xDSL(5) ISDN(6) T1 or T3 line [TRANSLATOR: Digital Multiplexconnection](7) Internet access via satellite(8) Other not mentioned (e.g. mobile)(9) DK

A12IF A11b=2,3,4,5,6,7

At home, did you have a connection before which was slower than yourcurrent one?

(1) yes(2) no(3) DK

A13IF A12=1

Since moving to this faster type of connection, has the amount of timeyou spend online per week decreased, increased or remained roughlythe same?

(1) Decreased(2) Increased(3) Remained roughly the same(4) DK

A14IF A7=1

In the last four weeks, have you accessed the Internet in any other waythan via PC or Mac, at least once?

(1) yes(2) no(3) DK


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A15IF A14=1

Which devices did you use for that: Did you use ...[INTERVIEWER: Read out and code those that apply]

MULTIPLE ANSWERS(1) Digital TV*,(2) a PDA or palmtop,(3) a mobile phone with WAP or 2.5G** capability,(4) a game console(5) other(6) DK[* TRANSLATOR: Make sure that you take localbrand names and colloquial terms into account]** TRANSLATOR: Use term used in your country(e.g. Germany: GPRS)]

A18IF A7=2,3

Now I will read to you a list of statements about the Internet.Please tell me for each statement whether you agree completely, agreesomewhat or do not agree.The Internet ... [item]. Do you ...(a) requires advanced computer skills,(b) is not easy enough to get access to,(c) is too time consuming,(d) is too expensive to use,(e) lacks useful or interesting information(f) is not something for me

FOR EACH(1) agree completely(2) agree somewhat(3) or do you not agree(4) DK

A19ALL

Do you have a mobile phone for your own personal use? (1) yes(2) no(3) DK

A20ALL

How many of your friends and relatives have a mobile phone for theirpersonal use?[INTERVIEWER: Read out answer categories]


A23IF A19=1 and A15~=3

Have you used your mobile phone to view webpages or WAP pages, orto read your email, at least once in the last 4 weeks?[TRANSLATORS: Confusion with SMS* to be avoided!]

(1) yes(2) no(3) DK

A26IF A23=1

Have you used your mobile phone at least once in the last 12 monthsto make any purchases in the Internet, to download online informationyou are charged for or to make online payments?

(1) yes(2) no(3) DK

A27IF A19=1

Have you, in the last four weeks, used SMS* messages for ...(a) communication with other people?(b) paying for purchases, admission tickets or something similar?(c) paying for downloads such as ringing tones?(d) receiving financial information, sport results or other subscriptionservices?[* TRANSLATOR: Check if another term is more common in yourcountry]

FOR EACH(1) yes(2) no(3) DK


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A30IF A19=1(For (d) and (e)I: IF A19=1 and(A8=1 or A7=1) and IN4=1)

Now, think about what your everyday life would be like if you didn’thave a mobile phone. Please tell me how much you agree that if youdidn’t have a mobile phone (ITEM). Would you say that you …

[INTERVIEWER: Read out answer categories for the first 2 items](a) you would often not be able to contact your friends and family, or bereached by them(b) you would be less exposed to dangerous electromagnetic radiation(c) you would be more helpless in case of emergencies(d) you would not receive some of the information you need for your job(e) you would have less exchange with some of your business contacts(f) you would have less fun

FOR EACH:(1) agree completely(2) agree somewhat(3) do not agree(4) DK

Module B: E-commerce and other uses of the Internet GPSTransition BIF A8=1 or A7=1

Now I would like to ask you a few questions about the Internet.

PROGRAMMING: B1 to B2: for each item in B1=1 ask directly B2, thengo to next item in B1

B1IF A8=1 or A7=1

You can use the Internet for many purposes. I´m going to read you alist of things you can do online and ask you whether you have done thisonline for your private purposes. For your private purposes, have youused it in the last 12 months...(a) to find information about a product or service(b) to order a product or service(c) to conduct online-banking or to buy financial products(d) to search for any health-related information(e) to look for a job


B2IF B1=1 and A7=1

[FOR EACH B1 ITEM] Have you done so in the last four weeks? (1) yes(2) no(3) DK

B5IF A7=1(For (c) and (d): IF A7=1 andIN4=1)

Many people in this country still do not have access to the Internet yet.Now please imagine our country were without the Internet for onemonth. What would it mean for your everyday life?Please tell me how much you agree that if our country were without theInternet for a month you would (ITEM). Would you say that you would…[INTERVIEWER: Read out answer categories for the first 2 items](a) be less well informed as a consumer(b) feel socially excluded(c) not receive some of the information you need for your job(d) have less communication with some of your contacts at work / yourbusiness contacts(e) have less contact with some of your friends(f) have less fun



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Module D: Skills GPSD1IF A7=1 or A8=1[Do not ask item (h) in UK, IRL,USA]

I would like to ask you a few questions about your skills in using theInternet. How confident would you feel... [item]Please tell me whether you feel..[INTERVIEWER: Read out answer categories for the first 2 items](a) using a search engine (such as Google or Yahoo) to findinformation on the Internet [TRANSLATORS: List two most widely usedsearch engine brands in your country19](b) identifying the source of information provided on the Internet(c) using e-mail to communicate with others(d) using Internet chat-rooms to contact other people(e) using the Internet to make telephone calls(f) creating a personal web / Internet page(g) downloading and installing software onto a computer[PROGRAMMING: Do not ask item (h) in UK, IRL, USA](h) understanding the content of websites written in English

FOR EACH(1) very confident(2) fairly confident(3) not confident(4) Do not know what this means [DO NOT READOUT](5) DK

Module L: e-Health GPSTransition LIF B1(d)=1

You said before, that you have used the Internet to search for health-related information:

L1IF B1(d)=1

Have you been able to find health related information on the Internet? (1) yes(2) no(3) DK

L2IF L1=1

Was the information suitable for your needs? (1) yes(2) no(3) DK

L3IF L2=1

Websites with health related information are available in manylanguages.When you searched, did you find Websites in your mother tonguesufficient or did you have to expand your search and consult sites inother languages, or did you even have to rely solely on sites in otherlanguages?

(1) Websites in mother tongue were sufficient(2) Had to expand my search and consultwebsites in other languages too(3) Had to rely solely on websites in otherlanguages(4) DK

L4IF B1(d)=1

And for what reasons did you search health-related information on theInternet?Did you search health-related information on the Internet to ...[item](a) seek a second opinion on your own, a family member’s, or afriend’s medical diagnosis?(b) be better informed on your general health?(c) gather additional information since you care for an ill person or aperson with a disability?


19 For example, check http://www.jupitermmxi.com/europelanding.html

http://www.jupitermmxi.com/europelanding.html


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L5IF B1(d)=1

How trustworthy would you consider each of the following providers ofhealth-related information:[Item] : Are those ...[INTERVIEWER: Read out answer categories for the first 2 items](a) Universities and other non-profit organisations active in the healthsector / the health field(b) pharmaceutical companies(c) private health insurance providers(d) patient advocacy and self-help groups(e) hospitals(f) professional medical associations

FOR EACH(1) very trustworthy(2) fairly trustworthy(3) not trustworthy(4) DK

Module J: Security GPSTransition JIF A7=1

Now the topic is internet security.

J1IF A7=1

How concerned are you about .[item]: Are you ...[INTERVIEWER: Read out answer categories](a) data security on the Internet, i.e. the loss or manipulation of yourdata?(b) privacy and confidentiality on the Internet, i.e. personal informationabout you being misused by third parties?

FOR EACH(1) very concerned(2) somewhat concerned(3) not concerned(4) DK

J2IF J1(a)=1,2 or J1(b)=1,2

Are these concerns stopping you from using the Internet to buy goodsor services online: often, sometimes, or never?

(1) often(2) sometimes(3) never(4) DK

J3IF A7=1

Would you report violations of your on-line security, privacy andconfidentiality to a third independent party, for example a public agencycreated for this task?[INTERVIEWER: Read out answer categories]

(1) yes, very likely(2) maybe(3) no(4) DK

J4IF J3=1,2,3

Would it be easier for you to do so if you could do it anonymously? (1) yes(2) no(3) DK

J5IF A7=1 & (B1(b)=1 or B1(c)=1)

How often are you aware of security features of websites when you usethe Internet to buy online: often, sometimes or never?


J6IF A7=1 & (B1(b)=1 or B1(c)=1)

And how often do you take security features of websites into accountwhen deciding about whether to buy online: often, sometimes or never?


Module K: e-Government GPSTransition KIF A7=1

Now I would like to ask you a few questions about the contact togovernment agencies through the Internet.

PROGRAMMING: K1 to K3: for each item in K1=1 ask directly K2, IfK2=1 ask directly K3, then go to next item in K1


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K1IF A7=1

Here is a list of activities that require citizens to get in touch with publicadministration.For each activity, please answer whether you would prefer to use theInternet or prefer to use the traditional way, that is face-to-face, bypostal mail, fax or phone:[INTERVIEWER: Repeat answer categories for the first 2 items](a) Tax declaration / filing your income tax return(b) Use of job search services of public employment service(c) Request for passport, driver's licence, birth certificates or otherpersonal documents(d) Car registration(e) Declaration to the police, e.g. in case of reporting theft(f) Searches for books in public libraries(g) Announcement of change of address

FOR EACH(1) Internet(2) traditional way(3) do not use this service [DO NOT READ OUT](4) DK

K2IF K1=1

FOR EACHIs it possible to use the Internet for this in the area you live?


K3IF K2=1

FOR EACHHave you ever tried using the Internet for this?


K4IF A7=1

For each of the following statements about online services of publicadministration, please indicate whether you agree. Public services onthe Internet ...[item].[INTERVIEWER: Read out answer categories for the first 2 items](a) are not useful enough(b) are faster than the traditional way(c) require that you install special equipment or software(d) reduce the number of mistakes public authorities make(e) do not seem as safe as using the traditional way(f) make it possible to deal with the authorities at more convenienttimes(g) make it possible to deal with the authorities at more convenientlocations, e.g. from home or from the workplace(h) are difficult to use

(1) agree completely(2) agree somewhat(3) do not agree(4) DK

Module E: Telework GPSTransition EIF IN4=1 or IN13=1 or IN7=1

Now let’s talk about another topic:With the help of telephone, fax and computer, many types of work canbe done from home. If work results are transferred electronically, this issometimes called telework.

E1IF IN4=1

Do you presently telework from home, for at least some of your workingtime?

(1) yes(2) no(3) DK

E2IF E1=2,3

Have you teleworked on a regular basis before, in the last five years? (1) yes(2) no(3) DK


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E3IF E2=1

Did you spend, on average, at least one full working day a week athome when you were teleworking?

(1) yes(2) no(3) DK

E4IF E1=1

Do you spend, on average, at least one full working day a weekteleworking from home?

(1) yes(2) no(3) DK

E5IF E1=1

You indicated before that you work on average [PROGRAMMER: Insertresult from IN5b, if blank insert result from IN11] hours per week. Howmany of these do you spend at home in a typical week?

|__|__|__| [DK][PROGRAMMER: Insert check with IN5b or IN11]

E7IF E1=1 and IN6=2

Has the equipment you use for teleworking at home been mainly, notmainly but partly, or not at all been paid for by your employer?

(1) mainly paid for by employer(2) not mainly, but partly paid for by employer(3) not at all paid for by employer(4) DK

E8IF IN7=1 or IN13=1 or (E1=2,3 orE4=2,3)

If it was offered to you, how interested would you be in ... [item]. Wouldyou be ...[INTERVIEWER: Read out answer categories for the first 2 items](a) doing almost all your work teleworking at home(b) telework where you did not spend all your working time, but at leastone full working day per week at home(c) work in an office provided near your home which would allow you toreduce commuting?

FOR EACH(1) very interested(2) somewhat interested(3) not interested(4) DK

E9aIF E1=2,3 or E4=2,3

Would you say that your job is feasible for telework, under theassumption that you spend at least one full working day per week athome?

(1) yes(2) no(3) DK

E9bIF E9a=2 and IN6=2

What are the main reasons why you consider your current job not to befeasible for telework? Is it because ...[INTERVIEWER: Read out answer categories and code all that apply]

MULTIPLE ANSWERS(1) your company does not permit telework?(2) your superior does not approve of telework?(3) your job requires face-to-face contact withcustomers, colleagues or other persons(4) your job requires access to machines or otherthings which cannot be accessed from home(5) Other reasons (DO NOT READ OUT)(6) DK

E10IF E1=1

For what reasons did you start teleworking? Please indicate for each ofthe following aspects how important it was for your decision to startteleworking. [item] Was this ... for you.[INTERVIEWER: Read out answer categories for the first 2 items](a) I needed a more peaceful working environment(b) I want to participate more in family life(c) I want to be closer to clients or customers(d) I need to look after a child or an other person who needs care(e) My company asked me to start teleworking(f) I want to reduce commuting(g) I wanted to have more flexibility in how to organise my work

(1) very important(2) somewhat important(3) not important(4) DK


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E11IF E1=1

Most working people are not allowed to work from home. Pleaseconsider you would not be allowed to telework from home, for whateverreasons.What would that mean for your ability to do your job? Would it meanthat you...[item]. Do you ...[INTERVIEWER: Read out answer categories for the first 2 items](a) could not be in paid work at all(b) could not do your job as well as with telework(c) would have to look for another job which is located closer to yourhome(d) would have to reduce your working hours per week


Module F: Mobile work GPSTransition FIF IN4=1

Now let’s talk about the topic of mobile working.

F1IF IN4=1

In the last four weeks, have you spent any of your working time awayfrom your home and from your main place of work, e.g. on businesstrips, in the field, travelling or on customer’s premises?

(1) yes(2) no(3) DK

F2IF F1=1

You indicated before that you work on average [PROGRAMMER: Insertresult from IN5b, or if blank result from IN11] hours per week. Howmany of these do you spend away from home and your main place ofwork?

|__|__|__|[DK][PROGRAMMER: Insert check with IN5b or IN11]

F3IF F2>5

In the last four weeks, have you used online computer connectionswhen travelling? By this I mean have you accessed the Internet forbusiness purposes, or electronically transferred data to colleagues?

(1) yes(2) no(3) DK

F4IF F3=1

For what purpose did you use these online connections? Have youused these to ...(a) access the Internet(b) send or read e-mails(c) connect to your company's internal computer system

FOR EACH:(1) yes(2) no(3) DK

F5IF F3=1

Where did you use an online computer connection? Have you used it inthe last four weeks at ...(a) a hotel, conference site or similar location?(b) another company's premises?(c) an Internet café or an other commercial teleservice center?(d) or on the move, using a mobile device for data transfer?


Module G: Tele-cooperation/Tele-collaboration GPSTransition GIF IN4=1 and (A1=1 or A7=1)

And how about the use of telecommunication technology at your workplace:

G1IF IN4=1 and A1=1

When you communicate with external contacts, do you sometimes usee-mail, video conference or electronic data transfer? [PROGRAMMER:skip the following if IN6=1] By external persons we mean customers,clients, suppliers, other business contacts, but also colleagues workingat other locations of the same company.

(1) yes(2) no(3) DK

G2IF G1=1

In a typical week, how often do you ...[item] for these external contacts?[INTERVIEWER: Read out answer categories for the first 2 items](a) use e-mail(b) use video-conferencing(c) use e-mail attachments or other electronic data transfer

FOR EACH(1) 10 or more times a day,(2) at least once a day,(3) at least once a week(4) less often than once a week(5) never(6) DK


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G4IF IN6=1 and A7=1

I would like to know about the role the Internet plays in your business.Do you sometimes attract new business through the Internet or via e-mail?

(1) yes(2) no(3) DK

G5IF IN6=1 and A7=1

Do you sometimes deliver work results to your clients or customersthrough the Internet or via e-mail?

(1) yes(2) no(3) DK

G6IF G4=1 and G5=1

Does it sometimes happen that you communicate with clients orcustomers exclusively by electronic means, i.e. via Internet, e-mail,phone or fax and without meeting face-to-face?

(1) yes(2) no(3) DK

Module H: Outcomes of work GPSTransition HIF IN4=1

I would like to ask you a few more questions about your work.

H1IF IN4=1

Please tell me for each of the following, how often you experience this.How often do you .. [item]?[INTERVIEWER: Read out answer categories for the first 2 items](a) Find your work stressful(b) Come home from work exhausted(c) Find your job prevents you from giving the time you want to yourpartner or family(d) Feel too tired after work to enjoy the things you would like to do athome(e) Find your partner/family gets fed up with the pressure of your job

FOR EACH(1) often(2) sometimes(3) never(4) does not apply [DO NOT READ](5) DK

H2IF IN6=2,3

In your current work arrangement, do you agree with the followingstatements about your job? [item] Do you ...[INTERVIEWER: Read out answer categories for the first 2 items](a) I have a lot of say over what happens in my job(b) I need to keep learning new things continuously(c) I have concerns about whether my job is secure(d) I have a high income(e) I can adapt my starting & finishing times to my personal preferences(f) I can adapt the number of weekly working hours to my personalpreferences

FOR EACH:(1) strongly agree(2) somewhat agree(3) disagree(4) DK

H3IF IN4=1

On the whole, are you very satisfied, somewhat satisfied, neithersatisfied nor dissatisfied, somewhat dissatisfied or very dissatisfied withyour job / your main job?

(1) very satisfied(2) somewhat satisfied(3) neither satisfied nor dissatisfied(4) somewhat dissatisfied(5) very dissatisfied(6) DK

Module C: Educational attainment and lifelong learning GPSTransition CIF IN4=1 or IN13=1 or IN7=1

Now I would like to ask you a few questions about training and learning.

C2IF IN6=2,3

Did you participate in some kind of work-related training activities thatwere provided either by your company or by an other organisation, inthe last four weeks?

(1) yes(2) no(3) DK

C9bIF IN7=1 or IN6=1

Did you participate in some kind of training activities with the aim ofpreparing you for a future job, in the last four weeks?

(1) yes(2) no(3) DK


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C14aIF IN4=1

Apart from the training that may have been provided by others, did youengage in some kind of self-directed learning related to your work, inthe last four weeks?

(1) yes(2) no(3) DK

C14bIF IN7=1 or IN6=1

Apart from the training that may have been provided by others, did youengage in some kind of self-directed learning which was aimed atpreparing you for a future job, in the last four weeks?

(1) yes(2) no(3) DK

C18IF A1=1 and (C2=1 or C9b=1 orC14a=1 or C14b=1)

Did you use, in the course of your training and learning in the last fourweeks, electronic learning materials such as learning programmes onCD-ROM, in company-internal computer systems or on the Internet?

(1) yes(2) no(3) DK

C19IF C18=1

What did you use? Did you use(a) CD-ROMs or other so-called offline media such as diskettes, audioor video tapes etc.?(b) online learning materials provided on the internal computer systemof your organisation or through the Internet


C20IF IN2=2 and A1=1

Did you use, in the course of your studies in the last four weeks,electronic learning material such as learning programmes on CD-ROM,on the internal computer system of your school/university or throughthe Internet?

(1) yes(2) no(3) DK

C21IF C20=1

What did you use? Did you use(a) CD-ROMs or other so-called offline media such as diskettes, audioor video tapes etc.?(b) online learning material provided on the internal computer system ofyour school/university or through the Internet?


Module Z: Standard demography GPSFinally we would like to ask you a few more questions for statisticalpurposes:

Z17ALL

How many people live in your household, yourself included? |__|__|[DK]

Z18aIF Z17>1

How old is the youngest? |__|__|[DK]

Z18bIF Z17>1

How many are 15 years and older? |__|__|[DK][PROGRAMMER: Build in check with Z17 andZ18a]

Z14ALL

Do you have any long-standing illness, disability or infirmity that limitsyour activities in any way? By long-standing I mean anything that hastroubled you over a period of time or that is likely to affect you for aperiod of time.

(1) yes(2) no(3) DK

Z19ALL

We also need some information about the income of this household tobe able to analyse this survey.What is your household's monthly net income (after tax)? Please countthe total wages and salaries per month of all members of thishousehold; all pensions and social security benefits; child allowancesand any other income like rents etc.[ADD IF NECESSARY: Of course, your answer (as all other answers inthis interview) will be treated confidentially and referring back to you oryour household will be impossible.]Is it less or more than <income 1>, <income 2> or <income 3>.

(1) less than <income 1>(2) <income 1> to less than <income 2>(3<income 2> to less than <income 3>.(4 <income 3> or more(5) DK(6) Refusal


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Z20ALL

Looking back over the last three years, has your household incomeincreased, decreased, or remained roughly the same?

(1) increased(2) decreased(3) remained roughly the same(4) DK(5) Refusal

Z21ALL

Gender[INTERVIEWER: Ask only if in doubt]

(1) male(2) female

Data provided by survey organisation CategoriesP0 Survey Number 101438P1 Country Code |__|__|P2 Interview Number |__|__|__|__|P3 Date of Interview: Day |__|__|,

Month |__|__|P4 Time of the beginning of the interview (USE 24 HOUR CLOCK): Hour |__|__|,

Minute |__|__|P5 Number of minutes the interview lastet |__|__|__|P6 Size of locality |__|__|P7 Region |__|__|P8a Postal Code / Area code

must be convertible into NUTS 2 regions|__|__|__|__|__|__|__|__|

P8b NUTS 2 regions |__|__|__|__|__|__|__|__|P9 Interviewer Number |__|__|__|__|__|P10 Weighting Factor |__| . |__|__|__|__|__|P11 Language of interview (Luxembourg, Belgium, Finland, Switzerland) |__|


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9.3.2 Questionnaire for the Decision Maker Survey (DMS)

Structure of the questionnaire:

ü Introduction and Screener Section

Module A: Basic characteristics

ü Type of organisationü Number of staff (employees)ü Turnover

Module B: Module B: Basic ICTs take-up and intensity of use (e-Business)

ü e-Mailü Internetü Intranetü EDIü Video-conferencingü Call-centreü Staff access to ICTs

Module C: e-Commerce

ü Website/ Internet presenceü Online salesü Barriers to e-commerce (selling)ü Benefits from / Outcomes of e-commerceü Online procurementü Barriers to online procurementü Benefits from/ Outcomes of online procurementü Online supply chain integrationü e-Marketplaces

Module D: e-Business security

ü Security breachesü Information security strategyü Barriers to securityü Security provisions

Module F: e-Government

ü Use of e-Government servicesü Barriers to e-Government

Module G: Website accessibility

ü Design for all” / ”universal design” principle awareness

Module E: R&D

ü R&D staffü Computer staff in R&D unit(s)ü IT staff providing computer services to R&Dü Outsourced computer services for R&Dü Vacancies in IT for R&D


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Introduction and Screener Section DMSDatabase/address information: Categories

A11ALL

Main business activityPROGRAMMER: Copy from database

NACE code (2-digit level)I__I__I

1 Mining, Energy(includes NACE 10 - 14/ 40, 41)

2 Manufacturing(includes NACE 15 - 37)

3 Construction (includes NACE 45) 4 Distribution

(includes NACE 50, 51, 52)5 Hotels, Restaurants

(includes NACE 55)6 Transport, Communication (includes NACE 60, 61,62, 63, 64) 7 Banking, Insurance

(includes NACE 65, 66, 67)8 Business Services (includes NACE 70, 71, 72, 73, 74[except: 74.13]) 9 Public Administration

(includes NACE 75 [except 75.2])10 Education

(includes NACE 80)11 Health and Social Work

(includes NACE 85)12 Other personal or social services

(includes NACE 90, 91, 92, 93)


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A12ALL

Establishment/ size (if available)PROGRAMMER: Copy from database

According to databasea) OPEN (if available)I__I__I__I__I__I__I 6-digitnumerical[1] not available from database

and

b) in categories, i.e.(1) 0 - 9(2) 10 - 49(3) 50 - 199(4) 200 - 499(5) 500+(6) not available from database

S1 (INTRO)ALL

At reception/switchboard:Good morning/good afternoon. My name is ... . I am calling for... [name of institute].We are presently conducting a scientific survey in severalEuropean countries. The topic is the use of information andcommunications technologies. I would like to talk to the personwho is responsible for DP/IT decisions at your location.INT.: NOTE:THIS SHOULD BE THE HEAD OF THE DP/IT DPT. OR ASENIOR PERSON IN THE DP/IT DPT. IN SMALLER FIRMS ITCAN ALSO BE THE MANAGING DIRECTOR, THE GENERALMANAGER OR THE OWNER.INT.: ADD, IF NECESSARY:Your participation is very important to us, because your firm hasbeen selected through a statistical procedure that will result in atypical selection of firms in [COUNTRY]INT.: ADD, IF NECESSARY:The interview will last approx. 15 minutes

(1) put through to target person CONTINUE(2) target person currently unavailable MAKE APPOINTMENT FOR CALLBACK(3) no such person TERMINATE(4) refusal to participate END


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S2 (INTRO)ALL

At target person:Good morning/good afternoon. My name is ... . I am calling for... [name of institute].We are presently conducting a scientific survey in severalEuropean countries. The topic is the use of information andcommunications technologies. We are talking to people who areresponsible for DP/IT decisions at their respective locations.Can I just check: Would you be the right person to talk to at yourlocation and can we do the interview now?INT.: ADD, IF NECESSARY:Your participation is very important to us, because your firm hasbeen selected through a statistical procedure that will result in atypical selection of firms in [COUNTRY]INT.: ADD, IF NECESSARY:The interview will last approx. 15 minutes

(1) yes, interview now CONTINUE(2) yes but no time at the moment MAKE APPOINTMENT FOR CALLBACK(3) no, other person responsible at thislocation ASK TO BE PUTTHROUGH TO THAT PERSON ,

RESPECTIVELY ASK FOR CONTACTDETAILS. AT NEW TARGETPERSON START AGAIN WITH

QUESTION S2(4) no, other person responsible at anotherlocation TERMINATE(5) refusal to participate TERMINATE

A13ALL

Function of target personWhat is your position in your establishment? What of thefollowing is the most appropriate?INT.: READ OUT. SINGLE ANSWER.

(1) Owner/Proprieter(2) Managing Director/Board Member(3) Head of Establishment/Site(4) Head of IT/DP(5) Other senior member of IT/DPDepartment (6) Other TERMINATE

Module A: Basic characteristics DMSTransition A

ALLLet us start with some general questions about yourestablishment.

A2

ALLDoes your organisation have only one establishment, or has itmore than one establishment?By establishment we mean a single indentifiable unit at aparticular address.[TRANSLATOR: Be very careful to identify a correcttranslation for "establishment"]

(1) only one establishment(2) more than one establishment(3) DK

A4IF A2=2

How many employees does your organisation have in total in[country], including yourself?INT.: IF "DK" SAY:If you do not know it exactly, can you give me an estimate?

I__I__I__I__I__I__I 6-digitnumerical[DK]

A5ALL

And how many employees work for your organisation AT THISESTABLISHMENT, including yourself?INT.: IF "DK" SAY: If you do not know it exactly, can you giveme an estimate?

PROGR.: CHECK:IF A2=(2), Answer in A5 MUST be < Answer in A4!IF NOT RE-ASK A4 / A5

I__I__I__I__I__I__I 6-digitnumerical

[DK] TERMINATE INTERVIEW


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PROGR.: CHECK QUOTA (according to answer in A5)

1 up to 9 employees QUOTA2 10 - 49 employees QUOTA3 50 - 199 employees QUOTA4 200 - 499 employees QUOTA5 500+employees QUOTA

IF "DK" TO QUESTIONS A5

A3IF A2=2

Is your establishment ...?INT.: READ OUT ALL ANSWER CATEGORIES. SINGLE

ANSWER.

(1) the headquarters of an internationallyoperating organisation(2) the headquarters of an organisationthat only operates in this country(3) a division or branch operation of aninternationally operating organisation(4) a division or branch operation of anorganisation that only operates in thiscountry(5) other [INT.: DO NOT READ](6) DK

A8ALLEXCEPT IF A11 (NACE Code)= 75, 80, 85

Please indicate your establishment's turnover in the lastfinancial year.INT.: IF "DK", SAY:If you do not know it exactly, can you give me a rough estimate?INT.: PLEASE TRY TO GET AT LEAST AN ESTIMATE.

INDICATE IF ANSWER IS GIVEN IN EURO OR IN PREVIOUS NATIONAL CURRENCY (/UK: RESP. ORIN GBP)

(1) Turnover given IN EURO(2) Turnover given IN PREVIOUSNATIONAL CURRENCY (UK:Always use GBP)(3) DK, no answer to turnover

Turnover given:I__I__I__I.I__I__I__I.I__I__I__I.I__I__I

__I12-digit numerical

A9ALLEXCEPT IF A11 (NACE-Code)=75, 80, 85

Has the turnover of your establishment increased, decreased orroughly stayed the same when comparing the last financial yearwith the year before?

(1) increased(2) decreased(3) roughly stayed the same(4) DK

Module B: Basic ICTs take-up and intensity of use (e-Business) DMSTransition BALL

Now we would like to ask you some questions about the use ofInformation and Communications Technologies in yourestablishment.

B1ALL

Does your establishment use e-mail? (1) yes(2) no(3) DK


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B2ALL

Does your establishment have access to the World Wide Web,i.e. the Internet?

(1) yes(2) no(3) DK

B3ALL

Does your establishment have an Intranet, i.e. an internalcomputer network that uses the Internet protocol?

(1) yes(2) no(3) DK

B5ALL

Does your establishment use EDI, i.e. electronic datainterchange using the EDI standard?

(1) yes(2) no(3) do not know what this is [IFSPONTANEOUSLY SAID](4) DK

B6IF B5=1

Is your EDI Internet based? (1) yes(2) no(3) do not know what this is [IFSPONTANEOUSLY SAID](4) DK

B7ALL

Does your establishment use video-conferencing in your ownfacilities?

(1) yes(2) no(3) DK

B8ALL

Does your establishment use a call center for communicationwith customers or other external contacts?

(1) yes(2) no(3) DK

B11IF B1=1

Which applications can be accessed by the majority of youroffice workers?Can the MAJORITY OF YOUR OFFICE WORKERS... send e-mails to external addresses?

(1) yes(2) no(3) DK

B12IF B2=1

(What applications can be accessed by the majority of youroffice workers?)Can the MAJORITY OF YOUR OFFICE WORKERS... browse Internet sites?

(1) yes(2) no(3) DK

B13IF B3=1

(What applications can be accessed by the majority of youroffice workers?)Can the MAJORITY OF YOUR OFFICE WORKERS... browse INTRANET sites?

(1) yes(2) no(3) DK

Module C: E-commerce DMSTransition CALL

Now we would like to ask you some questions about E-commerce. Please refer to your establishment when answering.

C1ALL

Does your establishment put information on the Internet, forexample by means of a website?

(1) yes(2) no(3) DK

C2IF C1=1 or 3

Do you sell goods or services via the Internet? (1) yes(2) no(3) DK


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C3aIF C1=1 or 3

Do you offer online reservation? By this we mean that yourcustomers can make a reservation for a product or servicethrough the Internet.

(1) yes(2) no(3) DK

C3bIF C2=1

Do you distribute digital products or services online? By this wemean that the product is transferred to the customer online, orthe service is provided online.

(1) yes(2) no(3) DK

C4aIF C2=1

Are some of your online sales to businesses? (1) yes(2) no(3) DK

C5aIF C4a=1

How large a share of your total sales to businesses areconducted online?Would you say ...INT.: READ OUT. SINGLE ANSWER

(1) less than 5%(2) 5 up to 25%(3) 26 up to 50%(4) 51 up to 75%(5) more than 75%(6) DK

C4bIF C2=1

Are some of your online sales to consumers? (1) yes(2) no(3) DK

C5bIF C4b=1

How large a share of your total consumer sales are conductedonline?Would you say ...INT.: READ OUT. SINGLE ANSWER


C4cIF C2=1

Are some of your online sales to the public sector? (1) yes(2) no(3) DK

C5cIF C4c=1

How large a share of your total sales to the public sector areconducted online?Would you say ...INT.: READ OUT. SINGLE ANSWER


C6IF C2=1

Are your online sales MAINLY to a local, national or globalmarket?INT.: SINGLE ANSWER.

(1) local market(2) national market(3) global market(4) DK


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C7IF C1=2ORIF C2=2 or 3

I am now going to read you a list of statements about sellingonline. For each statement, please tell me whether you agreecompletely, agree somewhat or do not agree from the point ofview of your establishment.How about the statement ... [item].Do you ...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.

(a) Selling our products and services requires face-to-face interaction with customers

(b) The necessary technology is expensive(c) The costs for the promotion of the online offer are high(d) The revenue potential of online sales is low(e) Customers might be concerned about data protection or

security issues(f) Adapting corporate culture to e-commerce is difficult(g) The necessary skills are not readily available(h) Handling the delivery process causes problems

FOR EACH:(1) agree completely(2) agree somewhat(3) or do you not agree(4) DK

C8IF C2=1

You said earlier that you make sales online.According to your experience, what effect has selling online on... [item]?Would you say the effect is ...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) your sales(b) your costs(c) your sales area(d) the quality of your customer service(e) the efficiency of your internal business processes

FOR EACH:(1) very positive(2) rather positive(3) neither positive nor negative(4) rather negative(5) very negative(6) DK

C9IF B2=1 or 3

Do you use the Internet or other online services to purchasegoods or services?

(1) yes(2) no(3) DK

C10IF C9=1

Roughly what proportion of the maintenance, repair andorganisation goods your establishment buys are purchasedonline, measured in amount spent?Would you say ...INT.: READ OUT. SINGLE ANSWER



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C11IF B2=2ORIF C9=2 or 3

I am now going to read you a list of statements aboutpurchasing online. For each statement, please tell me whetheryou agree completely, agree somewhat or do not agree from thepoint of view of your establishment.How about the statement ... [item].Do you ...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.

(a) Purchasing procurement products or services requires face-to-face interaction with suppliers

(b) Our suppliers do not sell online(c) The necessary technology is expensive(d) The cost advantage is negligible(e) We are concerned about data protection or security issues(f) The legal protection of online contracts is not sufficient(g) The necessary skills are not readily available(h) Suppliers´ technical systems are not compatible with ours

FOR EACH:(1) agree completely(2) agree somewhat(3) or do you not agree(4) DK

C12IF C9=1

You said earlier that you purchase goods or services online.According to your experience, what effect has onlineprocurement on ... [item]?Would you say the effect is ...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) your procurement costs(b) stock-keeping of maintenance, repair and organisation

goods(c) the number of suppliers(d) your relations to suppliers(e) the efficiency of your internal business processes

FOR EACH:(1) very positive(2) rather positive(3) neither positive nor negative(4) rather negative(5) very negative(6) DK

C13IF C1=1

Does your establishment have an EXTRANET, i.e. a private,secure network running on the Internet protocol and accessiblefor selected external users?

(1) yes(2) no(3) DK

C14IF C13=1

For which of the following purposes do you use your Extranet?Do you use it for ... [item]INT.: ONE ANSWER PER ITEM.(a) communication with customers or clients?(b) communication with suppliers?


C15IF B2=1

Do you have access to the Extranet of one of your supplier,partner or customer organisations?PROGR.: IF C1=2 or 3, add:By Extranet I mean a private, secure network running on theInternet protocol and accessible for selected external users.

(1) yes(2) no(3) DK

C19IF B2=1

Does your establishment trade goods or services through an e-marketplace? By e-marketplace I mean a business-to-businessInternet trading forum in which multiple buyers and sellersexchange goods and services within an industry group orgeographic region.

(1) yes(2) no(3) DK


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C20IF C19=1

On e-marketplaces, different types of business transactions canbe accomplished. In which of the following types is yourestablishment actively involved?INT.: READ OUT AND CODE ALL THAT APPLY

(1) catalogue-based offering of products orservices(2) catalogue-based purchasing ofproducts or services(3) auctions -- as a seller(4) auctions -- as a bidder(5) launching calls for tenders(6) answering calls for tenders(7) powerbuying, i.e. joint purchasestogether with other organisations to savecosts(8) none of these(9) DK

Module D: e-Business security DMSTransition DIF C1=1

Let us now turn to the topic of information security. Again,please refer to your establishment when answering.

D1IF C1=1

Many establishments are affected by security breaches such asidentity theft, online fraud, manipulation of software applications,computer viruses or unauthorised entry to internal networks.Have any breaches of your information security occurred in yourestablishment in the last 12 months?

(1) yes(2) no(3) DK

D2aIF D1=1

Progr.: Note for D2a to D2b:For each item in D2a=1, ask directly D2b; then go to next item in D2a!!

Which of the following types of information security breacheshave occurred in your establishment in the last 12 months? Didyou experience cases of ... [item]?INT.: READ OUT. ONE ANSWER PER ITEM.(a) Identity theft(b) Online fraud(c) Manipulation of software applications(d) Computer virus infections(e) Unauthorised entry to internal networks


D2b(For Each Item) IF D2a=1

And how substantial were the consequences of this securitybreach for your establishment? Would you say they were ...INT.: READ OUT ANSWER CATEGORIES. SINGLE

ANSWER (PER ITEM ASKED)

FOR EACH ITEM IF D2a=1

(1) very substantial(2) rather substantial(3) not substantial(4) DK


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D3IF D1=1

Where do you believe these breaches mainly came from? Doyou think the largest threat to online security came from ...INT.: READ OUT ANSWER CATEGORIES. CODE ALL

THAT APPLY

MULTIPLE ANSWERS(1) Customers(2) Suppliers/competitors(3) Former employees(4) Computer hackers(5) Internal users(6) Others, not mentioned yet(7) DK

D4IF D1=1

How have you learned about these breaches, in most cases?Were you ... [item]INT.: READ OUT, CODE ALL THAT APPLY

MULTIPLE ANSWERS(1) alerted by a customer/supplier(2) alerted by employees or did you noticeyourself(3) notified by your own informationsecurity system(4) made aware by damage or loss of data(5) alerted by the providers of outsourcedsecurity services(6) in another way (DO NOT READ)(7) DK

D5IF C1=1

Does your establishment or your organisation have aninformation security policy?

(1) yes(2) no(3) DK

D6IF D5=1

How would you describe it? As formal or informal? (1) formal(2) informal(3) DK

D7IF D5=1

Which are your information security priorities?How much priority is given to ... [item]INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) Blocking of unauthorised access(b) Expanding budget for security measures(c) Defining the security architecture(d) Outsourcing security management

FOR EACH(1) high priority(2) medium priority(3) low priority(4) DK


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D8IF C1=1

How important are the following factors as barriers to effectiveinformation security inside your establishment?How about ...[item]:Is this factor as a barrier to effective information security insideyour establishment...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) High costs for security measures(b) Lack of staff training(c) Lack of staff time(d) Complexity of the technology(e) Lack of employee co-operation

FOR EACH:(1) very important(2) fairly important(3) not important(4) DK

D9IF C1=1

Which of the following tools do you use for information securityin your establishment? Do you make use of ... [item]INT.: ONE ANSWER PER ITEM.

(a) Control of access to the computer system(b) Cryptography/ data encryption(c) Vulnerability Assessment Tools(d) Firewalls(e) Security Training and Awareness Rising Activities(f) Intrusion Detection Systems(g) End-user Security Training Classes


Module F: e-Government DMSTransition FIF B2=1

Now let´s turn to the topic of using online services for interactingwith public administration.

F1IF B2=1 AND A11 (NACE-Code) NOT =75 (PublicAdmin)

Progr.: Note for F1 to F2:For each item in F1=2, ask directly F2; then go to next item in F1!!

I am going to read you a list of activities for whichestablishments have to get in touch with public administration.For which of these activities do you already use online mediasuch as EDI or the Internet?What about ...[item]? Do you use online media such as EDI orthe Internet for this?INT.: ONE ANSWER PER ITEM.

(a) Payment of social contribution for employees(b) Corporation tax declaration(c) VAT declaration(d) Submission of data to statistical offices(e) Obtaining environment-related permits(f) Participation in public invitation to tender



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F2(For Each Item)IF F1=2

Would your establishment prefer to use online media such asEDI or the Internet for this purpose?

FOR EACH ITEM IF F1=2(1) yes(2) no(3) DK

Transition F3IF B2=2 or 3

Now let´s turn to the topic of using online services for interactingwith public administration.It is now possible to conduct at lest some of the interaction withpublic administration online, i.e. by using EDI or the Internet.

F3ALL

Now I will read you a list of statements about using online mediafor interacting with public administration. Please tell me for eachstatement whether you agree completely, agree somewhat or donot agree.

Public services on the Internet ... [item].Do you ...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) are not useful enough(b) are faster than the traditional way(c) require that you install special equipment or software(d) reduce the number of mistakes public authorities make(e) do not seem as safe as using the traditional way(f) make it possible to deal with the authorities at more

convenient times(g) make it possible to deal with the authorities at more

convenient locations, e.g. from the workplace(h) are difficult to use

FOR EACH(1) agree completely(2) agree somewhat(3) or do you not agree(4) DK

Module G: Website accessibility DMSTransition GIF C1=1

Now a few questions about the accessibility of your website forpeople with special needs.

G1aIF C1=1

What priority has making your website user friendly for ... [item]in your establishment?INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.(a) People with visual disabilities or sight difficulties(b) People with reduced or limited dexterities(c) People with limited literacy

FOR EACH:(1) high priority(2) medium priority(3) low priority(4) DK

G1bIF G1a (a) =2,3orIF G1a (b) =2,3orIF G1a (c) =2,3

Bearing the these groups in mind: Would you say that yourwebsite could be adapted rather easily, would prove difficult toadapt, or could not at all be adapted to these people's needs?INT.: SINGLE ANSWER.

(1) could be adapted rather easily(2) would prove difficult to adapt(3) could not at all be adapted(4) DK


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G2IF G1a (a) =1,2orIF G1a (b) =1,2orIF G1a (c) =1,2

Does your establishment or your organisation have formalGuidelines for making your website accessible to people withsuch special needs? By guidelines I mean rules which have tobe followed by your website developers?

(1) yes(2) no(3) DK

G3IF G1a (a) =1,2orIF G1a (b) =1,2orIF G1a (c) =1,2)

Was your website ever evaluated concerning its accessibility forpeople with such special needs?

(1) yes(2) no(3) DK

G4IF G3=1

Was this evaluation done internally or using externalevaluators?INT.: SINGLE ANSWER.

(1) internal evaluation(2) using external evaluators(3) both(4) DK

Module E: R&D DMSE1aALL

You said before that xyz [PROGR.: Insert answer to questionA5] employees work for your organisation at this establishment.From this, how many work in research & development, i.e.R&D? Please add up possible part time R&D personnel to full-time personnel.INT.: IF "DK", PROMPT:If you do not know it exactly, can you give me an estimate?

INT.: IF NECESSARY, EXPLAIN:Among R&D we include all creative work undertaken on asystematic basis in order to increase the stock of knowledgeand the use of this stock of knowledge to devise newapplications.

[OPEN]I__I__I__I__I__I__I 6-digitnumericalINT.: IF NONE, CODE "0".[DK]

Progr.: Answer to E1a (Numberemployed in R&D)

must be ≤Answer to A5 (Total number

employed in establishment)

If not, re-ask E1aE1bIF E1a > 0and E1a is NOT DK

R&D can be centralised in R&D units, or it can be distributedover various units of an establishment.Do you have at least one central R&D unit at yourestablishment?

(1) yes(2) no(3) DK


NoBranching


134

E2IF E1b=1

What is the size of the computer staff in your central R&Dunit(s)? Please add up part time computer staff to full-time staff.

INT.: IF NECESSARY, EXPLAIN:By computer staff we mean all staff that- manages the computers, networks and digital resources, or- manages the Internet access and presentation, or- carries out information searches and computations as their major work tasks, or- provides user training.

INT.: IF "DK", PROMPT:If you do not know it exactly, can you give me an estimate?


Progr.: Answer to E2 (Computer staff inR&D)

must be ≤Answer to E1a (Number

employed in R&D)

IF NOT, re-ask E2E3IF E1a > 0and E1a is NOT DK

Do you get IT services for R&D from internal computer staff thatare not members of your central R&D unit(s)?

(1) yes(2) no(3) DK

E4IF E3=1

What is the size of the internal computer staff outside of yourR&D unit(s) who provide IT services for R&D projects? Pleaseadd up part time computer staff to full-time staff again.INT.: IF "DK", PROMPT:If you do not know it exactly, can you give me an estimate?


Progr.: Answer to E4 (Computer staffoutside

R&D) must be ≤Answer to A5 (Total number

employed inestablishment)

IF NOT, re-ask E4E5IF E1a > 0and E1a is NOT DK

Do you buy IT services for R&D from external service providers? (1) yes(2) no(3) DK

E6IF E5=1

What is the number of additional computer staff in yourestablishment that would be necessary to substitute for the ITservices for R&D projects which are currently obtained fromexternal service providers?INT.: IF "DK", PROMPT:If you do not know it exactly, can you give me an estimate?


E7IF E1a > 0and E1a is NOT DK

Do your R&D activities suffer from a low supply of qualifiedcomputer staff in your establishment?

(1) yes(2) no(3) DK


NoBranching


135

E8IF E7=1

Please specify the number of open jobs for computer staffneeded to provide IT services for R&D projects in yourestablishment?INT.: IF "DK", PROMPT:If you do not know it exactly, can you give me an estimate?

[OPEN]I__I__I__I__I__I__I 6-digitnumerical[INT.: IF NONE, CODE "0".[DK]

X1ALL

Finally I would like to ask you for a brief assessment:In the course of the interview we talked, among others, aboutthe areas e-Commerce, i.e. selling and buying online, and e-Government, i.e. interacting online with public administration.That is about areas, which might not necessarily fall into yourdirect responsibility.

Thinking back to the questions about ... [item]: What would yousay: How familiar were you with the topics covered in thosequestions? Would you say...INT.: READ OUT ANSWER CATEGORIES. ONE ANSWERPER ITEM.

(a) e-Commerce, i.e. selling and bying online(b) e-Government, i.e. interacting online with public

administration

FOR EACH(1) very familiar(2) fairly familiar(3) not very familiar(4) not at all familiar(5) DK/ no answer

X2ALL

And all in all: How interesting did you find the questionnaire as awhole?Would you say ...INT.: READ OUT ANSWER CATEGORIES. SINGLE ANSWER.

(1) very interesting(2) fairly interesting(3) not very interesting(4) not at all interesting(5) DK/ no answer

End TextALL

These were all my questions. I would like to thank you verymuch for participating in the interview.Have a nice day/evening!Data to be provided by survey organisation Categories

P0 Survey Number 1 0 1 4 3 9P1 Country Code |__|__|P2 Interview Number |__|__|__|__|P3 Date of Interview: Day |__|__|,

Month |__|__|P4 Time of the beginning of the interview (USE 24 HOUR CLOCK): Hour |__|__|,

Minute |__|__|P5 Number of minutes the interview lasted |__|__|__|P9 Interviewer Number |__|__|__|__|__|__|__|__|

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