The determinants of ICT competencies among employees

60 New Technology Work and Employment

The determinants of ICTcompetencies among employees

Kea Tijdens and Bram Steijn

This study aims to explain employeesrsquo adaptability to infor-mation and communications technology (ICT) using a repre-sentative sample of 713 employees in the Netherlands Thewillingness to acquire ICT competencies and the mastery ofequipment and software are primarily affected by intensity ofICT use an informated ICT strategy of the organisation andan intensive personnel policy

IntroductionIn February 2000 the European Commission (EC) launched an ambitious plan toenhance educational levels and employment opportunities within the European Union(EU) given the rise of the information society One such measure involves awardingall employees an opportunity to procure the requisite level of qualification The EChas therefore appealed to the national governments to develop activities directed atachieving this insofar as such activities have not yet already been initiated Concernsabout the competitive position of the member states in relation to the US are an impor-tant factor underlying this move (eg European Union 2000) At the next EU Summitin Portugal various decisions were taken in the interests of increasing the informationand communications technology (ICT) competencies of employees The Dutch gov-ernment has also taken steps to this end For example various departments have established committees to chart the departmental impact of the information society

However to date scientific insight into the processes that affect employeesrsquo adapt-ability to new ICT developments has been fragmented This article which is based onthe lsquoICT competencies 2002rsquo project aims to consolidate and expand such insight1 Itfocuses on the following key question lsquoWhat factors explain if and if so to whatextent employees build up ICT competenciesrsquo These factors are sought in character-istics of the employees themselves such as educational background gender job ratingand so on and in characteristics of the workplace such as organisational form andpersonnel policy In so doing concurrence is established with the discussion of so-

New Technology Work and Employment 201ISSN 0268-1072

Kea Tijdens is Associate Professor and Research Coordinator at AIAS the Amsterdam Institute ofAdvanced Labour Studies University of Amsterdam Bram Steijn is Associate Professor at the Depart-ment of Public Administration Erasmus University Rotterdam

copy Blackwell Publishing Ltd 2005 9600 Garsington Road Oxford OX4 2DQ UK and 350 Main Street Malden MA02148 USA

called new production concepts (cf ILO 2002) inasmuch as it can be assumed thatthese new production concepts offer employees ample opportunities for learning andadaptation

This article first addresses existing research into this field Section 3 then focuses onthe hypotheses data and research method The manner in which the most importantconcepts are put into practice follows in Section 4 and the analysis results are pre-sented in Section 5 The final section contains the conclusions

Previous studiesThe evolution of production processes in times of rapid technological change leads toa new challenge to education and training Positions gained according to years of edu-cation may not work as systematically and steadily as before (Soete 2001) Rates ofreturns to a given degree or course may change and will thus influence individualbehaviour as regards their willingness for information technology (IT)-related educa-tion Moreover it seems obvious to assume that individual employee characteristicswill influence this willingness For example research into employability shows thatwomen older people and less well-educated people have greater difficulty comply-ing with supplementary educational requirements than men younger people andwell-educated people (Gaspersz and Ott 1996 28 Webster 1996) Concerning womenit should be noted that establishing a balance between work and care obligationsmakes it particularly difficult to comply with supplementary educational require-ments In practice however there are few differences between men and women whenit comes down to actually pursuing an education (Gaspersz and Ott 1996 29 ROA1998) Differences in age and educational background therefore appear to be moreimportant determinants of differences in willingness for education and following sup-plementary education programmes (ROA 1998 25ndash26)

Without detracting from the significance of individual factors as determinants forwillingness for education we are especially interested in the importance of workplacecharacteristics In recent times the influence of these characteristics has been empha-sised in both educational (Eraut 1999 Onstenk 1997) and organisational research (cfILO 2002) Additionally there is an important link with the literature on new pro-duction concepts (Steijn 2003) Onstenk (1997) points out that these concepts can con-tribute significantly to opportunities for employee education For example workingin teams has a positive impact on learning because lsquoemployees cooperate intensivelyexchange information and discuss the distribution of workrsquo (p 351) Assuming thatsuch opportunities will indeed be utilised we can expect that these are linked to ahigher level of willingness among employees to utilise such opportunities with respectto new production concepts

A broad survey carried out recently by the International Labour Organisation (ILO)(2002) also points out that high performance work organisations offer increasingopportunities for education to the employees concerned Additionally reference ismade to numerous studies that reveal the actual educational level and training optionsas being genuinely higher within this type of organisation (cf Osterman 1995 Lynchand Black 1998) A similar link is also highlighted in a study carried out by Appel-baum et al (2000) that surmises that employees in high performance work systems notonly require higher qualifications but are also awarded greater opportunities to gainsuch an education Finally reference can be made to the views of Zuboff (1988) whostates that two possible strategies can in principle be pursued when introducing IT Inthe first approach only the functions are automated ruling out the possibility of genuinely new production concepts The second involves an information strategyOnly in the latter case are the opportunities presented by IT utilised fully and can em-ployee competencies develop furthermdashthis implies a de facto increase in educationalopportunities

Rather than focusing on the determinants of the willingness for education or edu-cational opportunities in general this article is directed at gaining greater insight intothe determinants of ICT skills and the willingness that exists to learn such skills As

copy Blackwell Publishing Ltd 2005 Determinants of ICT competencies 61

far as we can ascertain there has been no previous research into this area As suchthis article will certainly reveal more about the determinants of ICT competencies andthe willingness to learn them

Hypotheses data and research methodWe consider the variables referred to above to be indicators for the adaptability ofemployees to ICT developments The concept of adaptability is here operationalisedas (1) employeesrsquo willingness to master new ICT competencies and (2 and 3) their pastperformance with regard to ICT qualifications This past performance is operation-alised as the respondentrsquos own assessment of his or her level of mastery of the device most used by him or her (computer cash register and so on) and the programsused most frequently (word processor statistics package and so on) The respondentsmake both assessments by giving themselves scores out of 10 for their mastery of thesetwo aspects A high score indicates the level to which employees have succeededmdashatleast in their own mindsmdashin adapting to recent ICT developments The willingness to acquire new competencies indicates a level of willingness to adapt to new ICT developments

The central question in our survey is which factors are determining the adapt-ability of employees to ICT developments The discussion in Section 2 shows that alarge number of factors can influence this adaptability We divided these factors intofour clusters of explanatory variables The four clusters are personal characteristicsjob characteristics characteristics of the ICT with which employees work and character-istics of the workplace Therefore in this study four hypotheses will be tested

(1) We have assumed that adaptability is lower for employees with a lower educa-tion who do not have a vocational education who are older who are female andwho take care of the children at home

(2) We have assumed that adaptability is lower if job performance creates obstaclesso that these employees cannot acquire new competencies The study lsquoSkill-BiasedTechnological Changersquo (Autor et al 1998) for example suggests that employeeswith a weak position in the job market lag behind in the development of ICT com-petencies Likewise it is likely that employees in a busy job will have less time toadapt to new developments This is why we have assumed that adaptability islower if the job level and job security are lower the workload is higher in the caseof a temporary contract part-time work or a non-managerial position

(3) We have assumed that adaptability is lower the lower the intensity with whichthe employee works with ICT We have also assumed that the nature of the tech-nology will have an influence In this respect we have drawn a distinctionbetween embedded and programmable technology Embedded technology is builtinto the equipment used (as with cash registers) whereas with programmabletechnology the equipment offers more possibilities for operation Our hypothesisis that adaptability to ICT is lower if embedded technology is used because the lsquoautomaticrsquo nature of this technology by definition offers fewer learning opportunities

(4) We have assumed that the adaptability is lower in a Tayloristic workplace designthan in a non-Tayloristic design Second we have also assumed that a more inten-sive personnel policy will be accompanied by greater adaptability Finally we willassess what the effect is of the ICT strategy implemented in the organisation Fol-lowing on from Zuboff (1988) we have distinguished between an automationstrategy and an information strategy We expect an information strategy to beaccompanied by greater adaptability

In order to test the hypotheses for a representative sample of Dutch employees weused the Telepanel which is a database with more than 2000 households that are ques-tioned weekly with the aid of computers This panel is managed by CenERdata Panelat the University of Tilburg the Netherlands As the respondents form part of the com-puter panel the fact that their computer skills are higher than the lsquoaveragersquo employee

62 New Technology Work and Employment copy Blackwell Publishing Ltd 2005

cannot for that matter be excluded This means that it would be advisable to presentthe questions under a different setting too Although Telepanel itself emphasises therepresentative character of the panel the average educational level and job rating ofthe respondents also appears to be relatively high (cf Tijdens and Steijn 2002 6)Nonetheless this has no impact on determining the scope of the effects of differentindependent variables on their adaptability

The survey on ICT competencies was taken in January 2002 The respondentsmdashpeople in paid employment aged between 15 and 64mdashwere asked 50 questions A totalof 938 people (597 men and 341 women) answered questions about their ICT use andcompetencies their jobs the human resources management policy and other charac-teristics of the organisation in which they work The average age of the men in thedataset was 430 whereas it was 397 for the women Almost three-quarters live witha partner slightly more men than women (77 per cent versus 71 per cent) Dividedinto family phase relatively more men live in a family with young children and morewomen live in a family in which the children have already left home On average themen work 378 hours per week and the women 285 hours

Table 1 presents the descriptive statistics on both the variables to be explained andexplanatory variables The data revealed that the level of computer use in the Nether-lands is extremely high In 2002 89 per cent of employees indicated that they use oneor more automated devices in their work This is higher than in previous measure-ments (Steijn 2001a Wetzels and Tijdens 2001) In 1994 the same panel showed that71 per cent of employees used automated equipment By 2000 this had risen to 80 percent and a year later 84 per cent of employees were using automated equipment Inother words computer use has grown dramatically in recent years The use of com-puters in sectors such as financial and business services the civil service and educa-tion has risen to between 96 per cent and 97 per cent On the other hand sectors suchas utilities construction and garages have the lowest percentage at 77 per cent fol-lowed by the health-care and welfare sector at 81 per cent

The automated equipment is used intensively For example 43 per cent of computerusers spend more than three-quarters of their time at work using the equipment Inthis respect there is almost no difference between men and women The more inten-sively employees used the automated equipment the more their colleagues alsoworked with this equipment Therefore computer use takes place in a computerisedorganisation context Satisfaction with the most frequently used device is high andemployees felt that it is easy to use However they did not have a lot of say regard-ing the purchase of the equipment

The majority of computer users feel that the equipment in their department ismodern half of them feel that the equipment is used optimally and just under half ofthem stated that new equipment had been purchased in the past year There arenotable differences between computer users and nonusers For example computerusers are more optimistic than nonusers that their work will become more interestingThis also applies to the expectation that the content of the work will change and tothe chance that the work will incorporate more automated tasks in the futureHowever the groups do not differ in their expectations regarding whether their workwill come to an end

The answers to one of the survey questions are also worth noting in the context ofthe subject of this article how did the respondents acquire their current ICT compe-tencies It turns out that there are major differences in the manner in which respon-dents learned to master the device or software they use most frequently With regardto mastery of equipment respondents indicated that they taught themselves (70 percent) Courses (43 per cent) and colleagues (39 per cent) also turned out to be highlyimportant Note that the respondents were able to name more than a single methodof procurement In terms of software mastery these three learning methods were againthe most important although self-learning (39 per cent) plays a much smaller role inthis case It is notable that schools play a relatively minor role in the acquisition ofboth competencies (17 per cent and seven per cent respectively) However age doesplay a significant role 32 per cent of those under 30 years of age said that their schools


had contributed to their mastery of the most frequently used device This is 20 percent for the most frequently used program These percentages are much lower forthose over 30 Therefore school is a relatively important institution for young peoplein the acquisition of ICT competencies Similar findings from 239 computer end-usersin 50 manufacturing firms and service organisations in the US indicate much higherlevels of in-house training (Culpan 1995) When asked how they had learned to usecomputers 80 per cent had received in-house training 13 per cent indicated that theytaught themselves whilst seven per cent said their colleagues helped them Cross-national varieties as well as IT evolution between 1995 and 2002 may have affectedthese differences

Which factors determine whether and to what extent employees adapt their com-petencies to ICT developments After we have looked at the operationalisation of thekey variables in the next section Section 5 will examine this central concept UsingOLS regression analyses an assessment will be made for each cluster of independent


Table 1 Descriptive statistics of the dependent and independent variables

N Minimum Maximum Mean Standarddeviation

Variables to be explainedWillingness to acquire ICT 733 100 2000 1392 338

competenciesEquipment mastery for the 733 100 1000 746 135

most frequently used device (mark 1ndash10)

Software mastery for the 702 100 1000 748 130most frequently program (mark 1ndash10)

Individual characteristicsMale 733 000 100 065 048Age 20ndash29 733 000 100 008 028Age 30ndash39 733 000 100 032 047Age 40ndash49 733 000 100 033 047Vocational training diploma 733 000 100 062 049High educational level 733 000 100 048 050Low educational level 733 000 100 017 038

Job characteristicsManagerial position 733 000 100 040 049Sufficient job security 733 000 100 090 030High workload 733 000 100 072 045Permanent contract 733 000 100 097 018Full-time 728 000 100 069 046Job level (1 = low 5 = high) 716 100 500 344 095

IT characteristicsEmbedded technology 733 000 100 014 035Intensity ICT use 720 002 100 062 033

Workplace characteristicsInformated ICT strategy (3 = 692 300 1200 930 218

very weak 12 = very strong)

Tayloristic production concept 733 000 100 015 036Intensity personnel policy 733 000 500 344 155

(1 = low 5 = high)

variables of the influence of these variables on adaptability Each analysis incorporatesthe variables from previous clusters so that by the fourth and final cluster it becomesclear which cluster(s) of variables play(s) a key role In these analyses we will limitourselves to the 713 respondents who (1) use automated equipment in their work and(2) have been employed by the company they work at for at least one year The latterlimitation is necessary because there is a large chance that employees who have beenemployed for a shorter period will provide unreliable and incomplete information ontheir job characteristics and in particular the organisation characteristics An initialanalysis for example shows that many of these employees either failed to answerquestions related to personnel policy or answered them inadequately

OperationalisationAdaptability has been operationalised in Section 3 as (1) the willingness of employeesto acquire new ICT competencies (2) the respondentrsquos own opinion regarding his orher level of mastery of the device used most frequently by him or her (computer cashregister and so on) and (3) the respondentrsquos own opinion regarding his or her levelof mastery of the software used most frequently (word processor spreadsheet and soon) In this section the operationalisation will be described Means and standard devi-ations are presented in Table 1 In the next section we will assess the extent to whichthese variables are determining the employeersquos adaptability to ICT

Willingness to acquire ICT competencies was measured by using four Likert itemsforming a scale with an alpha of 074 An example of an item of this nature is lsquoI enjoylearning how computers or programs operatersquo (cf Tijdens and Steijn 2002 23) Respon-dentsrsquo scores were between 4 (very low willingness applies to 0 per cent of respon-dents) and 20 (extremely high willingness applies to three per cent of respondents)Of the respondents 77 per cent scored above the median (12) of the scale Along withthe mean scale score of 139 this indicates that the respondents have a generally positive attitude towards the acquisition of new ICT competencies

The opinions of employees regarding their mastery of both equipment and softwarewere measured by awarding marks from 1 to 10 This showed that the respondentshad a high opinion of their abilities The mean score for equipment mastery was 746and for software mastery 748 Only seven per cent rated themselves as unsatisfactoryand 52 per cent gave themselves 8 out of 10 or higher The respondents were equallypositive about their mastery of the software only six per cent rated themselves asunsatisfactory and 54 per cent gave themselves 8 out of 10 or higher

Four clusters of explanatory variables are distinguished in Section 3 The operation-alisation of the personal characteristics of gender and age speak for themselves Three educational levels are distinguished (low medium and high)2 Another variableindicates whether the respondentrsquos highest education was a vocational one or ageneral one Care for children was operationalised by using a dummy variable to indi-cate whether the respondent had responsibility at home for children below 12 yearsof age

In order to measure the job characteristics the job level was determined by usingthe SBC92 job classification of Statistics Netherlands which distinguishes five levelsprimary lower medium higher and academic occupations A distinction was alsodrawn between employees on a permanent contract (including those on temporarycontracts with prospects of a permanent contract) on the one hand and temporaryagency and casual staff and staff with a verbal agreement on the other Questionsabout part-time work a managerial position sufficient job security in the past yearand a high workload were answered by the respondents with either lsquoYesrsquo or lsquoNorsquo

The ICT intensity characteristic was determined by dividing the number of hoursper week that respondents worked with ICT by the total number of hours worked perweek The distinction between embedded and programmable equipment was madeby definingmdashfor the device used most frequently by the respondentmdashPCs laptopspalmtops terminals and CAD-CAM equipment as programmable and other devices(cash registers scanning equipment robots industrial equipment and copiersfax


machines) as embedded3 Operationalised in this manner 86 per cent of the respon-dents work primarily with programmable equipment

The three workplace characteristics included in this analysis were operationalisedas follows The workplace organisation was dichotomised into two types using the operationalisation in Steijn (2001b) Tayloristic and non-Tayloristic In order tomeasure the intensity of the personnel policy an assessment was made for fiveaspects relevant to personnel policy as to whether these were discussed between theemployee and a manager ie career opportunities job performance salary increasestraining and performance of manager The context within which this meeting betweenmanager and employee took place is therefore of no consequence It might be duringa formal performance review during a formal meeting of a different nature duringan informal meeting or during work discussions These aspects together formed ascale (alpha 074) that indicated the intensity of the personnel policy On average 344of these five aspects were discussed between the employee and their manager sevenper cent of respondents said that not a single subject was discussed with them 32per cent said that all five aspects had been discussed The third workplace charac-teristic is its ICT strategy Using the analogy of the distinction made by Zuboff (1988)this was measured by using a scale consisting of three Likert items The key issuewith these items is that the respondents were asked whether they could indepen-dently operate the automated equipment used The questions also related to the levelof proficiency with respect to the programs used independently Although includingtwo related items improves the scale (alpha = 083 cf Tijdens and Steijn 2002 30)these have not been included here because 31 respondents do use a device in orderto carry out their work but do not use a program The three items form a reasonablescale (alpha = 071) The answers to these items are added together creating a scalewith values ranging from 3 (highly automated) to 12 (highly informated) The averagescale score was 930 The fact that the median is 75 implies that on average therespondents were working in an informated situation This is further emphasised bythe fact that only two per cent of the respondents had the lowest scale score of three (= the most automated) and 20 per cent the highest score of 15 (= the most informated) Furthermore only 19 per cent of respondents had a scale score notexceeding 7

The determinants of employee adaptability to ICTAs indicated above adaptability to ICT is operationalised by means of a scale thatmeasures willingness to acquire ICT competencies and the scores awarded by respon-dents to themselves for their mastery of the device and software used most frequentlyby them The results of the analyses are shown in Tables 2 3 and 4 respectively

First we evaluate the relationship between the personal characteristics and thesethree dependent variables (see the first _ column in Tables 2 3 and 4) In terms of will-ingness to acquire ICT competencies gender and educational level are importantfactors females and employees with a lower education level were less prepared toacquire competencies than men and people with a medium and higher education levelAt the same time the absence of other significant effects is notable This means forexample thatmdashcontrary to earlier findings regarding their willingness to retrainmdasholder people are certainly not less prepared to acquire ICT competencies than youngpeople are The personal variables appear primarily to affect the estimation of themastery of the equipment males and employees in their twenties and thirties gavethemselves a higher score for mastery of the equipment than others did whilstemployees with a vocational education and with a high or low level of education gavethemselves a lower score than employees with a general education or with a mediumeducational level Age is also an important factor with regard to mastery of softwarepeople in their thirties gave themselves a higher score whilst employees with a voca-tional education and a low educational level gave themselves a lower score for masteryof software In none of the three analyses was the obligation to care for (young) chil-dren shown to play a significant role For this reason this variable was left out of the



Tabl

e 2

Exp

lain

ing

the

will

ingn

ess

to a

cqui

re I

CT

com

pete

ncie

s fr

om in

divi

dual

cha

ract

eris

tics

job

cha

ract

eris

tics

IT

cha

ract

eris

tics

and

wor

kpla

cech

arac

teri

stic

s

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

erro

rer

ror

erro

rer

ror

(Con

stan

t)13

98

031

13

43

082

12

24

087

11

34

096

In

div

idua

l cha

ract

eris

tics

Mal

e0

430

21

045

025

ns0

590

24

054

025

A

ge 2

0ndash29

-01

50

39ns

003

040

ns-0

05

040

ns-0

12

040

nsA

ge 3

0ndash39

011

027

ns0

150

27ns

013

027

ns0

070

27ns

Age

40ndash

490

400

26ns

046

026

ns0

440

26ns

044

026

nsV

ocat

iona

l tra

inin

g 0

400

21ns

029

022

ns0

490

22

050

022

d

iplo

ma

Hig

h ed

ucat

iona

l -0

50

022

-0

37

026

ns-0

40

026

ns-0

37

026

nsle

vel

Low

ed

ucat

iona

l -0

14

032

ns-0

20

033

ns-0

20

032

ns-0

11

032

nsle

vel

Job

char

acte

rist

ics

Man

ager

ial p

osit

ion

-00

50

21ns

000

021

ns-0

07

021

nsSu

ffici

ent

job

-00

80

35ns

-01

00

34ns

-00

90

34ns

secu

rity

Hig

h w

orkl

oad

038

023

ns0

460

23

045

023

Pe

rman

ent

cont

ract

082

058

ns0

900

57ns

076

057

nsFu

ll-ti

me

003

025

ns0

060

25ns

002

025

nsJo

b le

vel (

1 =

low

-01

50

14ns

-01

40

14ns

-02

10

15ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

70

34ns

-02

80

36ns

tech

nolo

gyIn

tens

ity

ICT

use

140

032

1

290

32

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

010

005

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

01

030

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

140

07

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

016

00

026

001

60

179

003

20

013

025

50

065

004

40

285

008

10

056

N69

768

067

166

3

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 3

Exp

lain

ing

the

equi

pmen

t m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifan

ceB

Stan

dar

dSi

gnifi

canc

eB

Stan

dar

dSi

gnifi

canc

eE

rror

Err

orE

rror

Err

or

(Con

stan

t)7

420

15

800

039

6

750

38

570

043

In

div

idua

l cha

ract

eris

tics

Mal

e0

190

10ns

009

012

ns0

160

11ns

007

011

nsA

ge 2

0ndash29

071

020

0

730

20

050

018

0

430

18

Age

30ndash

390

560

13

054

013

0

380

12

032

012

A

ge 4

0ndash49

022

013

ns0

200

13ns

015

012

ns0

130

12ns

Voc

atio

nal t

rain

ing

-03

70

10

-03

60

11

-02

40

10

-01

70

10ns

dip

lom

aH

igh

educ

atio

nal

-02

50

11

-02

60

13

-01

20

12ns

-00

60

12ns

leve

lL

ow e

duc

atio

nal

-03

40

15

-03

40

15

-02

90

14

-01

70

14ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n0

060

11ns

009

010

ns0

050

10ns

Suffi

cien

t jo

b -0

12

016

ns-0

02

015

ns-0

08

015

nsse

curi

tyH

igh

wor

kloa

d-0

22

011

-0

21

010

-0

24

010

Pe

rman

ent

cont

ract

-03

90

28ns

-02

70

25ns

-04

00

26ns

Full-

tim

e0

140

13ns

013

012

ns0

110

11ns

Job

leve

l (1

=lo

w0

010

07ns

004

007

ns-0

01

007

ns

5 =

high

)IT

cha

ract

eris

tics

Em

bed

ded

0

760

14

094

016

te

chno

logy

Inte

nsit

y of

IC

T u

se1

200

14

117

014

W

orkp

lace

cha

ract

eris

tics

Info

rmat

ed I

CT

0

120

02

stra

tegy

(3

=ve

ry

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c 0

170

14ns

prod

ucti

on

conc

ept

Inte

nsit

y pe

rson

nel

009

003

po

licy

(1 =

low

5

=hi

gh)

R R

2 adj

R2

024

60

060

005

10

270

007

30

056

042

80

183

016

60

489

023

90

218

N73

171

470

366

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant

analysis Therefore based on the overall picture it appears that personal variables donot play a very important role in ICT adaptability

The next step is to evaluate which explanatory effect the job characteristics of therespondents have (see the second B column in Tables 2 3 and 4) It appears that noneof the job variables included had a significant effect on willingness to acquire compe-tencies The explanation of differences in equipment and software mastery as a resultof job characteristics also appears to be small A high workload turns out to be linkedto a lower level of equipment mastery whilst a higher professional level is linked tobetter software mastery There were no other significant effects

The link with the two variables which characterise ICT paint a different picture (seethe third B column in Tables 2 3 and 4) These two ICT variables are important in theexplanation of ICT adaptability The intensity of technology use affects significantlythe willingness to learn ICT competencies the mastery of equipment and the masteryof software The use of embedded technology affects significantly the mastery of theequipment

Finally we assess the explanatory effect of the workplace characteristics (see thefourth B column in Tables 2 3 and 4) Of the three characteristics included the ICTstrategy and intensity of personnel policy significantly affect the three dependent vari-ables Willingness to acquire ICT competencies and equipment and software masteryare higher the more intensive the personnel policy is and the more informated the ICTstrategy is This is in line with what was expected on the basis of the literature Theassumption that adaptability would be lower for employees working in a Tayloristicsetting does not come true The workplace setting does not have an influence on thethree dependent variables

If we compare the influence of the four explanatory clusters for the employee adapt-ability to ICT (see the fourth B column in Tables 1 2 and 3) it then becomes clear thatof the personal characteristics only age has an effect with regard to mastery of theequipment and software Employees in their twenties and thirties rate their ownmastery of their equipment and software higher than do other age groups Howeverage does not play a role in the willingness to acquire ICT competencies The educa-tion characteristics initially appeared to be of importance but the effect of these wasnegated in the subsequent models by the added variables Taking all the aspects intoaccount we find that mastery of equipment and software are not affected by educa-tion Equally willingness to acquire competencies is also not affected by the educationlevel Yet employees with a vocational education have a greater willingness to acquirecompetencies Finally there did not appear to be any difference between men andwomen with regard to equipment and software mastery although men are more oftenwilling to acquire ICT competencies

The job characteristics turned out to have little effect on the adaptability to ICT Theydo not contribute to the explanation of mastery of the software Pressure of work wasthe only aspect that affected equipment mastery and the willingness to acquire com-petencies Employees under greater work pressure indicated a low level of mastery ofthe equipment and a higher willingness to acquire competencies One interpretationof this could be that employees have insufficient time to gain a thorough knowledgeof the equipment they work with although they do have a need and willingness todo so

The ICT characteristics have a relatively greater influence on the ICT adaptabilityEmployees who work with embedded technology have a greater mastery of the equip-ment The intensity of ICT use plays a particular role Employees who work moreintensively with ICT indicated a higher level of mastery of equipment and softwareand also a greater willingness to acquire ICT competencies

Finally two out of three workplace characteristics made a relatively important con-tribution to the explanation of ICT adaptability An informated ICT strategy leads toa higher level of mastery of equipment and software and also to a greater willingnessto acquire ICT competencies An intensive personnel policy has the same effect

However in all the analyses the variance eventually explained was relatively lowit was only above 20 per cent with regard to equipment mastery The level of expla-


nation of willingness to acquire ICT competencies in particular was low This levelof willingness may be due to an attitude that can scarcely be influenced by structuralcharacteristics and we probably need to look for more socio-psychological factors toexplain this attitude Nevertheless the analyses show that the workplace characteris-ticsmdashparticularly an informated ICT strategy and an intensive personnel policymdashplaya significant role in the explanation of willingness to acquire ICT competencies Thisfinding in particular provides points of departure for organisations when they aim toincrease the ICT adaptability of employees

ConclusionsIf the results of this analysis are representative of the Dutch working population thenit would appear that there are few problems in terms of adaptability to ICT Accord-ing to the employees surveyed their mastery of the equipment and software is highalthough a more lsquoobjectiversquo measurement of this is needed in order to confirm it Thewillingness to acquire additional ICT competencies appears predominantly high

In this respect there are differences between employees However these differencesare only linked to a limited extent to personal and job characteristics This largely dis-proves the expectations formulated in Section 3 The fact that gender is linked to will-ingness to acquire competencies indicates that it might be worthwhilemdashif one is tryingto achieve greater adaptability to ICTmdashpaying extra attention to women although itshould be remembered in that case that whilst women may appear to have a lowerwillingness to undergo training in practice they are at the same level as the men inactual educational activities (compare with Section 2) The fact that older employeesindicate a lower level of mastery of equipment and software but are no less willing toacquire competencies indicates that it is worthwhile focusing educational efforts onolder people The idea that they lsquowould not want torsquo is disproved by our analysisresults

Job characteristics are shown to be barely relevant in terms of adaptability pressureof work is the only factor that plays a modest role This role does raise the questionof how employees who are already verytoo busy can be given the opportunity toacquire the necessary additional competencies

The modest effect of the job characteristics has a primarily theoretical relevance Inconnection with the lack of effects of educational level this implies that at first sightwe cannot support the findings of the American Skill-Biased Technological Changesurvey (Autor et al 1998) in which it is suggested that employees with a weak posi-tion in the labour market will fall further and further behind in the development ofICT competencies Further investigation is required to investigate whether the Nether-lands faces similar developments because it may for example well be that the impor-tant role of intensive personnel policy is absorbing the effects of education and jobcharacteristics

In view of the results of the analysis our expectations regarding the effects of tech-nological and organisation characteristics have been confirmed to a greater extent thanour expectations regarding the personal and job characteristics Therefore they alsoappear to be more important as a determinant of adaptability One relevant finding isthat more intensive ICT use is linked to higher mastery and greater willingness toacquire ICT competencies This suggests that lsquolearning by doingrsquo would be a feasiblestrategy for influencing adaptabilitymdashto a degree employees adapt by themselves when they start working with or work more with ICT In this context however organi-sation characteristics also play an important role A more intensive personnel policyand applying an informated ICT strategy both result in a higher adaptability Oneremarkable aspect however appears to be that the organisational conceptmdashcontraryto the literature on the subjectmdashdoes not have a (direct) influence on adaptability Itshould be noted here that a link does exist between the organisational concept theintensity of personnel policy and the ICT strategy pursued in a Tayloristic productionconcept personnel policy is less intensive and a strategy of automation is more oftenpursued In this sense the organisational concept does tie indirectly with adaptability


In view of the fact that of all the variables discussed here the intensity of person-nel policy and the ICT strategy implemented are the most readily manipulated invest-ment in these two variables would seem to be the most effective if the intention is toincrease employeesrsquo adaptability to ICT

Acknowledgements

The Netherlands Research Organisation (NWO-Small Grant no 014-43-604) has sup-ported this research An earlier version of this paper was presented at the 2002 3rdFlemish-Dutch Labour Market Congress held in Rotterdam the Netherlands KevinMartley is acknowledged for the language revision of the text The dataset is availablefrom the NIWIKNAW Steinmetz-data archive no P1566

Notes

1 This article is based on a study of both authors into the competencies of employees in the infor-mation society (Tijdens and Steijn 2002) It follows on from previous research conducted bythe authors in this area (Steijn and de Witte 1996 Tijdens and van Klaveren 1997 Tijdens 19992002 Wetzels and Tijdens 2001 Steijn 2001a 2002 van Klaveren et al 2000 de Witte and Steijn2000)

2 Primary education lower secondary vocational education (LBO) and lower level general secondary education (MAVO) are considered lower-level education higher level general secondary education (HAVO) pre-university education (VWO) and upper secondary voca-tional education (MBO) are considered mid-level education and higher vocational education(HBO) and university education (WO) are considered as higher-level education

3 At httpwwwjasaorjpetenglishfaq_ehtml embedded technology is defined as followslsquoAt present it commonly means a system that includes hardware and software that is em-bedded in a single package and that operates independently Mobile devices used to takeorders at places such as restaurants mobile phones which play a key role in computer andhome electronics car navigators set-top boxes for digital TVs and digital cameras are ex-amples of modern embedded systems Embedded systems are improving not only to operate autonomously but also to be connected on wired or wireless networksrsquo

References

Appelbaum E T Bailey P Berg and A Kalleberg (2000) Manufacturing Advantage Why HighPerformance Work Systems Pay Off (Ithaca Cornell University Press)

Autor DH LF Katz and AB Krueger (1998) lsquoComputing Inequality Have ComputersChanged the Labor Marketrsquo The Quarterly Journal of Economics 113 1169ndash1213

Culpan O (1995) lsquoAttitudes of End-Users towards Information Technology in Manufacturingand Service Industriesrsquo Information amp Management 28 167ndash176

Eraut M (1999) Learning in the WorkplacemdashA Framework for Analysis Paper presented at theEARLI Conference Goumlteborg August 1999

European Union (2000) News Update Brussels European Union DG Employment and SocialAffairs DG Issue No 5 6 April 2000

Gaspersz J and M Ott (1996) Management van Employability Nieuwe kansen in arbeidsrelaties(Assen Van Gorcum)

ILO (2002) Supporting Work Place Learning for High Performance Working httpwwwclmsleacukWWWILOindexhtm (accessed 02_02_2003)

Klaveren M van KG Tijdens and C Wetzels (2000) lsquoTelewerken Wie waar en wanneerrsquoEconomisch Statistische Berichten 4278 D22ndashD26

Lynch LM and SE Black (1998) lsquoBeyond the Incidence of Employer-Provided Trainingrsquo Indus-trial and Labor Relations Review 51 1 6ndash31

Onstenk JHAM (1997) Lerend leren werken Brede vakbekwaamheid en de integratie van lerenwerken en innoveren (Delft Eburon)

Osterman P (1995) lsquoSkill Training and Work Organisation in American Establishmentsrsquo Indus-trial Relations 34 2 125ndash146

ROA (1998) Employability in bedrijf Naar een Employability Index voor bedrijfssectoren (MaastrichtROA)


Soete L (2001) lsquoICTs Knowledge Work and Employment The Challenges to Europersquo Interna-tional Labour Review 140 2 143ndash163

Steijn B (2001a) Werken in de informatiesamenleving (Assen Van Gorcum)Steijn B (2001b) lsquoWork Systems Quality of Working Life and Attitudes of Workers An Em-

pirical Study towards the Effects of Team and Non-Team Workrsquo New Technology Work andEmployment 16 3 191ndash203

Steijn B (2002) lsquoWinnaars en verliezers in de informatiesamenlevingrsquo in R Batenburg JBenders N van den Heuvel and J Onstenk (eds) Arbeid en ICT in onderzoek (Utrecht Lemma)pp 59ndash73

Steijn B (2003) lsquoICT and Production Conceptsrsquo in P Ester D Fouarge M Kerkhofs and C deWolff (eds) ICT en de Nederlandse arbeidsmarkt (The Hague Elsevier Bedrijfsinformatie) pp17ndash35

Steijn B and MC de Witte (1996) lsquoChaotische patronen in de regradatie van arbeid Een toets-ing van de interne differentiatiehypothesersquo Tijdschrift voor Arbeidsvraagstukken 12 2 108ndash123

Tijdens KG (1999) lsquoBehind the Screens The Foreseen and Unforeseen Impact of Computeri-zation on Female Office Workerrsquos Jobsrsquo Gender Work and Organization 6 1 47ndash57

Tijdens KG (2002) lsquoWerken in de digitale delta De ontwikkeling van enquecirctevragen om ICT-gebruik in organisaties te metenrsquo in R Batenburg J Benders N van den Heuvel and JOnstenk (eds) Arbeid en ICT in onderzoek (Utrecht Lemma) pp 75ndash90

Tijdens KG and M van Klaveren (1997) lsquoStatutory Regulation and Workersrsquo Competence TheInfluence of Dutch Works Councils on the Introduction of New Technologyrsquo Economic andIndustrial Democracy 18 3 457ndash488

Tijdens K and B Steijn (2002) Competenties van werknemers in de informatiemaatschappij Eensurvey over ICT-gebruik Amsterdam AIAS research report 11 httpwwwuva-aiasnetfilesaiasRR11pdf (accessed 02_02_2003)

Webster J (1996) Shaping Womenrsquos Work Gender Employment and Information Technology (LondonNew York Longman)

Wetzels C and KG Tijdens (2001) A Digital Dutch Miracle in Households and Firms DefinitiveReport for the Ministry of Economic Affairs (Delft TNO-STB 2001)

Witte M de and B Steijn (2000) lsquoAutomation Job Content and Underemploymentrsquo WorkEmployment and Society 14 2 245ndash265

Zuboff Z (1988) In the Age of the Smart Machine The Future of Work and Power (New York BasicBooks)


called new production concepts (cf ILO 2002) inasmuch as it can be assumed thatthese new production concepts offer employees ample opportunities for learning andadaptation

This article first addresses existing research into this field Section 3 then focuses onthe hypotheses data and research method The manner in which the most importantconcepts are put into practice follows in Section 4 and the analysis results are pre-sented in Section 5 The final section contains the conclusions

Previous studiesThe evolution of production processes in times of rapid technological change leads toa new challenge to education and training Positions gained according to years of edu-cation may not work as systematically and steadily as before (Soete 2001) Rates ofreturns to a given degree or course may change and will thus influence individualbehaviour as regards their willingness for information technology (IT)-related educa-tion Moreover it seems obvious to assume that individual employee characteristicswill influence this willingness For example research into employability shows thatwomen older people and less well-educated people have greater difficulty comply-ing with supplementary educational requirements than men younger people andwell-educated people (Gaspersz and Ott 1996 28 Webster 1996) Concerning womenit should be noted that establishing a balance between work and care obligationsmakes it particularly difficult to comply with supplementary educational require-ments In practice however there are few differences between men and women whenit comes down to actually pursuing an education (Gaspersz and Ott 1996 29 ROA1998) Differences in age and educational background therefore appear to be moreimportant determinants of differences in willingness for education and following sup-plementary education programmes (ROA 1998 25ndash26)

Without detracting from the significance of individual factors as determinants forwillingness for education we are especially interested in the importance of workplacecharacteristics In recent times the influence of these characteristics has been empha-sised in both educational (Eraut 1999 Onstenk 1997) and organisational research (cfILO 2002) Additionally there is an important link with the literature on new pro-duction concepts (Steijn 2003) Onstenk (1997) points out that these concepts can con-tribute significantly to opportunities for employee education For example workingin teams has a positive impact on learning because lsquoemployees cooperate intensivelyexchange information and discuss the distribution of workrsquo (p 351) Assuming thatsuch opportunities will indeed be utilised we can expect that these are linked to ahigher level of willingness among employees to utilise such opportunities with respectto new production concepts

A broad survey carried out recently by the International Labour Organisation (ILO)(2002) also points out that high performance work organisations offer increasingopportunities for education to the employees concerned Additionally reference ismade to numerous studies that reveal the actual educational level and training optionsas being genuinely higher within this type of organisation (cf Osterman 1995 Lynchand Black 1998) A similar link is also highlighted in a study carried out by Appel-baum et al (2000) that surmises that employees in high performance work systems notonly require higher qualifications but are also awarded greater opportunities to gainsuch an education Finally reference can be made to the views of Zuboff (1988) whostates that two possible strategies can in principle be pursued when introducing IT Inthe first approach only the functions are automated ruling out the possibility of genuinely new production concepts The second involves an information strategyOnly in the latter case are the opportunities presented by IT utilised fully and can em-ployee competencies develop furthermdashthis implies a de facto increase in educationalopportunities

Rather than focusing on the determinants of the willingness for education or edu-cational opportunities in general this article is directed at gaining greater insight intothe determinants of ICT skills and the willingness that exists to learn such skills As

































(1 = low 5 = high)















Tabl

e 2

Exp

lain

ing

the

will

ingn

ess

to a

cqui

re I

CT

com

pete

ncie

s fr

om in

divi

dual

cha

ract

eris

tics

job

cha

ract

eris

tics

IT

cha

ract

eris

tics

and

wor

kpla

cech

arac

teri

stic

s

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

erro

rer

ror

erro

rer

ror

(Con

stan

t)13

98

031

13

43

082

12

24

087

11

34

096

In

div

idua

l cha

ract

eris

tics

Mal

e0

430

21

045

025

ns0

590

24

054

025

A

ge 2

0ndash29

-01

50

39ns

003

040

ns-0

05

040

ns-0

12

040

nsA

ge 3

0ndash39

011

027

ns0

150

27ns

013

027

ns0

070

27ns

Age

40ndash

490

400

26ns

046

026

ns0

440

26ns

044

026

nsV

ocat

iona

l tra

inin

g 0

400

21ns

029

022

ns0

490

22

050

022

d

iplo

ma

Hig

h ed

ucat

iona

l -0

50

022

-0

37

026

ns-0

40

026

ns-0

37

026

nsle

vel

Low

ed

ucat

iona

l -0

14

032

ns-0

20

033

ns-0

20

032

ns-0

11

032

nsle

vel

Job

char

acte

rist

ics

Man

ager

ial p

osit

ion

-00

50

21ns

000

021

ns-0

07

021

nsSu

ffici

ent

job

-00

80

35ns

-01

00

34ns

-00

90

34ns

secu

rity

Hig

h w

orkl

oad

038

023

ns0

460

23

045

023

Pe

rman

ent

cont

ract

082

058

ns0

900

57ns

076

057

nsFu

ll-ti

me

003

025

ns0

060

25ns

002

025

nsJo

b le

vel (

1 =

low

-01

50

14ns

-01

40

14ns

-02

10

15ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

70

34ns

-02

80

36ns

tech

nolo

gyIn

tens

ity

ICT

use

140

032

1

290

32

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

010

005

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

01

030

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

140

07

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

016

00

026

001

60

179

003

20

013

025

50

065

004

40

285

008

10

056

N69

768

067

166

3

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 3

Exp

lain

ing

the

equi

pmen

t m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifan

ceB

Stan

dar

dSi

gnifi

canc

eB

Stan

dar

dSi

gnifi

canc

eE

rror

Err

orE

rror

Err

or

(Con

stan

t)7

420

15

800

039

6

750

38

570

043

In

div

idua

l cha

ract

eris

tics

Mal

e0

190

10ns

009

012

ns0

160

11ns

007

011

nsA

ge 2

0ndash29

071

020

0

730

20

050

018

0

430

18

Age

30ndash

390

560

13

054

013

0

380

12

032

012

A

ge 4

0ndash49

022

013

ns0

200

13ns

015

012

ns0

130

12ns

Voc

atio

nal t

rain

ing

-03

70

10

-03

60

11

-02

40

10

-01

70

10ns

dip

lom

aH

igh

educ

atio

nal

-02

50

11

-02

60

13

-01

20

12ns

-00

60

12ns

leve

lL

ow e

duc

atio

nal

-03

40

15

-03

40

15

-02

90

14

-01

70

14ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n0

060

11ns

009

010

ns0

050

10ns

Suffi

cien

t jo

b -0

12

016

ns-0

02

015

ns-0

08

015

nsse

curi

tyH

igh

wor

kloa

d-0

22

011

-0

21

010

-0

24

010

Pe

rman

ent

cont

ract

-03

90

28ns

-02

70

25ns

-04

00

26ns

Full-

tim

e0

140

13ns

013

012

ns0

110

11ns

Job

leve

l (1

=lo

w0

010

07ns

004

007

ns-0

01

007

ns

5 =

high

)IT

cha

ract

eris

tics

Em

bed

ded

0

760

14

094

016

te

chno

logy

Inte

nsit

y of

IC

T u

se1

200

14

117

014

W

orkp

lace

cha

ract

eris

tics

Info

rmat

ed I

CT

0

120

02

stra

tegy

(3

=ve

ry

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c 0

170

14ns

prod

ucti

on

conc

ept

Inte

nsit

y pe

rson

nel

009

003

po

licy

(1 =

low

5

=hi

gh)

R R

2 adj

R2

024

60

060

005

10

270

007

30

056

042

80

183

016

60

489

023

90

218

N73

171

470

366

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant



















Acknowledgements


Notes




References




























































(1 = low 5 = high)















Tabl

e 2

Exp

lain

ing

the

will

ingn

ess

to a

cqui

re I

CT

com

pete

ncie

s fr

om in

divi

dual

cha

ract

eris

tics

job

cha

ract

eris

tics

IT

cha

ract

eris

tics

and

wor

kpla

cech

arac

teri

stic

s

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

erro

rer

ror

erro

rer

ror

(Con

stan

t)13

98

031

13

43

082

12

24

087

11

34

096

In

div

idua

l cha

ract

eris

tics

Mal

e0

430

21

045

025

ns0

590

24

054

025

A

ge 2

0ndash29

-01

50

39ns

003

040

ns-0

05

040

ns-0

12

040

nsA

ge 3

0ndash39

011

027

ns0

150

27ns

013

027

ns0

070

27ns

Age

40ndash

490

400

26ns

046

026

ns0

440

26ns

044

026

nsV

ocat

iona

l tra

inin

g 0

400

21ns

029

022

ns0

490

22

050

022

d

iplo

ma

Hig

h ed

ucat

iona

l -0

50

022

-0

37

026

ns-0

40

026

ns-0

37

026

nsle

vel

Low

ed

ucat

iona

l -0

14

032

ns-0

20

033

ns-0

20

032

ns-0

11

032

nsle

vel

Job

char

acte

rist

ics

Man

ager

ial p

osit

ion

-00

50

21ns

000

021

ns-0

07

021

nsSu

ffici

ent

job

-00

80

35ns

-01

00

34ns

-00

90

34ns

secu

rity

Hig

h w

orkl

oad

038

023

ns0

460

23

045

023

Pe

rman

ent

cont

ract

082

058

ns0

900

57ns

076

057

nsFu

ll-ti

me

003

025

ns0

060

25ns

002

025

nsJo

b le

vel (

1 =

low

-01

50

14ns

-01

40

14ns

-02

10

15ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

70

34ns

-02

80

36ns

tech

nolo

gyIn

tens

ity

ICT

use

140

032

1

290

32

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

010

005

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

01

030

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

140

07

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

016

00

026

001

60

179

003

20

013

025

50

065

004

40

285

008

10

056

N69

768

067

166

3

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 3

Exp

lain

ing

the

equi

pmen

t m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifan

ceB

Stan

dar

dSi

gnifi

canc

eB

Stan

dar

dSi

gnifi

canc

eE

rror

Err

orE

rror

Err

or

(Con

stan

t)7

420

15

800

039

6

750

38

570

043

In

div

idua

l cha

ract

eris

tics

Mal

e0

190

10ns

009

012

ns0

160

11ns

007

011

nsA

ge 2

0ndash29

071

020

0

730

20

050

018

0

430

18

Age

30ndash

390

560

13

054

013

0

380

12

032

012

A

ge 4

0ndash49

022

013

ns0

200

13ns

015

012

ns0

130

12ns

Voc

atio

nal t

rain

ing

-03

70

10

-03

60

11

-02

40

10

-01

70

10ns

dip

lom

aH

igh

educ

atio

nal

-02

50

11

-02

60

13

-01

20

12ns

-00

60

12ns

leve

lL

ow e

duc

atio

nal

-03

40

15

-03

40

15

-02

90

14

-01

70

14ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n0

060

11ns

009

010

ns0

050

10ns

Suffi

cien

t jo

b -0

12

016

ns-0

02

015

ns-0

08

015

nsse

curi

tyH

igh

wor

kloa

d-0

22

011

-0

21

010

-0

24

010

Pe

rman

ent

cont

ract

-03

90

28ns

-02

70

25ns

-04

00

26ns

Full-

tim

e0

140

13ns

013

012

ns0

110

11ns

Job

leve

l (1

=lo

w0

010

07ns

004

007

ns-0

01

007

ns

5 =

high

)IT

cha

ract

eris

tics

Em

bed

ded

0

760

14

094

016

te

chno

logy

Inte

nsit

y of

IC

T u

se1

200

14

117

014

W

orkp

lace

cha

ract

eris

tics

Info

rmat

ed I

CT

0

120

02

stra

tegy

(3

=ve

ry

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c 0

170

14ns

prod

ucti

on

conc

ept

Inte

nsit

y pe

rson

nel

009

003

po

licy

(1 =

low

5

=hi

gh)

R R

2 adj

R2

024

60

060

005

10

270

007

30

056

042

80

183

016

60

489

023

90

218

N73

171

470

366

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant



















Acknowledgements


Notes




References











































Tabl

e 2

Exp

lain

ing

the

will

ingn

ess

to a

cqui

re I

CT

com

pete

ncie

s fr

om in

divi

dual

cha

ract

eris

tics

job

cha

ract

eris

tics

IT

cha

ract

eris

tics

and

wor

kpla

cech

arac

teri

stic

s

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

erro

rer

ror

erro

rer

ror

(Con

stan

t)13

98

031

13

43

082

12

24

087

11

34

096

In

div

idua

l cha

ract

eris

tics

Mal

e0

430

21

045

025

ns0

590

24

054

025

A

ge 2

0ndash29

-01

50

39ns

003

040

ns-0

05

040

ns-0

12

040

nsA

ge 3

0ndash39

011

027

ns0

150

27ns

013

027

ns0

070

27ns

Age

40ndash

490

400

26ns

046

026

ns0

440

26ns

044

026

nsV

ocat

iona

l tra

inin

g 0

400

21ns

029

022

ns0

490

22

050

022

d

iplo

ma

Hig

h ed

ucat

iona

l -0

50

022

-0

37

026

ns-0

40

026

ns-0

37

026

nsle

vel

Low

ed

ucat

iona

l -0

14

032

ns-0

20

033

ns-0

20

032

ns-0

11

032

nsle

vel

Job

char

acte

rist

ics

Man

ager

ial p

osit

ion

-00

50

21ns

000

021

ns-0

07

021

nsSu

ffici

ent

job

-00

80

35ns

-01

00

34ns

-00

90

34ns

secu

rity

Hig

h w

orkl

oad

038

023

ns0

460

23

045

023

Pe

rman

ent

cont

ract

082

058

ns0

900

57ns

076

057

nsFu

ll-ti

me

003

025

ns0

060

25ns

002

025

nsJo

b le

vel (

1 =

low

-01

50

14ns

-01

40

14ns

-02

10

15ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

70

34ns

-02

80

36ns

tech

nolo

gyIn

tens

ity

ICT

use

140

032

1

290

32

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

010

005

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

01

030

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

140

07

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

016

00

026

001

60

179

003

20

013

025

50

065

004

40

285

008

10

056

N69

768

067

166

3

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 3

Exp

lain

ing

the

equi

pmen

t m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifan

ceB

Stan

dar

dSi

gnifi

canc

eB

Stan

dar

dSi

gnifi

canc

eE

rror

Err

orE

rror

Err

or

(Con

stan

t)7

420

15

800

039

6

750

38

570

043

In

div

idua

l cha

ract

eris

tics

Mal

e0

190

10ns

009

012

ns0

160

11ns

007

011

nsA

ge 2

0ndash29

071

020

0

730

20

050

018

0

430

18

Age

30ndash

390

560

13

054

013

0

380

12

032

012

A

ge 4

0ndash49

022

013

ns0

200

13ns

015

012

ns0

130

12ns

Voc

atio

nal t

rain

ing

-03

70

10

-03

60

11

-02

40

10

-01

70

10ns

dip

lom

aH

igh

educ

atio

nal

-02

50

11

-02

60

13

-01

20

12ns

-00

60

12ns

leve

lL

ow e

duc

atio

nal

-03

40

15

-03

40

15

-02

90

14

-01

70

14ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n0

060

11ns

009

010

ns0

050

10ns

Suffi

cien

t jo

b -0

12

016

ns-0

02

015

ns-0

08

015

nsse

curi

tyH

igh

wor

kloa

d-0

22

011

-0

21

010

-0

24

010

Pe

rman

ent

cont

ract

-03

90

28ns

-02

70

25ns

-04

00

26ns

Full-

tim

e0

140

13ns

013

012

ns0

110

11ns

Job

leve

l (1

=lo

w0

010

07ns

004

007

ns-0

01

007

ns

5 =

high

)IT

cha

ract

eris

tics

Em

bed

ded

0

760

14

094

016

te

chno

logy

Inte

nsit

y of

IC

T u

se1

200

14

117

014

W

orkp

lace

cha

ract

eris

tics

Info

rmat

ed I

CT

0

120

02

stra

tegy

(3

=ve

ry

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c 0

170

14ns

prod

ucti

on

conc

ept

Inte

nsit

y pe

rson

nel

009

003

po

licy

(1 =

low

5

=hi

gh)

R R

2 adj

R2

024

60

060

005

10

270

007

30

056

042

80

183

016

60

489

023

90

218

N73

171

470

366

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant



















Acknowledgements


Notes




References






























Tabl

e 3

Exp

lain

ing

the

equi

pmen

t m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifan

ceB

Stan

dar

dSi

gnifi

canc

eB

Stan

dar

dSi

gnifi

canc

eE

rror

Err

orE

rror

Err

or

(Con

stan

t)7

420

15

800

039

6

750

38

570

043

In

div

idua

l cha

ract

eris

tics

Mal

e0

190

10ns

009

012

ns0

160

11ns

007

011

nsA

ge 2

0ndash29

071

020

0

730

20

050

018

0

430

18

Age

30ndash

390

560

13

054

013

0

380

12

032

012

A

ge 4

0ndash49

022

013

ns0

200

13ns

015

012

ns0

130

12ns

Voc

atio

nal t

rain

ing

-03

70

10

-03

60

11

-02

40

10

-01

70

10ns

dip

lom

aH

igh

educ

atio

nal

-02

50

11

-02

60

13

-01

20

12ns

-00

60

12ns

leve

lL

ow e

duc

atio

nal

-03

40

15

-03

40

15

-02

90

14

-01

70

14ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n0

060

11ns

009

010

ns0

050

10ns

Suffi

cien

t jo

b -0

12

016

ns-0

02

015

ns-0

08

015

nsse

curi

tyH

igh

wor

kloa

d-0

22

011

-0

21

010

-0

24

010

Pe

rman

ent

cont

ract

-03

90

28ns

-02

70

25ns

-04

00

26ns

Full-

tim

e0

140

13ns

013

012

ns0

110

11ns

Job

leve

l (1

=lo

w0

010

07ns

004

007

ns-0

01

007

ns

5 =

high

)IT

cha

ract

eris

tics

Em

bed

ded

0

760

14

094

016

te

chno

logy

Inte

nsit

y of

IC

T u

se1

200

14

117

014

W

orkp

lace

cha

ract

eris

tics

Info

rmat

ed I

CT

0

120

02

stra

tegy

(3

=ve

ry

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c 0

170

14ns

prod

ucti

on

conc

ept

Inte

nsit

y pe

rson

nel

009

003

po

licy

(1 =

low

5

=hi

gh)

R R

2 adj

R2

024

60

060

005

10

270

007

30

056

042

80

183

016

60

489

023

90

218

N73

171

470

366

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant


Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant



















Acknowledgements


Notes




References






























Tabl

e 4

Exp

lain

ing

the

soft

war

e m

aste

ry s

elf-

asse

ssm

ent

(mar

k 1ndash

10)

from

indi

vidu

al c

hara

cter

isti

cs j

ob c

hara

cter

isti

cs I

T c

hara

cter

isti

cs a

ndw

orkp

lace

cha

ract

eris

tics

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

BSt

and

ard

Sign

ifica

nce

Err

orer

ror

erro

rer

ror

(Con

stan

t)7

600

15

742

039

6

770

41

593

044

In

div

idua

l cha

ract

eris

tics

Mal

e-0

13

010

ns-0

13

012

ns-0

04

011

ns-0

10

011

nsA

ge 2

0ndash29

036

019

ns0

500

19

046

019

0

410

19

Age

30ndash

390

450

13

044

013

0

460

12

041

012

A

ge 4

0ndash49

021

013

ns0

160

13ns

018

012

ns0

180

12ns

Voc

atio

nal t

rain

ing

-03

10

10

-02

20

11

-00

90

10ns

-00

60

10ns

dip

lom

aH

igh

educ

atio

nal

-01

00

11ns

-02

90

13

-02

30

12ns

-01

90

12ns

leve

lL

ow e

duc

atio

nal

-03

20

15

-02

50

16ns

-02

30

15ns

-01

30

15ns

leve

lJo

b ch

arac

teri

stic

sM

anag

eria

l pos

itio

n-0

05

010

ns-0

03

010

ns-0

10

010

nsSu

ffici

ent

job

-00

30

17ns

-00

20

16ns

003

016

nsse

curi

tyH

igh

wor

kloa

d-0

07

011

ns-0

05

011

ns-0

05

010

nsPe

rman

ent

cont

ract

-02

90

28ns

-02

30

27ns

-03

40

26ns

Full-

tim

e0

000

12ns

-00

20

12ns

-00

50

12ns

Job

leve

l (1

=lo

w0

180

07

014

007

0

100

07ns

5

=hi

gh)

IT c

hara

cter

isti

csE

mbe

dd

ed

-03

10

16ns

-01

30

16ns

tech

nolo

gyIn

tens

ity

of I

CT

use

086

015

0

780

15

Wor

kpla

ce c

hara

cter

isti

csIn

form

ated

IC

T

009

002

st

rate

gy (

3 =

very

wea

k

12

=ve

ry s

tron

g)Ta

ylor

isti

c -0

02

014

nspr

oduc

tion

co

ncep

tIn

tens

ity

pers

onne

l 0

080

03

polic

y (1

=lo

w

5 =

high

)

R R

2 adj

R2

020

30

041

003

20

233

005

40

036

033

10

110

009

00

375

014

10

117

N70

068

367

466

6

Sour

ce

ICT

com

pete

ntie

s 2

002

p

lt0

01

plt

005

ns

=no

t si

gnifi

cant



















Acknowledgements


Notes




References















































Acknowledgements


Notes




References





























The determinants of ICT competencies among employees

Documents

Transcript of The determinants of ICT competencies among employees