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2007 21: 121Work Employment SocietyJohn Benson and Michelle Brown

Knowledge workers: what keeps them committed; what turns them away

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Introduction

Underpinning many human resproposition that organizationsmitted workforce (Coopey and

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Volume 21(1): 121–141[DOI: 10.1177/0950017007073623]

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Knowledge workers: what keeps them committed;what turns them away

■■ John BensonUniversity of South Australia

■■ Michelle BrownUniversity of Melbourne, Australia

ABSTRACT

There is a well established literature on the antecedents of organizational commitment,though the relative importance of these antecedents to particular groups of workersremains unclear. Relying on a general set of antecedents for all workers may result inthe application of inappropriate HRM policies and practices. Our focus is on knowl-edge workers as they have been identified as important to organizational success.Theliterature is, however, divided on what constitutes knowledge work so we developand apply a measure that focuses on what these workers do.We then use this mea-sure to examine attitudinal and behavioural commitment. We find, using responsesfrom 1969 employees, knowledge workers have higher attitudinal commitment andlower intention to quit than routine-task workers. Further, the antecedents of com-mitment for knowledge workers and routine-task workers differ in many importantrespects, creating challenges for organizational decision makers.

KEY WORDS

attitudinal commitment / HRM / intention to quit / knowledge workers / routine-taskworkers

ource management (HRM) policies is the need to develop and retain a highly com- Hartley, 1991; Guest, 1992). This stems

121 at SAGE Publications on January 17, 2011.com


from the belief that organizations must adopt strategies that enhance employees’commitment if they are to be competitive in a globalized world (Porter, 1990;Rayton, 2006; Walton, 1985; Womack et al., 1991). While the literature hasdebated the meaning of commitment (Meyer and Allen, 1997; Morris et al.,1993; Porter et al., 1974) it is now generally accepted that commitment refersto two distinct although related concepts: attitudinal commitment which rec-ognizes an individual’s identification with an organization, and behaviouralcommitment which focuses on an individual’s actions and the maintenance oforganizational membership (Iverson and Buttigieg, 1999: 308). A substantialbody of research has now been undertaken that has established many of theantecedents of commitment and the positive organizational consequences ofhaving a highly committed workforce.

While organizational commitment has now become a key HRM outcome thecommitment literature has generally treated the employees as homogeneous andignored the nature of the work undertaken by employees. This point was firstmade by Reichers (1985: 469) who pointed out that the organization in the com-mitment literature ‘is viewed as a monolithic, undifferentiated entity that elicitsan identification and attachment on the part of the individual’. Similarly, Coopeyand Hartley (1991: 20) reiterated this concern and contended that the commit-ment literature must address the nature of the organization. This deficiency in theliterature is surprising given that numerous management writers have pointed tothe complexity and multi-faceted nature of the modern organization and thatwith this complexity comes diversity in employees (Pfeffer and Baron, 1988).

The diversity in an organization’s workforce can be seen in a variety ofways: personal characteristics, position in the organization, or the type of workundertaken. While commitment research has made some attempt to accommo-date these differences it is this latter division which has largely remained unex-plored. Our article focuses on differences based on the type of work undertaken,with a particular examination of knowledge work. Knowledge work is identifiedby the emphasis on information processing, problem solving and the productionof knowledge (Barley, 1996; Fleming et al., 2004; Reed, 1996; Tam et al., 2002).Two questions will be addressed: first, are knowledge workers as committed tothe organization as those workers who undertake more routine tasks? Andsecond, whether the antecedents of commitment vary between these two groupsof workers. These are important questions for organizational policy makers asunderstanding the antecedents of organizational commitment of different groupsof workers can help them ‘fine tune’ their HRM policies and practices.

Organizational commitment and knowledge work

Organizational commitment

Workers, it has long been argued, are more likely to remain with an organiza-tion and increase work effort where management adopt strategies that enhancetheir commitment (Porter, 1990; Walton, 1985; Womack et al., 1991). Typically

122 Work, employment and society Volume 21 ■ Number 1 ■ March 2007



commitment refers to ‘the strength of an individual’s identification with andinvolvement in a particular organization’ (Porter et al., 1974: 604). Commitmentcan be characterized by three factors: a belief in and an acceptance of the orga-nizations’ goals and values; a willingness to exert considerable effort; and adesire to maintain organizational membership (Porter et al., 1974: 604).

To overcome confusion between the concept and outcomes (Reichers,1985; Morrow, 1993) a distinction has been made between attitudinal andbehavioural commitment (Coopey and Hartley, 1991; Iverson, 1996; Mowdayet al., 1982). Attitudinal commitment emphasizes an individual’s identificationwith and involvement in the organization. On the other hand, behavioural com-mitment is where the individual has a desire to maintain organizational mem-bership (Iverson, 1996; Salancik, 1977). Commitment has also been brokeninto affective, continuance and normative commitment (Meyer and Allen,1997). These categories refer to the psychological underpinning of attitudinalcommitment: individuals remain with an organization because they want to,they need to or they feel they ought to (Allen and Meyer, 1990: 4).

A substantial body of research now exists on the antecedents and outcomesof organizational commitment (see Mathieu and Zajac, 1990; Meyer et al.,2002). The research has shown that age, tenure, education, job satisfaction, dis-tributive justice, job security, role ambiguity and role conflict are consistentantecedents of commitment (Morrow, 1993). Moreover, this research showsthat high commitment is related to lower turnover (Jaros, 1997; Michaels andSpector, 1982; Mueller and Price, 1990; Porter et al., 1974; Williams andHazer, 1986), lower absenteeism (Angle and Perry, 1981; Sagie, 1998), highermotivation and involvement (Farrell and Rusbult, 1981; Somech and Bogler,2002; Stumpf and Hartman, 1984), higher job performance (Angle and Perry,1981; Mowday et al., 1974; Steers, 1977), a willingness to accept change(Brewer and Hensher, 1998; Iverson, 1996), organizational citizen behaviour(Mathieu and Zajac, 1990; Schappe, 1998), and ethical corporate values(Valentine et al., 2002).

This literature has also debated the meaning of commitment (Meyer andAllen, 1997; Morris et al., 1993; Porter et al., 1974), the relevance of the con-cept (Meyer and Allen, 1997; Morrow, 1983 and 1993), and the adequacy ofexisting measures (Morrow, 1993; Reichers, 1985). While these issues havenow been generally settled (see Meyer and Allen, 1997; Morrow, 1993) thecommitment literature has generally treated the organization as comprised ofhomogeneous employees and ignored the possibility that different groups ofworkers may have different levels of commitment. While studies have exploredthe commitment of particular groups of workers within organizations such asengineers (Baugh and Roberts, 1994), contract labour (Benson, 1998; Pearce,1993), teleworkers (Golden, 2006), nurses (Iverson, 1996), psychiatric techni-cians (Porter et al., 1974), teachers (Somech and Bolger, 2002), and lawyers(Wallace, 1995) little attempt has been made to compare these groups withother workers within the organization. One exception was Koslowsky (1990),although in this case the comparison was between police officers in the field and

123Knowledge workers Benson & Brown



those that undertook administrative work. More recently, the commitment ofknowledge workers has attracted some research interest including knowledgeworkers’ discretionary work effort and job satisfaction (Tam et al., 2002), andtheir perceptions of organizational justice (Thompson and Heron, 2005). Inthese cases, however, an occupational or sector-based definition of knowledgework was used and again no attempt was made to compare the commitment ofknowledge workers with other employees in the organization.

Knowledge work

The term knowledge work is often used to characterize the shift from routineoperational tasks to more varied and complex work (Barley, 1996; Cortada,1998; Frenkel et al., 1995; Mohrman et al., 1995). This change is seen as nec-essary if firms are to optimize the value of employees and so develop a com-petitive, global advantage (Horibe, 1999). The growth in certain professions,occupations and the so-called ‘new economy’ sectors of finance and informa-tion technology is cited as evidence of the growth and importance of knowledgework (Barley, 1996; Frenkel et al., 1999; Thompson and Heron, 2005).

The critical management literature has questioned the growth in this typeof work (Alvesson, 2004; Fleming et al., 2004; Sewell, 2000; Thompson andWarhurst, 1998; Thompson et al., 2001). Thompson and Warhurst argued thatmany jobs in these new ‘knowledge’ occupations still require routine tasks to beperformed and that labelling an ever increasing range of jobs as knowledgework provides ‘a misleading appearance of the growth of more knowledgeableworkers’ (1998: 4). This theme is echoed by Alvesson (2004) who claimed thatmuch work in many knowledge intensive firms is routine, and Fleming et al.(2004) who found that by ‘going below the surface’ the growth in occupationsthat were deemed to be knowledge work revealed a growth in many of the moreroutine aspects of work.

Despite these arguments knowledge work is often equated with work in‘high-tech’ or professional, business and informational service sector companies(Frenkel et al., 1999; Reed, 1996), with workers’ professional status such asengineers, scientists and lawyers (Lee and Maurer, 1997), or with particularoccupations such as R&D workers, software designers, telecommunication spe-cialists and financial analysts (Reed, 1996; Tam et al., 2002; Thompson andHeron, 2005). This broad occupational approach to determining knowledgework, as pointed out by Sewell (2000: 9), ‘belies a degradation in the nature ofsome “knowledge work” while simultaneously ignoring the increasing cogni-tive demands placed on many employees in traditional employment’. As a con-sequence, ‘for the critics, the term ‘‘knowledge worker’’ itself is precisely wherethe trouble starts, leading to scholastic debates about the nature of knowledge,not to research on knowledge workers’ (Rose, 2002: 156).

One way around this impasse is to focus on areas of agreement rather thanon the issues that divide researchers. One area of agreement is that, in somefields and some jobs, emphasis is increasingly placed on information processing,




problem solving and the production of knowledge (Barley, 1996; Fleming et al.,2004; Reed, 1996; Tam et al., 2002). Workers undertaking these tasks aredefined as knowledge workers as they perform complex tasks that requireincreasing amounts of knowledge and problem solving abilities (Reich, 1991;Reed, 1996), where the main tool and output is knowledge (Parker, 1994) andwhere the core task is thinking (Fisher and Fisher, 1998). In short, knowledgeworkers add value to the enterprise through ‘their ideas, their analyses, theirjudgement, their syntheses, and their design’ (Horibe, 1999: xi). As such theseworkers are key organizational assets and the retention of these workers aprime organizational objective (Alvesson, 2000, 2004; Amar, 2002; Lee andMaurer, 1997).

This definition is similar to the distinction between routine and non-routinework proposed by Pava (1983) and Mohrman et al. (1995), where routine work(programmed, repeated patterns, analysable, well understood, static) is contrastedwith the emergent, variable, unique, interdependent, uncertain and dynamicnature of knowledge work (Mohrman et al., 1995: 17). This distinction allowsknowledge work to be broken into three distinct, but inter-related dimensions.The first dimension is the variation and dynamic nature of the work undertaken(Frenkel et al. 1999; Horibe, 1999; Reed, 1996; Scarbrough, 1999; Tam et al.,2002). Knowledge work will involve considerable variety and the key tasks willoften be characterized by ‘incomplete cause–effect understanding, which intro-duces uncertainty into the work’ (Mohrman et al., 1995: 16). The seconddimension is the degree of reciprocal interdependence of work with other tasksbeing performed in the team or organization (Cortada, 1998; Frenkel et al.1999; Scarbrough, 1999; Tam et al., 2002; Wallace, 1995). This interdepen-dence is due to the ‘multiple, concurrent conversion processes that influenceeach other’ (Mohrman et al., 1995: 17) and that are taking place at any onetime. Interdependency may well extend to activities beyond the team and attimes it may seem ‘as though everything totally depends on everything else’(Pava, 1983: 51). The third dimension is the degree of autonomy employeeshave in carrying out their work (Frenkel et al., 1999; Kubo and Saka, 2002;Reed, 1996; Thompson and Warhurst, 1998; Wallace, 1995). Knowledgeworkers will need to make numerous judgments about a variety of job-relatedissues and it is this uncertainty in the decision making process that is a key char-acteristic of knowledge work (Mohrman et al., 1995: 17).

Classifying work by these three dimensions overcomes the problems asso-ciated with occupational or sector-based definitions of knowledge work. Theadoption of this definition means, however, that the little we know about thecommitment of knowledge workers may now be inaccurate as research onknowledge workers has focused on employees of ‘new economy’ sectors oroccupations such as scientists and IT experts (Alvesson, 2000; Lee and Maurer,1997; Tam et al., 2002). As a consequence, many workers in these studies mayhave been involved in quite routine work which would confound the results andprohibit the drawing of definite conclusions on the attitudinal or behaviouralcommitment of knowledge workers.




Research hypotheses and explanatory model

Research hypotheses

Employees undertaking ‘knowledge work’, such as highly skilled tradespersons, com-puter experts and professionals were thought to have low organizational commitmentand be more committed to their occupation or profession (Cook, 1996; Gouldner, 1957;Hebden et al., 1969). As Cook (1996: 25) argued, ‘Occupational commitment may eas-ily provide points of conflict with the value and goals of employers and non-professionalcolleagues.’ Other research suggested that professional commitment may, however, rein-force notions of organizational commitment, particularly for those who are satisfied intheir work (Baugh and Roberts, 1994; Herriot and Pemberton, 1995). Similarly, Wallace(1995) found that professional and career fulfilment enhanced organizational commit-ment while Thompson and Heron (2003) found a link between innovative behaviourand organizational commitment. In contrast, Koslowsky (1990) found that police offi-cers in the field had higher levels of job commitment than those serving as administra-tors although the two groups did not differ in their level of organizational commitment.

These mixed findings provide some support to Alvesson’s (2004: 146) claimthat ‘there appears no reason to see the most typical characteristics of profession-als in organizations in terms of tensions between loyalty to the profession and tothe bureaucracy’. Nevertheless, the complexity and ambiguity of knowledge work,coupled with knowledge workers strong professional orientation, would tend topromote less identification with the organization (attitudinal commitment) andhigher levels of intention to quit (behavioural commitment) relative to routineworkers. It is therefore hypothesized that:

Hypothesis 1: Employees undertaking knowledge work will have lower attitu-dinal commitment than employees undertaking routine work.

Hypothesis 2: Employees undertaking knowledge work will have higher inten-tions to quit (behavioural commitment) than employees under-taking routine work.

The literature has established many of the factors influencing commitment(Mathieu and Zajac, 1990; Meyer et al., 2002; Mottaz, 1988) though it has not, witha few exceptions (Frenkel et al., 1999), considered whether these factors are moreapplicable to particular groups of workers. However, studies on service workers, sci-entists, R&D workers and professional lawyers (Frenkel et al., 1999; Randle andRainnie, 1997; Thompson and Heron, 2005; Wallace, 1995) suggest that work orga-nization factors, such as co-worker support, are important influences on the com-mitment of knowledge workers. The nature and organization of knowledge workwould therefore suggest these factors would be more important to the level of com-mitment of knowledge workers. It is therefore hypothesized that:

Hypothesis 3: Work organization factors will be more important antecedents ofattitudinal commitment and intention to quit (behavioural com-mitment) for knowledge workers than for those employees under-taking routine work.




The explanatory model

A single multivariate model, based on the literature, was developed to test theimpact of type of work on attitudinal commitment and the intention to quit(hypotheses 1 and 2). This model will also be used to explore whether differentfactors effect attitudinal commitment and the behavioural commitment (‘inten-tion to quit’) of knowledge workers when compared to that of those employeesundertaking routine work (hypothesis 3). Antecedents of commitment can bebroken into three broad categories: employee characteristics, general organiza-tional variables and work organization. Our focus is on work organizationvariables as these appear to be the major differentiating factors between knowl-edge and routine-task workers (Frenkel et al., 1999; Randle and Rainnie, 1997;Thompson and Heron, 2005; Wallace, 1995). Employee characteristics andorganizational variables will therefore act as controls.

The four work organization variables included in the model were role ambi-guity, role conflict, co-worker support, and supervisor support. Role ambiguityand role conflict relate to the nature and impact of work organization and havebeen found to correlate negatively with job satisfaction and positively withpropensity to leave (Rizzo et al., 1970). Given the relationships of job satisfactionand propensity to leave with organizational commitment (Michaels and Spector,1982; Williams and Hazer, 1986) it is expected that both these variables will benegatively related to organizational commitment. Co-worker and supervisor sup-port relate to the way the employee and work organization interact. A friendlyand supportive work environment has been found to be instrumental in develop-ing commitment (Benson, 1998; Frenkel et al., 1999; Iverson and Buttigieg, 1999;Mottaz, 1988; Reichers, 1985).

The control variables included in the model were based on the findings ofprevious research (see Benson, 1998; Iverson, 1996; Iverson and Buttigieg, 1999;Mathieu and Zajac, 1990; Meyer and Allen, 1997; Mottaz, 1988; Mowdayet al., 1982). These included five employee characteristics – age, education,union membership, emotional state (negative affectivity) and job motivation,and five organizational variables – job security, pay level satisfaction, satisfac-tion with benefits, promotional opportunity and resource adequacy. Definitionsof all variables are provided in Table 1 while the proposed relationships of thesevariables to commitment and intention to quit are indicated in Table 3.

Methods

Setting and subjects

The case study approach is an appropriate methodology when a researcherwants to investigate ‘a contemporary phenomenon within its real life context’(Sarantakos, 1998: 192). As the objective of this research was to explore thecommitment of different groups of workers it was considered preferable toconduct the research in one organization so as to control for ‘extraneous’




variables that may impact on commitment and to locate the findings withintheir organizational context. Moreover, given that the research would involvedeveloping a multivariate model for testing a case study approach was appro-priate as it relies on the ‘prior development of theoretical propositions to guidedata collection and analysis’ (Yin, 1994: 13).

The case study site was a large Australian semi-governmental, scientificresearch organization (PSR). PSR’s primary roles are to carry out scientificresearch, to assist Australian industry, and to encourage and facilitate the appli-cation and use of scientific research. PSR was considered an appropriate casestudy site given its size (6957 employees), the nature of the work and the occu-pational diversity of its workforce: tradespersons, technicians, clerical staff, andmanagerial and scientific research workers. The size and diversity of PSR pro-vided the opportunity to effectively compare and contrast the antecedents oforganizational commitment of knowledge and routine-task workers in a realworld context using a quantitative data collection method (Yin, 1994).Moreover, PSR had a standard set of HR policies and practices and so the casestudy design provided effective control of these factors. Notwithstanding itssemi-governmental status, PSR could not be considered a typical ‘public sec-tor’ organization as it worked closely with private industry, derived morethan 30 percent of its income from commercial activities, and operated underits own industrial and enterprise agreements that had been negotiated with thelocal union.

A questionnaire was mailed to the work address of all employees in theperiod December 1998 to March 1999. Questionnaires were returned directlyto the researchers by 3335 employees, a response rate of 47.9 percent. No sig-nificant differences between the sample and the population were found ongender and geographical location (t-test, p < .05). Variable definitions and theirsource, together with their alpha reliability coefficients (Cronbach, 1951) arepresented in Table 1.

Measures

(a) Commitment and intention to quit

The nine-item version of Porter’s organizational commitment scale (Mowdayet al., 1979; Porter et al., 1974) was used to measure attitudinal commitment.This scale was used because of its reliability and validity (Beck and Wilson,2000; Mowday et al., 1979), and its widespread use and acceptance (Beck andWilson, 2000; Morris et al., 1993). Intention to quit was measured by twoadditional items taken from Porter’s index (Mowday et al., 1979; Porter et al.,1974). Factor analysis was performed on the 11 items with a clear divisionoccurring between the attitudinal commitment and intention to quit items.Scale scores were calculated by averaging the responses to the items. The relia-bility coefficient was .86 for commitment and .68 for intention to quit.1

Descriptive statistics for both scales are presented in Table 2.




Tabl

e 1

Vari

able

def

initi

ons

Varia

ble

Kno

wle

dge

wo

rker

s

Dep

ende

nt v

aria

bles

Com

mitm

ent

Qui

tPe

rso

nal c

hara

cter

isti

csA

geEd

ucat

ion

Uni

onN

egat

ive

affe

ct

Job

mot

ivat

ion

Org

aniz

atio

nal v

aria

bles

Job

secu

rity

Pay

leve

l sat

isfa

ctio

n

Def

initi

on a

nd c

onst

ruct

ion

The

deg

ree

to w

hich

an

empl

oyee

’s jo

b is

rep

etiti

ve (

thre

e ite

ms

from

Pri

ce a

nd M

uelle

r,19

81),

the

degr

ee t

o w

hich

the

job

relie

son

oth

ers

(thr

ee it

ems

from

Kan

ungo

,198

2),a

nd t

he d

egre

e to

whi

ch a

n em

ploy

ee h

as in

fluen

ce o

ver

his

or h

er jo

b (fo

ur it

ems

from

Tet

rick

and

LaR

occo

,198

7),a

lpha

=.7

5.A

five

-poi

nt s

cale

whe

re 5

=hi

gh k

now

ledg

e w

ork.

Res

pond

ents

with

sco

re o

f 3.9

2an

d ab

ove

are

clas

sifie

d as

kno

wle

dge

wor

kers

and

tho

se w

ith s

core

s of

3.4

0 an

d be

low

as

rout

ine-

task

em

ploy

ees.

The

ext

ent

to w

hich

an

empl

oyee

bel

ieve

s in

,and

acc

epts

an

orga

niza

tion’

s go

als

and

valu

es,t

oget

her

with

a w

illin

gnes

s to

exe

rtco

nsid

erab

le e

ffort

for

that

org

aniz

atio

n as

mea

sure

d by

nin

e ite

ms

from

Por

ter

et a

l.(1

974)

,alp

ha =

.86.

Five

-poi

nt s

cale

with

5 =

high

ly c

omm

itted

.In

tent

ion

to q

uit

as m

easu

red

by t

wo

item

s fr

om P

orte

r et

al.

(197

4),a

lpha

=.6

8.Fi

ve-p

oint

sca

le w

ith 5

=hi

gh w

illin

gnes

s to

leav

e.

Age

mea

sure

d in

yea

rs.

Nin

e le

vels

of e

duca

tion

rang

ing

from

yea

r 10

or

low

er (

=1)

to

PhD

( =

9).

Dic

hoto

mou

s va

riab

le w

here

1 =

unio

n m

embe

r.N

egat

ive

affe

ctiv

ity (

the

exte

nt t

o w

hich

an

indi

vidu

al e

xper

ienc

es a

vers

ive

emot

iona

l sta

tes

over

tim

e an

d ac

ross

situ

atio

ns)

asm

easu

red

by t

hree

item

s fr

om W

atso

n et

al.

(198

7),a

lpha

=.8

6.Fi

ve-p

oint

sca

le w

ith 5

=hi

gh n

egat

ive

affe

ctiv

ity.

An

empl

oyee

’s no

rmat

ive

belie

f in

the

impo

rtan

ce o

f wor

k.M

easu

red

by s

even

item

s fr

om K

anun

go (

1982

),al

pha

=.8

9.Fi

ve-p

oint

scal

e w

here

5 =

high

job

mot

ivat

ion.

The

ext

ent

to w

hich

an

empl

oyee

per

ceiv

es lo

ng-t

erm

,sta

ble

empl

oym

ent

with

the

org

aniz

atio

n.Jo

b se

curi

ty is

mea

sure

d by

thr

eeite

ms

from

Old

man

et

al.(

1986

),al

pha

=.8

5.Fi

ve-p

oint

sca

le w

ith 5

=hi

gh jo

b se

curi

ty.

An

empl

oyee

’s ge

nera

l sat

isfa

ctio

n w

ith p

ay le

vel.

Satis

fact

ion

with

pay

leve

l is

mea

sure

d by

tw

o ite

ms

from

Hen

eman

and

Sch

wab

(198

5),a

lpha

=.7

5.Fi

ve-p

oint

sca

le w

ith 5

=ve

ry s

atis

fied.

(con

tinue

d)

129 at SAGE Publications on January 17, 2011wes.sagepub.comDownloaded from


130

Tabl

e 1

(con

tinue

d)

Varia

ble

Satis

fact

ion

with

ben

efits

Prom

otio

nal o

ppor

tuni

ties

Res

ourc

e ad

equa

cy

Wo

rk o

rgan

izat

ion

Rol

e am

bigu

ity

Rol

e co

nflic

t

Co-

wor

ker

supp

ort

Supe

rvis

ory

supp

ort

Def

initi

on a

nd c

onst

ruct

ion

An

empl

oyee

’s sa

tisfa

ctio

n w

ith b

enef

its a

s m

easu

red

by t

wo

item

s fr

om H

enem

an a

nd S

chw

ab (

1985

),al

pha

=.6

6.Fi

ve-p

oint

sca

lew

ith 5

=ve

ry s

atis

fied.

An

empl

oyee

’s pe

rcep

tion

of p

rom

otio

nal o

ppor

tuni

ties

with

in t

he o

rgan

izat

ion.

Prom

otio

nal o

ppor

tuni

ties

are

mea

sure

d by

thr

eeite

ms

from

Pri

ce a

nd M

uelle

r (1

981)

,alp

ha =

.70.

Five

-poi

nt s

cale

with

5 =

good

pro

mot

iona

l opp

ortu

nitie

s.T

he d

egre

e to

whi

ch a

n em

ploy

ee p

erce

ives

res

ourc

es a

re a

dequ

ate

to p

erfo

rm t

he jo

b.R

esou

rce

adeq

uacy

is m

easu

red

by t

hree

item

s fr

om Iv

erso

n (1

992)

,alp

ha =

.80.

Five

-poi

nt s

cale

whe

re 5

=hi

gh r

esou

rce

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(b) Knowledge workers

To accommodate the three dimensions of knowledge work proposed earlier10 items from the scales measuring the degree of job repetition (Price andMueller, 1981), task interdependence (Kanungo, 1982) and autonomy (Tetrickand LaRocco, 1987) were utilized. The 10 items were subjected to principalcomponents factor analysis with three factors being extracted (eigen values > 1).The factor loadings corresponded to the three underlying dimensions of knowl-edge work. The major factor, however, accounted for 49.2 percent of theexplained variance and all 10 items loaded substantially on this factor with fac-tor loadings ranging from 0.41 to 0.71. The alpha reliability coefficient(Cronbach, 1951) for the 10 items was 0.75. These 10 items were summatedand divided by 10. Individual scores thus ranged between 1 and 5 with a meanof 3.66 and standard deviation of 0.52.

Respondents were classified as knowledge workers if their score was morethan half a standard deviation above the mean while workers whose score wasmore than half a standard deviation below the mean were classified as routine-task workers. This classification led to 28.5 percent of respondents (N=920)being classified as knowledge workers and 32.5 percent of respondents(N=1049) being labelled as routine-task workers. The remaining respondentswere excluded from this study, resulting in an effective sample size of 1969.2

(c) Independent and control variables

Age, education, and union membership were single-item variables. The remaining11 variables were modifications of established scales (see Table 1) and includednegative affectivity (Watson et al., 1987), job motivation (Kanungo, 1982), jobsecurity (Oldman et al., 1986), pay level satisfaction (Heneman and Schwab,1985), satisfaction with benefits (Heneman and Schwab, 1985), promotionalopportunities (Price and Mueller, 1981), resource inadequacy (Iverson, 1992), roleambiguity (Rizzo et al., 1970), role conflict (Kahn et al., 1964), co-worker support(House, 1981), and supervisor support (House, 1981). The reliability of the scales(Cronbach, 1951) ranged from .66 for satisfaction with benefits3 to .90 for super-visor support. Descriptive statistics for these variables are presented in Table 2.

Statistical analysis and model estimation

Hypotheses 1 and 2 will be evaluated by a combination of t-tests and ordinaryleast squares (OLS) regression techniques. OLS allowed us to partial out theeffects of the employee characteristics and general organizational variables andto focus our attention on work organization.4 The testing of Hypothesis 3 alsoused OLS techniques with the knowledge work variable being used to catego-rize the data into two groups; knowledge workers and routine-task workers.The possibility of multicollinearity rendering the estimates unreliable appearedlow for two reasons. First, a variance inflation test (vif) was run for all models




(reported in Table 3). In all cases the mean vif was below 1.5; substantiallybelow the level at which problems can occur (Chatterjee et al., 2000). Second,the correlations between all variables in the model were relatively small andwere well below the .80 figure at which multicollinearity can be considered aproblem (Studenmund and Cassidy, 1987).5

Results

Hypothesis 1 was not supported. As shown in Table 2, knowledge workers had a sig-nificantly higher attitudinal commitment than routine-task workers (0.37, p < .01). Thisdifference remained statistically significant after controlling for the 14 employee andorganizational variables discussed in Section 3. Hypothesis 2 was also not supportedwith knowledge workers having a significantly lower intention to quit (behaviouralcommitment) than routine-task workers (0.49, p < .01). Again, this difference remainedstatistically significant after controlling for the 14 variables discussed above.6


Table 2 Descriptive statistics

Mean (SD) Mean (SD) Mean (SD)Variable Full sample Knowledge workers Routine-task workers

Dependent variablesCommitment 3.37 (0.64) 3.57 (0.56)* 3.20 (0.66)Quit 2.73 (0.88) 2.47 (0.82) 2.96 (0.87)*

Employee characteristicsAge 42.11 (10.04) 44.27 (9.52)* 40.18 (10.11)Education 6.36 (2.45) 7.21 (2.45)* 5.61 (2.42)Union member 0.56 (0.5) 0.61 (0.49)* 0.52 (0.50)Negative affect 2.78 (0.82) 2.65 (0.95) 2.90 (0.87)*Job motivation 2.68 (0.82) 2.96 (0.76)* 2.43 (0.79)

Organizational variables Job security 2.73 (0.99) 2.92 (1.01)* 2.57 (0.95)Pay level satisfaction 3.14 (0.92) 3.34 (0.92)* 2.97 (0.88)Satisfaction with benefits 3.45 (0.77) 3.54 (0.78)* 3.36 (0.74)Promotional opportunity 2.90 (0.89) 3.25 (0.88)* 2.59 (0.77)Resource adequacy 3.26 (0.87) 3.14 (0.86) 3.36 (0.93)*

Work organizationRole ambiguity 3.67 (0.69) 3.85 (0.67)* 3.51 (0.66)Role conflict 2.79 (0.81) 2.67 (0.85) 2.89 (0.78)*Co-worker support 3.51 (0.80) 3.76 (0.72)* 3.29 (0.80)Supervisor support 3.65 (0.94) 3.90 (0.86)* 3.43 (0.96)

Notes: a. N ranged between 1827 and 1969 for individual items in the full sample (knowledge and routine-taskworkers).b. *p < .01 (t-test, two-tail) between the knowledge and routine-task worker samples.



Hypothesis 3 was partially supported. Separate OLS regressions were car-ried out for knowledge workers and routine-task workers for both dependent vari-ables. The model explained substantial amounts of variance in the attitudinalcommitment of knowledge workers (24%) and of routine-task workers (37%).Results are presented in the first two columns of Table 3. Three important differ-ences between the two groups of workers were identified. First, the explanatorypower of the model, as measured by the adjusted R2, was substantially higher forroutine-task workers than for knowledge workers. Second, three of the four workorganization variables (role ambiguity, co-worker and supervisor support) weresignificant determinants of attitudinal commitment for knowledge workers; onlyrole ambiguity and supervisor support were significant for routine-task workers.Third, while there were a number of significant common control variables in bothmodels negative affectivity was an important determinant of knowledge workers’attitudinal commitment while job security and satisfaction with benefits wereimportant determinants of the attitudinal commitment of routine-task workers.

A similar pattern was found with intention to quit (behavioural commit-ment) (see columns 3 and 4 of Table 3). Two key differences existed betweenthe two groups of workers. First, the explanatory power of the model was againsubstantially higher for routine-task workers (23%) than for knowledge work-ers (17%). Second, for knowledge workers, two work organization variables(co-worker and supervisor support) were significant determinants of intentionto quit; neither of these factors was significant for routine-task workers. Third,while again there were a number of significant common control variables inboth models the one difference was that role ambiguity was an importantdeterminant of intention to quit for routine-task workers.

Discussion and conclusion

Using a measure of knowledge work based on its key attributes (variation,interdependency and autonomy) we found that knowledge workers were dis-tributed across all occupational groups. This finding provided support for thosewho argued that the growth in knowledge work cannot be measured by occu-pational changes (Fleming et al., 2004). Contrary to our hypotheses knowledgeworkers had a significantly higher attitudinal commitment than routine-taskworkers and a lower intention to quit. This finding suggests that the attitudeand values of knowledge workers may be different to their professional coun-terparts (Cook, 1996) and supported the notion that job commitment may rein-force organizational commitment (Baugh and Roberts, 1994; Herriot andPemberton, 1995). The lower level of intention to quit may, however, be areflection of the external labour market and the prestigious status of PSR: itsinternational standing has been important in retaining knowledge workers evenin the face of increased competition from private and better funded researchorganizations. Alternatively, the semi-governmental status of PSR may meanthat knowledge workers are more risk averse when it comes to considering




changing employment. There is, however, no reason to believe that this wouldnot equally apply to both groups of employees. Finally, it was found that thelevel of attitudinal and behaviour commitment of knowledge workers was morelikely to be determined by work organization factors such as the relationshipwith supervisors and co-workers than was the case for routine-task employees.


Table 3 Organizational commitment and intention to quit of knowledge workers (KW) and routine-task workers (RTW): OLS regression

Commitment Intention to Quit

Variable KW RTW KW RTW

Intercept 2.53 1.34 4.46 4.91(0.23) (0.26) (0.36) (0.37)

Age (+/−) –0.00 0.01 –0.01** –0.01**(0.01) (0.00) (0.00) (0.00)

Education (−/+) –0.05** –0.04** 0.05** 0.05**(0.01) (0.01) (0.01) (0.01)

Union member (−/+) –0.02 –0.00 –0.08 –0.04(0.04) (0.04) (0.06) (0.06)

Negative affect (−/+) –0.04* –0.02 0.07* 0.12**(0.02) (0.02) (0.03) (0.03)

Job motivation (+/−) 0.26** 0.37** –0.16** –0.30**(0.02) (0.02) (0.04) (0.04)

Job security (+/−) 0.00 0.06** –0.01 0.02(0.02) (0.02) (0.03) (0.03)

Pay level satisfaction (+/−) –0.00 0.03 –0.12** –0.12**(0.02) (0.03) (0.04) (0.04)

Satisfaction with benefits (+/−) 0.02 0.07* –0.02 –0.00(0.03) (0.03) (0.04) (0.04)

Promotional opportunity (+/−) 0.05* 0.12** –0.16** –0.18**(0.02) (0.03) (0.04) (0.04)

Resource adequacy (+/−) 0.07** 0.05* –0.01 0.02(0.02) (0.02) (0.03) (0.04)

Role ambiguity (−/+) –0.08** –0.11** 0.03 0.11*(0.03) (0.03) (0.05) (0.05)

Role conflict (−/+) –0.02 –0.03 0.05 0.06(0.02) (0.03) (0.03) (0.04)

Co-worker support (−/+) 0.07* 0.01 –0.09* –0.04(0.03) (0.03) (0.04) (0.04)

Supervisor support (−/+) 0.07** 0.07** –0.08* –0.05(0.02) (0.02) (0.04) (0.03)

Adjusted R2 0.24 0.37 0.17 0.23Mean vif 1.27 1.33 1.27 1.32

* p < .05; ** p < .01. Note: unstandardized coefficients; standard errors in parentheses.Note: the signs in parentheses after each variable represent the proposed relationship between the variable andcommitment and intention to quit respectively.



These findings have important implications for the management of knowledgeworkers. While these workers have a strong attitudinal commitment to theorganization and a lower intention to quit the key factor in maintaining thiscommitment was work relationships. A positive relationship with co-workerswas crucial to attitudinal commitment while this coupled with a positive rela-tionship with their supervisor were crucial to knowledge workers’ lower inten-tions to quit. Factors previously found to be important for attitudinalcommitment, such as job security and satisfaction with benefits, and for inten-tion to quit such as role ambiguity were not important to knowledge workers,although they were important for routine-task workers.

These findings suggest that managerial policies to enhance commitment(Becker et al., 1996; Iverson and Buttigieg, 1999) may need to be tailored to theneeds of different groups of workers. While Guest (1992) raised doubts as towhether commitment can be managed the research showed that the commit-ment of knowledge workers was related to aspects of work organization andthe way these workers were managed. The development of strong systems ofco-worker support via such mechanisms as teams will clearly be important forbuilding and maintaining stronger organizational commitment among knowl-edge workers. In addition, supervision must accommodate a higher degree offreedom so as to allow knowledge workers to carry out their work unimpeded.In contrast, providing job security or improving benefits, factors important tothe commitment of routine-task workers, will be unlikely to have an apprecia-ble effect on knowledge workers. The challenge for organizations is thus todevelop and apply policies that recognize the different antecedents of commit-ment without creating conflict between them. For organizational commitmentresearchers, the theoretical and empirical challenge is to develop and testmodels that recognize the heterogeneous nature of work. A set of HRM poli-cies that might be effective in promoting commitment of one group of employeesmay be detrimental to the commitment of another group of employees withinthe same organization.

This research has provided a means to further advance our understandingof the commitment of knowledge workers by defining knowledge workers onthe basis of what they do rather than who they are (Blackler, 1995: 1023).Nevertheless, further research is required in three areas to test and extend thesefindings. First, future commitment research will need to extend this line ofinquiry by examining knowledge workers in a range of private sector organiza-tions where there exists a greater capacity to differentiate on pay, working con-ditions and employment contracts than there was in PSR. Second, moreattention must be focused on understanding the key attributes of knowledgework and how these characteristics are played out in the work setting. This willallow for further refinement of the definition and measure of knowledge workused in this article. Finally, the model developed in this article explained sub-stantial amounts of variance in commitment and intention to quit. For knowl-edge workers the amount of variance explained was lower than that forroutine-task workers. As such, research will need to explore more deeply the




processes involved in knowledge work if we wish to more fully understandwhat keeps these workers committed and what turns them away.


Notes

1 The alpha coefficient for the scale ‘intention to quit’ was slightly lower than the0.70 recommended as the lower bound for the acceptance of a scale (Cortina,1993). Following the method outlined by Cortina (1993) the inter-item anditem-total correlations were examined for the two items making up this scale.The inter-item correlation was 0.52 and the item-total correlations in bothcases exceeded 0.86 thus indicating this scale had acceptable reliability.

2 Analysis using the full sample and distinguishing on the basis of the meanyielded no meaningful differences to that reported in this article.

3 In this case the inter-item correlation was 0.51 and the item-total correlations inboth cases exceeded 0.84. This indicates that this scale had acceptable reliability.

4 The dependent variables were attitudinal commitment and intention to quit. Asboth variables were made up of a number of items the process of summatingscores and dividing by the number of items meant that resultant scores approx-imated interval data. As such OLS regression was selected as this technique issufficiently robust to handle this type of data (Berry and Feldman, 1985).

5 A full correlation matrix is available from the authors upon request.6 Ten of the 14 variables proved to be significantly related to either commitment

or intention to quit, with seven of these variables being statistically significantin both models. The number of significant variables in the model indicates therobustness of these findings.

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John Benson

John Benson is Professor and Head of the School of Management at the University of

South Australia. Previous appointments include Professor and Chair of the School of

International Business at the University of Tsukuba (Japan) and Reader in the Department

of Management and Marketing at the University of Melbourne. His major research inter-

ests are Japanese management and unions, the restructuring of Chinese industry, out-

sourcing and knowledge work. John has published numerous articles and monographs and

his most recent work is Unemployment in Asia (Routledge: London, 2006) with Ying Zhu.

Address: School of Management, University of South Australia, North Terrace,Adelaide,

South Australia, Australia, 5001.

E-mail: [email protected]

Michelle Brown

Michelle Brown is a an associate professor in the Department of Management and

Marketing at the University of Melbourne. Previous appointments have been with the

University of Wisconsin, Milwaukee and Victoria University. She has research interests in

labour market adjustments, employee participation and performance management sys-

tems. Recent work in these areas has appeared in Industrial and Labor Relations Review,

Group and Organization Management and the British Journal of Industrial Relations.A book

examining performance pay in eight countries (Paying for Performance: An International

Comparison) was published in 2002 (with John S. Heywood).

Address: Department of Management and Marketing, Faculty of Economics and

Commerce, University of Melbourne, Parkville, Australia, 3010.

E-mail: [email protected]

Date submitted July 2005Date accepted August 2006



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Work, Employment & Society, 21, 121 - Sage