Does gender matter? A reviewof work-related gender

commonalitiesG. Ronald Gilbert and Meredith F. Burnett

Department of Management and International Business,College of Business Administration, Florida International University,

Miami, Florida, USA

Ian PhauSchool of Marketing, Curtin University of Technology, Perth, Australia, and

Jerry HaarDepartment of Management and International Business,

College of Business Administration, Florida International University,Miami, Florida, USA

Abstract

Purpose – The purpose of this study is to examine the degree to which differences and similaritiesexist between female and male business professionals.

Design/methodology/approach – A total of 1,164 students from three English-speaking countriescompleted a 75-item multi-dimensional tool that consists of 17 empirically independent work preferenceconstructs associated with psychological learning styles, work values, work interests, and personalitytemperament.

Findings – There are few notable or significant differences between the work preferences of femaleand male business professionals within each country. Differences between the work preferences offemale and male business professionals are not consistent from nation to nation.

Research limitations/implications – Additional research on gender differences of workpreferences needs to include larger samples of college students majoring in non-business subjectsas well as working adults drawn from related occupational fields.

Practical implications – Managers need to understand that biological sex may be irrelevant whenit comes to the selection, placement, training, development, and appraisal of employees.

Originality/value – Contrary to prior research, the results refute the existence of work-relateddifferences between females and males.

Keywords Gender, Culture

Paper type Research paper

IntroductionThe participation of women in the global labour force has increased dramatically overthe past three decades, occurring in nations of varying levels of development (Raynor,2007). Given the emerging global economy, understanding gender and culturaldifferences is critical to business success (Parboteeah et al., 2008; Stedham andYamamura, 2004).

Current research in management presumes the existence of work-related differencesbetween females and males. However, it is not known if notable differences exist

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1754-2413.htm

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Gender in Management: AnInternational JournalVol. 25 No. 8, 2010pp. 676-699q Emerald Group Publishing Limited1754-2413DOI 10.1108/17542411011092336

among those who are engaged in comparable work. If no practical differences exist,then the challenge of managing gender gaps should be of little practical concern. In thisstudy, we will examine the degree to which differences and similarities exist betweenfemale and male business professionals.

TheoryBehavioural researchers have undertaken several strategies to discern disparities asthey relate to the performance of working female and male adults in organisations.Their research on gender differences is generally associated with either culture valuesystems (Hofstede, 1980; House et al., 2004) or personal attributes (Eagley, 1987;Malach-Pines and Kaspi-Baruch, 2008). The findings from cultural studies indicatethat males are more aggressive and competitive and less gentle, tender minded andconcerned with home and family than females (Hofstede, 1980, 2001; House et al.,2004). Subsequent examinations show that value differences between males andfemales are more evident in high-power distance cultures than low-power distancecultures (Parboteeah et al., 2008). Cumulatively, these differences present uniquechallenges to those who are responsible for the effective management of globalteams.

In this study, we examine the personal attributes (as opposed to cultural values) ofmales and females with a specific focus on English-speaking business professionals whoshare similar cultural values. It seeks to answer the question: “Are there differences inthe personal attributes of females and males among business professionals who arelikely to work together in teams and across national boundaries?”

Research on personal attributes and gender. Gender differences that relate topersonal attributes reported in the literature are vast. Table I provides a brief summaryof some of the more notable differences based on six categories:

(1) biology/heredity;

(2) intelligence/aptitude;

(3) academic achievement;

(4) personality;

(5) interests; and

(6) work values.

What are the causal explanations of gender differences? The evolution/heredityexplanation of a gender differences suggests that the key factors associated with themare attributed to different hormonal characteristics that occur as a result of evolution(Boring, 1969; Buss, 1984). These theorists believe different adaptive challengesthroughout evolutionary history resulted in different responses by male and females toprocreation, pregnancy, childbirth, child-rearing, hunting, arousals needed to detectand avoid danger, and the like. The theory is not exclusively biologically deterministic.Rather, it suggests that there are biological predispositions that may be potentiatedunder specific environmental conditions, and in this regard, the human psychologicalsystem functions in response to its environment.

The social learning explanation of gender differences is based on social role theory(Eagley, 1987). The basis of this theory is a reciprocal interaction of the individual withthe environment (Bandura, 1999). This psychological foundation holds that males and

Does gendermatter?

677

S.

no.

Psy

chol

ogic

alle

vel

Psy

chol

ogic

alle

vel

char

acte

rist

ics

Gen

der

dif

fere

nce

sb

etw

een

men

and

wom

enS

ourc

eof

fin

din

g

1.B

iolo

gic

al/

her

edit

ary

Th

atw

hic

his

tran

smit

ted

gen

etic

ally

from

gen

erat

ion

tog

ener

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dw

omen

var

yw

ith

reg

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tom

otor

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oman

tic

attr

acti

on,

and

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ance

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and

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(198

5),

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e-Q

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dsp

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esh

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mu

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ity

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less

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ity

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sd

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pro

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ity

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(200

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acad

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ich

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nce

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kel

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alit

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Men

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feel

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mit

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8),

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(200

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ckli

n(1

974)

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Ru

ther

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(200

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dy

and

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l(2

000)

,F

ein

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d(1

994)

,M

un

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and

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ney

(200

6)

(continued

)

Table I.Summary of researchfindings on genderdifferences forpsychological levels

GM25,8

678

S.

no.

Psy

chol

ogic

alle

vel

Psy

chol

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alle

vel

char

acte

rist

ics

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dif

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etw

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and

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eof

fin

din

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Mal

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ore

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ean

dop

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idea

sM

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ea

hig

her

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esar

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ssp

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less

ten

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rted

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ork

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rest

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tab

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nst

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tion

ofp

sych

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ical

char

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that

are

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eto

ind

ivid

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s

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essc

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low

eron

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lan

d’s

RIA

SE

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tist

ic,

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al,

and

con

ven

tion

altr

aits

Mal

essc

ore

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her

onH

olla

nd

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EC

real

isti

c(i

.e.

mec

han

ics,

carp

entr

y,

etc.

)an

din

ves

tig

ativ

etr

aits

Cos

taet

al.

(198

4),

Wes

term

anan

dS

imm

ons

(200

7),

Lip

pa

(200

1),

Hir

sch

ian

dL

age

(200

7),

Bet

zet

al.

(199

6),

Pre

dig

er(1

976)

,H

olla

nd

(199

2)

Mal

esar

ele

ssp

eop

le-o

rien

ted

Mal

esd

emon

stra

tem

ore

inte

rest

inth

ing

s,d

ata,

and

idea

s6.

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e/w

ork

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intr

insi

call

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able

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fean

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yto

val

ue

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mp

lish

men

tan

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dep

end

ence

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etal.

(200

5),

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rim

anet

al.

(200

9)

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esar

ele

ssli

kel

yto

val

ue

frie

nd

ship

and

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alit

yM

ales

pla

cem

ore

imp

orta

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onh

igh

sala

ries

,tak

ing

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s,an

dor

gan

isat

ion

alp

rest

ige

Mal

esp

lace

less

val

ue

onw

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,re

spec

tin

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gu

es,

clea

nw

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ity

and

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ily

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dfr

ien

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ips

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ele

ssti

me

toth

eir

care

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Table I.

Does gendermatter?

679

females are potentially alike. They are, however, differentiated as a result of roleexpectations or from learned social roles through cultural, social, and otherenvironmental factors (Eagley, 1987; Shafiro et al., 2003).

The evolution and social learning interaction explanation of gender differencessuggests disparities between females and males are a result of the interaction of bothevolution (i.e. genetics) and culture (i.e. gender or environmental influences) (Hicks et al.,2008). It is believed that evolutionary and social influences form the highly complexstage upon which humans enact their stories, individually and collectively. Othersubject matter experts view evolutionary and social role influences as practicallyirrelevant. Instead, they suggest that there are more similarities between females andmales than differences (Epstein and Feist, 1988; Hyde, 2005; Macoby and Jacklin, 1974).These researchers point to the fallibility of gender difference research and suggest thevariations are minor (Hyde, 2005; Singer et al., 2005). Thus, they hold that differencessuch as those presented in Table I are questionable in terms of the practicalimplications for those who manage female and male employees.

What are the bases for gender similarities hypotheses? People tend to focus more onthe differences between females and males when the similarities between them areoften much greater (Hyde, 2005; Tarvis, 1992). Differences found between males andfemales indicate that the degree of variance between the two may be marginal.Although many studies show statistically significant differences between females andmales, the effect sizes associated with the differences are weak. This may indicate that,in practice, those differences are trivial and have little practical importance.

In the following, we pose three theoretical explanations to assume gender similarityamong English-speaking students who are part of the business profession.

The commonly shared language explanation of gender similarities is based on theGLOBE study (House et al., 2004) which found that cultural values and beliefs areinfluenced by those sharing a common language.

The commonly shared social institutions explanation of gender similarities suggeststhat national institutions contribute to the socialisation of shared knowledge, values, andnorms of those affected by them (Kostova, 1999). As a social institution, educationprepares individuals to act in society (Meyer, 1977). Those who belong to a commoncultural cluster (Anglo-Saxon, South Asian, Latin American, Sub-Sahara African, etc.) areexpected to share common educational development through their nations’ institutions(House et al., 2004). That being the case, they are more likely to have gender role and valuesimilarity (Parboteeah et al., 2008).

The open systems theory explanation of gender similarities (Boulding, 1956; Miller,1968; von Bertalanffy, 1951) identifies the existence of subsystems within larger systemsthat are specialised and distinct from those larger systems (Katz and Kahn, 1978).Applying systems theory to the study of the work preferences between the genders ofbusiness students, one would expect that there are more similarities than differencesamong those who belong to this educational subsystem. Those who are attracted to thestudy and practice of business are more similar than different in terms of their workpreferences.

For the previous reasons, the following hypotheses are posited:

H1. Within national samples of English-speaking business students, males andfemales share more similarities than differences in their work preferences.

GM25,8

680

H2. Across national English-speaking business student samples, males andfemales share more similarities than differences in their work preferences.

H3. National country will not moderate differences in the work preferences offemale and male business students who fall within the English-speakingAnglo-Saxon culture.

MethodologyWork preferenceThe term work preference is used to define intrinsic and extrinsic motivational factors(Amabile et al., 1994), and consists of multiple measures representing several specificdisciplines within the field of psychological measurement (Dowd, 2006; Gilbert et al.,2008). It is used to help working adults make informed academic (Gilbert et al., 2010) andcareer-related choices (Dowd, 2006; Gilbert et al., 2008). It is used to help working adultsmake informed academic (Gilbert et al., 2010) and career-related choices (Dowd, 2006;Gilbert et al., 2008). It includes overlapping constructs related to work values (Roundsand Armstrong, 2005; Rowe and Snizek, 1995), job attributes (Konrad et al., 2000),interests (Barrick et al., 2003; Holland, 1997), motivation (Amabile et al., 1994),temperament (McCaulley, 1990), and practical work-related considerations (Dowd,2006). Work preferences influence career choice decisions (Brown, 1996) and may shedlight on the person-to-work environment fit (Gilbert et al., 2008, 2010; Rounds et al., 1987).

Measurement toolThe work preference indicator (WPI; Gilbert et al., 2008) is a 75-item multi-dimensionaltool that consists of 17 empirically independent constructs associated withpsychological learning styles, work values, work interests, and personalitytemperament. When taking the WPI assessment, participants are asked to respondto Likert scale items ranging from 1 ¼ strongly disagree to 5 ¼ strongly agree. Table IIgives a brief definition of each of the 17 dimensions embedded in the WPI as reportedin more detail by Gilbert et al. (2008).

SampleThe use of multiple samples from three separate nations is advantageous for thisinvestigation because it allows us to test for gender differences both within and acrossthe three countries. If differences are found within but not across the samples from thethree nations, such differences are likely attributable to national context rather thanbiologically determined sex (evolution) per se. The samples in all three nations are ofthe convenient type and representative of the actual number (a census) of students whowere registered in each of the three student populations during the same academicsemester. The samples allowed us to compare individuals from all three nations whowere studying in the same field and were seeking occupations that would qualify themto join domestic and cross-national business teams. All business students in thesamples took the WPI as part of their normal coursework. The students were informedthat their participation was voluntary and that scores on the 17 measures would notaffect their grades. As an incentive, each student participant was provided with a freeindividualised career-related confidential report based on their responses.

The American sample included 262 male and 498 female graduate andundergraduate students. The Jamaica sample included 50 male and 89 female

Does gendermatter?

681

WP

Ip

sych

olog

ical

con

stru

ctla

bel

Defi

nit

ion

ofW

PI

psy

chol

ogic

alco

nst

ruct

Con

cep

tual

anch

ors

Sou

rce

Learningstyle

Preferto

[...]

Som

eem

ployees[...]

1.A

ura

lle

arn

ing

(AU

RL

)[...

]le

arn

atw

ork

thro

ug

hop

end

iscu

ssio

ns

wit

hot

her

s[...

]le

arn

atw

ork

thro

ug

hp

rev

iou

sor

alex

pla

nat

ion

s

[...

]p

roce

ssan

du

nd

erst

and

info

rmat

ion

dif

fere

ntl

y[...

]h

ave

dis

tin

ctau

ral

and

vis

ual

lear

nin

gst

yle

s

An

der

son

and

Ad

ams

(199

2),

Faz

arro

and

Ste

ven

s(2

004)

,D

ewae

lean

dF

urn

ham

(199

9)

2.W

ritt

enle

arn

ing

(WR

IT)

[...

]le

arn

atw

ork

thro

ug

hre

adin

gp

rin

ted

,el

ectr

onic

,an

dot

her

sou

rces

ofv

isu

alin

form

atio

n

[...

]w

ith

vis

ual

lear

nin

gst

yle

sar

ein

trov

erte

d[...

]w

ith

aura

lle

arn

ing

sty

les

are

extr

aver

ted

Workvalues

1.W

ork

ind

epen

den

ce(I

ND

E)

[...

]w

ork

ind

epen

den

tly

[...

]m

ake

wor

k-r

elat

edd

ecis

ion

sw

ith

out

hel

pfr

omau

thor

ity

[...

]v

alu

ew

ork

ind

epen

den

cean

dd

ecis

ion

mak

ing

Dou

gla

san

dS

hep

ard

(200

2),

Rou

nd

set

al.

(198

1)

[...

]w

ork

auto

nom

ousl

y2.

Wan

tto

be

lik

eab

le(L

KB

L)

[...

]g

etal

ong

wel

lw

ith

oth

ers

atw

ork

[...]

pla

ceh

igh

val

ue

onb

ein

gli

ked

and

resp

ecte

db

yot

her

sH

ogan

and

Hog

an(1

992)

[...

]b

ew

ell-

lik

edb

yot

her

sat

wor

k[...

]b

ev

alu

edb

yot

her

sat

wor

k3.

Wor

kw

ith

oth

ers

inte

ams

(TE

AM

)[...

]w

ork

wit

hot

her

sto

get

the

wor

kd

one

[...]

val

ue

team

-bas

edw

ork

Du

nn

and

Du

nn

(199

9)

[...

]w

ork

inte

ams

wh

ere

they

are

anef

fect

ive

team

pla

yer

[...

]p

lay

anin

teg

ral

par

tin

ah

igh

-p

erfo

rmin

gte

am[...

]sh

are

succ

ess

wit

hot

her

son

aw

ork

team

(continued

)

Table II.Definitions and anchorsused in the WPI

GM25,8

682

WP

Ip

sych

olog

ical

con

stru

ctla

bel

Defi

nit

ion

ofW

PI

psy

chol

ogic

alco

nst

ruct

Con

cep

tual

anch

ors

Sou

rce

4.Jo

bfu

lfilm

ent

(JF

UL

)[...

]w

ork

injo

bs

that

are

per

son

ally

sati

sfy

ing

[...

]v

alu

ew

ork

that

pro

vid

esin

trin

sic

rew

ard

san

dm

ean

ing

ful

wor

kA

mab

ileet

al.

(199

4),

Mal

ka

and

Ch

atm

an(2

003)

[...

]w

ork

injo

bs

that

are

imp

orta

nt

and

mea

nin

gfu

l5.

Car

eer

lad

der

(CL

AD

)[...

]w

ork

for

anor

gan

isat

ion

that

pro

vid

esa

clea

rly

defi

ned

care

erla

dd

er[...

]v

ary

inth

eir

val

ue

for

up

war

dm

obil

ity

wit

hin

the

org

anis

atio

nC

oxan

dC

oop

er(1

989)

,Ju

dg

eetal.

(199

5)

[...

]k

now

care

erp

oten

tial

wit

hin

the

org

anis

atio

n[...

]m

ove

up

wit

hin

the

syst

em6.

Ach

iev

ere

sult

s(R

SL

T)

[...

]ac

hie

ve

resu

lts

onth

ejo

b[...

]b

eef

fect

ive

atd

oin

gon

e’s

wor

k[...

]co

ntr

ibu

teto

the

over

all

succ

ess

ofth

eor

gan

isat

ion

[...

]val

ue

get

tin

gre

sult

sfr

omth

eir

wor

kM

cCle

llan

d(1

985)

,C

osta

and

McC

rae

(199

2)

Workinterests

1.H

elp

ful

toot

her

s(H

EL

P)

[...

]h

elp

oth

ers

atw

ork

[...

]ca

refo

rot

her

sat

wor

k[...

]co

ach

oth

ers

atw

ork

[...

]p

rov

ide

serv

ice

toth

ose

wit

hw

hom

they

wor

k

[...

]ar

em

ore

agre

eab

le(i

.e.

com

pas

sion

ate

and

coop

erat

ive)

,so

cial

,an

dp

eop

le-o

rien

ted

than

oth

ers

Hol

lan

d(1

992)

,Cos

taan

dM

cCra

e(1

992)

,P

red

iger

(197

6)

2.W

ork

wit

hd

ata

(DA

TA

)[...

]w

ork

wit

hd

ata

[...

]an

aly

sen

um

ber

s[...

]k

eep

dat

are

cord

s

[...

]ar

em

ore

con

ven

tion

al,

real

isti

c,an

dor

ien

ted

tow

ard

sd

ata

Hol

lan

d(1

992)

,P

red

iger

(197

6)

3.W

ork

wit

hm

ech

anic

alth

ing

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Table II.

GM25,8

684

graduate students. The Australian sample included 107 male and 158 femaleundergraduate business students. Correlations among the 17 WPI psychologicalconstructs are shown in Table III. Correlations among the 17 WPI psychologicalconstructs ranged from a high of 0.47 and 20.33 and a low of 0.02. Reliabilities arereported along the diagonal. As shown, all Cronbach alpha reliability estimates areabove 0.80, and are generally 0.87 or higher.

Data analysisPrior to testing our hypotheses, we established measurement equivalence of the WPIamong all three national samples, by conducting a confirmatory factor analysis andassessed the overall fit of our constrained model by comparing the comparative fit index

Mean SD 1 2 3 4 5 6 7 8 9 101. JOBP 4.76 0.45 (0.91)2. JSAT 4.57 0.63 0.47 (0.88)3. LEAD 3.72 0.83 0.25 0.22 (0.89)4. TASC 4.39 0.65 0.38 0.25 0.17 (0.84)5. TIMM 4.08 0.68 0.26 0.13 0.23 0.21 (0.87)6. FLEX 2.96 0.94 20.10 0.02 0.05 20.05 20.33 (0.80)7. FACT 4.20 0.66 0.36 0.15 0.19 0.42 0.33 20.07 (0.88)8. WRIT 3.50 0.77 0.18 0.03 0.19 0.15 0.21 0.02 0.30 (0.82)9. INDE 4.10 0.74 0.30 0.26 0.27 0.19 0.10 0.07 0.17 0.04 (0.85)

10. CLAD 4.34 0.66 0.45 0.26 0.37 0.36 0.31 20.03 0.37 0.14 0.21 (0.92)11. DATA 3.47 0.90 0.18 0.01 0.20 0.06 0.21 20.10 0.21 0.31 0.09 0.2012. MECH 3.27 0.94 0.03 0.04 0.19 0.07 0.09 0.10 0.18 0.21 0.02 0.0513. IDEA 4.21 0.67 0.30 0.22 0.21 0.15 0.30 20.05 0.35 0.09 0.21 0.3614. LKBL 3.90 0.65 0.17 0.33 0.19 0.20 0.17 0.08 0.16 0.04 0.11 0.2715. HELP 4.20 0.62 0.35 0.17 0.21 0.21 0.21 0.01 0.31 0.23 0.18 0.2116. TEAM 4.28 0.65 0.41 0.23 0.33 0.38 0.34 20.03 0.32 0.23 0.17 0.3917. ORAL 3.99 0.66 0.13 0.22 0.18 0.17 0.07 0.14 0.15 0.09 0.13 0.20

11 12 13 14 15 16 171. JOBP 4.76 0.452. JSAT 4.57 0.633. LEAD 3.72 0.834. TASC 4.39 0.655. TIMM 4.08 0.686. FLEX 2.96 0.947. FACT 4.20 0.668. WRIT 3.50 0.779. INDE 4.10 0.74

10. CLAD 4.34 0.6611. DATA 3.47 0.90 (0.93)12. MECH 3.27 0.94 0.21 (0.90)13. IDEA 4.21 0.67 0.37 0.17 (0.90)14. LKBL 3.90 0.65 20.02 0.07 0.16 (0.83)15. HELP 4.20 0.62 0.19 0.13 0.21 0.33 (0.88)16. TEAM 4.28 0.65 0.20 0.15 0.21 0.33 0.52 (0.90)17. ORAL 3.99 0.66 0.01 0.05 0.20 0.33 0.16 0.16 (0.82)

Notes: n ¼ 1,164; Alphas are shown on the diagonal; correlations greater than j0.07j are significant atp , 0.05 correlations greater than j0.10j are significant at p , 0.01

Table III.Means, standard

deviations, coefficientalphas, and

intercorrelations of WPIpsychological constructs

Does gendermatter?

685

(CFI), the goodness-of-fit index (GFI), and the root-mean-square error of approximation(RMSEA). First, GFIs for work interests (i.e. help others, mechanics, data, factualinformation, and take the lead) indicate superior fit for our constrained model across theUS (CFI ¼ 0.98; GFI ¼ 0.96; RMSEA ¼ 0.03), Australian (CFI ¼ 0.95; GFI ¼ 0.97;RMSEA ¼ 0.05), and Jamaican samples (CFI ¼ 0.96; GFI ¼ 0.97; RMSEA ¼ 0.05).Second, GFIs for learning styles (i.e. written material and aural learning) indicatesuperior fit for our constrained model across the US (CFI ¼ 1.00; GFI ¼ 0.98;RMSEA ¼ 0.02), Australian (CFI ¼ 0.99; GFI ¼ 0.98; RMSEA ¼ 0.03), and Jamaicansamples (CFI ¼ 0.99; GFI ¼ 0.99; RMSEA ¼ 0.03). Third, GFIs for work values(i.e. work independence, likeable, team-oriented, upward mobility, results orientation,and job fulfilment) indicate superior fit for our constrained model across the US(CFI ¼ 1.00; GFI ¼ 0.96; RMSEA ¼ 0.00), Australian (CFI ¼ 1.00; GFI ¼ 0.97;RMSEA ¼ 0.00), and Jamaican samples (CFI ¼ 1.00; GFI ¼ 1.01; RMSEA ¼ 0.01).Fourth, GFIs for personal temperament (i.e. task clarity, time management, flexibility,and exploring ideas and concepts) indicate superior fit for our constrained model acrossthe US (CFI ¼ 1.00; GFI ¼ 0.98; RMSEA ¼ 0.00), Australian (CFI ¼ 1.00; GFI ¼ 0.98;RMSEA ¼ 0.00), and Jamaican samples (CFI ¼ 0.96; GFI ¼ 0.97; RMSEA ¼ 0.00). Wedetermined that the constrained models support superior discriminant validity in theAmerican, Australian, and Jamaican samples on the basis of these results.

In order to test our hypotheses, the students’ responses were dichotomised by maleand female for each of the Australian, Jamaican, and US samples, and analysed with thestudent t-test and multivariate analysis of variance (MANOVA) statistical applications.Partial h 2 effect sizes were derived from means tests applications generated by theMANOVA analyses when we tested for differences among all respondents combined(AUS, JAM, and US samples). The differences found between males and females on the17 WPI constructs are shown in Table IV. For the purposes of this study, effect sizesequal to or greater than 0.04 are considered noteworthy (Cohen, 1992).

Combined AUS, JAM, and US tests for differences. We used a one-way MANOVAto test for gender differences in work preferences in the combined samples of all threecountries. Differences were found in MECH (h 2 ¼ 0.04), TASC (h 2 ¼ 0.02), LEAD(h 2 ¼ 0.02), DATA (h 2 ¼ 0.01), and TIMM (h 2 ¼ 0.01). Only with MECH (malesrating higher than females) was the effect size considered noteworthy (0.04), and thisfinding is consistent with others regarding males rating working with mechanicalthings (realistic) higher than women (Betz et al., 2003; Prediger, 1976). Tests fordifferences between males and females based on the 17 combined constructs weremoderately significant, but no one dimension was sufficient to explain the differencenoted (Table IV; Wilks’ l ¼ 0.099 (17.000) F ¼ 4.31, p , 0.001, partial h 2 ¼ 0.090).

Within-nation tests for differences. We used three separate one-way MANOVAs totest for gender difference by work preference within each country. The analysis of ourdata revealed similar gender differences in US (Wilks’ l ¼ 0.850 (17.000) F ¼ 3.51,p , 0.001, partial h 2 ¼ 0.15), JAM (Wilks’ l ¼ 0.804 (17.000) F ¼ 1.72, p , 0.05, partialh 2 ¼ 0.196) and AUS (Wilks’ l ¼ 0.860 (17.000) F ¼ 2.36, p , 0.002, partial h 2 ¼ 0.14)samples. Unlike other studies that have identified such gender differences, for each ofour national samples of business students no differences were found in any of the 17dimensions to have high practical value owing to their marginal effect sizes.

Summary of differences identified in this study. An analysis of each of the 17 WPImeasures by national sample found only one measure, working with mechanical things

GM25,8

686

Measure/countrye Sample n Mean SD df MS F h 2

RSLTALLa

M 262 4.68 0.50 1 0.61 2.81 0.001F 498 4.75 0.45 760US 0.023 * *

M 105 4.61 0.61 1 2.04 7.91F 252 4.78 0.46 356JAM 0.002M 50 4.93 0.20 1 0.01 0.26F 88 4.91 0.25 137AUS 0.001M 107 4.64 0.44 1 0.12 0.55F 158 4.61 0.48 263JFULALLM 262 4.53 0.70 1 0.33 0.79 0.001F 498 4.57 0.62 760US 0.006 * *

M 105 4.46 0.81 1 1.18 2.63F 252 4.58 0.60 356JAM 0.004M 50 4.55 0.56 1 0.33 0.69F 88 4.45 0.75 137AUS 0.001M 107 4.59 0.64 1 0.08 0.25F 158 4.63 0.54 263LEADALLM 262 3.88 0.80 1 9.30 13.00 0.015 * *

F 498 3.64 0.87 760USM 105 3.72 0.88 1 0.77 0.99 0.023 * *

F 252 3.62 0.88 356JAMM 50 4.13 0.66 1 8.15 13.15 0.016F 88 3.62 0.85 137AUSM 107 3.91 0.76 1 3.05 4.57 0.008F 158 3.69 0.85 263TASCALL 0.016 * *

M 262 4.33 0.73 1 4.64 13.08F 498 4.49 0.68 760US 0.023 * *

M 105 4.30 0.77 1 3.55 8.46F 252 4.52 0.59 356JAM 0.016M 50 4.38 0.59 1 0.70 2.19F 88 4.53 0.55 137AUS 0.018

(continued )

Table IV.Comparison of genderdifferences among alla

respondents andseparately by the USAb,Jamaicac, and Australiad

based on ratings on the 17WPI measures

Does gendermatter?

687

Measure/countrye Sample n Mean SD df MS F h 2

M 107 4.32 0.56 1 0.59 2.06F 158 4.42 0.52 263TIMMALLM 262 3.99 0.73 1 0.269 0.5.61 0.002F 498 4.12 0.68 760USM 105 3.92 0.68 1 4.25 0.9.13 0.024 * *

F 252 4.16 0.68 356JAMM 50 4.20 0.68 1 0.39 0.74 0.005F 88 4.10 0.74 137AUSM 107 3.96 0.77 1 0.62 1.33 0.005F 158 4.06 0.62 263FLEXALLM 262 3.01 0.90 1 0.07 0.08 ,0.001F 498 2.99 0.93 760USM 105 2.95 0.86 1 0.37 0.42 0.004F 252 3.02 0.97 356JAMM 50 2.73 0.98 1 0.37 0.39 0.033 *

F 88 2.84 0.97 137AUSM 107 3.19 0.86 1 1.98 2.87 ,0.001F 158 3.01 0.81 263FACTALLM 262 4.14 0.63 1 0.34 0.83 ,0.001F 498 4.18 0.65 760USM 105 4.18 0.60 1 0.67 1.74 0.004F 252 4.27 0.63 356JAMM 50 4.36 0.59 1 0.43 0.92 0.008F 88 4.24 0.73 137AUSM 107 3.99 0.65 1 0.00 0.01 ,0.001F 158 4.00 0.60 263VISUALALLM 262 3.41 0.79 1F 498 3.48 0.75 760 0.83 1.41 ,0.001USM 105 3.48 0.77 1 1.99 3.39 0.009F 252 3.64 0.76 356JAMM 50 3.51 0.87 1 0.49 0.82 0.006

(continued )Table IV.

GM25,8

688

Measure/countrye Sample n Mean SD df MS F h 2

F 88 3.38 0.72 137AUSM 107 3.29 0.76 1 0.04 0.07 ,0.001F 158 3.27 0.70 263INDEALLM 262 4.02 0.75 1 0.86 1.69 0.007F 498 4.09 0.69 760USM 105 3.39 0.89 1 4.06 6.01 0.016 * *

F 252 4.11 0.79 356JAMM 50 4.31 0.61 1 0.04 0.10 ,0.001F 88 4.28 0.56 137AUSM 107 4.03 0.76 1 0.29 0.86 0.003F 158 3.96 0.70 263CLADALLM 262 4.43 0.59 1 0.02 0.05 ,0.001F 498 4.42 0.58 760USM 105 4.37 0.70 1 0.06 0.14 ,0.001F 252 4.39 0.63 356JAMM 50 4.62 0.42 1 0.15 0.75 0.005F 88 4.55 0.46 137AUSM 107 4.40 0.51 1 0.03 0.08 0.018F 158 4.38 0.53 263DATAALLM 262 3.42 0.94 1 2.43 2.77 0.007 * *

F 498 3.30 0.93 760USM 105 3.57 0.90 1 2.26 2.52 0.008F 252 3.39 0.97 356JAMM 50 3.83 0.96 1 1.98 2.32 0.017F 88 3.58 0.91 137AUSM 107 3.08 0.86 1 0.49 0.70 0.003F 158 2.99 0.82 263MECHALLM 262 3.39 0.94 1 25.197 31.348 0.040 * * *

F 498 3.00 0.92 760USM 105 3.40 0.85 1 9.03 10.54 0.030 * *

F 252 3.05 0.95 356

(continued ) Table IV.

Does gendermatter?

689

Measure/countrye Sample n Mean SD df MS F h 2

JAMM 50 3.25 0.89 1 4.75 5.18 0.038 *

F 88 2.87 0.99 137AUSM 107 3.40 0.85 1 11.81 17.58 0.063 * * *

F 158 2.97 0.80 263IDEAALLM 262 4.23 0.65 1 2.17 0.141 0.003F 498 4.15 0.69 760USM 105 4.18 0.70 1 0.48 0.91 0.004F 252 4.10 0.74 356JAMM 50 4.47 0.49 1 2.13 5.00 0.033 *

F 88 4.21 0.73 137AUSM 107 4.16 0.65 1 0.03 0.08 ,0.001F 158 4.18 0.59 263LKBLALLM 262 3.95 0.60 1 2.94 0.09 0.004F 498 3.99 0.68 760USM 105 3.81 0.64 1 0.07 0.13 0.001F 252 3.83 0.73 356JAMM 50 3.82 0.53 1 0.02 0.05 ,0.001F 88 3.85 0.63 137AUSM 107 4.15 0.54 1 1.80 0.7.01 0.026 * *

F 158 4.31 0.49 263HELPALLM 262 4.09 0.66 1 2.06 0.16 0.003F 498 4.18 0.62 760USM 105 4.07 0.63 1 1.96 4.90 0.015 * *

F 252 4.23 0.63 356JAMM 50 4.31 0.66 1 0.12 0.31 0.005F 88 4.37 0.61 137AUSM 107 4.01 0.67 1 0.06 0.16 0.018F 158 3.98 0.55 263TEAMALLM 262 4.22 0.67 1 0.01 0.91 ,0.001F 498 4.22 0.65 760USM 105 4.07 0.63 1 0.31 0.70 0.002

(continued )Table IV.

GM25,8

690

(MECH), to be significantly different in each of the three nations, and in each casemales rated this measure higher than females. Separate analyses of the tests for genderdifference in each of the 17 WPI measures are presented as follows.

Work with mechanical things (MECH). As shown in Table IV, we found significantgender differences within each of the three national samples. In our Australian( p , 0.001), Jamaican ( p , 0.05), and American ( p # 0.02) samples, males scoredhigher than females in their preference for working with mechanical things. The effectsizes were notable (h 2 ¼ 0.063, 0.038, and 0.030, respectively).

Working with others in teams (TEAM), job fulfilment (JFUL), career ladder (CLAD,working with DATA), and factual information (FACT), aural (WRIT) and visual (AURL)learning styles. We found no significant gender differences within the three samplesregarding male and female preference for working on teams, job fulfilment, moving up thecareer ladder, working with data, or factual information, visual and aural learning.

Work with task-specific instructions (TASC), time management (TIMM), lead others(LEAD), wanting to help others (HELP), work independently (INDE), and result oriented(RSLT). We found no significant gender difference within the Australian and Jamaicansamples. In the American sample, however, females scored significantly higher thanmales in their preference for task-specific work instructions to do their jobs (h 2 ¼ 0.023;p , 0.05), time management (h 2 ¼ 0.023; p , 0.05), wanting to help others (h 2 ¼ 0.015),p , 0.05), and wanting to work independently (h 2 ¼ 0.016, p , 0.05), andresults-oriented achievement (h 2 ¼ 0.023, p , 0.01). In contrast, males scored higherthan did females on their preference for leading others (h 2 ¼ 0.023; p , 0.05).

Measure/countrye Sample n Mean SD df MS F h 2

F 252 4.23 0.63 356JAMM 50 4.45 0.58 1 0.10 0.30 0.003F 88 4.39 0.55 137AUSM 107 4.15 0.63 1 0.21 0.51 0.002F 158 4.10 0.65 263AURALALLM 262 4.04 0.62 1 0.12 0.28 ,0.001F 498 4.05 0.69 760USM 105 4.00 0.61 1 0.08 0.16 ,0.001F 252 3.97 0.75 356JAMM 50 3.90 0.70 1 0.03 0.07 ,0.001F 88 3.88 0.67 137AUSM 107 4.15 0.59 1 0.92 2.92 0.011F 158 4.27 0.54 263

Notes: Significance at: *p # 0.05, * *p , 0.02, p # 0.001; a ¼ 1Wilks’ l ¼ 0.099 (17.000) F ¼ 4.31,p , 0.001, partial h 2 ¼ 0.090; b ¼ 1Wilks’ l ¼ 0.850 (17.000) F ¼ 3.51, p , 0.001, partial h 2 ¼ 0.150;c ¼ 1Wilks’ l ¼ 0.804 (17.000) F ¼ 1.72, p , 0.049, partial h 2 ¼ 0.196; d ¼ 1Wilks’ l ¼ 0.860 (17.000)

F ¼ 2.36, p , 0.002, partial h 2 ¼ 0.140 Table IV.

Does gendermatter?

691

Flexible work environment (FLEX); work with ideas (IDEA). We found nosignificant gender differences within the Australian and American samples. However,in the Jamaican sample, females scored significantly higher than did males on theirpreference for a flexible work environment (h 2 ¼ 0.033; p , 0.05). In the Jamaicansample, males scored significantly higher than did females on their preference forworking with ideas (h 2 ¼ 0.033; p , 0.05).

Wanting to be likeable (LKBL). We found no significant gender differences withinthe American and Jamaican samples. However, in the Australian sample, we found adifference between males and females, with females scoring higher than males( p # 0.05), but the effect size was weak (h 2 ¼ 0.026).

The effect of national identity on gender differences. We used a two-way MANOVAto examine all 17 constructs by gender and country to discern the moderating effects ofcountry on gender differences. We found that country has marginal effects on genderdifferences (Wilks’ l ¼ 0.840 (34.000) F ¼ 1.357, p , 0.083, partial h 2 ¼ 0.030).Significant interaction between gender and country was identified for two of the 17constructs, RSLT and INDE, indicating that national culture appears to play a verylimited role in gender differences found among the samples of the three countries. Theeffects of the two differences found are weak (h 2 ¼ 0.030).

DiscussionGender similarity is influenced by shared language (House et al., 2004), common nationalinstitutions (Kostova, 1999; Meyer, 1977), and among those who reside withinsubsystem having common interests that are differentiated from larger systems inwhich they endure (Boulding, 1956; Katz and Kahn, 1978; von Bertalanffy, 1951). Giventhese research findings, the H1 posited more similarities than differences in male andfemale work preferences within each of the national samples. As shown in Table IV,when our work preference constructs were aggregated within each sample, we foundthat there are large differences within all three samples across all 17 work preferencemeasures combined as shown by their strong effect sizes (US: h 2 ¼ 0.15; Jamaica:h 2 ¼ 0.20; Australia: h 2 ¼ 0.14). As also revealed in Table IV, however, when each ofthe 17 measures was analysed separately, we found only weak effect sizes within each ofthe three countries. Within each of the three samples of business students (AUS, JAM,and US) more similarities in gender work preferences than differences were found. Moredifferences were found within the US sample than the JAM or the AUS samples. In theAmerican sample, statistically significant differences were found in RSLT, JFUL,LEAD, TASC, TIMM, INDE, MECH, and HELP, but none had effect sizes that werenotable ($0.04) The JAM sample revealed differences in LEAD, FLEX, and MECH, withno effect sizes of consequence. Among those in the AUS sample, differences were foundin MECH and LKBL with a moderate effect size associated with MECH (0.06). Thus,consistently with the H1, the data reveal that within each country there are moresimilarities than differences in work preferences between males and females.

Our H2 predicted more similarities than differences between males and females intheir work preferences in the combined three national samples (see ALL, Table IV).When the work preference constructs were aggregated across all three countries, wefound that there were large differences within all three samples across all 17 measuresas shown by the strong effect size (h 2 ¼ 0.09). The data revealed, however, that femaleand male strengths of work preference among the three samples were more similar

GM25,8

692

than different when we examined each construct independently of the others. In onlyone of the 17 work preference dimensions was a difference noted: males were found tohave higher preference for working with things (MECH; h 2 ¼ 0.04) than females.Thus, consistently with the H2, the data reveal that across all three countries there aremore similarities than differences in work preferences between males and females.

Although many cultural differences have been found to exist across nationalboundaries (Hofstede, 1980; House et al., 2004; Inglehart and Baker, 2000), the sharingof a common language provides support for the H3 generated by this study. It positsthat national boundaries will have less effect on gender differences than will thecommonality of language and interests which business students share. Fundamental tothis hypothesis is that those within academic subsystems formed by commonproperties of attraction will have more similarities among them than differences evenas they travel across national boundaries. Two-way MANOVA was used to examineall 17 constructs by gender and country. No notable effects on gender differences werefound. Significant interaction between gender and national identity was found in onlytwo of the 17 constructs. Thus, based on our samples from Australia, Jamaica, and theUSA, our findings are consistent with hypothesis three – national country does notmoderate differences in the work preferences of females and males who share anEnglish-speaking, predominantly Anglo culture.

In summary, when each of the 17 work preferences was analysed within eachcountry, some significant differences were found, but few were noteworthy, and theywere not consistent from nation to nation. Thus, the evolution-based proposition thatgender differences found within countries would also be found across nationalboundaries was not supported by this study. Our study tends to support the gendersimilarities hypothesis posited by Hyde (2005) and others.

The preponderance of our evidence supports our “gender similarities” hypothesis.We cannot accept it unconditionally, however, since among the 17 dimensions thereappear to be some differences among work preferences of males and females. Yet, withthe exception of MECH, such differences could not be discerned in terms of any of theother 16 constructs included in our study.

When compared with previous findings reported in the literature, our study tends tosupport differences found between males and females in only a few areas. Our findingsare similar to Betz et al. (2003), Holland (1997) and Prediger (1976) who found thatmales score higher than females in preference for working with mechanical things.However, it is important to note that whereas males prefer to work with mechanicalthings more than females, Nash (1975) found that both males and females performequally well when working on mechanical tasks. Thus, even though males included inour business school samples prefer to work with mechanical things more than females,such differences do not give us reason to infer that a male with a high preference forworking with mechanical things will perform better than a female who has a similarlyhigh preference.

Implications and concluding commentsOne of the principal implications of the study is the emergence of increased gendersimilarity. This study has revealed that the type of work females and males may opt todo when participating in business-related work teams is much more similar than it isdifferent. These findings indicate that in terms of the person-environment fit theory,

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both females and males are well-suited for like work-related roles and assignments inbusiness teams, domestically and English-speaking countries globally. Only onemeasure, working with mechanical things (MECH), seemed to differentiate male andfemale work environment attraction, and that difference was moderate.

Although males and females have long been recognised as being different(biologically, and in other ways that are culturally shaped), the study findings provideadditional evidence to support a gender “similarities hypothesis” as it pertains toemployee work preferences. Managers can expect similar work performance andperson-environment fit relationships among those on their teams who share a commonattraction to business, both academically and vocationally.

There are several limitations of this study. The constructs used in this study havenot been empirically demonstrated to be equivalent to those used in other studies wheregender and sex differences were noted, beyond that of face validity. Samples from thethree nations are relatively small. Although they include all students in three differentbusiness programmes at three different schools in three different nations, the samplefrom each nation needs to be enlarged to allow greater confidence in the conclusionsdrawn from this study. The research is limited to business graduates, and additionalresearch on gender differences of work preferences needs to include college studentspursuing other subjects as well as working adults drawn from similar occupationalfields.

Given the above limitations, the message from this study for managers of bothdomestic and global teams is that biological sex does not seem to matter when it comes tothe selection, placement, training, development, and appraisal of team members – they aremore alike than different. Other studies have suggested that women may be more likely towant to get along with others, whereas males may be more driven to lead and controlothers and achieve results (Meyers-Levy, 1988; McClelland et al., 1976). However, ourstudy did not confirm such differences within or among our business school samples.

Conclusions drawn from other studies about gender and sex might mislead leadersof work teams. This is especially relevant for business managers of global teams, whereinthe gender differences such leaders have experienced within their own nations may,indeed, not exist across national boundaries. There is much more to be gained by teamleaders to build on the talents of all on the team, without gender consideration, than toemploy predisposed limitations or expectations based on their own narrow life experienceor others’ more generalised studies pertaining to gender differences.

Global business teams, both physical and virtual, are gaining in both prominenceand importance (Kanawattanachai and Yoo, 2002). More women are filling managerialpositions in global companies, broadening their technical backgrounds and arebecoming amenable to both internationally focused work and overseas assignments.It may well be that globalisation is mitigating differences caused by culturalbackground and gender (Ralston et al., 1997). The findings from this study requirecompanies in their quest to identify, cultivate and expand competitive human capital toconsider women and men as equals when staffing their work teams.

References

Ackerman, P.L., Bowen, K.R., Beier, M.E. and Kanfer, R. (2001), “Determinants of individualdifferences and gender differences in knowledge”, Journal of Educational Psychology,Vol. 93 No. 4, pp. 797-825.

GM25,8

694

Amabile, T., Hill, K., Hennessey, B. and Tighe, E. (1994), “The work preference inventory:assessing intrinsic and extrinsic motivational orientations”, Journal of Personaliy andSocial Psychology, Vol. 66 No. 5, pp. 950-67.

Anderson, J. and Adams, M. (1992), “Acknowledging the learning styles of diverse studentpopulations: implications for instructional design”, New Directions for Teaching andLearning, Vol. 49, pp. 19-31.

Bandura, A. (1999), “Moral disengagement in the perpetration of inhumanities”, Personality &Social Psychology Review, Vol. 3 No. 3, p. 193.

Barrick, M.R., Mount, M.K. and Gupta, R. (2003), “The five-factor model of personality andHolland’s RIASEC types: a meta-analysis”, Personnel Psychology, Vol. 56, pp. 45-74.

Betz, N.E., Harmon, L.W. and Borgen, F.H. (1996), “The relationships of self-efficacy for theHolland themes to gender, occupational group membership, and vocational interest”,Journal of Counseling, Vol. 43, pp. 90-8.

Betz, N.E., Borgen, F.H., Rottinghaus, P., Paulson, A., Halper, C.R. and Harmon, L.W. (2003),“The expanded skills confidence inventory”, Journal of Vocational Behavior, Vol. 62,pp. 76-100.

Birenbaum, M. and Kraemer, R. (1995), “Gender and ethnic-group differences in causalattributions for success and failure in mathematics and language examinations”, Journalof Cross-Cultural Psychology, Vol. 26, pp. 342-59.

Boring, E.G. (1969), “The influence of evolutionary theory upon American psychologicalthought”, in Persons, S. (Ed.), Evolutionary Thought in America, Yale University Press,New Haven, CT, pp. 266-99.

Boulding, K.E. (1956), “General systems theory – the skeleton of science”, Management Science,Vol. 2 No. 3, pp. 197-208.

Brody, L.R. and Hall, J.A. (2000), “Gender, emotion and expression”, in Lewis, M. andHaviland-Jones, J.M. (Eds), Handbook of Emotions: Part IV: Social/Personality Issues, 2nded., Guilford Press, New York, NY, pp. 325-414.

Brown, D. (1996), “Brown’s value-based, holistic model of career and life-role choices andsatisfaction”, in Brown, D. and Brooks, L.O. (Eds), Career Choices and Development, 3rded., Jossey-Bass, San Francisco, CA, pp. 337-72.

Buss, D.M. (1984), “Evolutionary biology and personality psychological science”, PsychologicalInquiry, Vol. 6, pp. 1-30.

Chan, K. and Drasgow, F. (2001), “Toward a theory of individual differences and leadership:understanding the motivation to lead”, Journal of Applied Psychology, Vol. 86 No. 6,pp. 481-98.

Cohen, J. (1992), “A power primer”, Psychological Bulletin, Vol. 112, pp. 155-9.

Contreras, M.J. (2007), “Sex difference in dynamic spatial ability: the unsolved question ofperformance factors”, Memory & Cognition, Vol. 35 No. 2, pp. 297-303.

Costa, P.T. and McCrae, R.R. (1992), Revised NEO-Personality Inventory (NEO-PI-R) and NEOFive Factor Inventory (NEO-FFI): Professional Manual, Psychological AssessmentResources, Odessa, FL.

Costa, P.T., McCrae, R.R. and Holland, J.L. (1984), “Personality and vocational interests in anadult sample”, Journal of Applied Psychology, Vol. 69, pp. 390-400.

Costa, P.T., Terracciono, A. and McCrae, R.R. (2001), “Gender differences in personality traitsacross cultures: robust and surprising findings”, Journal of Personality and SocialPsychology, Vol. 81, pp. 322-31.

Does gendermatter?

695

Cox, C. and Cooper, C. (1989), “The making of the British CEO: childhood, work experiences,personality, and management style”, Academy of Management Executive, Vol. 3, pp. 241-5.

Dewaele, J. and Furnham, A. (1999), “Extraversion: the unloved variable in applied linguisticresearch”, Language Learning, Vol. 49, pp. 509-44.

Dio, L.D., Saragovi, C., Koestner, R. and Aube, J. (2005), “Linking personal values to gender”,Sex Roles, Vol. 34 Nos 9-10, pp. 621-36.

Douglas, E. and Shepard, D. (2002), “Self employment as a career choice: attitudes,entrepreneurial intentions and utility maximization”, Entrepreneurial Theory andPractice, Vol. 26 No. 3, pp. 81-90.

Dowd, L. (2006), The Work Preference Match: Administrator’s Guide, JIST, Indiana, IN.

Dunn, R. and Dunn, K. (1999), The Complete Guide to the Learning Strategies Inservice System,Allyn & Bacon, Boston, MA.

Eagley, A.N. (1987), Sex Differences in Social Behavior: A Social Role Interpretation, Erlbaum,Hillsdale, NY.

Else-Quest, N.M., Hyde, J.S., Goldsmith, H.H. and van Hulle, C.A. (2006), “Gender differences intemperament: a meta analysis”, Psychological Bulletin, Vol. 132 No. 1, pp. 33-72.

Epstein, S. and Feist, G.J. (1988), “Relation between self- and other-acceptance and its moderationby identification”, Journal of Personality and Social Psychology, Vol. 54 No. 2, p. 309.

Fazarro, D. and Stevens, A. (2004), “Topography of learning style preferences of undergraduatestudents in industrial technology and engineering programs at historically black andpredominantly white institutions”, Journal of Industrial Teacher Education, Vol. 4 No. 8,pp. 5-29.

Feingold, A. (1994), “Gender differences in personality: a meta-analysis”, Psychological Bulletin,Vol. 116, pp. 429-56.

Ferriman, K., Lubinski, D. and Benbow, C.P. (2009), “Work preferences, life values, personalviews of top math/science graduate students and the profoundly gifted: developmentalchanges and gender differences during emerging adulthood and parenthood”, Journal ofPersonality and Social Psychology, Vol. 97 No. 3, pp. 517-32.

Gilbert, G.R., Burnett, M. and Leartsurawat, W. (2010), “The psychological work preferences ofbusiness students”, Journal of Career Assessment, Vol. 18 No. 2, pp. 189-206.

Gilbert, G.R., Sohi, R.S. and McEachern, A.G. (2008), “Measuring work preferences:a multidimensional tool to enhance career self management”, Career DevelopmentInternational, Vol. 13 No. 1, pp. 56-78.

Hicks, B.M., Johnson, W., Iacono, W.G. and McGue, M. (2008), “Moderating effects of personalityon the genetic and environmental influences of school grades helps to explain sexdifferences in scholastic achievement”, European Journal of Personality, Vol. 22, pp. 247-68.

Hirschi, A. and Lage, D. (2007), “Holland’s secondary constructs of vocational interests andcareer choice readiness of secondary students”, Journal of Individual Differences, Vol. 28No. 4, pp. 205-18.

Hofstede, G. (1980), “Motivation, leadership and organization: do American theories applyabroad”, Organizational Dynamics, Vol. 9, pp. 42-63.

Hofstede, G. (2001), Cultures Consequences: Comparing Values, Behaviors, Institutions, andOrganizations across Nations, 2nd ed., Sage, Thousand Oaks, CA.

Hogan, R. and Hogan, J. (1992), Hogan Personality Inventory Manual, Hogan AssessmentSystems, Tulsa, OK.

GM25,8

696

Holland, J. (1992), Making Vocational Choices, 2nd ed., Psychological Assessment Resources,Odessa, FL.

Holland, J. (1997), Making Vocational Choices: A Theory of Vocational Personalities and WorkEnvironments, 3rd ed., Psychological Assessment Resources, Odessa, FL.

House, R.J., Hanges, P.J., Javidan, M., Dorfman, P.W. and Gupta, V. (2004), Culture, Leadership,and Organizations: The GLOBE Study of 62 Societies, Sage, Thousand Oaks, CA.

Hyde, J.S. (2005), “The gender similarities hypothesis”, American Psychologist, Vol. 60 No. 6,pp. 581-92.

Inglehart, R. and Baker, W.E. (2000), “Modernization of cultural change and the persistence oftraditional values”, American Sociological Review, Vol. 65, pp. 19-51.

Judge, T., Cable, D., Boudreau, J. and Bretz, R. (1995), “An empirical investigation of thepredictors of executive career success”, Personnel Psychology, Vol. 52, pp. 621-52.

Kanawattanachai, P. and Yoo, Y. (2002), “Dynamic nature of trust in virtual teams”, Journal ofStrategic Information Systems, Vol. 11, pp. 187-213.

Katz, D. and Kahn, R.L. (1978), The Social Psychology of Organizations, 2nd ed., Wiley,New York, NY.

Kleinfeld, J. (1999), “Student performance: males vs females”, Public Interest, Vol. 134, Winter,pp. 3-20.

Konrad, A.M., Ritchie, J.E. Jr, Lieb, P. and Corrigall, E. (2000), “Sex differences and similarities injob attribute preferences: a meta-analysis”, Psychological Bulletin, Vol. 126 No. 4,pp. 593-641.

Kostova, T. (1999), “Transnational transfer of strategic organizational practices: a contextualperspective”, Academy of Management Review, Vol. 24 No. 2, pp. 308-24.

Kuhn, J. and Holling, H. (2009), “Gender, reasoning ability, and scholastic achievement:a multilevel mediation analysis”, Learning and Individual Differences, Vol. 19 No. 2,pp. 229-33.

Lippa, R.A. (2001), “On deconstructing masculinity-femininity”, Journal of Research inPersonality, Vol. 35, pp. 168-207.

McClelland, D.C. (1985), “How motives, skills, and values determine what people do”, AmericanPsychologist, Vol. 40 No. 7, pp. 812-25.

McClelland, D.C. and Boyatzis, R.E. (1982), “The leadership motive pattern and long-term successin management”, Journal of Applied Psychology, Vol. 6, pp. 737-43.

McClelland, D.C., Atkinson, J.W., Clark, R.A. and Lowell, E.L. (1976), The AchievementMotivation, Irvington, New York, NY.

McCaulley, M. (1990), “The Myers-Briggs type indicator: a measure for individuals and groups”,Measurement and Evaluation in Counseling and Development, Vol. 24 No. 4, pp. 181-95.

Macoby, E.E. and Jacklin, C.N. (1974), The Psychology of Sex Differences, Stanford UniversityPress, Stanford, CA.

Malach-Pines, A. and Kaspi-Baruch, O. (2008), “The role of culture and gender in the choice of acareer in management”, Career Development International, Vol. 13 No. 4, pp. 306-19.

Malka, A. and Chatman, J. (2003), “Intrinsic and extrinsic orientations as moderators of the effectof annual income on subjective well-being: a longitudinal study”, Personality and SocialPsychology Bulletin, Vol. 29 No. 6, pp. 737-46.

Meier-Pesti, K.A. (2008), “Sex or gender? Expanding the sex-based view by introducingmasculinity and femininity as predictors of financial risk taking”, Journal of EconomicPsychology, Vol. 29 No. 2, pp. 180-96.

Does gendermatter?

697

Meyer, J.W. (1977), “The effects of education as an institution”, American Journal of Sociology,Vol. 83 No. 1, pp. 55-77.

Meyers-Levy, J. (1988), “Influence of sex roles in judgement”, Journal of Consumer Research,Vol. 14, pp. 522-30.

Miller, J.G. (1968), “Living systems; basic concepts”, in Gray, W., Duhl, F.D. and Rizzo, N.D. (Eds),General Systems Theory and Psychiatry, Little Brown, Boston, MA.

Munroe, R.L. and Romney, A.K. (2006), “Gender and age differences in same-sex aggregation andsocial behavior: a four-culture study”, Journal of Cross-Cultural Psychology, Vol. 37,pp. 3-19.

Nash, S.C. (1975), “The relationship among sex-role stereotyping, sex-role preference, andsex-difference in spatial visualization”, Sex Roles, Vol. 1, pp. 15-32.

Parboteeah, K.P., Hoegl, M. and Cullen, J.B. (2008), “Manager’s gender role attitudes: a countryinstitutional profile approach”, Journal of International Business Studies, Vol. 39,pp. 795-813.

Prediger, D. (1976), “A world of work map for career exploration”, Vocational GuidanceQuarterly, Vol. 24, pp. 198-208.

Ralston, D.A., Holt, D.H., Terstra, R.H. and Kai-Cheng, Y. (1997), “The impact of national cultureand economic ideology on managerial work values: a study of the United States, Russia,Japan and China”, Journal of International Business Studies, Vol. 28 No. 1, pp. 177-207.

Raynor, J.L. (2007), “Comparative civilian labor force statistics, 10 countries: a visual essay”,Monthly Labor Review, Vol. 130 No. 12, pp. 32-7.

Rounds, J. and Armstrong, P.I. (2005), “Assessment of needs and values”, in Brown, S.D. andLent, R.W. (Eds), Career Development and Counseling: Putting Theory and Research toWork, Wiley, Hoboken, NJ, pp. 305-29.

Rounds, J., Dawis, R. and Lofquist, L. (1987), “Measurement of person-environment fit andprediction of satisfaction in the theory of work adjustment”, Journal of VocationalBehavior, Vol. 31 No. 3, pp. 297-318.

Rounds, J., Henly, G. Jr, Dawis, R., Lofquist, L. and Weiss, D. (1981), Manual for the MinnesotaImportance Questionnaire: A Measure of Vocational Needs and Values, University ofMinnesota, Minneapolis, MN.

Rowe, R. and Snizek, W. (1995), “Gender differences in work values: perpetuating the myth”,Work and Occupations, Vol. 22 No. 2, pp. 215-29.

Rutherford, S. (2001), “Any difference? An analysis of gender and divisional management stylesin a large airline”, Gender, Work and Organization, Vol. 8 No. 3, pp. 326-45.

Schmitt, D.P., Realo, A., Voracek, M. and Allik, J. (2008), “Why can’t a man be more like awoman? Sex differences in Big Five personality traits across 55 cultures”, Journal ofPersonality and Social Psychology, Vol. 96 No. 1, pp. 168-82.

Shafiro, M.V., Himelein, M.J. and Best, D. (2003), “Ukrainian and US American females:differences in individualism/collectivism and gender attitudes”, Journal of Cross-CulturalPsychology, Vol. 34, pp. 297-303.

Singer, A.R., Cassin, S.E. and Dobson, K.S. (2005), “The role of gender in the career aspirations ofprofessional psychology graduates: are there more similarities than differences”, CanadianPsychology, Vol. 46 No. 4, pp. 215-22.

Stedham, Y.E. and Yamamura, J.H. (2004), “Measuring national culture: does gender matter?”,Women in Management Review, Vol. 19 No. 4, pp. 233-43.

Tarvis, C. (1992), The Mismeasure of Women, Simon and Schuster, New York, NY.

GM25,8

698

Thomas, J.R. and French, K.E. (1985), “Gender differences across age in motor performance:a meta-analysis”, Psychological Bulletin, Vol. 98, pp. 260-82.

von Bertalanffy, L. (1951), Theoretische Biologie, Vols. I, II, Borntraeger, Berlin, (1932, 1942;2nd ed., Francke, Bern).

Westerman, J.W. and Simmons, B.L. (2007), “The effects of work environment on thepersonality-performance relationship: an exploratory study”, Journal of Managerial Issues,Vol. 19, pp. 288-306.

Corresponding authorG. Ronald Gilbert can be contacted at: Ron.GilbertEMS@gmail.com

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