8 cluster countries
TRANSCRIPT
"Academy of Management Review, 1985, Vol. 10, No. 3, 435-454.
Clustering Countrieson Attitudinal Dimensions:
A Review and Synthesisby
SIMCHA RONENNew York University
ODED SHENKARTel-Aviv University, Israel
Eight empirical studies using attitudinal data to cluster countries arereviewed. The major dimensions accounting for similarities amongcountries are discussed, and a final synthesis of clusters is presented.
As a field of inquiry, comparative managementinvolves the cross-cultural comparison of behav-ior in organizations. More specifically, it attemptsto establish the degree to which cultural environ-ment systematically influences employees' atti-tudes and behavior in addition to influencingintracultural individual differences. Assumingthat there is sufficient justification for treatingcultures as distinct entities, and assuming alsothat nations can be operationalized as practicalproxies for these entities, one line of researchhas attempted to establish clusters of countriesbased on their relative similarity according torelevant organizational variables. This paperreviews the published literature on country clus-tering and proposes a map that integrates andsynthesizes the available data.
The variables forming the basis for the empiri-cal grouping reviewed here are related to em-ployee work attitudes. The comparisons are basedprimarily on general attitudes towards work (asreflected in the individual's work values or goals)rather than on more specific attitudes relevant tothe immediate job and its conditions. These vari-ables are used to group countries or nations, asopposed to cultures, as the unit of analysis.
By defining the country as the unit of analysis,the clustering of these countries has important
Requests for reprints should be sent to Simcha Ronen, Man-agement Department, Graduate School of Business Admi-nistration, New York University, 90 Trinity Place, New York,NY 10006.
implications for managers and academicians.Managers in multinational corporations (MNCs)can better understand the basis for similaritiesand differences between countries. With thisknowledge, they can more effectively place inter-national assignees, establish compatible regionalunits, and predict the results of policies and prac-tices across national boundaries (Ronen & Kraut,1977). Clusters also can help academicians bydefining the extent to which results should begeneralized to other countries. Properly employedresults from one country can be generalized tothe entire group of countries sharing a particularvariable within the same cluster. Clusters alsoaid the researcher in identifying variables thatexplain the variance in work goals and manage-rial attitudes—variables such as language, religion,or level of industrialization.
StudiesEight cluster studies emerged from the litera-
ture search. These included Haire, Ghiselli, andPorter (1966); Sirota and Creenwood (1971);Ronen and Kraut (1977); Hofstede (1976); Griffeth,Hom, Denisi, and Kirchner (1980); Hofstede(1980); Redding (1976); and Badawy (1979).
Two of the studies under review examined oneworld region each. Redding (1976) studied eightcountries in Southeast Asia, and Badavkry (1979)studied six countries in the Middle East. Al-though these studies did not perform any cluster-ing of countries, there are good reasons to include
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them in the review. The Arab group that Badawysurveyed did not appear in any other study, andits inclusion provides information on a worldregion with distinct work goals. Redding's studyof Southeast Asia provides additional informa-tion on work values in countries not surveyedelsewhere—namely, Indonesia, Malaysia, andSouth Vietnam—thus allowing a broader inspec-tion of the variations within this region. Also,data from different organizations in Hong Kong,Japan, the Philippines, Singapore, and Thailandcan be compared to data collected by Hofstede(1980) on subsidiaries of an MNC in thosecountries.
Two of the eight studies reviewed take the formof books rather than papers (Haire et al., 1966;Hofstede, 1980). Needless to say, the book formatallowed a more detailed report of both theoryand methodology than would have been possiblein a paper. Also, some studies used in-house datacollected by an MNC; others collected datadesigned specifically for the study (Haire et al.,1966).
This paper discusses the variables used in thestudies, the sampling, questionnaire administra-tion, and the procedure for data analysis. It evalu-ates the methodological rigor of these studies,establishes a basis for comparison and synthesis,and suggests future directions for research.
Variables
The studies reviewed dealt with various vari-ables that can be grouped into four categories:work goal importance; need deficiency, fulfill-ment, and job satisfaction; managerial and organi-zational variables; and work role and interper-sonal orientation. The variables used in eachstudy and the research instruments are presentedin Table 1.
Work goal importance was surveyed by Haireet al. (1966) through an 11-item scale, later uti-lized by Redding (1976). Sirota and Greenwood(1971) listed 14 work goals; Ronen and Kraut(1977) used a list of 22 work goals (for their owndata); and Hofstede (1980) used several surveys,each with a different number of work goals.However, all the scales used are based on a modi-fied Maslow (1954) list of categories, and thereappears to be a reasonable basis for comparison.
Need deficiency, fulfillment, and job satisfac-tion were examined by Haire et al. (1966) through11 items depicting a modified Maslow needcategories. The questionnaire omits biologicalneeds and splits the ego needs into autonomyand esteem. The same instrument was used byRedding (1976). Badawy (1979) utilized a 13-iteminstrument based on Porter's (1961) derivation ofMaslow's categories. Hofstede (1980) used morethan one survey and therefore a different numberof items. Griffeth et al. (1980) used an attitudesurvey to measure satisfaction with nine jobfacets.
Need importance and need satisfaction are fun-damentally different. Unlike need importance,need satisfaction is constrained by the indivi-dual's immediate job (Guion, 1958) and is tied tothe particular reward structure (Deci, 1971). Canstudies that survey work goal importance becompared, then, to studies that survey aspects ofsatisfaction? A partial empirical answer is pro-vided by Haire et al. (1966) as well as by Redding(1976) who studied both importance and satisfac-tion variables with similar results. Caution issuggested, however, when these two differenttypes of job attitudes are compared.
Four studies examined managerial or organiza-tional variables. Two studies used eight itemsdepicting classical versus democratic managerialattitudes toward the capacity for leadership andinitiative, the sharing of infonnation and objec-tives, and participation and internal control(Badawy, 1979; Haire et al., 1966). Hofstede(1980), who also examined managerial styles,used a different instrument, asking respondentsto choose among four tjrpes of managers charac-terizing their actual and preferable supervisor.Griffeth et al. (1980) examined organizationalvariables; role overload, organizational commit-ment, organizational climate, and organizationalstructure.
Three studies surveyed work role and interper-sonal orientation. Haire et al. (1966) researchedcognitive descriptions of the managerial roleusing a semantic differential technique (which,incidentally, reduced the response rate for theentire study). Redding (1976) briefly studied rela-tions with subordinates. Hofstede (1976) used thesurvey of personal values (Gordon, 1967, 1976)to measure practical mindedness, achievement.
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Table 1Variables Used in the Studies Reviewed
Fieldstudies
Variables
Work goalsimportance
Needdeficiency.fulfillment.ft jobsatisfaction
Managerial ftorganizationalvariables
Work role ftinterpersonalorientation
Haire, SirotaGhiselli, ft
ft GreenwoodPorter (1971)(1966)
11 itemsbased onmodified 14 workMaslow's goals
categories'
11 itemsbased onmodified —Maslow's
categories
8 itemsdepictingclassical
or democratic —managerialstyle
Cognitivedescriptions
of the —managerialrole
Hofstede(1976)
—
• - <-••
— . , .
Survey ofPersonalValues (SPV)ft Survey ofInterpersonalValues (SrV)
Redding(1976)
11 itemsas inHaireet al. (1966)
11 itemsas inHaireet al. (1966)
Relationswith
subordinates
, • - ' • !
Ronenft
Kraut Badawy(1977) (1979)
22 work —goals'"
13 itemsbased on
— Maslow'scategories
(Porter'sinstrument)
8 itemsdepictingmanagerial
— styleas inHaire et al.(1966)
— —
Griffeth,Hom, Denisi,
ftKirchner
(1980)
65 items ofsatisfactionwith 9jobfacets
Organizationalvariables.role overload.organizationalcommitment.organizationalclimate andstructure
—
• ' • • • - . ! . ' . ' ' " • •
• , . . . . , . ^ . - . • . , _
Hofstede(1980)
Varyingnumberof itemsfromdifferentsurveys'̂Variousnumberof itemsfromdifferentsurveys
Manager'sstyle:present ftdesired
, : -,. ,
• . , - ' — •
' The modified Maslow's hierarchy applied by Haire, Ghiselli, ft Porter (1966) omits biological needs and adds the higher levelneed of autonomy. The modified list thus contains the following needs: (1) security, (2) social, (3) esteem, (4) autonomy, (5) selfactualization. : . .
•Tlonen ft Kraut (1977) also analyzed Haire et al's and Sirota ft Greenwood's data.Tactors extracted were power distance, uncertainty avoidance, individualism, and masculinity. ' ,
variety, decisiveness, orderliness, £ind goalorientation; he also used the survey of interper-sonal values (Gordon, 1975) to measure support,conformity, recognition, independence, benevo-lence, and leadership.
A review of the variables raises the question ofhow comparable the data are in these eightstudies. Five studies referred to work goals im-portance; another five surveyed need deficiency,fulfillment, and job satisfaction; four studiesincluded managerial or organizational variables;and three studies examined work role and inter-personal orientation. Furthermore, the same vari-
ables were frequently measured using differentinstruments.
Nevertheless, there seem to be important rea-sons for comparing and synthesizing the variousstudies. First and foremost, these studies repre-sent the most sophisticated efforts available inclustering work attitude by nations, and they pro-vide guidelines for future research. Second, thereis a substantial overlap in the variables exam-ined in the various studies, which increases thereliability of the comparison. Finally, five of thereviewed studies used multiple variables; theremaining three employed values or work goals.
437
It is suggested here, however, that work goals arepreferable to other variables. Work goals are lessconstrained by the immediate job and environ-ment, and they best represent the cultural milieuof individuals, thus allowing for more thoroughcross-national research. It has been suggested thatone of the major links between the cultural milieuand individuals' job behavior lies in their workvalues (England, 1978, Haire et al. 1966; Hofstede,1980). The use of alternate measures to examinethe stability of clusters is another possible stra-tegy. It may be necessary, however, to use diversemeasures in the same study to attribute cluster-ing differences to the measures applied.
r SamplingThe sampling method carries important impli-
cations for how representative the studies are.
how much one can generalize from them, andhow easily they can be replicated. Table 2 pre-sents the sampling methods in the studiesreviewed.Sample Size
The samples reviewed vary from 248 employ-ees in six Middle Eastern countries (Badawy,1979) to 88,000 in 66 countries (Hofstede, 1980).Fiscal and technical considerations constrain theuse of large samples, which usually are unavail-able to the academic researcher. In some of thestudies reviewed, however, the samples seem toosmall to represent the worker population in thecountries surveyed. It is recommended that thesample size for each country be reported and thatresearchers follow Sirota and Creenwood (1971)and Hofstede (1976) in omitting from their analy-sis countries represented by too few respondents.
Table 2Research Procedure Describing Samples and Questionnaires
Haire,Ghiselli,& Porter(1966)
Sirota& Greenwood
(1971)Hofstede
(1976)Redding(1976)
Ronen &Kraut
(1977)'Badawy(1979)
Griffeth.Hom, Denisi.& Kirchner
(1980)
Hofstede(1980)
SampleSize
^:p:i:yi%i:'^rNumber
of countries
MinimumSample Sizeof eacbcountry
Organiza-tion level/function
Control forethnic/linguisticaffiliation
Responserate
Inclusion ofonly thosebom. reared.educated insame country
3,641
14
All samplesare above100
Various levelsof manage-ment
Notreported
Notreported
Notreported
about 13.000
40 in eachoccupationalgroup y;
SalesmenTecbnical
PersonnelService
Pereonnel
Notreported
Notreported
Notreported
315
14
7
Middle-levelmanagers
Reported
Notreported
Notreported
736
8(SoutheastAsia only)
Notreported
Middle-levelmanagers
Reported
Notreported
Reported
4.000
At least 40
Tecbnicians
Notreported
Notreported
Notreported
248
6in the Middle
EastNot
reported
Mid-manage-ment (exactdefinitiongiven)
Notreported
85% (251,248 usableout of 295)
Notreported
1768
15 Westerncountries
11
Managers
- . ,
Reported
Notreported
Notreported
Total of88,000 respon-dents in twosurveys.
65(66 including
U.S.)Varies, whereless tban 8respondentson some itemsdata omitted.Variousoccupationallevels
Reported
Notreported
Notreported
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Table 2 (Continued)
Haire,Gbiselli.& Porter(1966)
Sirota& Greenwood
(1971)Hofstede
(1976)Redding(1976)
Ronen &Kraut
(1977)*Badawy(1979)
Griffetb,Hom. Denisi.ft Kircbner
(1980)
Hofstede(1980)
Backgroundinformationon employees
Organizationsize
Industry
Headquarterslocation
Question-nairetranslation
Question-naireadministra-tion
• Age• Education
Reported
A variety ofbusinesses ftindustries
Irrelevant
Yes, includ-ing backtranslation +cbecking bylocal socialscientists ftbusinessmen
Throughcompanies.employers'associations.universities.trainingcenters.
Occupation(tbe above 3groups)
Notreported
Manufacturerof electricalequipment(one organi-zation)
U.S.A.
Yes, includ-ing backtranslation ftpretesting
Groupsession.on site.companytime.
• Age• Occupation• Sex (3females)
Notreported
Notreported
Irrelevant
No. Question-naireadministeredin English
A manage-ment deve-lopmentprogram atIMEDE,Switzerland.
Notreported
Reported.just overbalf fromorganiza-tionsemployingless than100 people.
Notreported
Irrelevant
Only for 3countries.Face-to-faceadministra-tion
Part timetraining invariousinstitutionsof bigbereducation +in-company
• occupation(comparisonto Haire etal.; Siroteft Greenwood)
Not reported(large sizeimplicit fromnumber ofsubsidiaries)
Multi-nationalelectroniccompany (oneorganization)
U.S.A.
Yes, includ-ing back-translation
Companytime
• Age• Experience• Education• Occupation• Department
Reported
• Cbemical• Petroleum• Transpor-
tation(no control)
Irrelevant
No transla-tion. Res-pondentsfluent inEnglish
Trainingprogram'sparticipantsin SaudiArabia. ,
• . - , ' - • - ' •
Notreported
Reportedas "large"
Intemationaimanufacturingcorporation(one organi-zation)
U.S.A.
Yes
On location
- • • . • • . 1
. - :...• . - [.:
• Occupation• Sex•Age
Implicit fromnumber ofsubsidiaries.
Manufacturerft seller ofbigb tecbno-logy products(one organi-zation)
U.S.A.
Yes. Gbeck byin-companypersonnel.Back-translationonly exceptio-nally
Gompany-administered
" Ronen ft Kraut (1977) also reanalyzed tbe data from Haire, Gbiselli, ft Porter (1966) and Sirota ft Greenwood (1971). Tbe data presented in tbiscolumn pertain only to Ronen ft Kraut's own data. .
Response Rate
With the exception of Badawy (1979), none ofthe reviewed studies reported the rate of responsefor their sample. The rate of response, however,may influence the representativeness of the sam-ple because a possible bias may be inherent inthe process of self-selection. Haire et al. (1966)were aware of the response problem and sug-gested that those inclined to cooperate may havebeen impressed by modern human relationsmanagement.
Organizational Level
The eight studies surveyed different groups ofemployees. The middle management groups(used in three samples) were too vaguely definedin two studies (Hofstede, 1976; Redding, 1976).One study provided a detailed list of occupa-tional titles included in the middle managementsample (Badawy, 1979). In Criffeth et al. (1980),the group studied was even broader—namely,managers—with no specification of level. Haire etal. (1966) studied various levels of managers and
439
noted the modest impact of managerial levels ontheir findings. Extending beyond the manageriallayer, however, there were few studies. Hofstede(1980) studied various occupational groups.
Sirota and Creenwood (1971) surveyed threenonsupervisory groups: salesmen, technical per-sonnel, and service personnel. Ronen and Kraut(1977), in addition to reanalysis of Haire et al.(1966), and Sirota and Creenwood (1971) stud-ied technicians, thus adding to the relatively lim-ited knowledge of nonmanagerial personnel.Sirota and Creenwood (1971) illustrated the prob-lems involved in comparing data sets based ondifferent types of workers. They reported sub-stantial differences in the importance of workgoals for the different kinds of workers studied.For instance, job security was ranked 2.5 by ser-vice personnel, but only 10 and 11 by salesmenand technical personnel. Elsewhere, Kraut andRonen (1975) have shown that both country andoccupation contributed to differences in workattitude and behavior.
Organizational Size
The size of the employing organization wasnot always reported (Hofstede, 1976). In somestudies, a large organization was implicit in thenumerous subsidiaries reported (Ronen & Kraut,1977). Redding (1976) noted that just over half ofthe respondents in his sample came from organi-zations employing less than 100 people. Haire etal. (1966) reported organizational size for allrespondents. The omission of organizational sizeby several authors may point to an additionalconstraint on the ability to generalize findingsbased on the samples reviewed. The impact ofsize on organizational structure as well as on jobattitudes and behavior (Porter & Lawler, 1965)has already been established. Haire et al. (1966),for instance, found that managers from largercompanies were more inclined towards a demo-cratic-participative managerial attitude. Badawy(1979) found that those coming from smallerorganizations were more democratic regardingsubordinates' capacity for leadership and partici-pation in goal setting. Workers in smaller organi-zations, however, held a classical view towardthe sharing of information and the intemal con-trol of rewards. Organizational size thus was the
only variable that could explain variation in inter-nal control. ,, . ._
Industry
Some studies (Hofstede, 1976; Redding, 1976)did not specify the industry in which the respon-dents were employed. Badawy (1979) specifiedthe type of industry, but did not report any break-down of findings by this variable. (For a fewstudies that researched the employees of onecompany each, the question was, of course,irrelevant.) If differences in departmental affilia-tion can explain some of the variance in employeework goals, one can assume that the type of indus-try in which workers are employed also will havean impact on these goals.
Headquarters Location
The studies involving one company (Sirota &Greenwood, 1971) were careful to note the loca-tion of company headquarters, a variable thatseems to have considerable importance. Know-ing the country of origin, for instance, may helpassess the extent to which an MNC influencesthe values of its overseas workforce toward greaterconformity with the values of its country of origin.
Departmental Affiliation
Hofstede (1976) found that employees' area ofemployment (e.g., finance, marketing) influencedtheir work-related personal values (though theinfluence was not significant). Badawy (1979)reported that marketing and general administra-tion managers were most democratic in their lead-ership style preference and production execu-tives had the most autocratic attitude. Productionmanagers favored the sharing of objectives andinformation; financial executives objected. Par-ticipation in goal setting was endorsed only bypersonnel managers.
Demographic Variables
Some studies did not report any demographicinformation on employees (Criffeth et al., 1980;Redding, 1976). Age was reported in four studies;occupation, in five studies; sex and education, intwo studies; experience and department, in onestudy (Badawy, 1979). Data already at hand,however, suggest that part of the variance in
440
employee work goals is explained by demo-graphic variables rather than by country.
Education
Hofstede (1980) found that education correlatedwith both individualism and masculinity indi-ces (which he extracted from work goals), thusestablishing a connection between educationallevel and work goals.
Age and Experience
Haire et al. (1966) reported that older manag-ers showed greater fulfillment of needs but weremore dissatisfied with this fulfillment. Hofstede(1976) reported that older managers describedthemselves as more "conforming" and more"benevolent" (with nonsignificant lower "sup-port" and "independence"). Badawy (1979)found that managers in the 30 to 39 age grouptook a more democratic view of leadership stylethan did both younger and older managers; thatthose between 25 and 34 had a more democraticattitude towards the sharing of infonnation andobjectives; and that those between 40 and 44favored participation in goal setting more thanothers. Badawy found that managers with lessexperience favored a classic autocratic attitudetowards subordinates and that the two middlegroups held a classical view of participation ingoal setting.
Sex
As Hofstede (1980) summarized, males in moststudies rated advancement and earnings as moreimportant; females scored interpersonal relations,service, and physical environment as moreimportant.
Origin and Ethnic Affiliation
Almost no information about origin of therespondents is provided by the studies. OnlyRedding (1976) emphasized that he included onlythose born, reared, and educated in the samecountry. Needless to say, a failure to account forthose factors might be an enormous source oferror in such studies.
Not all studies surveyed have taken intoaccount the diversity within a country's borders.Haire et al. (1966), Sirota and Creenwood (1971),Ronen and Kraut (1977), and Badawy (1979) do
not report whether they took note of this factor.In contrast. Redding (1976) included only desig-nated ethnic and linguistic groups—for instance,the Chinese in Singapore. Similarily, both Hof-stede (1976, 1980) and Criffeth et al. (1980) dis-tinguished among the different linguistic seg-ments of Swiss population.
Reporting a country's internal diversity isimportant. Many countries are not homogeneous;they consist of various populations. They maydiffer according to language (French and Flemishin Belgium; French, Cerman, and Italian inSwitzerland, etc.); according to climate and dif-fering proximity to other countries (e.g.. North-em and Southern Italy); or according to urban/mral and other differences. These factors shouldaffect the choice of sample—or at least be notedand accounted for.
To summarize the sampling procedures, thereseems to be enough overlap in the samples cho-sen to justify a synthesis despite the differencein the sampling methods. For instance, most stud-ies include a managerial layer in their sample,and all four studies that examined one MNCchose a U.S.-based corporation. It is recom-mended, however, that in the future, researcherswill report national sample sizes and responserates as well as individual and organizationalinformation for respondents. The additional datawill facilitate the assessment of the representa-tiveness of the samples and will enable a moreprecise comparison of work goals and attitudesamong various groupings.
Preparation and Administration ,of Questionnaire u
An essential part of any empirical research isthe method for collecting data from the desig-nated sample. Two aspects are of particularimportance in cross-cultural research: translationand administration of questionnaires. The dataare presented in Tahle 2.
Language is not only an important explanatoryvariable in cross-cultural studies, but also a vitalinstrument of research in such studies. Of theeight studies reviewed, two (Badaviry, 1979;Hofstede 1976) did not use translated question-naires because the respondents were fluent inEnglish. Although the problem is minimized inthis case, there is a possibility that respondents
441
from different countries attach different mean-ings to similar questions. In Redding's study(1976), translation was made for three of the eightcountries surveyed. This might raise a problemof reliability, although the face-to-face adminis-tration of the questionnaire may have solved partof the problem.
The other six studies relied on translation ofthe questionnaire into the local languages. At leastone study (Criffeth et al., 1980) did not report aback-translation or any other measure to exam-ine the instrument's validity. (Back-translationmeans the translation of the questionnaire intothe native language, then translation back intothe original language as a check.) Hofstede (1980)checked translation by in-company personnel, butback-translation was used only sporadically.Ronen and Kraut (1977) used back-translation;Sirota and Creenwood (1971) supplemented itwith pretesting. The most rigorous translation wasused by Haire et al. (1966), whose back-translationwas supplemented by the checking of the transla-tion by local social scientists and businessmen.
Researchers administered the questionnaires indifferent ways. Three of the studies used the con-venience of a training program to collect informa-tion (Badawy, 1979; Hofstede, 1976; Redding,1976). However, this arrangement might intro-duce a source of error—namely, trainees could bea particular group whose goals do not necessar-ily represent those of the entire organization (notto mention the entire population of workers in agiven country). Other studies collected informa-tion on location (Criffeth et al., 1980), on com-pany time (Ronen & Kraut, 1977), or else collec-tion was company-administered (Hofstede, 1980).What seems particularly unreliable is a mixtureof the two types discussed. Redding (1976) col-lected information from managers undergoingtraining programs and made "a small addition"of in-company executives. Redding did not pro-vide a breakdown of findings for the two groups,thus making it impossible to account for possiblediscrepancies in their responses.
The use of some kind of check on virtually alltranslations suggests that there is a basis for com-paring and synthesizing the data generated fromthe various studies. A thorough back-translationof questionnaires, however, is strongly urged forfuture studies. It also is recommended that, when-
ever possible, questionnaires be administered onsite rather than in various training programs.
Procedure and Analysis
The six studies that performed worldwide clus-tering all employed some type of multivariateprocedure in their analysis. These proceduresmay be classified as either metric or nonmetricmethods. Metric analysis was predominant, assignified by its use in five of the six clusteringstudies.
Haire et al. (1966) used factor analysis to studycognitive descriptions of the managerial rolethrough a semantic differential technique. Factorscores were calculated on the basis of the factorloadings of the nine scales comprising that partof the study. To create country clusters, theauthors obtained a correlation matrix on the basisof all three parts of their study, each given equalweight. Countries were grouped on the basis ofsimilarity, each cluster consisting of countriessimilar to one another and dissimilar to coun-tries in other clusters.
A Q (inverted) factor analysis was used bySirota and Creenwood (1971) and by Hofstede(1976). In his 1980 study, Hofstede performedfactor analysis within and between groups(ecological). He acknowledged trying smallestspace analysis with very similar results to factoranalysis. Hofstede (1980) preferred factor analy-sis because of his greater familiarity with thismethod.
Griffeth et al. (1980) used the generalizedPjrthagorean distance measure (D )̂ to measureprofile similarity. Cluster analysis was appliedto the D^ scores to create country clusters. Theauthors applied a one-way multivariate analysisof variance to determine the main effect of nation-ality. A multigroup discriminant analysis wasperformed to interpret the results of the analysis.
The only use of nonmetric multivariate analy-sis was by Ronen and Kraut (1977), who em-ployed the technique for their own data as wellas for their reanalysis of the data in Haire et al.(1966) and Sirota and Greenwood (1971).
The consensus among the researchers thatmultivariate analysis is vital in the process ofclustering raises the question of whether metricor nonmetric techniques are preferable. There are
442
advantages and disadvantages to each method,but the present authors suggest that nonmetrictechniques generally are better suited to the pur-pose of cross-cultural clustering (Ronen, 1982).
Smallest Space Analysis (SSA)
Smallest space analysis is one of several non-metric multidimensional scaling techniques. (Asimilar technique is the ALSCAL, by Takane,Young, & DeLeeuw, 1976.) Developed by Guttman(1968) and Lingoes (1965, 1977), the SSA pro-vides a geometric representation of the variablesas points in Euclidean space, so that distances inthis space are inversely related to correlations.
Factor analysis and SSA both identify clustersand presumed factors by finding interrelatedgroups of correlation coefficients. In both tech-niques, a set of coordinates (factor loadings) iscalculated for locating tbe cases as points inspace, yielding a similar basic configuration(Scblesinger & Guttman, 1969). SSA and factoranalysis differ, however, in several respects:
1. Factor analysis treats the correlation coefficientas a measure of the common variance to bedecomposed; SSA uses the correlation coeffi-cient as an index of similarity (Karni & Levin,1972).
2. Factor analysis assumes an interval level ofmeasurement; SSA requires only ordinal mea-surement (Karni & Levin. 1972).
3. Factor analysis tries to account for commonvariance through a limited number of presumedunderlying variates; SSA emphasizes the con-figuration of the variables and the interpreta-tion of order relations among the data (Karni &Levin, 1972).
4. In contrast to SSA, factor analysis utilizes asingle, rigid formula for reproducing observedcorrelations from the interpoint distances inthe common-factor space (Schlesinger & Gutt-man, 1969).
5. SSA involves a priori assumptions on the struc-ture of tbe variables; factor analysis does not.
As a result of tbe above differences, SSA main-tains several important advantages over factoranalysis, some of whicb are particularly usefulfor tbe clustering of countries in terms of em-ployee work goals (Ronen, 1982).
1. Tbe statistical rigidities and indeterminanciesregarding both rotations and stopping criteriacontained in factor analysis have some draw-backs. For instance, tbe classification of a largenumber of variables into factors based on a vari-ety of rotational criteria may obscure ratber than
clarify tbe relationsbips of tbe variables to oneanotber botb witbin and across factors (Ronen,Kraut, Lingoes, and Aranya, 1979).
2. Relationsbips among clusters can be identifiedmore easily in SSA than in factor analysis. Instudying work goals, for example, tbe SSAenables tbe identification of clusters of em-ployee work goals, interrelationsbips amongtbese clusters, and interrelationsbips amongindividual work goals witbin tbe clusters. Inotber words, SSA reveals tbe relationsbipsamong variables witbin regions as well as therelationsbips of various regions to one anotber(Ronen et al., 1979).
3. Tbe SSA is less sensitive to measurement diffi-culties sucb as noninterval level measurement,distributional properties due to scaling, or atten-uation due to cbanges in reliability (Ronen etal., 1979). For example, it is questionablewbetber an interval assumption on work goalsis justifiable, because it assumes equal inter-vals among tbe values of eacb item.
4. Tbe SSA can reveal more fundamental orderrelations (order in terms of classification andnot in terms of tbe prepotency of factors). Byviewing tbe space as a wbole ratber tban con-centrating on specialized problems of rotationof axes, SSA is more useful tban factor analysisin identifying tbe general configurationalproblems, ieading to a better understanding oftbe researcbed pbenomenon. Tbus, tbe analy-sis of work goals in terms of SSA definitionalfacets may lead to more fundamental insigbtsinto tbe laws of formation of tbe structure ofcorrelation matrices (Scblesinger & Guttmem,1969).
5. A priori assumptions on configuration of vari-ables against wbicb tbe empirical data are vali-dated enable better testing of bypotbeses. Per-baps tbe most important advantage of SSA overfactor analysis for country clustering is tbe rela-tive parsimony of tbe SSA: Tbe smallest spaceanalysis usually renders a space of fewer dimen-sions tban tbat produced by factor analysis(Scblesinger & Guttman, 1969). Tbis parsimonymeems tbat meemingful displays of complex dataoften can be grapbed in only two dimensions,providing visual accessibility to researcbers(Ronen et al., 1979). Sucb accessibility is evenmore important for practitioners, wbo coulduse data as a decision making tool.
Tbe use of diverse procedures in tbe studiesreviewed does not negate tbe possibility of syn-thesizing tbeir findings. Tbere are SSA analysesof four of tbe six studies tbat performed world-wide clustering: Ronen and Kraut's (1977) owndata; Ronen and Kraut's SSA reanalysis of Haireet al. (1966); Ronen and Kraut's reanalysis ofSirota and Greenwood; and Hofstede's report of
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having tried tbe SSA witb results similar to tbosefrom factor analysis. Ronen and Kraut's reanaly-sis of Sirota and Greenwood's data produced somedifferences in clustering—for example, tbe exclu-sion of Switzerland and Austria from tbe Anglocluster. Tbe exclusion of tbese two countries fromtbe Anglo cluster, however, was supported bytbe findings of all otber studies.
Country Clusters and their UnderlyingDimensions
The clusters of countries identified by the vari-ous studies are presented in Table 3. The use ofnational units for clustering is logical becausenational boundaries delineate tbe legal, political,and social environments witbin wbicb organiza-tions and workers operate. Yet, to understandwhy certain countries cluster, one sbould lookacross national boundaries for tbe dimensionsunderlying tbe clusters. Tbree sucb dimensionsare discussed bere: geograpby, language, andreligion. Tbe differentiation of tbese dimensionsis mainly analytical, because geograpby, lan-guage, and religion are closely intertwined.
It is apparent from Table 3 tbat countries tendto group togetber geographically. Indeed, tbenames of tbe clusters describe geograpbic areas.One could argue tbat geograpby casually precedesother variables, sucb as language and religion,because a culture spreads first to tbose areas near-est its "birthplace." Tbere is one striking excep-tion, however, to tbis geographical grouping: tbeAnglo-American cluster, wbicb contains coun-tries from all five continents. In tbis case, tbespread of culture may be attributed to coloniza-tion and immigration. In addition, geograpby mayinfluence work goals in ways otber tban territo-rial proximity. Hofstede (1980), for instance,found tbat a country's climate was correlated withits masculinity index, hence witb its employees'work values.
Language is anotber dimension underlying tbeclusters. A language contains meanings and val-ues that are likely to influence individuals' workgoals. For tbe most part, tbe countries in eachcluster sbare a language or language group. Forinstance, people in tbe Anglo countries speakEnglisb; people in tbe Germanic countries speakGerman; and tbose in Nordic countries (with the
Table 3Country Clusters by Studies Reviewed
so
Haire,Ghiselli,Porter(1966)
U.K.U.S.
i Sirota &Greenwood(1971)
U.K.U.S.AustraliaCanadaIndiaNew ZealandSouth AfricaAustriaSwitzerland
Ronen &Kraut (1977);SSA ofSirota &Greenwood(1971)
U.K.U.S.AustraliaCanadaIndiaNew ZealandSouth Africa
AustriaGermanySwitzerland
Hofstede Redding(1976) (1976)
VX. •: :• '.v - . - . ^ ,
U.S.Sweden ;
AustriaGermanySwitzerland
Ronen &Kraut Badawy(1977) (1979)
U.K.Ireland /South AfricaIsrael
AustriaGermanySwitzerland
Griffeth,Hom. Denisi.& Kirchner(1980)
U.K.Canada
AustriaDenmarkFinlandGermanyNorwaySwedenSwitzerland
Hofstede(1980)
U.K. ,U.S.AustraliaCanadaIrelandNew ZealandSouth Africa
AustriaGermanyIsraelSwitzerland
444
Table 3 (Continued)
1§
y, <
P °-< o_3 oc
S U
<
(/J
i
5g
S Q
Haire,Ghiselli, &Porter(1966)
DenmarkGermanyNorwaySweden
BelgiumFranceItalySpain
ArgentinaChileIndia
•
Japan
Sirota &Greenwood(1971)
DenmarkFinlandNorway
BelgiumFrance
ArgentinaChileColomhiaMexicoPeru
-
BrazilGermanyIsraellapanSwedenVenezuela
Ronen &Kraut (1977);SSA ofSirota &Greenwood(1971)
DenmarkFinlandNorway
BelgiumFrance
ArgentinaChileColomhiaMexicoPeruVenezuela
BrazilIsraelJapanSweden
Hofstede(1976)
DenmarkNorway
BrazilFranceItalySwitzerland
IndiaIranJapan
Redding(1976)
Hong KongIndonesiaJapanMalaysiaPhilippinesSingaporeS. VietnamThailand
Ronen &Kraut(1977)
DenmarkFinlandNorwaySweden
BelgiumFrance
Badawy(1979)
• • . . . . ; . •
Ahu-DhabiBahrainKuwaitOman
• • : ' . \
Griffeth,Hom, Denisi,& Kirchner(1980)
BelgiumGreeceItalyNetherlandsPortugalSpain
Saudi ArabiaUnited Arab
Emirates
Hofstede(1980)
DenmarkFinlandNetherlandsNorwaySweden
ArgentinaBelgiumBrazilFranceItalySpain
ChileColomhiaMexicoPeruPortugalVenezuela
GreeceIranTurkeyYugoslavia
Hong KongIndiaPakistanPhilippinesSingaporeTaiwanThailand
Jap>an
445
exception of Finns) speak a variety of languagesthat are members of a separate branch of the Ger-manic linguistic family. Language and geogra-phy are highly interdependent: the spread of lan-guage and culture is associated primarily withphysical (or in the case of the Anglo-Americacluster, with colonial) elements.
Religion, too, affects how the countries cluster.Religious beliefs are associated with certain val-ues and norms, and some support for the correla-tion of those norms with employee work goalshas been found (Ajiferuke & Boddewyn, 1970).Most groupings in the clusters have religion incommon. For example, the Anglo, Germanic, andNordic clusters are predominantly Protestant; theLatin American and Latin European clusters arepredominantly Catholic.
It is apparent that these three dimensions—geography, language, and religion— £ire not inde-pendent. In fact, it is likely (though not certain)that countries with one of these elements in com-mon will share all three.
Another dimension on which countries cluster,though less likely to be related to the previousthree, is technological development. Accordingto Webber (1969), the level of technology and thecorresponding level of development will affectmanagerial style and attitudes. Some indirect evi-dence of this is visible in some of the clusters.Haire et al. (1966) show the three developingcountries of Argentina, Chile, and India clusteredtogether despite cultural differences. More directevidence of this effect can be seen in the SSAplot of the Haire et al. data done by Ronen andKraut (1977), which shows a progression fromleft to right of countries with increasing levels ofdevelopment. Hofstede (1980) presents additionalevidence. He found that his individualism index(an underlying aspect explaining work values)was highly correlated (r=.82, p<.01) with percapita GNP. Country scores on this index are themajor difference between the Latin Europeancountries and the Latin American countries,which Hofstede refers to as more and less devel-oped Latin countries, respectively.
Hofstede's cultural dimensions are worth not-ing because of his unusual methodology and hisdeparture from more traditional dimensions. Ashort description of each of Hofstede's indicesfollows. The first index, power distance, is de-
fined as a measure of the interpersonal power orinfluence between boss and a subordinate as per-ceived by the less powerful of the two. Uncer-tainty avoidance measures the degree to which asociety deals with the uncertainty and risk pres-ent in everyday life. People with high uncertaintyavoidance tend to worry more about the future,have higher job stress, tolerate less change, andstay with one employer for a longer length oftime. The third factor, individualism, indicateslevel of dependence on or independence fromthe organization. It was positively related to suchvariables as personal time, freedom, challenge,the organization, and negatively related to theuse of skills, physical conditions, and training.Hofstede labeled the last dimension the mascu-linity index. Concepts such as manager, coopera-tion, desirable area, and employment securitywere negatively related to this factor; challenge,advancement, recognition, and earnings contrib-uted positively.
Hofstede (1980) clustered the countries in hisstudy on the basis of their placement on the fourindices. The results of this cluster analysis areshown in Table 3. Each cluster can now bedescribed by its placement on the four continu-ums and by the attitudinal and work goal char-acteristics associated with that placement. It isnow known which countries are most similar,and one is in a hetter position to predict thesources of similarities and differences. Hofstedethus provides four defining factors of culture(nationality) backed both by theory and empiri-cal evidence. More importantly these four defin-ing factors are continuous variables, whereas cul-ture and nationality are discrete variables.
Purpose and Implicationsof Clustering
According to Hartigan (1975), the principalfunctions of clustering are to (a) name, (b) display,(c) summarize, (d) predict, and (e) require expla-nation. These functions may illustrate the impli-cations of clustering countries according to theirwork values. The contributions appear to be inboth the practical and theoretical domains.
To Name
By giving all countries in the same cluster thesame name (e.g., Nordic), the characteristic work
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values of the group are identified. For example,the Latin European group is high on uncertaintyavoidance, the Latin American group is low onindividualism, and the Near Eastern group is highon power distance. This provides for a prelimi-nary infonnation hase on work values in coun-tries in which ventures are considered.
To Display
For suhtle differences to become more apparent,all countries in the same cluster are physicallyadjoined on a map. This display facilitates pre-dicting the difficulty in assignment hetween anytwo countries. It also may simplify identifyingareas in which difficulties may arise. This infor-mation may help in deciding overseas assign-ments and in training personnel for such assign-ments. The display also may assist the groupingof business units or country organizations intointernational combinations (Kraut, 1975; Ronen& Kraut, 1977).
To Summarize
Data are summarized by referring to propertiesof clusters rather than to properties of individualcountries. The summary makes it easier to under-stand and manipulate the data. For instance, itbecomes apparent that power distance and uncer-tainty avoidance tend to vary together (except forFar Eastern countries, where Western instrumentsmay be inadequate). The summary of data helpsin enhancing understanding of the interactionsamong various work values.
To Predict
If some countries in a cluster have a certainwork values system, other countries in the clus-ter probably have something similar. Hartigan(1975) notes that prediction might occur in eitherof two ways. First, if a new country is classifiedinto one of these groups by some other means,the same values will be predicted for the va-riables. Thus, Honduras would be expected to bein the Latin American group and to have highpower distance and uncertainty avoidance withlow individualism. This may enable some predic-tion of work values in countries not yet studied.Second, a new measurement of a similar typewould produce a similar grouping. Thus, if Den-mark is low on rules emphasis, it may be pre-
dicted that Norway also is low on this same value.This may enable better forecasting of problemsassociated with the introduction of organizationalpolicies and practices. It also may indicatewhether the problems of certain groups of coun-tries require different types of handling (Kraut,1975; Ronen & Kraut, 1977).
To Require Explanation
Clear-cut clusters require an explanation oftheir existence and thus promote the develop-ment of theories. Of special importance are thoseclusters that differ from geographic, linguistic,and religious classifications. For example, Brazilis not included in the Latin American cluster,and this increases awareness of nongeographicvariables; it suggests that one should simulta-neously consider factors such as economic devel-opment. In the long range, increased awarenessof all factors will encourage the development oftheories incorporating social, economic, andpolitical phenomena as explanatory variables.Here, perhaps, lies the greatest theoretical signifi-cance of cluster studies of work values in differ-ent countries.
Implications
The practical implications of country cluster-ing can be illustrated through the following hypo-thetical case. An MNC is establishing a venturein Switzerland. The corporation's directors mustdetermine if management skills will be importedfrom its subsidiaries in France, Cermany, or Italy.(All three languages are spoken in Switzerland,albeit in different areas.) The country clusteringsuggests that managers be brought from Germanybecause Switzerland and Germany belong to thesame cluster of work values. German managerstherefore can be expected to be closer to and morefamiliar with workers' attitudes in Switzerland.
Critiques of the Cluster Approach
Some researchers feel that cluster studiesgreatly exaggerate the differences between coun-tries. They conclude that the sources of differ-ences in attitudes are primarily occupational andindividual. For example, England and Negandhi(1979) compared steel workers in India and theUnited States as to their concern for societalissues and problems, their perceived job factor
447
importance, and their preferred managementstyle. They utilized a reference group of U.S. autoworkers in order to compare between- and within-country differences. As expected, large countrydifferences were found in the workers' concernfor societal issues and problems. Indian workerswere highly concerned only with the economyand housing problems; U.S. workers were consid-erably more concerned about a variety of issuessuch as peace, health, crime, and pollution. Thesedifferences, however, did not transfer into otherareas. In rating work factor importance, the Indianworkers rated all factors as more important thandid both of the U.S. samples. The differencesbetween the two U.S. groups were as large orlarger than the differences between the U.S.-Indiagroups on four of the eight job factors. The rela-tive ranking of the eight items also was very sim-ilar for all three groups. England and Negandhithus concluded that there were few if any nationaldifferences in work values across the two coun-tries. They went on to say: "In our judgment, theliterature purporting to show real national andcultural differences in employee attitudes, behav-ior and commitment are highly exaggerated"(1979, p. 180). Unfortunately, this study involvedonly two countries, although it was part of a largernine-country study, the rest of which has yet tobe published. In addition, the statistical analysispresented was not sufficient to show areas inwhich real national differences might exist.
A second study supporting this line of thoughtwas an eight-country investigation by Schauppand Kraut (1975). The workers were employedby subsidiaries of an American company.Schaupp and Kraut found no significant differ-ences between countries in the ranking of atti-tudes by blue-collar workers. A Q-factor analysisshowed that all of the countries loaded on onefactor, indicating a high degree of similarity.Intercorrelations among countries were neverlower than .69, with most above .85. To testwhether the data might reflect company socia-lization, Schaupp and Kraut split their sampleby the length of service with the organization.The Q-factor analysis of each group again resultedin only one factor, suggesting that companysocialization probably was not the reason for thesimilarity among countries. Schaupp and Krautleave open the possibility that this company may
attract a particular type of worker by virtue of itsmanagement style, which could account for thehigh degree of similarity.
The findings of these researchers support theimportance of individual and occupational dif-ferences without negating the contribution of vari-ance that can be explained by cultural differences.In their study, Haire et al. (1966) note that it seemsclear from the data reported in their study thatthere is a high degree of similarity amongmanagers' attitudes in all the countries studied.Haire et al. go on to state, however, that approxi-mately one third of the variance in work goalsand managerial attitudes could be explained bycountry. This result is supported by England(1978) and by Griffeth et al. (1980), who foundthat approximately one-third and one-half of thevariance, respectively, can be explained by coun-try differences. It should be noted, however, thatthe degree of similarity between countries is notdetermined on an absolute scale, but is relativeto the level of dissimilarity with other countries,and therefore influenced by the number of coun-tries included in the clustering.
Synthesizing the Clusters
Applying the dimensions discussed earlier tothe different studies, and drawing from the simi-larities of results across the reviewed studies, asynthesis of the results of the eight studies wasprepared (Table 3). This synthesis is presentedin Figure 1 as a map rather than as a table, usingper capita GNP as a general guideline (Kraut,1975) for the concentric distances from the cen-ter of the map: that is, the nearer to the center aparticular country is placed in comparison toother countries, the higher the GNP per capita incomparison to those other countries. The mosthighly developed countries are placed close tothe center, indicating the effect of the level ofdevelopment on the values and attitudes of thecountries. However, because of the limitation ofa two-dimensional presentation, cluster arrange-ment (as well as proximity) is not always an indi-cation of intercluster similarity.
The Anglo cluster was found in all of the clus-ter studies. The only inconsistencies were Sirotaand Greenwood (1971), whose Anglo clusterincluded Switzerland, Austria, and India, and
448
NEAR EASTERN
Abu-Dhabi
United Arab Emirates
Kuwait
United States
Canada
New Zealand ANCLOFAR EASTERN
Philippines / Venezuela
Chile
United Kingdom
Ireland
South Africa
South Vietnam
Indonesia
Taiwan LATIN EUROPEAN
LATIN AMERICAN
BrazilIsrael
INDEPENDENT
Japan
Figure 1. A sjrnthesis of country clusters.
Hofstede's (1976) inclusion of Sweden. Ronenand Kraut's reanalysis of the Sirota and Green-wood data did not support the inclusion of Swit-zerland and Austria. A close observation of theAnglo clusters in Tahle 3 indicates that with theahove exceptions, the countries in the Anglo clus-ters were former British colonies. This also would
explain the inclusion of India (Sirota & Green-wood, 1971) and Israel (Ronen & Kraut, 1977). Atone time both were under British rule, althoughculturally they are quite diverse on other dimen-sion. Hofstede (1980) found that countries in theAnglo cluster generally have a low to mediumscore on the power distance index, a low to
449
medium score on the uncertainty avoidanceindex, and high scores on the individualism andmasculinity indices.
For the purpose of synthesis, the countries thatwere characterized as former British colonies areincluded in the Anglo cluster. These include theUnited Kingdom, the United States, Canada,Australia, New Zealand, South Africa, and Ire-land. India appears as Independent in Figure 1because of the confusion of study results over itsplacement. As can be seen from Table 3, it hasbeen included in the Latin American cluster(Haire et al., 1966), as an independent (Hofstede,1976), and in the Far Eastern cluster (Hofstede,1980).
The Germanic and the Nordic countries weredifferentiated in four studies (Hofstede, 1976,1980; Ronen & Kraut, 1977; and Ronen & Kraut's1977 reanalysis of Sirota & Greenwood, 1971).There appears to be some degree of reliability inthe countries appearing in these clusters, subjectto the countries included in the study: Norway,Sweden, Denmark, and Finland consistentlyappear in the Nordic cluster; Germany, Austria,and Switzerland compose the Germanic group.Two studies did not differentiate between theNordic and the Germanic clusters (Griffeth et al.,1980; Haire et al., 1966). In both of these studies,the two clusters were combined into a NorthernEuropean cluster. The Haire et al. results may beattributed to their inclusion of more Germaniccountries. Griffeth et al. (1980), however, hadthree Germanic and four Nordic countries andstill found only one cluster. Sirota and Green-wood (1971) did not find a Germanic cluster intheir analysis; however, Ronen and Kraut's SSAmap of their data showed it clearly. Hofstede's(1980) data revealed that the two clusters werequite similar on three of the four indices hedefined; with the exception of the masculinityindex, the clusters are very close and can becombined.
In the present s5Tithesis, the Nordic and Ger-manic clusters are separate but contiguous, re-flecting the empirical results of Table 3. Austria,Germany, and Switzerland are included in theGermanic cluster; Finland, Norway, Denmark,and Sweden are included in the Nordic group.
The Latin European cluster was the last clustercommonly found. Its most consistent members
were France and Belgium. When Spain, Italy, andPortugal were included in a study, they also fellinto this group. Although these countries differin language, they all are variations of the Romancetongue, and religion and geography are commondimensions of the cluster. There is some indica-tion that this cluster may be subdivided into twogroups: one containing Spain and Italy, the otherFrance and Belgium.
A cluster that might be expected to resemblethe Latin Europeans is the Latin American group.There is some indirect evidence to support thisnotion. Spain and Portugal colonized LatinAmerica, and this suggests strong cultural ties.One effect of colonization is similarity in reli-gion and language, both certainly evident in theLatin American group. Another cluster consistsof Great Britain and its former colonies; it isprobable that Spain and Portugal and their for-mer colonies form one also. Hofstede's (1980)indices provide futher support for the combina-tion of the Latin European and Latin Americanclusters. Both Latin clusters are characterized bya high power distance, high uncertainty avoid-ance, and high variance in masculinity. The majordifference is on the individualism index, whichis low for Latin American countries. As Hofstedehas shown, the individualism index is highly cor-related (r = .82, p<.01) with a country's per capitaGNP. This observation implies that the major dif-ference between the Latin European cluster andthe Latin American cluster is their level of devel-opment; if this is true, then they may be consid-ered a single cultural cluster. Spain, the leastdeveloped member of the Latin European cluster,also had the lowest score on individualism inthat cluster. In addition, Ronen and Kraut's SSAmap of the Haire et al. data shows Spain andItaly distinctly separate from the more developedFrance and Belgium, and closer to the develop-ing countries of Argentina and Chile.
These arguments for combining the Latin Euro-pean and Latin American clusters assume thatchanges in the level of development causechanges in a country's individualism index.However, if cultural differences cause differencesin level of development or rate of development,the above arguments are meaningless. Under thishypothesis, a less-developed country may neverdevelop, or may develop at a much slower rate,
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because of the relatively unchanging values andgoals of society. Following this argument, theLatin European and Latin American clusters mayremain distinct clusters.
To resolve this apparent conflict of theory, val-ues related to individualism should be observedover time for significant change. Hofstede (1980)attempted this by comparing the results from the1968 portion of his data set to the results fromthe 1972 portion. He found that the individual-ism index for countries increased over the periodfrom 1968 to 1972, although convergence did nottake place. Hofstede speculates that the individu-alism index for a country will increase with thewealth of that country. More evidence collectedover a longer time period is needed, however,before one can draw this conclusion.
The present clusters of Latin American andLatin European countries follow fairly closely theresults of Hofstede (1980) and Sirota and Green-wood (1971). Consistent with the argument madeconcerning the similarities between these twoclusters, they are contiguous on the map in Fig-ure 1. These countries are not combined into onecluster because the evidence from the studies(Table 3) suggests stronger support for differenti-ating these clusters.
In six of the studies, results were limited to theclusters so far described. Hofstede (1980) investi-gated other countries in addition to those that fitinto the previous five clusters. Not surprisingly,he found two new clusters that are included inthe conceptualization presented here. The NearEastern cluster contains Greece, Iran, Yugoslavia,and Turkey. This cluster is characterized by highpower distance, high uncertainty avoidance, lowindividualism, and medium masculinity. Asidefrom Hofstede's dimensions, geography appearsto be the main dimension in common amongthese countries. The diversity of language,religion, and history of these countries makes it aparticularly complex grouping. It is difficult toevaluate the validity of Hofstede's technique, asreflected in this finding, because these countrieswere not included in any other study. Griffethet al. (1980) included Greece in the Latin Euro-pean cluster. The differences in Hofstede's andGriffeth's methodologies, however, and in theirunderlying dimensions for clustering, create dif-ficulty when comparing these results. As the other
countries were not included in the Griffeth et al.study, one may only guess whether a separatecluster of Near Eastern countries would haveemerged had these countries been samples. Inthe present synthesis, the Near Eastern countriesreflect Hofstede's grouping, forming a separatecluster.
Hofstede (1980) also found a Far Eastern cluster,including Pakistan, India, Taiwan, Hong Kong,Thailand, Singapore, and the Philippines. Thesecountries are characterized by high power dis-tance, low to medium uncertainty avoidance, lowindividualism, and medium masculinity. Redd-ing (1976) studied eight countries in the Far Eastusing the Haire et al. questionnaire. These areconsidered here as a Far Eastern cluster (despitethe unavailability of other countries to form abasis for comparison) on the grounds of resultssimilar to Hofstede's (1980), and in keeping withthe present authors' own expectations. However,given the diversity of religion and language, andgiven the huge geographic area covered by thesecountries, one Far East cluster may be a seriousoversimplification. Furthermore, the Westerninstruments used here may be inadequate to mea-sure validly the differences among Far Easterncountries' cultural dimension. Because of theselimitations, a Far East cluster has been includedin the present synthesis, but with the reservationthat more countries from the Oriental world mustbe included in future studies before reliable con-clusions can be drawn.
Finally, one study defined an Arab cluster.Badavkry (1979) used the Haire et al. question-naire to examine Saudi Arabia, Kuwait, Abu-Dhabi, Bahrein, Oman, and the United ArabEmirates. As in the Redding (1976) study, Badawy(1979) did not include countries representingother clusters; thus comparisons are difficult. Itis proposed, however, that this grouping repre-sents a separate cluster of countries, distinct fromthe others described thus far.
Several countries studied by one or more re-searchers are noticeably absent from the clustersshown here, and are grouped in different clus-ters or classified as independent across studies.For example, Ronen and Kraut (1977) clusteredIsrael with the Anglo countries. This makes in-tuitive sense, because the British controlled"Palestine" for several decades and because many
451
Israeli professionals are trained in the Anglo-American countries. On the other hand, Hofstede(1980) placed Israel in his Germanic cluster. Thisplacement also is credible, given the large num-ber of Westem European Jews who immigratedto Israel in the 1930s and after World War II.These disparate findings suggest that differencesin samples can have an important impact on clus-ter membership. Sirota and Greenwood (1971)and the Ronen and Kraut (1977) reanalysis foundIsrael to be an independent country. Clearly, moreevidence is needed before Israel can be placed ina particular cluster. Until such evidence is avail-able, it may be considered independent.
Japan also has posed problems for the cluster-ing process. It has been included in six studies.Five of the six classified it as an independent.Redding (1976) includes Japan in the Far Eastcluster but, as mentioned earlier, his study waslimited to countries in the Far East. It thereforeappears that Japan's combination of culture anddevelopment is not similar to any other country's.An alternative explanation is available for Japan'sapparent uniqueness. With the exception ofHofstede and Redding, the studies that includeJapan do not include any other countries fromthe Far East. It seems likely that Japan wouldappear to be independent from the Germanic,Latin European, and Latin American countriesstudies by Haire et al. (1966). If researchers hadincluded more countries, especially those withcultural dimensions in common with Japan, acluster including Japan might have emerged.Given the present findings, however, it seemssafest to consider Japan its own cluster, indepen-dent from other countries. S
The countries classified as independents allowone to hypothesize that economic developmentand technology override the traditional dimen-sions of language, geography, and religion as abasis for cluster membership. Those countrieshigher on economic development tend to sepa-rate from their geographic groupings (e.g., Israel,Sweden, Brazil, Japan). Countries listed as inde-pendent are separate from other clusters, yet notnecessarily similar to one another.
ConclusionsThe clusters presented here include much of
the non-Communist world. Many areas, such as
Africa, have not been studied at all; other areas,such as the Middle East and the Far East, havenot been studied sufficiently. These gaps in theresearch make it difficult to draw conclusionsabout cluster membership in these parts of theworld. Major studies need to be undertaken inwhich countries from all areas of the world willbe included. Otherwise, one will continue to con-front the problems of countries such as Japan,because conclusions about cluster membershipare limited by the countries included in thesample.
Despite these limitations, however, the resultsavailable thus far allow one to draw certainconclusions. First, it appears that countries/nations can be clustered according to similaritieson certain cultural dimensions. These dimensionstypically measure work goals, values, needs, andjob attitudes. The discriminant validity of thesevariables is supported: the resulting clusters con-sistently discriminate on the basis of language,religion, and geography. The support for theAnglo, Germanic, Nordic, Latin European, andLatin American clusters appears to be quitestrong. Clusters describing the Far East and Arabcountries are ill-defined and require furtherresearch, as do countries classified as indepen-dents (e.g., Israel and Japan).
As multinational companies increase theirdirect investment overseas, especially in lessdeveloped and consequently less studied areas,they will require more information concerningtheir local employees in order to implement effec-tive types of interactions between the organiza-tion and the host country. The knowledgeacquired thus far can help one to understand bet-ter the work values and attitudes of employeesthroughout the world. American theories workvery well for Western nations. Are they equallyapplicable in non-Western countries? Clearly,more cluster research is called for, includingresearch in countries from all parts of the globe.
Data in cross-national research are hard toacquire. It is an expensive operation and requiresthe collaboration of researchers in different loca-tions; it is long term in nature. The rewards ofsuch studies for individual researchers (in com-parison to noncultural studies) are questionable.It is not surprising, therefore, that the most reli-able and extensive data come from the in-house
452
researchers in MNCs.The present review was undertaken to utilize
and interpret the available information on cross-cultural clustering of employee work values. Asa result, future researchers will not have to referto the findings of individual studies, but may usethe exhaustive interpretation of the data as pre-sented here. A critical evaluation of the studieshas been given, and a tentative, cautious synthe-sis has been suggested as a starting point for futurestudies.
In the future, researchers are urged to increasethe methodological rigor of their studies and toreport in detail the procedures for sampling, datacollection, and analysis. Obtaining a sample thatrepresents the various groups, strata, and organi-zations of a given country is almost impossible.Studies that surveyed only one MNC (Hofstede,1980), although far from representative, con-trolled for industrial and organizational climatevariables, thus enabling researchers to attributevariation in work values to national differences.Other studies should consider various organiza-tional and demographic variables in the courseof sampling as well as in collecting and analyz-ing the data. It also is suggested that question-
naires undergo a thorough back-translation pro-cess and be administered, whenever possible, ina similar, in-company setting. Only such precau-tions will increase a sense of confidence that thefindings result from national differences and notfrom other variables.
The use of a noimietric cluster analysis such asthe SSA or the ALSCAL (Takane et al., 1976)rather than factor analysis is recommended as amethod rendering a parsimonious but meaning-ful configuration of clusters of employee workgoals by countries. It is suggested, however, thatother clustering techniques be applied in thefuture so as to determine their usefulness.
The clusters produced in the present synthesiscan be used as a general framework of referencefor theoreticians and practitioners. Researchersin the future should put these clusters to continu-ous empirical testing. They should be concerned,however, not only with the predictive qualitiesof clustering, but also with its promotion of theo-retical development. Rather than just inquireabout the nature of differences in employee workgoals, future researchers should proceed to in-vestigate the underlying cultural and social traitsthat may produce those differences.
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Simcha Ronen is Associate Professor of Managementand Organizational Behavior in the Graduate Schoolof Business Administration, New York University.
Oded Shenkar is a lecturer of Management and O;:gani-zational Behavior in the Faculty of Management, Tel-Aviv University, Israel.
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