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Evaluating the structure of human valueswith conrmatory factor analysis

Shalom H. Schwartz a, * and Klaus Boehnke b

a Department of Psychology, The Hebrew University of Jerusalem, Jerusalem 91905, Israel b International University Bremen, Bremen, Germany

Abstract

This is the rst statistical test of a theory of the structure of human values (Schwartz, 1992).The theory postulates that 10 basic values are discriminated in all societies and that these val-ues form a quasi-circumplex structure based on the inherent conict or compatibility betweentheir motivational goals. Past support for the theory came from subjective judgments of visualplots of the relations among value items in samples from over 60 countries. We formally testthe postulated structure and several potential renements. We employ a specially designedconrmatory factor analysis (CFA) approach with new data from two sets of 23 samples from27 countries ( N 10,857). In both data sets, CFAs conrm the 10 basic values, a modiedquasi-circumplex rather than a simple circumplex structure, and the claim that values forma motivational continuum. 2003 Elsevier Inc. All rights reserved.

Keywords: Values; Conrmatory factor analysis; Value structure; Cross-cultural analyses

1. Introduction

The past 45 years have seen a steady stream of papers that propose that the bestway to represent personality and affect is a circumplex structure (Fabrigar, Visser, &Browne, 1997; Tracey, 2000). That is, they postulate that personality or affect vari-ables lie on the circumference of a circle, and the strength of association betweenvariables decreases as the distance between variables on the circle increases. A recentbook on models of personality and emotions (Plutchik & Conte, 1997a) has given

* Corresponding author.E-mail address: [email protected] (S.H. Schwartz).

0092-6566/$ - see front matter 2003 Elsevier Inc. All rights reserved.doi:10.1016/S0092-6566(03)00069-2

Journal of Research in Personality 38 (2004) 230255

www.elsevier.com/locate/jrp

JOURNAL OFRESEARCH INPERSONALITY
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this approach even greater impetus. The current paper concerns the domain of individual values in which the most widely recognized current model also proposesa circumplex structure (Rohan, 2000; Schwartz, 1992).

Factor/principal components analysis and multidimensional scaling (MDS) are themethods commonly used to test circumplex structures, but they are usually inade-quate to provide statistical tests. Neither offers a simple, quantiable method to for-mally assess the extent to which the observed data possess a circumplex structure (fordetailed critiques of these methods, see Fabrigar et al., 1997 or Tracey, 2000). Instead,researchers typically reach conclusions by making two subjective judgments of the ob-served plot of relations among variables. First, they assess how well this plot appearsto conform to a circular pattern. Then they assess the extent to which the order of thevariables around the circle appears to correspond to the order in the theory. All pastassessments of the structure of basic human values have relied on such subjective judgments of plots produced by an MDS approach. This paper is the rst direct,quantitative evaluation of the postulated circumplex structure of values.

2. Value theory and past assessments

The theory of basic human values (Schwartz, 1992) identies 10 motivationallydistinct types of values that are likely to be recognized within and across cultures:power, achievement, hedonism, stimulation, self-direction, universalism, benevo-lence, tradition, conformity, and security. Table 1, below, denes the 10 values.

The most important feature of the theory is the structure of dynamic relationsamong the 10 values that it explicates. It postulates that actions expressive of anyvalue have practical, psychological, and social consequences that may conict orbe compatible with the pursuit of other values. For example, actions that express he-donism values are likely to conict with those that express tradition values and viceversa, and acting on self-direction values is likely to conict with maintaining con-formity values and vice versa. On the other hand, hedonism values are compatiblewith self-direction values, and tradition values are compatible with conformity val-ues. Studies in 19 countries reveal systematic associations of many behavior, atti-

tude, and personality variables with priorities for these values (see citations inSchwartz & Bardi, 2001). The structure of value relations explains the patterns of these associations. When the constructs in a set vary in the degree of their similarityand dissimilarity or conict, as the values do, they are likely to yield a circumplexstructure (Plutchik & Conte, 1997b).

The circular structure in Fig. 1 portrays the total pattern of relations among val-ues postulated by the theory. The circular arrangement of the values represents amotivational continuum. The closer any two values in either direction around thecircle, the more similar their underlying motivations; and the more distant anytwo values, the more antagonistic their underlying motivations. The motivational

signicance of items that operationalize adjacent values overlaps in part but differssharply from that of items that operationalize distant values. This structure is a cir-cumplex, except for the placement of tradition outside conformity. The claim of a

S.H. Schwartz, K. Boehnke / Journal of Research in Personality 38 (2004) 230255 231


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motivational continuum is especially important for relating value priorities to othervariables. It implies that these relations take the shape of a sinusoidal curve that fol-lows the order of the values around the circle (Schwartz, 1992). Note that the theorypostulates a circular arrangement of the 10 values, not of the items. For items, it pos-tulates that each item correlates more highly with the set of items that measure the

same value than with the set of items that measure a different value. Thus, in tech-nical terms, the theory assumes that the items in the value survey form 10 latent fac-tors and only the factors relate to one another in a circular manner.

Extensive research has assessed the theory in over 200 samples in more than 60countries from every inhabited continent (representative national samples, schoolteachers, university students, adolescents, samples of workers in specic occupa-tions). Researchers examined two-dimensional projections of the relations amongvalue items, using MDS or Similarity Structure Analysis (SSA; Borg & Shye,1993; Guttman, 1968). They concluded that the data largely support (a) the distinc-tiveness of the 10 values, (b) the idea that these values are comprehensive of the ma-

jor, motivationally distinctive types of values, and (c) the ordering of valuespostulated by the circumplex structure (Fontaine, 1999; Schwartz, 1992, 1994;Schwartz & Bardi, 2001; Schwartz & Sagiv, 1995; Schwartz, in press).

Table 1Samples included in the analyses

Set I Set II

N N

Belgium University Students 249 Australia University Students 111Denmark School Teachers 682 Austria School Teachers 196East Germany Adults 233 Brazil University Students 151East Germany University Students 441 Bulgaria University Students 241France (Nancy) University Students 214 England School Teachers 209Ghana School Teachers 214 France (Paris) University Students 390Hong Kong University Students 222 Ghana University Students 210Hungary University Students 160 Hong Kong School Teachers 126Israel School Teachers 188 Hungary School Teachers 130Japan School Teachers 173 Israel Adults 181Macedonia University Students 245 Israel University Students 427Netherlands University Students 217 Japan University Students 327Peru University Students 145 Macedonia School Teachers 206Philippines University Students 289 Mexico School Teachers 361Poland University Students 141 Philippines School Teachers 157Russia School Teachers 194 Russia Adults 189Russia in Israel Adult Immigrants 202 Russia in Ber-

linAdult Immigrants 181

Slovakia School Teachers 186 Slovakia University Students 233Turkey University Students 242 Switzerland University Students 264USA School Teachers 108 Uganda University Students 188USA (Seattle) University Students 270 USA (Illinois) University Students 374West Germany University Students 388 USA Nurses 259West Germany School Teachers 148 West Germany University Students 195

5551 5306

232 S.H. Schwartz, K. Boehnke / Journal of Research in Personality 38 (2004) 230255


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These conclusions were based on visual inspection of the spatial plots, guided by apriori criteria (Schwartz, 1992; Schwartz & Sagiv, 1995). They revealed that, in thevast majority of samples, the items that operationalize each value occupied a distinctregion in the space, with no substantial empty spaces between regions. Moreover, theorder of these distinct regions around the circle generally approximated the theorizedorder shown in Fig. 1. As noted, however, visual inspections cannot formally testwhether the observed data possess a circumplex structure. Data that appear to ta circumplex structure may or may not be found to t such a structure when testeddirectly, as Fabrigar et al. (1997) demonstrated. Therefore, a rst objective of thispaper is directly to test the circumplex structure of the theory of human values usingan application of structural equation modeling designed for this purpose. We ask:Does conrmatory factor analysis (CFA) corroborate the theoretical structure of va-

lue relations that was supported by interpretations of past SSA and MDS analyses?Equally important is our second objectiveto test possible renements to the va-lue theory. These renements were suggested in the published literature but nevertested. Each renement was inspired by examining the separate plots of relationsamong value items in large numbers of samples. The renements t the majorityof samples. The theory formally incorporated one renement: It modied the strictcircumplex structure of 10 values into the structure shown in Fig. 1. This structureplaces tradition and conformity values at the same polar angle around the circle,but tradition is outside conformity. It provided a better visual t than the strict cir-cumplex to the average plot of the rst 40 samples studied and to the separate plots

in 29 of these samples, and no worse a t in the remaining 11 samples (Schwartz,1992, p. 35). Although this presumed renement has been justied conceptually, ithas never been tested formally.


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3. Models tested

Below, we spell out each renement proposed to the theory, note the conceptualarguments for it, and then test it. One could perform these tests with the data frompast research. However, the renements drew upon post hoc examination of thosedata. Hence, this would not test the power of the theory to account for new data.Therefore, for totally independent, stringent tests of the theory and tentative rene-ments, we analyze data that have not gured in any previous assessments of thestructure of values. We wish to assess which theoretical model best ts the basic pat-tern of value relations common to cultures, rather than to identify unique variants inparticular cultures. We therefore combine the individual data from many cultures. Inorder to assess the robustness of the ndings, we replicate the analyses in two inde-pendent sets of samples.

3.1. Model 1: 10 orthogonal factors

The theory of basic human values (Schwartz, 1992, 1994) derived the 10 motiva-tionally distinct types of values from three universal requirements of the human con-dition: needs of individuals as biological organisms, requisites of coordinated socialinteraction, and survival and welfare needs of groups. The theory holds that groupsand individuals represent these requirements cognitively, as specic values aboutwhich they communicate in order to coordinate with others in pursuing the goalsthat are important to them. The 10 values are the content aspect of the theory.The structural aspect of the theory species relations of similarity and dissimilarityamong these values. Perhaps, however, each value is independent. This would bein line with Rokeach s (1973) view of values, on which Schwartz built, and with tra-ditional exploratory factor analysis. We therefore rst test how well a model of 10orthogonal factors ts the data.

3.2. Model 2: A quasi-circumplex model of 10 factors 1

At the beginning of the chapter that rst presented the value theory, Schwartz

(1992, pp. 1315) speculated that the 10 values might form a perfect circular struc-ture. That is, the 10 values would form a circle as in Fig. 1, but with tradition locatedbetween benevolence and conformity. The theory made no assumption as to whether

1 A comment on the terminology used with circumplex models is necessary to clarify the usage thatfollows. Guttman (1954) rst used the term circumplex to include any model that postulates a circulararrangement of relations among variables. He subdivided such models into those that assume the variablesare equally spaced on the circumference of the circle ( circulant ) and those that do not assume equal spacing(quasi-circumplex ). We use these terms as he did. Guttman provided no label for models that assume acircular arrangement of variables but do not locate all the variables on the circumference of the circle.Hence, there is no term for the denitive model proposed by the value theory. It postulates thatconformity values are more central and tradition values more peripheral (see Fig. 1). The remaining valuesare arrayed in order around the circle, though not necessarily equidistant. We label this model modiedquasi-circumplex.



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values are spaced equally around the circle (a circulant model) or unequally (a quasi-circumplex model). The chapter rejected this circumplex, but provided no direct,quantitative test of the appropriate circumplex model to justify this rejection. Wetherefore next test the t of a circumplex model to the data. Because the theory doesnot assume that the values are distributed at equal intervals around the circle (circ-ulant model), we test a quasi-circumplex model. We compare the t of this model tothe t of the model of ten orthogonal factors.

3.3. Model 3: The 1992 theory A modied quasi-circumplex model

The denitive version of the theory of basic values postulates the modied qua-si-circumplex structure presented in Fig. 1. As noted, this change derived from nd-ing that a theory that locates tradition outside of conformity at the same polar anglein the circle was a better visual t to the plots of data in the available samples. Scru-tinizing plots from many later samples reaffirmed this model (Schwartz, 1994; Sch-wartz & Sagiv, 1995). The theoretical explanation for locating conformity andtradition at the same polar angle in the circle is that they share the same broad mo-tivational goalsubordinating self in favor of socially imposed expectations. Whatdistinguishes them is that conformity values entail subordination to persons withwhom one is in frequent interactionparents, teachers, and bosses. Tradition valuesentail subordination to more abstract objectsreligious and cultural customs andideas (Schwartz, 1992, p. 40). Conformity values emphasize restraint of actions, in-clinations, and impulses that might upset or harm others and violate their expecta-tions. Tradition values emphasize respect, commitment, and acceptance of thecustoms and ideas of one s culture or religion.

Central versus peripheral locations in a circle typically reect differences betweenconstructs in the degree of their abstractness, closeness to the self, or prevalence ineveryday interaction (Levy, 1985). On all three counts, tradition values are morelikely to be located peripherally than conformity values. The more peripheral the lo-cation of a value, the less positive its correlations with the values on the opposite sideof the circle. Hence, the peripheral location of tradition would signify that it is lesscompatible than conformity with hedonism and stimulation values. We test the t of

the denitive, modied quasi-circumplex model of values to the data and compareits t to that of the quasi-circumplex model. We label this model modied quasi-cir-cumplex because it orders the values around the circle but includes central vs. pe-ripheral positioning.

3.4. Model 4: Combining tradition and conformity to yield nine values

If tradition and conformity values share the same broad motivational goal, per-haps a simpler, more parsimonious model would t the data better. Tradition andconformity may constitute a single value. This would be a quasi-circumplex model

of nine values, with the combined tradition/conformity value located between benev-olence and security. We formally test this quasi-circumplex model and compare itwith the modied quasi-circumplex model.



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3.5. Model 5: Power values peripheral to achievement values

In discussing the plots of the rst 40 samples studied, Schwartz (1992, p. 40) notedthat, in 26 samples, a distinct region of power values could be drawn toward the periph-ery of the circle behind achievement values. In most samples, however, it was also pos-sible to connect the region of power values to the center of the circle. Hence, thedenitive version of the theory located power values between achievement and secu-rity. Was this decision correct? Might a model locating achievement and power valuesat the same polar angle in the circle, with power peripheral to achievement, t the databetter? Theoretical arguments for this alternative model appear in Schwartz (1992, pp.4041):

[Both values] focus on social esteem. However, achievement values refer more to striving todemonstrate competence in everyday interaction . . . whereas power values refer more to theabstract outcomes of action in the form of status in the social structure. . . . achievement val-ues refer to the striving of the individual . . . whereas power values also refer to the hierarchi-cal organization of relations in society.

Thus, like tradition and conformity, power and achievement differ on character-istics that might lead to a central versus peripheral order: degree of abstractness,closeness to the self, and prevalence in everyday interaction. We therefore testwhether this model ts the data better than the previous models. We also testwhether a more parsimonious model that treats power and achievement as a singlevalue (model 6) is an even better t.

3.6. Model 7: Higher-order types of value

Based on the SSA analyses in the rst 40 samples, Schwartz (1992, p. 43) sug-gested a simpler way to view value structures. Relationships among the values canbe summarized in terms of a two-dimensional structure composed of four higher-or-der value types. One higher-order type, called openness to change, combines stimu-lation and self-direction values. It forms a bipolar dimension with the higher-ordertype called conservation that combines security, conformity, and tradition values.

This dimension arrays values in terms of the extent to which they motivate peopleto follow their own emotional and intellectual interests in unpredictable and uncer-tain directions (openness) versus to preserve the status quo and the certainty it pro-vides (conservation).

A third higher-order type, called self-enhancement, combines power and achieve-ment values. It forms a bipolar dimension with the higher-order type called self-tran-scendence that combines universalism and benevolence values. This dimensionarrays values in terms of the extent to which they motivate people to enhance theirown personal interests even at the expense of others (self-enhancement) versus totranscend selsh concerns and promote the welfare of others, close and distant,

and of nature (self-transcendence). Hedonism values share some elements of bothopenness and self-enhancement. Consequently, hedonism is located between thesetwo higher-order types.



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Schwartz treats the higher-order types merely as a way to describe the value struc-ture more simply. Nevertheless, he and others sometimes use these four types, ratherthan the 10 values, to predict behavior and attitudes (e.g., Bilsky, 1998; Hrubes, Aj-zen, & Daigle, 2001; Ros, Schwartz, & Surkiss, 1999; Schwartz, 1994). If one wantsto simplify the value structure, is this particular set of higher-order types more mean-ingful than other possible groupings of values? Or do the values form a continuum,so any combination of adjacent values (e.g., power with security) would be equallylegitimate? We address these questions by evaluating their implications for associa-tions among the values.

Let us assume that this particular set of four higher-order types is more meaning-ful conceptually than alternative combinations. We would then expect adjacent val-ues within these higher-order types to be more strongly associated with one anothersubstantively and empirically than they are with the adjacent values from other high-er-order types. For example, the two self-transcendence values, universalism andbenevolence, should be more highly intercorrelated than universalism is with self-di-rection (also adjacent, but in the openness higher-order type) or than benevolence iswith conformity (adjacent, but a conservation value). We put this idea to a formaltest by specifying a model in which correlations between values within higher-ordertypes are higher than the correlations of these values with adjacent values from otherhigher-order types.

3.7. Model 8: Freely estimating hegher,


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scale from opposed to my principles ( ) 1), through not important (0), to of su-preme importance (7). As markers for each of the 10 values, we used the items rec-ommended as standard indexes for cross-cultural research, based on the consistencyof their meanings across cultures (Schwartz, 1992, 1994). Table 2 presents brief def-initions of each value followed by its marker items. We included self-indulgence,from the expanded SVS, to provide a third item to measure hedonism.

4.3. Analyses

We designed an approach for the CFA analyses suited for testing all of the differ-ent structural models. This approach must test quasi-circumplex models as well asmodied quasi-circumplex models. It must also test a model that species differentdistances among particular values, to represent relations within and between high-

er-order value types. Additionally, it must test the existence of subtypes within values(universalism and security). Finally, the approach must treat the values as latentvariables and the items as observed variables, allowing a test of the appropriatenessof the marker items for measuring the 10 values in a unied analysis.

Tracey (2000) described computer programs specically designed to test circum-plex conceptual models. Both of the most available programs, CIRCUM (Browne,1992) and RANDALL (Tracey, 1997), do not t the requirements of testing all as-pects of the current theory and its proposed renements. Neither program permitsspecifying two-level models as required here. We cannot test the circumplex assump-tion for the latent variables (the values) together with a simple factorial structure for

the manifest variables. This limitation, that precludes simultaneously modeling rela-tionships of items to factors and relations among factors, is the primary reason wedo not use these programs. In addition, neither program provides an appropriate

Table 2Denitions of the motivational types of values and items used as markers

Power : Social status and prestige, control or dominance over people and resources (authority, social

power, wealth, preserving my public image)Achievement : Personal success through demonstrating competence according to social standards

(ambitious, successful, capable, inuential)Hedonism : Pleasure or sensuous gratication for oneself (pleasure, enjoying life, self-indulgent)Stimulation : Excitement, novelty, and challenge in life (daring, a varied life, an exciting life)Self-direction : Independent thought and actionchoosing, creating, exploring (creativity, freedom,

independent, choosing own goals, curious)Universalism : Understanding, appreciation, tolerance, and protection for the welfare of all people and

for nature (equality, social justice, wisdom, broadminded, protecting the environment, unity withnature, a world of beauty)

Benevolence : Preservation and enhancement of the welfare of people with whom one is in frequentpersonal contact (helpful, honest, forgiving, loyal, responsible)

Tradition : Respect, commitment, and acceptance of the customs and ideas that traditional culture orreligion provide (devout, respect for tradition, humble, moderate)

Conformity : Restraint of actions, inclinations, and impulses likely to upset or harm others and violatesocial expectations or norms (self-discipline, politeness, honoring parents and elders, obedience)

Security : Safety, harmony, and stability of society, of relationships, and of self (family security, nationalsecurity, social order, clean, reciprocation of favors)



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way to handle more central as opposed to peripheral locations of factors in a circle.Hence, they are not suited to testing the denitive model of the value theory, amodied quasi-circumplex. We therefore developed a strategy tailored to the require-ments of testing all aspects of the models of interest, using a structural equationmodeling program (LISREL 8.14; J oreskog & S orbom, 1993).

We tested the model of 10 orthogonal factors with an ordinary CFA on 10 latentvariables. To test the theory-driven models of the value structure, we specied a ref-erence matrix of expected correlations among the values for each model. This matrixrepresents exactly a pattern of expected correlations among the values that repro-duces the model. We then tested the t of the reference matrix to the observed data.

In order to create a reference matrix for a model, it is necessary to specify actualcorrelation coefficients that t the expected pattern of associations of the model to betested. Any set of arbitrarily chosen coefficients that ts the pattern of expected as-sociations might be used, because the model must reproduce the pattern . Once refer-ence values are chosen for any two correlation coefficients, all the remainingcoefficients follow from the pattern needed to reproduce the model.

We adopted a data-driven approach to determine reasonable reference coefficients.In a preliminary analysis, we estimated a model of 10 freely intercorrelated latent fac-tors in both samples, with LISREL. We then calculated the average intercorrelationbetween all of the pairs of factors that the theory postulates to be adjacent in the circle(e.g., self-direction/universalism; see Fig. 1). This yielded a reference correlation of .68for adjacent values. We applied the same procedure to all pairs of values that the the-ory postulates to have opposing substantive contents (e.g., self-direction/security) andobtained a reference correlation of .08 for values on opposite sides of the circle.

Based on these analyses, we xed the correlation coefficient between all pairs of adjacent values at .68 for the circumplex model of 10 equally spaced values. Thus,we xed the correlations for power/achievement, power/security, security/conformi-ty, and so on around the circle, at .68 in the reference matrix. Similarly, we xed thecorrelation between all pairs of values on opposite sides of the circle (universalism/power, benevolence/achievement, etc.) at .08. Distances between pairs of valuesaround a circle of 10 values can range from adjacent to four steps away (opposite).We therefore computed the amount to reduce the correlation for each step by divid-

ing the difference between the maximum correlation (.68) and the minimum (.08) byfour. This yielded a reduction of .15 for each step. Table 3, below the diagonal, pre-sents the resulting reference matrix. Table 3 arranges the values according to theirpostulated order around the circle from universalism to self-direction. The greaterthe distance between any pair of values, the less positive the correlation betweenthem. The coefficients that reproduce the ve expected distances among 10 valuesaround the circle are .68, .53, .38, .23, and .08. 2

2 A reviewer of an earlier version of this paper remarked that a constant difference between correlationcoefficients does not produce equidistance of items along a circle. This is not a problem for the currentapproach because the theory does not posit equidistance among the 10 values. Rather, it posits relations of q 1 > q 2 > q 3 > q 4 > q 5 < q 6 < q 7 < q 8 < q 9 , where q 1 to q 9 stand for the correlations of one value withthe other nine values in the order presented in Fig. 1. The reference matrix represents this set of relations.



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For each subsequent model (38), we modied the reference matrix of expectedcorrelations to represent the relations among the values expected according to thatmodel. In the results, we explain how we constructed the reference matrix of ex-pected correlations for each of these models. The models that postulate the existenceof subtypes (9 and 10) imply that each subtype consists of items that correlate morehighly with one another than expected from their relation to the same latent value.That is, the correlations with the latent value of the items expected to constitute eachsubtype do not account fully for the intercorrelations among the items themselves.

To model this pattern, we permitted correlated errors between the items in each sub-type. We then tested whether models with these correlated errors t the data betterthan models with no correlated errors.

Our criterion for the goodness of t of the models is a combination of two in-dexes, RMSEA and SRMR, recommended by Hu and Bentler (1999; cf. MacCallum& Austin, 2000). RMSEA is especially sensitive to models with misspecied factorcovariances or latent structures, SRMR to models with misspecied factor loadings.Hu and Bentler suggest that, for samples of 5000, the approximate size of our sam-ples, the probabilities of rejecting a valid model or of accepting an invalid model areextremely small when RMSEA is close to .06 and SRMR to .11. We report v 2 sta-tistics to test differences in t between nested models. Many of the models are notnested, however. To test differences between non-nested models, we report the Ak-aike information criterion, AIC (Akaike, 1973; Sakamoto, Ishiguro, & Kitagawa,1986). Among a set of hypothesized, non-nested models, the best model is the onethat minimizes the value of AIC. In all cases, our aim is to select the best modelfor describing the data among the theory-based alternatives. 3

Table 3Reference matrixes of expected factor intercorrelations for conrmatory factor analyses: 10 factor quasi-circumplex (model 2) below the diagonal and basic theory modied quasi-circumplex (model 3) above thediagonal

Values UN BE TR CO SE PO AC HE ST SD

Universalism (UN) 1.00 .68 .43 .48 .28 .08 .08 .28 .48 .68Benevolence (BE) .68 1.00 .68 .68 .48 .28 .08 .08 .28 .48Tradition (TR) .53 .68 1.00 .88 .68 .43 .18 ) .07 ) .07 .18Conformity (CO) .38 .53 .68 1.00 .68 .48 .28 .08 .08 .28Security (SE) .23 .38 .53 .68 1.00 .68 .48 .28 .08 .08Power (PO) .08 .23 .38 .53 .68 1.00 .68 .48 .28 .08Achievement (AC) .23 .08 .23 .38 .53 .68 1.00 .68 .48 .28Hedonism (HE) .38 .23 .08 .23 .38 .53 .68 1.00 .68 .48Stimulation (ST) .53 .38 .23 .08 .23 .38 .53 .68 1.00 .68

Self-Direction (SD) .68 .53 .38 .23 .08 .23 .38 .53 .68 1.00

3 The decision whether one model ts the data better than another is sometimes difficult in this study.With the large samples, trivial differences in v 2 are statistically signicant. We therefore set a conservativeprobability level of p < : 001 for considering D v 2 between nested models to be signicant. Moreover,differences in the t coefficients of the models are often small. When this is so, we use the differences in theRMSEA, SRMR, and AIC as aids to choice, picking the model that is most convincing conceptually andthat is also best according to the set of statistics.



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As noted, we conducted all analyses on two independent sets of data. For bothdata sets, we rst calculated ordinary covariance matrixes. 4 All analyses used max-imum-likelihood estimation.

5. Results

5.1. Model 1: 10 orthogonal factors

We rst tested a model that treats each value as independent. Table 4 reports resultsfor this model of 10 orthogonal factors. An RMSEA index greater than .06 and anSRMR index greater than .11 indicate that this model t the empirical data poorly.

5.2. Model 2: A quasi-circumplex of 10 factors

The preliminary model of the value theory, suggested but then rejected by Sch-wartz (1992), was a perfect circumplex structure of 10 factors. We tested this modelby using the reference correlation matrix below the diagonal in Table 3. The patternof correlations among all the values in this matrix represents exactly the pattern of expected correlations for a circumplex structure. The second row in Table 4 presentsthe t statistics for this model. The RMSEA index is slightly higher than the recom-mended cutoff criterion in set I and just at that level in set II. The SRMR criterion ismet in both sets of samples. Thus, the 10-factor quasi-circumplex model shows amoderate t to the data. It clearly ts the data better than the model of 10 orthog-onal factors. Both the v 2 value and the AIC value decreased substantially in both setsof samples. In this and all subsequent theory-driven models, all items loaded signif-icantly ( p < : 0001) on the appropriate latent value.

5.3. Model 3: The 1992 theory A modied quasi-circumplex model

The denitive representation of the value theory is the quasi-circumplex struc-ture presented in Fig. 1 (Schwartz, 1992, 1994). It locates tradition outside of confor-

mity, but at the same polar angle in the circle. This reduces the number of locationsaround the circle from 10 to 9. The pattern of expected correlations above the diag-onal in Table 3 represents this structure. We generated this pattern by modifying thecorrelations for the quasi-circumplex model (below the diagonal in Table 3) as fol-lows. With only nine locations of values, the number of steps from any value tothe opposite location in either direction around the circle is three. We therefore de-

4 The samples that make up the data sets vary substantially in size. Hence, we also did the analyses on acorrelation matrix for each set that weighted each sample equally. We constructed the average matrixes asfollows. We transformed the correlations in each sample-specic correlation matrix into a Fisher- Z score,averaged these Z -scores across the samples of the data set, and transformed the mean Z -scores back intocorrelation coefficients. Analyses of these average correlation matrixes yielded results very similar to thosereported below. Because the mathematical properties of a matrix of averaged correlation coefficients areuncertain, the text reports analyses on the unweighted covariance matrix.



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Table 4Conrmatory analyses of models of the structure of values in two sets of samples

Model df Sample set I, N 5551 Sample set

v 2 RMSEA SRMR AIC v 2

1. Ten orthogonal factors 989 39126.8 .083 .160 39310.8 33538.2 .02. Quasi-circumplex of 10 factors 989 24048.0 .065 .088 24232.0 19611.1 .03. The 1992 theorya modied

quasi-circumplex989 23356.1 .064 .081 23540.1 19031.8

4. Combining tradition andconformity to yield nine values

989 23532.6 .064 .082 23716.6 18964.7

5. Power values peripheral toachievement values

989 24036.5 .065 .083 24220.5 19334.3

6. Combining power and achievementto yield nine values

989 24711.2 .066 .083 24595.2 19699.2

7. Higher-order types of value 989 23526.3 .064 .080 23710.3 19170.2 .08. Free estimation of hedonism 987 22730.9 .063 .080 22918.9 18635.5 .09. Subtypes within universalism:

nature and social concern981 21153.9 .061 .079 21353.9 17343.1

10. Subtypes within security:personal and group

977 20840.0 .061 .078 21048.0 17044.1


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termined the size of a step by subtracting the minimum correlation between pairs of values (.08) from the maximum (.68) and dividing by three, yielding steps of .20.Thus, in the reference matrix, adjacent values are expected to correlate .68, valuesseparated by one other value around the circle (e.g., universalism and stimulation).48, those separated by two other values (e.g., universalism and hedonism) .28,and those separated by three other values (e.g., universalism and achievement) .08.

In order to represent the fact that tradition and conformity are located at thesame polar angle, we increased the expected correlation between them by one stepto .88. To represent the location of tradition toward the periphery of the circle,we reduced the expected correlations of tradition with the values that were one,two, and three steps away from it around the circle. The reduction had to increasewith each step without reaching the equivalent of a full step, .20. We therefore re-duced the expected correlations of tradition by .05 for each step. The expected cor-relations of tradition with its adjacent values (benevolence and security) wereunchanged at .68. Its expected correlations with the values one step away (universal-ism and power) were reduced by .05, compared with the expected correlations of conformity, and xed at .43. The expected correlations of tradition with the valuestwo steps away (self-direction and achievement) were reduced by .10 and xed at.18. Finally, its expected correlations with the values three steps away, on the oppo-site side of the circle (hedonism and stimulation), were reduced by .15 and xed at) .07.

Row three in Table 4 presents the t statistics for this model. The RMSEA indexis slightly higher than the recommended cutoff criterion in set I and the criterion ismet in set II. The SRMR criterion is met in both sets of samples. As compared withthe quasi-circumplex model (2), the modied quasi-circumplex model ts the empir-ical data somewhat better. The goodness of t indexes improved slightly in both setsof samples, and both the AIC value and the v 2 value decreased substantially both inset I and in set II.

5.4. Model 4: Combining tradition and conformity to yield nine values

The modied quasi-circumplex model locates tradition and conformity values at

the same polar angle on the circle because they share the same broad motivationalgoal. Model 4 asks whether tradition and conformity might better be treated as a sin-gle value rather than as separate values. This model is a quasi-circumplex with ninerather than 10 values. It combines the tradition and conformity items to form a sin-gle value located between benevolence and security. The reference matrix of expectedcorrelations to reproduce this model is similar to that for model 3. However, tradi-tion values are dropped from the matrix. The joint tradition/conformity value hasthe same expected correlations as conformity did in model 3.

Row four in Table 4 presents the t statistics for this model. RMSEA shows noimprovement in either set of samples compared with model 3. SRMR increases

slightly in set I and decreases slightly in set II. Both models t the data reasonablywell. The increase in the AIC value in set I (176.5) suggests that model 3 is better, butthe decrease in the AIC value in set II (67.1) favors model 4. Thus, treating tradition



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and conformity as a single value reduces the goodness of t a little in set I andimproves it even less in set II. On empirical grounds, it is difficult to choose betweenthe two models. To remain consistent with the value theory and with the researchevidence that conformity and tradition have meaningfully different associationswith other variables, we retain model 3. We treat conformity and tradition as distinctvalues, as the basis for further analyses.

5.5. Model 5: Power values peripheral to achievement values

Schwartz (1992) raised the possibility that power and achievement values might belocated at the same polar angle in the circle, with power peripheral to achievement.The proposed relationship between these two values parallels the relationship of tra-dition and conformity. We therefore followed the same procedures used to generatethe matrix of expected correlations for model 3 in order to generate the matrix formodel 5. That is, we xed the correlation between power and achievement at .88and reduced the expected correlations of power with the values that are one, two,and three steps away from it around the circle by .05, .10, and .15, respectively, ascompared with achievement. The expected correlations of power with its adjacentvalues are xed at .68 for security and hedonism. Its expected correlations withthe values one step away are xed at .43 (stimulation and conformity) and .38 (tra-dition). Its expected correlations with the values two steps away are xed at .18 (be-nevolence and self-direction). Finally, its expected correlation with universalism, theonly value three steps away, is xed at ) .07.

Row ve in Table 4 presents the t statistics for this model. Compared to model 3,the RMSEA and the SRMR indexes show a poorer t in both sets of samples. Thesubstantially higher AIC values in both sets indicate that model 5 describes the dataless well than model 3. We therefore reject this model and continue to use model 3,the modied quasi-circumplex, as the basis for comparing subsequent models.

5.6. Model 6: Combining power and achievement to yield nine values

Model 6 asks whether power and achievement might better be treated as a single

value rather than as separate values. The reference matrix of expected correlations toreproduce this model is similar to that for model 3 in Table 3, with necessary changesto reect reducing the number of distinct values by one. 5 Row ve in Table 4 indi-cates that this model ts the observed data less well than model 3 in both sets of sam-ples, judged by all indexes. We therefore reject this model as an improvement on themodied quasi-circumplex model.

5 The combined power/achievement value has the same expected correlations with security, tradition,and conformity that power did in model 3, and the same expected correlations with hedonism, stimulation,and self-direction that achievement did in model 3. In addition, the expected correlations of hedonism are.2 higher with conformity and security and .1 higher with tradition, and the expected correlation of stimulation with security is .2 higher.



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5.7. Model 7: Higher-order types of value

Schwartz (1992, 1994) proposed that four sets of values form higher-order valuetypes: openness to changejoining stimulation and self-direction values; conserva-tionjoining security, conformity, and tradition values; self-enhancementjoiningpower and achievement values; and self-transcendencejoining universalism and be-


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evaluated this assumption. This and the subsequent models are nested, so we use D v 2

to estimate the signicance of changes.The t statistics in row eight of Table 4 all show some improvement over model 3.

D v 2 values decreased signicantly in both sample sets ( D v 2 625 : 2 and 396.3, 2 df , p < : 001). The freely estimated correlations of hedonism in sets I and II, respectively,were .39 and .42 with achievement and .63 and .64 with stimulation. This indicatesthat hedonism is closer to openness, though it also relates to self-enhancement.Given the signicant improvement in t, we compare the remaining models withmodel 8.

5.9. Model 9: Nature and social concern subtypes within universalism

This model tests the existence of two potential subtypes of universalism proposedin the literature: social concernincluding the items equality, world at peace, andsocial justice; and natureincluding the items unity with nature, protecting the en-vironment, and world of beauty. The existence of these subtypes implies that eachconsists of items that correlate more highly with one another than expected fromtheir relation to the latent universalism factor. To model this pattern, we permittedcorrelated errors between the items in each subtype. We then tested whether thismodel ts the data better than the model with no correlated errors.

Row nine in Table 4 presents the t statistics for this model. Compared to model8, RMSEA improves in both sets of samples and SRMR improves in set I. More-over, v 2 values are signicantly lower in both sample sets ( D v 2 1577 and 1292.4,7df , p < : 001). This test supports the existence of social concern and nature subtypeswithin universalism values.

5.10. Model 10: Personal and group subtypes within security

This model tests the existence of two potential subtypes of security: personal se-curityincluding the items family security, reciprocation of favors, and clean; andgroup security or security of the wider collectivityincluding the items social orderand national security. Following the same procedure as in model 9, we modeled this

pattern by permitting correlated errors between the items in each subtype.Row 10 in Table 4 presents the t statistics for this model. Compared to model 9,RMSEA is unchanged in both sets of samples, while SRMR improves slightly onlyin set I. However, v 2 values are signicantly lower in both sample sets ( D v 2 313 : 7and 298.9, 4 df , p < : 001), indicating improved t. These ndings support, albeitweakly, discriminating the personal and group subtypes within security values.

5.11. Loadings of items on factors in the nal model

Table 5 provides the loading patterns of items on the latent factors in the nal

model (10) for both data sets. Not only are all loadings signicant ( p < : 001), butall are substantial ( > .40), with only one exception. Accepting one s portion in life

loads .26 on the tradition value factor in set I, though it too is signicant



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Table 5Loading pattern of items on latent factors for nal model (10)

Item Universal-ism

Benevo-lence

Tradition Confor-mity

Security Power Achieve-ment

SI SII SI S II SI SII SI SII SI SII SI SII SI SII SI

Equality .43 .46World at peace .49 .51Unity with

nature.40 .47

Wisdom .45 .41World of beauty .48 .54Social justice .58 .59Broadminded .59 .43Protecting the

environment.54 .54

Loyal .57 .49Honest .66 .58Helpful .62 .63Responsible .59 .52Forgiving .55 .49Respectful .49 .53Moderate .51 .44Humble .61 .50Accepting one s

portion in life

.26 .30

Devout .53 .48Politeness .66 .64Self-discipline .57 .57Honoring

parents andelders

.73 .66


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Obedient .61 .57Social order .53 .52National

security.62 .59

Reciprocation of favors

.53 .45

Family security .48 .45Clean .67 .64Social power .54 .54Wealth .59 .58Authority .62 .65Preserving

public image.54 .57

Ambitious .62 .56Inuential .57 .57Capable .55 .50Successful .69 .63Pleasure Enjoying life .Self-indulgent .Exciting life Varied life Daring Freedom Creativity Independent Choosing own

goalsCurious

Note. SI is sample set I; SII is sample set II.


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p < : 001. Furthermore, loadings are quite similar in the two data sets, differing by .08or less for 43 items. Only in three cases, broadminded , independent, and humble,

is there a difference in loadings of more than .10 between the two data sets.

6. Discussion

The current analyses are the rst formal, quantitative assessment of the theory of the structure of basic human values (Schwartz, 1992). Analyses in two independentsets of 23 samples from 27 countries yielded very similar results. We can thereforehave considerable condence in the conclusions these results suggest. The analysessupport the denitive, modied quasi-circumplex version of the theory and someproposed renements, but reject others.

6.1. The basic value structure

The discrimination of items into 10 distinct values, each dened by its motiva-tional content, is conrmed. Each of the 46 items correlates signicantly( p < : 001) with its a priori latent value factor. The SRMR statistic, which is espe-cially sensitive to misspecied factor loadings, shows an excellent t. Moreover,had correlations with multiple factors been permitted, no item would have correlatedas highly with any other factor. 7

The poor t of the model of 10 orthogonal factors conrms that the 10 values arenot independent. The quasi-circumplex structure of relations among the 10 values(model 2), proposed as a preliminary theory (Schwartz, 1992), provides a reasonablet to the data. Subjective judgments of the SSA plots of relations among values in 40samples had led Schwartz (1992) to reject the simple quasi-circumplex structure. In-stead, he proposed a modied quasi-circumplex, with tradition values peripheral toconformity values (model 3). The current analyses support this change. Substantialimprovements in AIC and in the RMSEA and SRMR indexes in both sets of samplesprovide a statistical justication for adopting the modied quasi-circumplex as thedenitive model for the theory of value structure.

6.2. Proposed model renements

6.2.1. Tradition and conformityBecause tradition and conformity values share the same broad motivational

goal, we evaluated a simpler model that combined them into one (model 4). Com-pared with the modied quasi-circumplex, the t indexes are virtually the same forthis model. The AIC values indicate a better t for model 3 in sample set I but abetter t for model 4 in sample set II. Thus, the CFA results give no denitive an-swer whether to retain the distinction between tradition and conformity values. A

decision therefore depends on the fruitfulness of this distinction. Because tradition

7 The relevant modication indexes are available from the authors.



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and conformity values are adjacent in the value structure, their associations withother variables should be quite similar. This is indeed the most common nding.However, numerous differences in the associations of these two values indicate thatit is fruitful to treat them as distinct. We cite a subset of the varied ndings thatsupport the distinction.

Tradition and conformity values have signicantly different correlations withthree of the Big 5 traitsagreeableness, extraversion, and conscientiousness(Roccas, Sagiv, Schwartz, & Knafo, 2002), with views of how much the govern-ment is doing about human rights (Spini & Doise, 1998), and with indicators of religiosity, across religions and nations (e.g., Schwartz & Huismans, 1995). Tradi-tion values discriminate strongly among voters for different political parties inmany nations, whereas conformity values do not (Barnea, 2003; Barnea & Sch-wartz, 1998). Parentchild value similarity is high for tradition values, among bothadolescents and young adults, but low for conformity values (Boehnke, 2001; Kna-fo & Schwartz, 2002). Finally, in samples from 61 nations, conformity values tendto be moderately important (typically 5th or 6th in the hierarchy of 10 values),whereas tradition values are signicantly less important (typically 8th or 9th; Sch-wartz & Bardi, 2001).

6.3. Power and achievement

Like tradition and conformity, power and achievement differ on characteristicsthat might lead to a central versus peripheral order. The peripheral location of power(model 5) is rejected by the analyses. It yields poorer t indexes than the modiedquasi-circumplex in both sets of samples. The simpler model that combines powerand achievement into a single value (model 6) is also rejected.

6.4. Higher-order value types

The most signicant, applied modication of the value structure has been to useonly the four higher-order value typesopenness to change, conservation, self-en-hancement, and self-transcendence typesas predictors. Are these particular high-

er-order types more justied than other possible groupings of the 10 values? Useof these particular types implies that the values that constitute each are substantivelycloser to one another than to the other values to which they are adjacent in the valuecircle (model 7). Schwartz (1992, 1994) attributed no substantive signicance to theparticular higher-order types. He grouped the 10 values only to describe the valuestructure more simply. He maintained that the values form a motivational contin-uum. If the 10 values do form a continuum, other groupings of adjacent values(e.g., universalism with self-direction) would be equally legitimate for purposes of simplifying.

The CFA analyses reveal that increasing intercorrelations among values within

higher-order types provides no improvement in t. This supports the assumptionthat the values do indeed form a motivational continuum. The continuum ideaimplies that the array of value items can be partitioned into as many or as few



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categories as is optimal for a researcher s purposes. Higher-order types can beformed, but alternative combinations of adjacent values into higher-order typesare as legitimate as the previously designated higher-order types.

Universalism and self-direction, for example, can form a higher order intellec-tual openness type, and power and security an uncertainty control type. Thesehigher-order types predict a classic liberal vs. conservative orientation in politics,whereas the previously specied higher-order types do not (Barnea, 2003). Benev-olence, tradition, and conformity, for example, can form a conventional proso-cial type that predicts the agreeableness trait of the Five Factor Model morestrongly than either the previously specied self-transcendence or conservationhigher-order types (data from Roccas et al., 2002). In sum, the support for a mo-tivational continuum of values gives researchers the freedom and exibility tochoose higher-order combinations of adjacent values particularly suited to the top-ics they study.

6.5. Hedonism

Hedonism values share with power and achievement values their emphasis on theinterests of self. They share with stimulation and self-direction their emphasis onopenness to change. The value theory does not specify which emphasis is stronger.Freeing the correlations of hedonism with its adjacent values (model 8) addressedthis issue. A signicant improvement in t indexes in both sets of samples indicatesthat hedonism is not equally close to self-enhancement and openness. Although itcorrelates signicantly with both, it is clearly closer to openness. This suggests that,for most people, hedonism values focus more on freely experiencing pleasure and lesson pursuing pleasure competitively.

6.6. Universalism and security subtypes

The motivational goal of universalism values is to understand, appreciate, andprotect the welfare of all people and nature. The literature suggested that this broadvalue includes two separable subtypes, social concern and nature. Allowing corre-

lated errors among the items in each subtype (model 9) signicantly improves t in-dexes in both sample sets. This supports the division of universalism into subtypes.The motivational goal of security values is safety, harmony, and stability of society,relationships, and self. Schwartz (1992) ed that this value too might includeseparable subtypes, one focused more on self and the other on groups and society.Allowing correlated errors among the items in these subtypes (model 10) also im-proves the t indexes in both sample sets.

We did not test the possibility of treating the subtypes of universalism and of se-curity as distinct values, because such a model has not been proposed in the litera-ture. For studying particularly relevant issues, however, separate indexes for the

subtypes might be useful. For example, a nature index might be used for environ-mental issues and a personal security index for personal safety issues (e.g., installingburglar alarms and other home protection devices).



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6.7. Reections on the theory of value structure

One crucial assumption underlies the theory of value structure: Actions that ex-press any value have consequences that conict or are compatible with the pursuitof other values. The motivational goals of some values (e.g., power and benevolence)are postulated to be inherently antagonistic, the goals of others (e.g., power andachievement) to be inherently congruent. The total set of antagonistic and congruentrelations among the 10 values gives rise to the modied quasi-circumplex value struc-ture (Fig. 1). Conict or antagonism implies negative correlations between values onopposite sides of the structure. Yet, the correlations between opposing values in thereference matrixes for the various models ranged only from +.08 to ) .07. Does thiscontradict the assumption of opposition between conicting values?

As noted above, some people tend to rate all values relatively high or low, regard-less of content. This biases observed intercorrelations among values upward. Stan-dardizing each participant s responses eliminates this bias, though it introducesother problems. 8 Freely estimated correlations among the latent factors for the 10values, based on the standardized data, provide a rough assessment of the true de-gree of opposition. The correlations between pairs of values that the theory describesas antagonistic ranged from ) .49 to ) .81, averaging ) .72. Thus, these data supportthe assumption of opposition between conicting values that is central to the valuetheory.

Future theorizing about the value structure might consider and test two issuesthat our analyses indirectly raised. First, do the 10 values differ in the breadth of their content? Schwartz (1992) suggested that universalism and security are concep-tually broad, including subtypes that were conrmed here. Are other values espe-cially narrow conceptually (e.g., hedonism and stimulation)? The methodemployed here could be used to model and test theory-based specications of differ-ences in the conceptual breadth of the values. For that purpose, however, it would bedesirable to index each value with an equal number of items.

The second issue concerns the central-peripheral distinction found with confor-mity and tradition values. Do values vary on this general dimension in addition tothe dimension of motivational content? This dimension was interpreted as indicating

variation in the closeness of a value to the self, its involvement in everyday interac-tion, and its specicity vs. abstractness. Centrality may also signify greater normativeimportance (Melech, 2001). The centrality of value items in the space correlates pos-itively with their importance ratings. Systematic theorizing that considers the loca-tions of value items on this potential dimension might enrich the value theory andpoint to hypotheses testable with the methods used here.

In conclusion, it is worth noting the overlap between the inferences supported bydifferent methods. The theory of the structure of values was rened by examining

8 We did not standardize in the main analyses for two reasons. First, this would impose the samevariance on everyone s responses. But people differ greatly in the degree to which they discriminate amongtheir values. Hence standardizing would distort responses. Second, standardizing exacerbates problemswith missing data.



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subjective judgments of SSA plots in many samples. Such judgments can be mislead-ing. In this case, however, the key judgments were supported by the statistical tests.This was so even though the theoretical model makes ne distinctions and the testswere performed on new data. Studies using multidimensional scaling methods led tothe conclusion that the value structure is robust to respondents gender, age, or levelof education (Schwartz, 1992, 1994; Struch, Schwartz, & van der Kloot, 2002). Thefact that the CFAs conrm the value structure inferred from earlier visual inspec-tions increases our condence in this conclusion. The success of these subjective judgments demonstrates that visual inspection of spatial representations can revealreliable, theoretically meaningful relations among variables. It is most successfulwhen guided by a clear theory and when replicated in many samples.

Acknowledgments

This research was supported by Grant No. 94-00063 from the United StatesIsraelBinational Science Foundation (BSF) and by a grant from the National Science Foun-dation (Israel Academy of Sciences) to the rst author, and by Grant I-242-065.04/92from the German-Israeli Foundation for Scientic Research and Development to bothauthors, and was facilitated by the Leon and Clara Sznajderman Chair of Psychology.

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