Evaluating the structure of human values with

JOURNAL OF

Journal of Research in Personality 38 (2004) 230–255

RESEARCH IN PERSONALITY www.elsevier.com/locate/jrp

Evaluating the structure of human values with confirmatory factor analysis Shalom H. Schwartza,* and Klaus Boehnkeb a

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

Abstract This is the first 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 values form a quasi-circumplex structure based on the inherent conflict or compatibility between their motivational goals. Past support for the theory came from subjective judgments of visual plots of the relations among value items in samples from over 60 countries. We formally test the postulated structure and several potential refinements. We employ a specially designed confirmatory factor analysis (CFA) approach with new data from two sets of 23 samples from 27 countries (N ¼ 10,857). In both data sets, CFAs confirm the 10 basic values, a modified quasi-circumplex rather than a simple circumplex structure, and the claim that values form a motivational continuum. Ó 2003 Elsevier Inc. All rights reserved. Keywords: Values; Confirmatory factor analysis; Value structure; Cross-cultural analyses

1. Introduction The past 45 years have seen a steady stream of papers that propose that the best way to represent personality and affect is a circumplex structure (Fabrigar, Visser, & Browne, 1997; Tracey, 2000). That is, they postulate that personality or affect variables lie on the circumference of a circle, and the strength of association between variables decreases as the distance between variables on the circle increases. A recent book 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 Ó 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0092-6566(03)00069-2

S.H. Schwartz, K. Boehnke / Journal of Research in Personality 38 (2004) 230–255

231

this approach even greater impetus. The current paper concerns the domain of individual values in which the most widely recognized current model also proposes a circumplex structure (Rohan, 2000; Schwartz, 1992). Factor/principal components analysis and multidimensional scaling (MDS) are the methods commonly used to test circumplex structures, but they are usually inadequate to provide statistical tests. Neither offers a simple, quantifiable method to formally assess the extent to which the observed data possess a circumplex structure (for detailed critiques of these methods, see Fabrigar et al., 1997 or Tracey, 2000). Instead, researchers typically reach conclusions by making two subjective judgments of the observed plot of relations among variables. First, they assess how well this plot appears to conform to a circular pattern. Then they assess the extent to which the order of the variables around the circle appears to correspond to the order in the theory. All past assessments of the structure of basic human values have relied on such subjective judgments of plots produced by an MDS approach. This paper is the first direct, quantitative evaluation of the postulated circumplex structure of values.

2. Value theory and past assessments The theory of basic human values (Schwartz, 1992) identifies 10 motivationally distinct types of values that are likely to be recognized within and across cultures: power, achievement, hedonism, stimulation, self-direction, universalism, benevolence, tradition, conformity, and security. Table 1, below, defines the 10 values. The most important feature of the theory is the structure of dynamic relations among the 10 values that it explicates. It postulates that actions expressive of any value have practical, psychological, and social consequences that may conflict or be compatible with the pursuit of other values. For example, actions that express hedonism values are likely to conflict with those that express tradition values and vice versa, and acting on self-direction values is likely to conflict with maintaining conformity values and vice versa. On the other hand, hedonism values are compatible with self-direction values, and tradition values are compatible with conformity values. Studies in 19 countries reveal systematic associations of many behavior, attitude, and personality variables with priorities for these values (see citations in Schwartz & 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 similarity and dissimilarity or conflict, as the values do, they are likely to yield a circumplex structure (Plutchik & Conte, 1997b). The circular structure in Fig. 1 portrays the total pattern of relations among values postulated by the theory. The circular arrangement of the values represents a motivational continuum. The closer any two values in either direction around the circle, the more similar their underlying motivations; and the more distant any two values, the more antagonistic their underlying motivations. The motivational significance of items that operationalize adjacent values overlaps in part but differs sharply from that of items that operationalize distant values. This structure is a circumplex, except for the placement of tradition outside conformity. The claim of a

232


Table 1 Samples included in the analyses Set I

Set II N

Belgium Denmark East Germany East Germany France (Nancy) Ghana Hong Kong Hungary Israel Japan Macedonia Netherlands Peru Philippines Poland Russia Russia in Israel

University Students School Teachers Adults University Students University Students School Teachers University Students University Students School Teachers School Teachers University Students University Students University Students University Students University Students School Teachers Adult Immigrants

249 682 233 441 214 214 222 160 188 173 245 217 145 289 141 194 202

Slovakia Turkey USA USA (Seattle) West Germany West Germany

School Teachers University Students School Teachers University Students University Students School Teachers

186 242 108 270 388 148 5551

N Australia Austria Brazil Bulgaria England France (Paris) Ghana Hong Kong Hungary Israel Israel Japan Macedonia Mexico Philippines Russia Russia in Berlin Slovakia Switzerland Uganda USA (Illinois) USA West Germany

University Students School Teachers University Students University Students School Teachers University Students University Students School Teachers School Teachers Adults University Students University Students School Teachers School Teachers School Teachers Adults Adult Immigrants University University University University Nurses University

Students Students Students Students Students

111 196 151 241 209 390 210 126 130 181 427 327 206 361 157 189 181 233 264 188 374 259 195 5306

motivational continuum is especially important for relating value priorities to other variables. It implies that these relations take the shape of a sinusoidal curve that follows the order of the values around the circle (Schwartz, 1992). Note that the theory postulates a circular arrangement of the 10 values, not of the items. For items, it postulates 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 technical terms, the theory assumes that the items in the value survey form 10 latent factors 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 60 countries from every inhabited continent (representative national samples, school teachers, university students, adolescents, samples of workers in specific occupations). Researchers examined two-dimensional projections of the relations among value items, using MDS or Similarity Structure Analysis (SSA; Borg & Shye, 1993; Guttman, 1968). They concluded that the data largely support (a) the distinctiveness of the 10 values, (b) the idea that these values are comprehensive of the major, motivationally distinctive types of values, and (c) the ordering of values postulated by the circumplex structure (Fontaine, 1999; Schwartz, 1992, 1994; Schwartz & Bardi, 2001; Schwartz & Sagiv, 1995; Schwartz, in press).


233

Fig. 1. Theoretical model of relations among 10 motivational types of values.

These conclusions were based on visual inspection of the spatial plots, guided by a priori criteria (Schwartz, 1992; Schwartz & Sagiv, 1995). They revealed that, in the vast majority of samples, the items that operationalize each value occupied a distinct region in the space, with no substantial empty spaces between regions. Moreover, the order of these distinct regions around the circle generally approximated the theorized order shown in Fig. 1. As noted, however, visual inspections cannot formally test whether the observed data possess a circumplex structure. Data that appear to fit a circumplex structure may or may not be found to fit such a structure when tested directly, as Fabrigar et al. (1997) demonstrated. Therefore, a first objective of this paper is directly to test the circumplex structure of the theory of human values using an application of structural equation modeling designed for this purpose. We ask: Does confirmatory factor analysis (CFA) corroborate the theoretical structure of value relations that was supported by interpretations of past SSA and MDS analyses? Equally important is our second objective—to test possible refinements to the value theory. These refinements were suggested in the published literature but never tested. Each refinement was inspired by examining the separate plots of relations among value items in large numbers of samples. The refinements fit the majority of samples. The theory formally incorporated one refinement: It modified the strict circumplex structure of 10 values into the structure shown in Fig. 1. This structure places tradition and conformity values at the same polar angle around the circle, but tradition is outside conformity. It provided a better visual fit than the strict circumplex to the average plot of the first 40 samples studied and to the separate plots in 29 of these samples, and no worse a fit in the remaining 11 samples (Schwartz, 1992, p. 35). Although this presumed refinement has been justified conceptually, it has never been tested formally.

234


3. Models tested Below, we spell out each refinement proposed to the theory, note the conceptual arguments for it, and then test it. One could perform these tests with the data from past research. However, the refinements drew upon post hoc examination of those data. 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 refinements, we analyze data that have not figured in any previous assessments of the structure of values. We wish to assess which theoretical model best fits the basic pattern of value relations common to cultures, rather than to identify unique variants in particular cultures. We therefore combine the individual data from many cultures. In order to assess the robustness of the findings, we replicate the analyses in two independent sets of samples. 3.1. Model 1: 10 orthogonal factors The theory of basic human values (Schwartz, 1992, 1994) derived the 10 motivationally distinct types of values from three universal requirements of the human condition: needs of individuals as biological organisms, requisites of coordinated social interaction, and survival and welfare needs of groups. The theory holds that groups and individuals represent these requirements cognitively, as specific values about which they communicate in order to coordinate with others in pursuing the goals that are important to them. The 10 values are the content aspect of the theory. The structural aspect of the theory specifies relations of similarity and dissimilarity among these values. Perhaps, however, each value is independent. This would be in line with RokeachÕs (1973) view of values, on which Schwartz built, and with traditional exploratory factor analysis. We therefore first test how well a model of 10 orthogonal factors fits the data. 3.2. Model 2: A quasi-circumplex model of 10 factors1 At the beginning of the chapter that first presented the value theory, Schwartz (1992, pp. 13–15) speculated that the 10 values might form a perfect circular structure. That is, the 10 values would form a circle as in Fig. 1, but with tradition located between 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 that follows. Guttman (1954) first used the term ‘circumplex’ to include any model that postulates a circular arrangement of relations among variables. He subdivided such models into those that assume the variables are 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 a circular arrangement of variables but do not locate all the variables on the circumference of the circle. Hence, there is no term for the ‘‘definitive’’ model proposed by the value theory. It postulates that conformity values are more central and tradition values more peripheral (see Fig. 1). The remaining values are arrayed in order around the circle, though not necessarily equidistant. We label this model ‘‘modified quasi-circumplex.’’


235

values are spaced equally around the circle (a circulant model) or unequally (a quasicircumplex model). The chapter rejected this circumplex, but provided no direct, quantitative test of the appropriate circumplex model to justify this rejection. We therefore next test the fit of a circumplex model to the data. Because the theory does not assume that the values are distributed at equal intervals around the circle (circulant model), we test a quasi-circumplex model. We compare the fit of this model to the fit of the model of ten orthogonal factors. 3.3. Model 3: The 1992 theory—A modified quasi-circumplex model The ‘‘definitive’’ version of the theory of basic values postulates the modified quasi-circumplex structure presented in Fig. 1. As noted, this change derived from finding that a theory that locates tradition outside of conformity at the same polar angle in the circle was a better visual fit to the plots of data in the available samples. Scrutinizing plots from many later samples reaffirmed this model (Schwartz, 1994; Schwartz & Sagiv, 1995). The theoretical explanation for locating conformity and tradition at the same polar angle in the circle is that they share the same broad motivational goal—subordinating self in favor of socially imposed expectations. What distinguishes them is that ‘‘conformity values entail subordination to persons with whom one is in frequent interaction—parents, teachers, and bosses. Tradition values entail subordination to more abstract objects—religious and cultural customs and ideas’’ (Schwartz, 1992, p. 40). Conformity values emphasize restraint of actions, inclinations, and impulses that might upset or harm others and violate their expectations. Tradition values emphasize respect, commitment, and acceptance of the customs and ideas of oneÕs culture or religion. Central versus peripheral locations in a circle typically reflect differences between constructs in the degree of their abstractness, closeness to the self, or prevalence in everyday interaction (Levy, 1985). On all three counts, tradition values are more likely to be located peripherally than conformity values. The more peripheral the location of a value, the less positive its correlations with the values on the opposite side of the circle. Hence, the peripheral location of tradition would signify that it is less compatible than conformity with hedonism and stimulation values. We test the fit of the ‘‘definitive,’’ modified quasi-circumplex model of values to the data and compare its fit to that of the quasi-circumplex model. We label this model ‘‘modified quasi-circumplex’’ because it orders the values around the circle but includes central vs. peripheral positioning. 3.4. Model 4: Combining tradition and conformity to yield nine values If tradition and conformity values share the same broad motivational goal, perhaps a simpler, more parsimonious model would fit the data better. Tradition and conformity may constitute a single value. This would be a quasi-circumplex model of nine values, with the combined tradition/conformity value located between benevolence and security. We formally test this quasi-circumplex model and compare it with the modified quasi-circumplex model.

236


3.5. Model 5: Power values peripheral to achievement values In discussing the plots of the first 40 samples studied, Schwartz (1992, p. 40) noted that, in 26 samples, a distinct region of power values could be drawn toward the periphery of the circle behind achievement values. In most samples, however, it was also possible to connect the region of power values to the center of the circle. Hence, the ‘‘definitive’’ version of the theory located power values between achievement and security. Was this decision correct? Might a model locating achievement and power values at the same polar angle in the circle, with power peripheral to achievement, fit the data better? Theoretical arguments for this alternative model appear in Schwartz (1992, pp. 40–41): [Both values] focus on social esteem. However, achievement values refer more to striving to demonstrate competence in everyday interaction. . . whereas power values refer more to the abstract outcomes of action in the form of status in the social structure. . . .achievement values refer to the striving of the individual. . . whereas power values also refer to the hierarchical organization of relations in society.

Thus, like tradition and conformity, power and achievement differ on characteristics that might lead to a central versus peripheral order: degree of abstractness, closeness to the self, and prevalence in everyday interaction. We therefore test whether this model fits the data better than the previous models. We also test whether a more parsimonious model that treats power and achievement as a single value (model 6) is an even better fit. 3.6. Model 7: Higher-order types of value Based on the SSA analyses in the first 40 samples, Schwartz (1992, p. 43) suggested a simpler way to view value structures. Relationships among the values can be summarized in terms of a two-dimensional structure composed of four higher-order value types. One higher-order type, called openness to change, combines stimulation and self-direction values. It forms a bipolar dimension with the higher-order type called conservation that combines security, conformity, and tradition values. This dimension arrays values in terms of the extent to which they motivate people to follow their own emotional and intellectual interests in unpredictable and uncertain directions (openness) versus to preserve the status quo and the certainty it provides (conservation). A third higher-order type, called self-enhancement, combines power and achievement values. It forms a bipolar dimension with the higher-order type called self-transcendence that combines universalism and benevolence values. This dimension arrays values in terms of the extent to which they motivate people to enhance their own personal interests even at the expense of others (self-enhancement) versus to transcend selfish concerns and promote the welfare of others, close and distant, and of nature (self-transcendence). Hedonism values share some elements of both openness and self-enhancement. Consequently, hedonism is located between these two higher-order types.


237

Schwartz treats the higher-order types merely as a way to describe the value structure more simply. Nevertheless, he and others sometimes use these four types, rather than the 10 values, to predict behavior and attitudes (e.g., Bilsky, 1998; Hrubes, Ajzen, & Daigle, 2001; Ros, Schwartz, & Surkiss, 1999; Schwartz, 1994). If one wants to simplify the value structure, is this particular set of higher-order types more meaningful 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 equally legitimate? We address these questions by evaluating their implications for associations among the values. Let us assume that this particular set of four higher-order types is more meaningful conceptually than alternative combinations. We would then expect adjacent values within these higher-order types to be more strongly associated with one another substantively and empirically than they are with the adjacent values from other higher-order types. For example, the two self-transcendence values, universalism and benevolence, should be more highly intercorrelated than universalism is with self-direction (also adjacent, but in the openness higher-order type) or than benevolence is with conformity (adjacent, but a conservation value). We put this idea to a formal test by specifying a model in which correlations between values within higher-order types are higher than the correlations of these values with adjacent values from other higher-order types. 3.7. Model 8: Freely estimating hedonism correlations The theory of value structure locates hedonism values between stimulation and achievement values because they share elements of both openness and self-enhancement. The theory does not specify whether hedonism is related more to one or to the other higher-order type, so the above models treated it as equally linked to both. The CFA approach enables us to ask whether hedonism is closer to openness, to self-enhancement, or equally close to both. Model 8 addresses this question. 3.8. Models 9 and 10: Subtypes of values Partitioning the domain of value items, like partitioning any circular structure, entails an arbitrary selection of class-intervals (Plutchik & Conte, 1997b). The domain could as easily be partitioned into more or fewer intervals, since the values constitute a motivational continuum. Schwartz (1992) judged that 10 distinct values are sufficient to capture the major motivational differences in value meanings and to create useful indexes for measuring individualsÕ value priorities. These 10 values are psychologically and socially meaningful and each has links to important constructs in the literature. However, for some purposes, finer discriminations may be desirable within particular values. 3.8.1. (9) Nature and social concern subtypes within universalism Two potentially useful subtypes of universalism have been proposed (Sagiv, 1994; Schwartz, 1997; Schwartz, Sagiv, & Boehnke, 2000). One subtype, labeled Ôsocial

238


concern,Õ includes the value items equality, world at peace, and social justice. This subtype is more strongly associated than the other universalism items with concern for and action to promote the welfare of people outside oneÕs in-group. The second proposed subtype, labeled Ônature,Õ includes the value items unity with nature, protecting the environment, and world of beauty. This subtype is more strongly associated than the other universalism items with environmental attitudes and actions. Are these merely subsets of universalism items worth distinguishing only when one studies particular topics to which they are relevant? Or are they real subtypes in the sense that the value items within each are more closely related to one another than to the other universalism items? We test a model that represents them as real subtypes that constitute components of universalism. 3.8.2. (10) Personal and group subtypes within security In presenting the value theory, Schwartz (1992, p. 9) raised the possibility of splitting security into two separate types of values, one concerned with personal security and the other with the security of larger groups. The motivational goal of the general security value is safety, harmony, and stability of society, of relationships, and of self. Visual examination of the plots in the first 40 samples supported the existence of a single security value. Perhaps, security of oneÕs groups is a precondition for security for self. Nonetheless, the plots did suggest ‘‘that people may distinguish somewhat between the security of self and that of the collectivities of which they are members’’ (Schwartz, 1992, p. 41). We therefore test a model that represents personal and group subtypes as components of security. Various additional refinements to the structure of values postulated in the value theory are possible. However, we limit ourselves to the above models because they cover all of the refinements suggested in the literature until now.

4. Methods 4.1. Samples Respondents from 46 samples in 27 countries (N ¼ 10,857) provided the values data. None of these respondents had been included in assessments of the structure of values in past reports. Table 1 describes the sample characteristics. Samples were volunteers recruited at their place of work or study or at home. We randomly assigned each sample to one of the two sets, in order to replicate the analyses in each set of samples. Set I included 5551 individuals and set II 5306 individuals. 4.2. Instrument Respondents completed a slightly expanded, 57-item version, of the Schwartz Value Survey (SVS) in their native language. Each item is followed in parentheses by a short explanatory phrase (e.g., EQUALITY [equal opportunity for all]). Respondents rate the importance of each value item as a guiding principle in their life on a 9-point


239

Table 2 Definitions 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, influential) Hedonism: Pleasure or sensuous gratification 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 action—choosing, 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 with nature, a world of beauty) Benevolence: Preservation and enhancement of the welfare of people with whom one is in frequent personal contact (helpful, honest, forgiving, loyal, responsible) Tradition: Respect, commitment, and acceptance of the customs and ideas that traditional culture or religion provide (devout, respect for tradition, humble, moderate) Conformity: Restraint of actions, inclinations, and impulses likely to upset or harm others and violate social 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, national security, social order, clean, reciprocation of favors)

scale from ‘‘opposed to my principles’’ ()1), through ‘‘not important’’ (0), to ‘‘of supreme importance’’ (7). As markers for each of the 10 values, we used the items recommended as standard indexes for cross-cultural research, based on the consistency of their meanings across cultures (Schwartz, 1992, 1994). Table 2 presents brief definitions 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 different structural models. This approach must test quasi-circumplex models as well as modified quasi-circumplex models. It must also test a model that specifies different distances among particular values, to represent relations within and between higher-order value types. Additionally, it must test the existence of subtypes within values (universalism and security). Finally, the approach must treat the values as latent variables and the items as observed variables, allowing a test of the appropriateness of the marker items for measuring the 10 values in a unified analysis. Tracey (2000) described computer programs specifically designed to test circumplex conceptual models. Both of the most available programs, CIRCUM (Browne, 1992) and RANDALL (Tracey, 1997), do not fit the requirements of testing all aspects of the current theory and its proposed refinements. Neither program permits specifying two-level models as required here. We cannot test the circumplex assumption for the latent variables (the values) together with a simple factorial structure for the manifest variables. This limitation, that precludes simultaneously modeling relationships of items to factors and relations among factors, is the primary reason we do not use these programs. In addition, neither program provides an appropriate

240


way to handle more central as opposed to peripheral locations of factors in a circle. Hence, they are not suited to testing the ‘‘definitive’’ model of the value theory, a modified quasi-circumplex. We therefore developed a strategy tailored to the requirements of testing all aspects of the models of interest, using a structural equation modeling program (LISREL 8.14; J€ oreskog & S€ orbom, 1993). We tested the model of 10 orthogonal factors with an ordinary CFA on 10 latent variables. To test the theory-driven models of the value structure, we specified a reference matrix of expected correlations among the values for each model. This matrix represents exactly a pattern of expected correlations among the values that reproduces the model. We then tested the fit of the reference matrix to the observed data. In order to create a reference matrix for a model, it is necessary to specify actual correlation coefficients that fit the expected pattern of associations of the model to be tested. Any set of arbitrarily chosen coefficients that fits the pattern of expected associations might be used, because the model must reproduce the pattern. Once reference values are chosen for any two correlation coefficients, all the remaining coefficients 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 factors in both samples, with LISREL. We then calculated the average intercorrelation between 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 .68 for adjacent values. We applied the same procedure to all pairs of values that the theory postulates to have opposing substantive contents (e.g., self-direction/security) and obtained a reference correlation of .08 for values on opposite sides of the circle. Based on these analyses, we fixed the correlation coefficient between all pairs of adjacent values at .68 for the circumplex model of 10 equally spaced values. Thus, we fixed the correlations for power/achievement, power/security, security/conformity, and so on around the circle, at .68 in the reference matrix. Similarly, we fixed the correlation between all pairs of values on opposite sides of the circle (universalism/ power, benevolence/achievement, etc.) at .08. Distances between pairs of values around a circle of 10 values can range from adjacent to four ÔstepsÕ away (opposite). We therefore computed the amount to reduce the correlation for each step by dividing the difference between the maximum correlation (.68) and the minimum (.08) by four. This yielded a reduction of .15 for each step. Table 3, below the diagonal, presents the resulting reference matrix. Table 3 arranges the values according to their postulated order around the circle from universalism to self-direction. The greater the distance between any pair of values, the less positive the correlation between them. The coefficients that reproduce the five expected distances among 10 values around 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 correlation coefficients does not produce equidistance of items along a circle. This is not a problem for the current approach because the theory does not posit equidistance among the 10 values. Rather, it posits relations of q1 > q2 > q3 > q4 > q5 < q6 < q7 < q8 < q9 , where q1 to q9 stand for the correlations of one value with the other nine values in the order presented in Fig. 1. The reference matrix represents this set of relations.


241

Table 3 Reference matrixes of expected factor intercorrelations for confirmatory factor analyses: 10 factor quasicircumplex (model 2) below the diagonal and basic theory modified quasi-circumplex (model 3) above the diagonal Values

UN

BE

TR

CO

SE

PO

AC

HE

ST

SD

Universalism (UN) Benevolence (BE) Tradition (TR) Conformity (CO) Security (SE) Power (PO) Achievement (AC) Hedonism (HE) Stimulation (ST) Self-Direction (SD)

1.00 .68 .53 .38 .23 .08 .23 .38 .53 .68

.68 1.00 .68 .53 .38 .23 .08 .23 .38 .53

.43 .68 1.00 .68 .53 .38 .23 .08 .23 .38

.48 .68 .88 1.00 .68 .53 .38 .23 .08 .23

.28 .48 .68 .68 1.00 .68 .53 .38 .23 .08

.08 .28 .43 .48 .68 1.00 .68 .53 .38 .23

.08 .08 .18 .28 .48 .68 1.00 .68 .53 .38

.28 .08 ).07 .08 .28 .48 .68 1.00 .68 .53

.48 .28 ).07 .08 .08 .28 .48 .68 1.00 .68

.68 .48 .18 .28 .08 .08 .28 .48 .68 1.00

For each subsequent model (3–8), we modified the reference matrix of expected correlations to represent the relations among the values expected according to that model. In the results, we explain how we constructed the reference matrix of expected correlations for each of these models. The models that postulate the existence of subtypes (9 and 10) imply that each subtype consists of items that correlate more highly 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 each subtype do not account fully for the intercorrelations among the items themselves. To model this pattern, we permitted correlated errors between the items in each subtype. We then tested whether models with these correlated errors fit the data better than models with no correlated errors. Our criterion for the goodness of fit of the models is a combination of two indexes, RMSEA and SRMR, recommended by Hu and Bentler (1999; cf. MacCallum & Austin, 2000). RMSEA is especially sensitive to models with misspecified factor covariances or latent structures, SRMR to models with misspecified factor loadings. Hu and Bentler suggest that, for samples of 5000, the approximate size of our samples, the probabilities of rejecting a valid model or of accepting an invalid model are extremely small when RMSEA is close to .06 and SRMR to .11. We report v2 statistics to test differences in fit between nested models. Many of the models are not nested, however. To test differences between non-nested models, we report the Akaike information criterion, AIC (Akaike, 1973; Sakamoto, Ishiguro, & Kitagawa, 1986). Among a set of hypothesized, non-nested models, the best model is the one that minimizes the value of AIC. In all cases, our aim is to select the best model for describing the data among the theory-based alternatives.3 3 The decision whether one model fits the data better than another is sometimes difficult in this study. With the large samples, trivial differences in v2 are statistically significant. We therefore set a conservative probability level of p < :001 for considering Dv2 between nested models to be significant. Moreover, differences in the fit coefficients of the models are often small. When this is so, we use the differences in the RMSEA, SRMR, and AIC as aids to choice, picking the model that is most convincing conceptually and that is also best according to the set of statistics.

242


As noted, we conducted all analyses on two independent sets of data. For both data sets, we first calculated ordinary covariance matrixes.4 All analyses used maximum-likelihood estimation.

5. Results 5.1. Model 1: 10 orthogonal factors We first tested a model that treats each value as independent. Table 4 reports results for this model of 10 orthogonal factors. An RMSEA index greater than .06 and an SRMR index greater than .11 indicate that this model fit 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 Schwartz (1992), was a perfect circumplex structure of 10 factors. We tested this model by using the reference correlation matrix below the diagonal in Table 3. The pattern of 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 presents the fit statistics for this model. The RMSEA index is slightly higher than the recommended cutoff criterion in set I and just at that level in set II. The SRMR criterion is met in both sets of samples. Thus, the 10-factor quasi-circumplex model shows a moderate fit to the data. It clearly fits the data better than the model of 10 orthogonal factors. Both the v2 value and the AIC value decreased substantially in both sets of samples. In this and all subsequent theory-driven models, all items loaded significantly (p < :0001) on the appropriate latent value. 5.3. Model 3: The 1992 theory—A modified quasi-circumplex model The ‘‘definitive’’ representation of the value theory is the quasi-circumplex structure presented in Fig. 1 (Schwartz, 1992, 1994). It locates tradition outside of conformity, but at the same polar angle in the circle. This reduces the number of locations around the circle from 10 to 9. The pattern of expected correlations above the diagonal in Table 3 represents this structure. We generated this pattern by modifying the correlations for the quasi-circumplex model (below the diagonal in Table 3) as follows. With only nine locations of values, the number of ÔstepsÕ from any value to the opposite location in either direction around the circle is three. We therefore de4

The samples that make up the data sets vary substantially in size. Hence, we also did the analyses on a correlation matrix for each set that weighted each sample equally. We constructed the average matrixes as follows. We transformed the correlations in each sample-specific 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 into correlation coefficients. Analyses of these average correlation matrixes yielded results very similar to those reported below. Because the mathematical properties of a matrix of averaged correlation coefficients are uncertain, the text reports analyses on the unweighted covariance matrix.

Model

df

Sample set I, N ¼ 5551 2

1. Ten orthogonal factors 2. Quasi-circumplex of 10 factors 3. The 1992 theory—a modified quasi-circumplex 4. Combining tradition and conformity to yield nine values 5. Power values peripheral to achievement values 6. Combining power and achievement to yield nine values 7. Higher-order types of value 8. Free estimation of hedonism 9. Subtypes within universalism: nature and social concern 10. Subtypes within security: personal and group

Sample set II, N ¼ 5306

v

RMSEA

SRMR

AIC

v2

RMSEA

SRMR

AIC

989 989 989

39126.8 24048.0 23356.1

.083 .065 .064

.160 .088 .081

39310.8 24232.0 23540.1

33538.2 19611.1 19031.8

.079 .060 .059

.150 .079 .073

33722.2 19795.1 19215.8

989

23532.6

.064

.082

23716.6

18964.7

.059

.072

19148.7

989

24036.5

.065

.083

24220.5

19334.3

.059

.074

19518.9

989

24711.2

.066

.083

24595.2

19699.2

.060

.074

19883.2

989 987 981

23526.3 22730.9 21153.9

.064 .063 .061

.080 .080 .079

23710.3 22918.9 21353.9

19170.2 18635.5 17343.1

.059 .058 .056

.074 .072 .072

19354.2 18823.5 17543.1

977

20840.0

.061

.078

21048.0

17044.1

.056

.072

17252.1


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

243

244


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, values separated 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 the same polar angle, we increased the expected correlation between them by one step to .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 increase with each step without reaching the equivalent of a full step, .20. We therefore reduced the expected correlations of tradition by .05 for each step. The expected correlations of tradition with its adjacent values (benevolence and security) were unchanged at .68. Its expected correlations with the values one step away (universalism and power) were reduced by .05, compared with the expected correlations of conformity, and fixed at .43. The expected correlations of tradition with the values two steps away (self-direction and achievement) were reduced by .10 and fixed at .18. Finally, its expected correlations with the values three steps away, on the opposite side of the circle (hedonism and stimulation), were reduced by .15 and fixed at ).07. Row three in Table 4 presents the fit statistics for this model. The RMSEA index is slightly higher than the recommended cutoff criterion in set I and the criterion is met in set II. The SRMR criterion is met in both sets of samples. As compared with the quasi-circumplex model (2), the modified quasi-circumplex model fits the empirical data somewhat better. The goodness of fit indexes improved slightly in both sets of samples, and both the AIC value and the v2 value decreased substantially both in set I and in set II. 5.4. Model 4: Combining tradition and conformity to yield nine values The modified quasi-circumplex model locates tradition and conformity values at the same polar angle on the circle because they share the same broad motivational goal. Model 4 asks whether tradition and conformity might better be treated as a single value rather than as separate values. This model is a quasi-circumplex with nine rather than 10 values. It combines the tradition and conformity items to form a single value located between benevolence and security. The reference matrix of expected correlations to reproduce this model is similar to that for model 3. However, tradition values are dropped from the matrix. The joint tradition/conformity value has the same expected correlations as conformity did in model 3. Row four in Table 4 presents the fit statistics for this model. RMSEA shows no improvement in either set of samples compared with model 3. SRMR increases slightly in set I and decreases slightly in set II. Both models fit the data reasonably well. The increase in the AIC value in set I (176.5) suggests that model 3 is better, but the decrease in the AIC value in set II (67.1) favors model 4. Thus, treating tradition


245

and conformity as a single value reduces the goodness of fit a little in set I and improves it even less in set II. On empirical grounds, it is difficult to choose between the two models. To remain consistent with the value theory and with the research evidence that conformity and tradition have meaningfully different associations with other variables, we retain model 3. We treat conformity and tradition as distinct values, 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 be located at the same polar angle in the circle, with power peripheral to achievement. The proposed relationship between these two values parallels the relationship of tradition and conformity. We therefore followed the same procedures used to generate the matrix of expected correlations for model 3 in order to generate the matrix for model 5. That is, we fixed the correlation between power and achievement at .88 and 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, as compared with achievement. The expected correlations of power with its adjacent values are fixed at .68 for security and hedonism. Its expected correlations with the values one step away are fixed at .43 (stimulation and conformity) and .38 (tradition). Its expected correlations with the values two steps away are fixed at .18 (benevolence and self-direction). Finally, its expected correlation with universalism, the only value three steps away, is fixed at ).07. Row five in Table 4 presents the fit statistics for this model. Compared to model 3, the RMSEA and the SRMR indexes show a poorer fit in both sets of samples. The substantially higher AIC values in both sets indicate that model 5 describes the data less well than model 3. We therefore reject this model and continue to use model 3, the modified 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 to reproduce this model is similar to that for model 3 in Table 3, with necessary changes to reflect reducing the number of distinct values by one.5 Row five in Table 4 indicates that this model fits the observed data less well than model 3 in both sets of samples, judged by all indexes. We therefore reject this model as an improvement on the modified 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.

246


5.7. Model 7: Higher-order types of value Schwartz (1992, 1994) proposed that four sets of values form higher-order value types: openness to change—joining stimulation and self-direction values; conservation—joining security, conformity, and tradition values; self-enhancement—joining power and achievement values; and self-transcendence—joining universalism and benevolence values. The 1992 chapter treated the higher-order types as descriptive. Some later publications, however, treated them as though the values within each are substantively more related to one another than they are to the adjacent values from other higher-order types. If this is so, the correlations between the values within each higher-order type should be greater than their correlations with the adjacent values in another higher-order type. To generate a reference matrix of expected correlations to reproduce this model, we increased the correlations among values within the same higher-order type by .05, from .68 to .73 (e.g., self-direction/stimulation).6 Correlations between adjacent pairs of values from different higher-order types were left at .68 (e.g., power/security). According to the theory, hedonism shares elements with both openness and self-enhancement. To model this, we increased correlations of hedonism with the values in these higher-order types by .025, half the increase between the values within each higher-order type. This yielded expected correlations of hedonism with achievement and stimulation of .705, and with self-direction and power of .505. Row seven in Table 4 presents the fit statistics for this model. The RMSEA index is slightly higher than the recommended cutoff criterion in set I and the criterion is met in set II. The SRMR criterion is met in both sets of samples. Thus, a quasi-circumplex structure that treats the higher-order types as more than merely descriptive provides a reasonable fit to the empirical data. Comparing this model (7) to the modified quasi-circumplex model (3) that assumes no greater association among values within the same higher-order type reveals no improvement of fit. RMSEA is unchanged and SRMR decreases slightly in sample set I but increases slightly in sample set II. However, the AIC values are larger for model 7 than for model 3 in both sample sets (set I, 170.2; set II, 138.4). This suggests that model 3 fits the observed data better. The greater simplicity and conceptual elegance of model 3, together with the statistics, support retaining the theory of values as forming a motivational continuum that it represents rather than accepting this refinement. 5.8. Model 8: Freely estimating hedonism correlations The modified quasi-circumplex model (3) constrained hedonism to correlate equally with its adjacent values, achievement and stimulation. This assumed that the motivation underlying hedonism is as much self-enhancement as openness. By freeing the correlations of hedonism with achievement and stimulation, model 8

6 The correlation between tradition and conformity was not increased further because it had already been increased to .88 in model 3.


247

evaluated this assumption. This and the subsequent models are nested, so we use Dv2 to estimate the significance of changes. The fit statistics in row eight of Table 4 all show some improvement over model 3. Dv2 values decreased significantly in both sample sets (Dv2 ¼ 625:2 and 396.3, 2df, 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 indicates that hedonism is closer to openness, though it also relates to self-enhancement. Given the significant improvement in fit, we compare the remaining models with model 8. 5.9. Model 9: Nature and social concern subtypes within universalism This model tests the existence of two potential subtypes of universalism proposed in the literature: social concern—including the items equality, world at peace, and social justice; and nature—including the items unity with nature, protecting the environment, and world of beauty. The existence of these subtypes implies that each consists of items that correlate more highly with one another than expected from their relation to the latent universalism factor. To model this pattern, we permitted correlated errors between the items in each subtype. We then tested whether this model fits the data better than the model with no correlated errors. Row nine in Table 4 presents the fit statistics for this model. Compared to model 8, RMSEA improves in both sets of samples and SRMR improves in set I. Moreover, v2 values are significantly lower in both sample sets (Dv2 ¼ 1577 and 1292.4, 7df, p < :001). This test supports the existence of social concern and nature subtypes within universalism values. 5.10. Model 10: Personal and group subtypes within security This model tests the existence of two potential subtypes of security: personal security—including the items family security, reciprocation of favors, and clean; and group security or security of the wider collectivity—including the items social order and 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 fit statistics for this model. Compared to model 9, RMSEA is unchanged in both sets of samples, while SRMR improves slightly only in set I. However, v2 values are significantly lower in both sample sets (Dv2 ¼ 313:7 and 298.9, 4df, p < :001), indicating improved fit. These findings support, albeit weakly, discriminating the personal and group subtypes within security values. 5.11. Loadings of items on factors in the final model Table 5 provides the loading patterns of items on the latent factors in the final model (10) for both data sets. Not only are all loadings significant (p < :001), but all are substantial (>.40), with only one exception. ÔAccepting oneÕs portion in lifeÕ loads .26 on the tradition value factor in set I, though it too is significant

248

Item

Equality World at peace Unity with nature Wisdom World of beauty Social justice Broadminded Protecting the environment Loyal Honest Helpful Responsible Forgiving Respectful Moderate Humble Accepting oneÕs portion in life Devout Politeness Self-discipline Honoring parents and elders

Universalism

Benevolence

Tradition

Conformity

Security

Power

SI

SII

SI

S II

SI

SII

SI

SII

SI

SI

.43 .49 .40

.46 .51 .47

.45 .48 .58 .59 .54

.41 .54 .59 .43 .54 .57 .66 .62 .59 .55

.49 .58 .63 .52 .49 .49 .51 .61 .26

.53 .44 .50 .30

.53

.48 .66 .57 .73

.64 .57 .66

SII

SII

Achievement

Hedonism

Stimulation

Selfdirection

SI

SI

SI

SI

SII

SII

SII

SII


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

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

.61

.57 .53 .62

.52 .59

.53

.45

.48 .67

.45 .64 .54 .59 .62 .54

.54 .58 .65 .57 .62 .57 .55 .69

.56 .57 .50 .63 .69 .71 .60

.66 .66 .57 .66 .62 .52

.69 .69 .53 .54 .47 .52 .57

.53 .53 .34 .45

.46

.50


Obedient Social order National security Reciprocation of favors Family security Clean Social power Wealth Authority Preserving public image Ambitious Influential Capable Successful Pleasure Enjoying life Self-indulgent Exciting life Varied life Daring Freedom Creativity Independent Choosing own goals Curious

249

250


p < :001. Furthermore, loadings are quite similar in the two data sets, differing by .08 or less for 43 items. Only in three cases, ÔbroadmindedÕ, Ôindependent,Õ and Ôhumble,Õ is there a difference in loadings of more than .10 between the two data sets.

6. Discussion The current analyses are the first formal, quantitative assessment of the theory of the structure of basic human values (Schwartz, 1992). Analyses in two independent sets of 23 samples from 27 countries yielded very similar results. We can therefore have considerable confidence in the conclusions these results suggest. The analyses support the ‘‘definitive,’’ modified quasi-circumplex version of the theory and some proposed refinements, but reject others. 6.1. The basic value structure The discrimination of items into 10 distinct values, each defined by its motivational content, is confirmed. Each of the 46 items correlates significantly (p < :001) with its a priori latent value factor. The SRMR statistic, which is especially sensitive to misspecified factor loadings, shows an excellent fit. Moreover, had correlations with multiple factors been permitted, no item would have correlated as highly with any other factor.7 The poor fit of the model of 10 orthogonal factors confirms that the 10 values are not independent. The quasi-circumplex structure of relations among the 10 values (model 2), proposed as a preliminary theory (Schwartz, 1992), provides a reasonable fit to the data. Subjective judgments of the SSA plots of relations among values in 40 samples had led Schwartz (1992) to reject the simple quasi-circumplex structure. Instead, he proposed a modified quasi-circumplex, with tradition values peripheral to conformity values (model 3). The current analyses support this change. Substantial improvements in AIC and in the RMSEA and SRMR indexes in both sets of samples provide a statistical justification for adopting the modified quasi-circumplex as the ‘‘definitive’’ model for the theory of value structure. 6.2. Proposed model refinements 6.2.1. Tradition and conformity Because tradition and conformity values share the same broad motivational goal, we evaluated a simpler model that combined them into one (model 4). Compared with the modified quasi-circumplex, the fit indexes are virtually the same for this model. The AIC values indicate a better fit for model 3 in sample set I but a better fit for model 4 in sample set II. Thus, the CFA results give no definitive answer 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 modification indexes are available from the authors.


251

and conformity values are adjacent in the value structure, their associations with other variables should be quite similar. This is indeed the most common finding. However, numerous differences in the associations of these two values indicate that it is fruitful to treat them as distinct. We cite a subset of the varied findings that support the distinction. Tradition and conformity values have significantly different correlations with three of the ‘‘Big 5’’ traits—agreeableness, extraversion, and conscientiousness (Roccas, Sagiv, Schwartz, & Knafo, 2002), with views of how much the government is doing about human rights (Spini & Doise, 1998), and with indicators of religiosity, across religions and nations (e.g., Schwartz & Huismans, 1995). Tradition values discriminate strongly among voters for different political parties in many nations, whereas conformity values do not (Barnea, 2003; Barnea & Schwartz, 1998). Parent–child value similarity is high for tradition values, among both adolescents and young adults, but low for conformity values (Boehnke, 2001; Knafo & Schwartz, 2002). Finally, in samples from 61 nations, conformity values tend to be moderately important (typically 5th or 6th in the hierarchy of 10 values), whereas tradition values are significantly less important (typically 8th or 9th; Schwartz & Bardi, 2001). 6.3. Power and achievement Like tradition and conformity, power and achievement differ on characteristics that might lead to a central versus peripheral order. The peripheral location of power (model 5) is rejected by the analyses. It yields poorer fit indexes than the modified quasi-circumplex in both sets of samples. The simpler model that combines power and achievement into a single value (model 6) is also rejected. 6.4. Higher-order value types The most significant, applied modification of the value structure has been to use only the four higher-order value types—openness to change, conservation, self-enhancement, and self-transcendence types—as predictors. Are these particular higher-order types more justified than other possible groupings of the 10 values? Use of these particular types implies that the values that constitute each are substantively closer to one another than to the other values to which they are adjacent in the value circle (model 7). Schwartz (1992, 1994) attributed no substantive significance to the particular higher-order types. He grouped the 10 values only to describe the value structure more simply. He maintained that the values form a motivational continuum. 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 fit. This supports the assumption that the values do indeed form a motivational continuum. The continuum idea implies that the array of value items can be partitioned into as many or as few

252


categories as is optimal for a researcherÕs purposes. Higher-order types can be formed, but alternative combinations of adjacent values into higher-order types are as legitimate as the previously designated higher-order types. Universalism and self-direction, for example, can form a higher order ‘‘intellectual openness’’ type, and power and security an ‘‘uncertainty control’’ type. These higher-order types predict a classic liberal vs. conservative orientation in politics, whereas the previously specified higher-order types do not (Barnea, 2003). Benevolence, tradition, and conformity, for example, can form a ‘‘conventional prosocial’’ type that predicts the agreeableness trait of the Five Factor Model more strongly than either the previously specified self-transcendence or conservation higher-order types (data from Roccas et al., 2002). In sum, the support for a motivational continuum of values gives researchers the freedom and flexibility to choose higher-order combinations of adjacent values particularly suited to the topics they study. 6.5. Hedonism Hedonism values share with power and achievement values their emphasis on the interests of self. They share with stimulation and self-direction their emphasis on openness to change. The value theory does not specify which emphasis is stronger. Freeing the correlations of hedonism with its adjacent values (model 8) addressed this issue. A significant improvement in fit indexes in both sets of samples indicates that hedonism is not equally close to self-enhancement and openness. Although it correlates significantly with both, it is clearly closer to openness. This suggests that, for most people, hedonism values focus more on freely experiencing pleasure and less on pursuing pleasure competitively. 6.6. Universalism and security subtypes The motivational goal of universalism values is to understand, appreciate, and protect the welfare of all people and nature. The literature suggested that this broad value includes two separable subtypes, social concern and nature. Allowing correlated errors among the items in each subtype (model 9) significantly improves fit indexes 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) suggested that this value too might include separable 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 improves the fit indexes in both sample sets. We did not test the possibility of treating the subtypes of universalism and of security as distinct values, because such a model has not been proposed in the literature. For studying particularly relevant issues, however, separate indexes for the subtypes might be useful. For example, a nature index might be used for environmental issues and a personal security index for personal safety issues (e.g., installing burglar alarms and other home protection devices).


253

6.7. Reflections on the theory of value structure One crucial assumption underlies the theory of value structure: Actions that express any value have consequences that conflict or are compatible with the pursuit of 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 and achievement) to be inherently congruent. The total set of antagonistic and congruent relations among the 10 values gives rise to the modified quasi-circumplex value structure (Fig. 1). Conflict or antagonism implies negative correlations between values on opposite sides of the structure. Yet, the correlations between opposing values in the reference matrixes for the various models ranged only from +.08 to ).07. Does this contradict the assumption of opposition between conflicting values? As noted above, some people tend to rate all values relatively high or low, regardless of content. This biases observed intercorrelations among values upward. Standardizing each participantÕs responses eliminates this bias, though it introduces other problems.8 Freely estimated correlations among the latent factors for the 10 values, based on the standardized data, provide a rough assessment of the true degree of opposition. The correlations between pairs of values that the theory describes as antagonistic ranged from ).49 to ).81, averaging ).72. Thus, these data support the assumption of opposition between conflicting values that is central to the value theory. Future theorizing about the value structure might consider and test two issues that our analyses indirectly raised. First, do the 10 values differ in the breadth of their content? Schwartz (1992) suggested that universalism and security are conceptually broad, including subtypes that were confirmed here. Are other values especially narrow conceptually (e.g., hedonism and stimulation)? The method employed here could be used to model and test theory-based specifications of differences in the conceptual breadth of the values. For that purpose, however, it would be desirable to index each value with an equal number of items. The second issue concerns the central-peripheral distinction found with conformity and tradition values. Do values vary on this general dimension in addition to the dimension of motivational content? This dimension was interpreted as indicating variation in the closeness of a value to the self, its involvement in everyday interaction, and its specificity vs. abstractness. Centrality may also signify greater normative importance (Melech, 2001). The centrality of value items in the space correlates positively with their importance ratings. Systematic theorizing that considers the locations of value items on this potential dimension might enrich the value theory and point to hypotheses testable with the methods used here. In conclusion, it is worth noting the overlap between the inferences supported by different methods. The theory of the structure of values was refined by examining 8 We did not standardize in the main analyses for two reasons. First, this would impose the same variance on everyoneÕs responses. But people differ greatly in the degree to which they discriminate among their values. Hence standardizing would distort responses. Second, standardizing exacerbates problems with missing data.

254


subjective judgments of SSA plots in many samples. Such judgments can be misleading. In this case, however, the key judgments were supported by the statistical tests. This was so even though the theoretical model makes fine distinctions and the tests were performed on new data. Studies using multidimensional scaling methods led to the conclusion that the value structure is robust to respondentsÕ gender, age, or level of education (Schwartz, 1992, 1994; Struch, Schwartz, & van der Kloot, 2002). The fact that the CFAs confirm the value structure inferred from earlier visual inspections increases our confidence in this conclusion. The success of these subjective judgments demonstrates that visual inspection of spatial representations can reveal reliable, theoretically meaningful relations among variables. It is most successful when guided by a clear theory and when replicated in many samples.

Acknowledgments This research was supported by Grant No. 94-00063 from the United States–Israel Binational Science Foundation (BSF) and by a grant from the National Science Foundation (Israel Academy of Sciences) to the first author, and by Grant I-242-065.04/92 from the German-Israeli Foundation for Scientific Research and Development to both authors, and was facilitated by the Leon and Clara Sznajderman Chair of Psychology.

References Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov, & N. Csaki (Eds.), Second international symposium on information theory (pp. 267–281). Budapest: Akademiai Kiado. Barnea, M. (2003). Relations of personal values to political orientations across cultures. Doctoral Dissertation. The Hebrew University of Jerusalem, Israel. Barnea, M., & Schwartz, S. H. (1998). Values and voting. Political Psychology, 19, 17–40. Bilsky, W. (1998). Values and motives. Paper presented at the International Research Workshop ‘‘Values: Psychological Structure, Behavioral Outcomes, and Inter-Generational Transmission.’’ MaaleHachamisha, Israel. Boehnke, K. (2001). Parent-offspring value transmission in a societal context: Suggestions for a utopian research design with empirical underpinnings. Journal of Cross-Cultural Psychology, 32, 241–255. Borg, I., & Shye, S. (1993). Facet theory: The method and its application. Newbury Park, CA: Sage. Browne, M. W. (1992). Circumplex models for correlation matrices. Psychometrika, 57, 469–497. Fabrigar, L. R., Visser, P. S., & Browne, M. W. (1997). Conceptual and methodological issues in testing the circumplex structure of data in personality and social psychology. Personality and Social Psychology Review, 1, 184–203. Fontaine, J. R. J. (1999). Cultural bias in Schwartz’ value instrument: An exemplary study on cultural bias in social psychological and personality questionnaires. Unpublished doctoral dissertation, Katholieke Universiteit Leuven, Belgium. Guttman, L. (1954). A new approach to factor analysis: The radex. In P. F. Lazarsfeld (Ed.), Mathematical thinking in the social sciences (pp. 258–348). New York: Columbia University Press. Guttman, L. (1968). A general nonmetric technique for finding the smallest coordinate space for a configuration of points. Psychometrika, 33, 469–506. Hrubes, D., Ajzen, I., & Daigle, J. (2001). Predicting hunting intentions and behavior: An application of the theory of planned behavior. Leisure Sciences, 23, 165–178.


255

Hu, L.-t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. J€ oreskog, K., & S€ orbom, D. (1993). LISREL 8: A guide to the program and applications. Chicago: SPSS. Knafo, A., & Schwartz, S. H. (2002). Accounting for parent–child value congruence: perception, acceptance, and beyond. The Hebrew University of Jerusalem, Israel, submitted manuscript. Levy, S. (1985). Lawful roles of facets in social theories. In D. Canter (Ed.), The facet approach to social research (pp. 59–96). New York: Springer-Verlag. MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201–226. Melech, G. (2001). Value development in adolescence. Unpublished doctoral dissertation, The Hebrew University of Jerusalem, Israel. Plutchik, R., & Conte, H. R. (Eds.). (1997a). Circumplex models of personality and emotions. Washington, DC: American Psychological Association. Plutchik, R., & Conte, H. R. (1997b). Epilogue: The future of the circumplex. In R. Plutchik, & H. R. Conte (Eds.), Circumplex models of personality and emotions. Washington, DC: American Psychological Association. Roccas, S., Sagiv, L., Schwartz, S. H., & Knafo, A. (2002). The Big Five personality factors and personal values. Personality and Social Psychology Bulletin, 28, 789–801. Rohan, M. J. (2000). A rose by any name? The values construct. Personality and Social Psychology Review, 4, 255–277. Rokeach, M. (1973). The nature of human values. New York: Free Press. Ros, M., Schwartz, S. H., & Surkiss, S. (1999). Basic Individual values, work values, and the meaning of work. Applied Psychology: An International Review, 48, 49–71. Sagiv, L. (1994, July). Cross-cultural differences in the components and meaning of universalism values. Paper presented at the XII International Conference of the International Association for CrossCultural Psychology, Pamplona, Spain. Sakamoto, Y., Ishiguro, M., & Kitagawa, G. (1986). Akaike information criterion statistics. Dordrecht, Netherlands: Reidel. Schwartz, S. H. (1992). Universals in the content and structure of values: Theory and empirical tests in 20 countries. In M. Zanna (Ed.), Advances in experimental social psychology (Vol. 25, pp. 1–65). New York: Academic Press. Schwartz, S. H. (1994). Are there universal aspects in the content and structure of values? Journal of Social Issues, 50, 19–45. Schwartz, S. H. (1997). When are universalism values particularistic? Paper presented at the International Colloquium: Universalism vs. Particularism Toward the 21st Century, Prague, Czech Republic. Schwartz, S. H. (in press). Basic human values: Their content and structure across countries. In A. Tamayo & J. Porto (Eds.), Valores e trabalho [Values and work]. Brasilia: Editora Universidade de Brasilia. Schwartz, S. H., & Bardi, A. (2001). Value hierarchies across cultures: Taking a similarities perspective. Journal of Cross-Cultural Psychology., 32, 268–290. Schwartz, S. H., & Huismans, S. (1995). Value priorities and religiosity in four Western religions. Social Psychology Quarterly, 58, 88–107. Schwartz, S. H., & Sagiv, L. (1995). Identifying culture specifics in the content and structure of values. Journal of Cross-Cultural Psychology, 26, 92–116. Schwartz, S. H., Sagiv, L., & Boehnke, K. (2000). Worries and values. Journal of Personality, 68, 309–346. Spini, D., & Doise, W. (1998). Organizing principles of involvement in human rights and their social anchoring in value priorities. European Journal of Social Psychology, 28, 603–622. Struch, N., Schwartz, S. H., & van der Kloot, W. A. (2002). Meanings of basic values for women and men: A cross-cultural analysis. Personality and Social Psychology Bulletin, 28, 16–28. Tracey, T. J. G. (1997). RANDALL: A Microsoft FORTRAN program for the randomization test of hypothesized order relations. Educational and Psychological Measurement, 57, 164–168. Tracey, T. J. G. (2000). Analysis of circumplex models. In H. E. A. Tinsley, & S. D. Brown (Eds.), Handbook of applied multivariate statistics and mathematical modeling (pp. 641–664). New York: Academic Press.