Measuring the Meaning of Consumption Objects: an Empirical Investigation

Robert E. Kleine, III, University of Cincinnati
Jerome B. Kernan, University of Cincinnati
ABSTRACT - Since Holbrook and Hirschman's (1982) elucidation of the experiential perspective, the "meaning" of consumption objects has been accorded renewed prominence in consumer research. Surprisingly few studies explicate meaning as a scientific construct, however. Using ordinary consumption objects, this paper proposes a definition of meaning and a measure MOCOM -- derived from that definition. An initial test of MOCOM (Measure Of Consumption Object Meaning) suggests that it elicits comparatively rich qualitative data and that it also has desirable psychometric properties.
[ to cite ]:
Robert E. Kleine and Jerome B. Kernan (1988) ,"Measuring the Meaning of Consumption Objects: an Empirical Investigation", in NA - Advances in Consumer Research Volume 15, eds. Micheal J. Houston, Provo, UT : Association for Consumer Research, Pages: 498-504.

Advances in Consumer Research Volume 15, 1988      Pages 498-504

MEASURING THE MEANING OF CONSUMPTION OBJECTS: AN EMPIRICAL INVESTIGATION

Robert E. Kleine, III, University of Cincinnati

Jerome B. Kernan, University of Cincinnati

ABSTRACT -

Since Holbrook and Hirschman's (1982) elucidation of the experiential perspective, the "meaning" of consumption objects has been accorded renewed prominence in consumer research. Surprisingly few studies explicate meaning as a scientific construct, however. Using ordinary consumption objects, this paper proposes a definition of meaning and a measure MOCOM -- derived from that definition. An initial test of MOCOM (Measure Of Consumption Object Meaning) suggests that it elicits comparatively rich qualitative data and that it also has desirable psychometric properties.

INTRODUCTION

The proposition that consumers respond according to the meanings hey ascribe to marketplace stimuli was, until Holbrook and Hirschman's (1982) elucidation of the experiential perspective, accepted virtually without question. As a consequence, only a few consumer researchers (e.g., Csikszentimihali and Rochberg-Halton 1981; Douglas and Isherwood 1979; Friedman 1986; Hirschman 1980; Kernan and Sommers 1967; Levy 1959; 1981; McCracken 1986; Mick 1986) have even discussed, much less studied meaning. This suggests that (1) there is a gap in appropriate theory and methodology and/or (2) that the influence of meaning is thought to be so obvious that little is to be gained from its study.

To the extent that we accept the notion that objects have subjective meanings, we must simultaneously reject the account that meaning's influence on consumers is too obvious to study. As though by default, then, it appears that consumer researchers have not explicated meaning as a scientific construct because they have lacKed the requisite theory and methodology. Before meaning can assume its place 'at the nucleus of consumer behavior" (Mick 1986), it must be formalized as a construct that reflects the key characteristics of consumption phenomena, i.e., one that incorporates people's subjective reactions to consumption experiences, those stimulated by objects and/or behaviors. This requires that we overcome the limitations of past efforts, which typically have yielded either rich qualitative content (e.g., anthropological and psychoanalytic approaches) or well-behaved quantitative representations (e.g., semantic differentiation) and develop a procedure that simultaneously provides both these properties.

This paper is an initial attempt to formalize meaning as a scientific construct. We propose a definition of consumption-object meaning and a measure based on that definition. We also offer the results of an empirical study as initial evidence of our conceptualization s validity.

TOWARD A DEFINITION OF OBJECT MEANING

Kleine and Kernan (1987) have outlined the multidisciplinary traditions through which the meaning construct has been studied. Although they identified two dimensions -- contextual sensitivity of meaning and level of analysis -- that distinguish the research traditions reviewed, they fail to specify which research tradition (or combination) should serve as the foundation for developing the meaning construct in a consumption context. Ogden and Richards' (1953) "triangle of reference", however, explicates a key assumption common to most researchers, regardless of tradition: the relation between a referent, the perceived stimulus (e.g., an automobile), and a symbol, the result of the referent's interpretation (e.g., "that's a Porsche 924S"), is an indirect one. Referent and symbol are related through thought (or reference3. Meaning is not inherent in the referent; it is ascribed to it by the interpreter.

Yet Ogden and Richards' triangle raises two questions important in the development of a definition of meaning. First, who is doing the thought (or reference); i.e., what is the level of analysis? Kleine and Kernan suggest that most researchers determine this by their trainingCthose of a psychological and/or social-psychological tradition tend to prefer a micro (i.e., individual) level of analysis, while those trained in the anthropological tradition prefer a macro (e.g., cultural system) level of analysis. Although this paper adopts the individual level of analysis, it recognizes the embeddedness of the individual within a social world. The second question raised by the triangle is what type of referent does the researcher wish to examine; i.e., what is the unit of analysis? Although objects and behaviors are paramount in the experiential perspective, the present research emphasizes the consumption object as the analytic unit, for reasons of tractability. This combination of individual levels of analysis and consumption-object stimuli influences our definition of meaning and, consequently, the type of measure proposed. However, it presents us with an opportunity to fill an important gap in the literature. Most meaning research uses words as the focal stimuli. The meaning individuals ascribe to objects is perforce an under-researched phenomenon.

Our definition of object meaning incorporates three essential characteristics: (1) polysemy; (2) contextual sensitivity; and (3) consensus. Polysemy refers to the fact that a given object can mean many things -- baking soda, for example, can be a refrigerator deodorizer, a dentifrice or an antacid. Contextual sensitivity suggests that the meaning of a turkey on a Thanksgiving Day dinner table probably differs from that of a turkey placed on a dinner table during mid-May. And consensus refers to the fact that, even though each person holds idiosyncratic information about an object, some minimal amount of object information (meaning) must be shared by people in order for them to communicate about the object. These characteristics, plus the forgoing discussion, locate our conceptualization of meaning in what Kleine and Kernan call a social-psychological research tradition. Apropos of that tradition is Szalay and Deese's (1978) characterization of meaning as an individual's subjective reaction to a stimulus, composed of certain salient elements. Although they propose no a priori structure regarding these elements (preferring instead to rely on post hoc "semantic clustering"), Kernan and Sommers (1967) advance two orthogonal dimensions of an object's meaning -- its attributes and performance potential. Attribute refers to the physical dimension of meaning, to one's perception of an object's palpable characteristics (baking soda is white and powdery). Performance refers to the functional dimension of meaning, to one's perception of the object's action potential or what the object can do or be used for (a dentifrice or an antacid, in the case of baking soda). The Szalay and Deese and Kernan and Sommers definitions of meaning are complementary. Both define meaning as an aggregate perception. Szalay and Deese suggest that this perception consists of a constellation of "reactions" that vary in salience, while Kernan and Sommers introduce the possibility that these "reactions" are manifestations of attribute and performance. Thus we propose that the meaning to an individual of a consumption object is that person's aggregate perception of the object. One's perception, in turn, consists of two dimensions: an interpretation of the object's physical attributes and of its action potential. These perceptual dimensions vary in salience among objects and individuals and according to the context in which the object is perceived.

A MEASURE OF CONSUMPTION OBJECT MEANING

Based on the preceding discussion, we can identify several properties a measure of consumption-object meaning should possess. It should: (1) adduce the attribute and performance dimensions ascribed to the object; (2) determine the salience of those dimensions; and (3) distinguish meaning that is shared from that which is idiosyncratic. Additionally, the measure should be amenable to large samples.

The method of continued associations (Szalay and Deese 1978) provides a foundation from which to build such a measure. The method requires subjects to produce all the one-word stimulus-bound responses they can muster within a 60-second interval. These responses are the salient elements of the object's meaning. Since a subject's first responses are assumed to be more dominant (i.e., salient), each response is assigned a dominance score (DS) that is a measure of its relative salience. In our adaptation of the procedure -- which we designate MOCOM (for Measure Of Consumption Object Meaning) -- subjects' responses are then categorized as attribute or performance, the two proposed dimensions of meaning. Three totals, useful for both inter- and intra-subject and/or object analysis, can be computed: a total DS for the attribute dimension, a total DS for the performance dimension, and a total DS for all meaning elements. Thus, the procedure can be used to assess the idiosyncratic meaning perceived by an individual or that shared by a group of individuals.

AN EMPIRICAL TEST

A study was conducted to assess the proposed MOCOM and the conceptualization upon which it rests. We admonish the reader that, in this initial test, our focus was not on the actual meanings subjects ascribed to the focal objects (although qualitative results are available to adduce these). Following scaling convention, our quantitative results portray meaning in the form of inter-object similarities, rather than in terms of absolute object perceptions.

Hypotheses

Two measures that purport to measure the same construct should be highly correlated. To explore this psychometric property of MOCOM, the semantic differential (Osgood, Suci, and Tannenbaum 1957), a measure of meaning with which most consumer researchers are familiar, was chosen as a criterion measure of meaning. Thus:

H1: MOCOM and the semantic differential will be significantly correlated.

Kernan and Sommers (1967) propose that one's attitude toward an object ("value" in their terminology) is a function of an object's perceived meaningCi.e., of attribute and performance. Thus, the meaning construct should be discriminable from the attitude construct. Szalay and Bryson (1974) present an analysis in which this distinction is supported. Since Osgood et al. make no assertions regarding the functional relationships among the three dimensions of the semantic differential, the second hypothesis is advanced:

H2: The correlation between MOCOM and a reduced form of the semantic differential, composed of the activity and potency dimensions, will be significantly greater than the correlation between MOCOM and the full, three-dimensional, semantic differential

Our definition of meaning postulates two dimensions of perception that underlie meaning: attribute and performance. Hence a goal of this study is to explore the psychological reality of these dimensions. If consumers' perceptions of consumption objects are characterized by these two dimensions it follows that the responses produced by subjects on the continued-association task should be characterizable as either attribute or performance. Thus:

H3: The meaning dimensions revealed via the method of continued associations can be reliably characterized as either attribute or performance.

Common sense indicates that any measure of meaning should reveal every object to have a unique meaning and some objects to be more similar in meaning than others. It follows that consumption objects determined a priori to be similar should be indicated by the meaning measure to be more similar than objects deemed dissimilar, a priori. Two natural categories of consumption objects were identified -- food and clothing -- to assess whether the proposed MOCOM possesses this characteristic. In order to test the efficacy of our measurement procedure (and to avoid any affect-laden contamination that might result from subjects' familiarity with branded stimuli), three generic objects were selected to represent each category. A black fedora, a white cotton pullover sweater with a button-up v-neck, and a "dirty buck" shoe were selected to represent the clothing category. The food category was represented by one-quarter pound of uncooked #19 linguine, a ripe banana, and a slice of whole wheat bread. Thus, Hypothesis 4:

H4: Objects within a natural category should be perceived as more similar in meaning to other objects within that category than to objects from other categories (i.e., a given clothing item should be more similar in meaning to other clothing items than it is to any food items).

TABLE 1

MEAN FACTOR SCORES FOR EACH OBJECT ON EACH SEMANTIC DIFFERENTIAL DIMENSION STIMULUS OBJECT

The notion of inter-object meaning similarity raises the interesting question of which dimension, attribute or performance, is meaning similarity largely a function? We make no prediction regarding this intriguing question.

Procedure

Ninety-six students at a Midwestern university were subjects for- this study. They were processed in four groups.

Each subject received a packet containing: (1) instructions for the continued-association task; (2) seven continued-association response forms; (3) instructions for the semantic differential task; and (4) seven semantic- differential response forms. The three dimensions of the semantic differential were operationalized with 34 bi-polar adjective scales selected because of their frequent use in studies reported by Osgood et al. (1957).

Subjects first responded to a trial object, an 18" inflatable lobster, to familiarize them with the continued-association task. They were then exposed to the six experimental objects, one at a time, in one of two random orders, for 60 seconds. Subjects recorded their associations during this time. Stimuli were referred to only by an identifying number. Subjects were then instructed how to use the semantic differential. They then responded to the warm-up object and then to the six experimental objects. No time constraint was imposed on this task. A new stimulus object was presented when all subjects were ready.

Data Preparation

Data from the 34 semantic-differential scales were reverse coded where necessary and a confirmatory factor analysis (SAS procedure) was performed, with a three-factor solution specified. Both eigenvalues and a scree test clearly indicated the appropriateness of the three-factor solution. Following Osgood et al., the five scales with the highest loading on each of the three semantic-differential factors were retained for subsequent data analyses (see Table 1).

Because an object's meaning is its location within the three-dimensional semantic space, the mean factor scores for each stimulus object on each dimension of the semantic differential were computed (Table 1). Inter-object meaning similarity is also of interest so Dis, or inter-object Euclidian distances within the three-dimensional space, were calculated from the mean factor scores (Table 2). Note that smaller values of Di indicate greater inter-object meaning similarity.

TABLE 2

INTER-OBJECT DISTANCES WITHIN THE THREE-DIMENSIONAL SEMANTIC SPACE

Data produced by the continued-association task require extensive preparation prior to analysis. The desired result is a list, for each stimulus object, of associations, and their dominance scores. These scores were assigned according to Szalay and Deese's recommendation: 6 to the first response produced by a subject, 5 to the second response, 4 to the third response, 3 to the fourth through seventh responses, 2 to the eighth and ninth responses, and 1 to each subsequent response. Dominance scores for common responses were summed across subjects. Affinity refers to the degree to which persons see relations of any sort between any two stimuli and is operationalized as the amount of overlap between two response lists (i.e., the number of meaning elements two objects have in common). Affinity is thus analogous to meaning similarity and is assessed by means of an index. Calculation of the inter-object affinity index involves summing dominance scores across the overlapping elements and across stimuli. This total is then divided by the sum of the total dominance scores of the objects being compared. The resulting index value is the proportion of the combined total dominance scores accounted for by the affinial relations. The index has a theoretic range of zero to one and increases in value as inter-object affinity increases. The affinity index for each pair of stimulus consumption objects is given in Table 3.

TABLE 3

INTER-OBJECT AFFINITY INDEX VALUES

Results

With Hypothesis 1 we predicted that the correlation between MOCOM and the semantic differential would be significantly greater than zero. Because the affinity index (representing MOCOM) increases and Di (representing the semantic differential) decreases as inter-object meaning similarity increases, a negative correlation is expected. To test this hypothesis, the off-diagonal elements of the affinity-index matrix (Table 3) were correlated with the corresponding elements in the matrix of inter-object Dis in the three-dimensional semantic space (Table 2). Since the obtained Pearson correlation of -0.52 is significantly greater than zero (p < .05), the data are consistent with Hypothesis 1: There is some evidence that MOCOM has convergent validity.

With Hypothesis 2 we advance a stronger assertion than in Hypothesis 1, namely that the correlation between MOCOM and a two-dimensional version of the semantic differential, composed of the activity and potency dimensions, will be significantly greater than the correlation explored in Hypothesis 1. (This follows from the fact that MOCOM associations -which are categorized into attribute or performance (or "other") dimensions -- do not measure affect directly.) To test this hypothesis the off-diagonal elements of the matrix of inter-object Dis in the two-dimensional semantic space (Table 4) were correlated with the off-diagonal elements of the matrix of inter-object affinity indices (Table 3). Inter-measure correlations (all significant at p = .05) are summarized in Table 5. The difference between the two theoretically important correlations, -0.52 and -0.73, is statistically significant (Fisher's z = 2.41, p < .01)Ca result consistent with Kernan and Sommers' assertion (and our H2) that the meaning construct is discernible from the attitude construct. This theoretic consistency increases our confidence that MOCOM is indeed a measure of meaning, hence subsequent analyses employ the reduced, two-dimensional space.

TABLE 4

INTER-OBJECT DISTANCES WITHIN THE REDUCED (2-D) SEMANTIC SPACE

TABLE 5

CORRELATIONS BETWEEN MEANING MEASURES

Hypothesis 3 seeks to assess the psychological reality of attribute and performance as dimensions of meaning. To test H3, standard measure-development procedures were followed: operational definitions of attribute and performance were developed (see Table 6) and two trained judges applied the coding categories to subjects' responses to each of the six focal objects. Inter-coder agreement averaged 85%, a rate acceptably high for an exploratory study. Unresolved disputes, refereed by one of the authors, were categorized as "other." The distribution of attribute and performance, expressed as a percent of the total dominance score for each stimulus object, is presented in Figure 1. Overall, the attribute and performance dimensions capture 87% of the total dominance score and 96% of the responses, a result that strongly supports H3 -- a consumption object's psychological meaning is recoverable with its attribute and performance dimensions.

Hypothesis 4 contends that MOCOM should recover the two natural categories of stimulus objects; that objects within a category will be judged more similar to other items within that category than to items in the other category. For example, a shoe should be indicated as more similar to other clothing items than to any food item.

Using the reduced-space semantic differential measures, Figure 2 plots the locations of the stimuli within the semantic space. (Identical inter-object similarity can be gleaned from the distance measures in Table 4.) Figure 2 reveals the food category to be recovered nicely -- its three items are clustered. In contrast, the clothing category was not completely recovered -- the sweater and the shoe are quite similar but the hat has a very dissimilar meaning. A reading of subjects' association data suggests the explanation that, compared to the shoe and sweater, the hat is an extremely expressive consumption object. Accordingly, a two-group (food and clothing) MANOVA was performed (SAS's GLM procedure). The significant MANOVA (F(2 577) = 102.59, p < .01) indicates that the group mean vectors on activity and potency factor scores differ. Univariate ANOVAs reveal a significant effect for potency (F(1, 578) = 204.08, p < .01) but not for activity (F(1, 578) = .50, p > .01) -- within category variance exceeded between category variance on this latter dimension, reinforcing our previous observation that the clothing category was not recovered well by the semantic differential. Thus, a three-group MANOVA (splitting out the hat) was performed and, as expected, significant univariate effects were observed on both the activity (F(2, m) = 60.23, p < .01) and potency (F(2, 573) = 113.53, p < .01) dimensions. Thus, the semantic differential did a good job of recovering our food category but it did not completely recover our clothing category.

TABLE 6

OPERATIONAL DEFINITIONS OF ATTRIBUTE AND PERFORMANCE

FIGURE 1

PERCENT OF TOTAL DOMINANCE SCORE ACCOUNTED FOR BY THE MEANING DIMENSIONS

FIGURE 2

MEAN FACTOR SCORES

ACTIVITY AND POTENCY DIMENSIONS

To assess the efficacy of MOCOM relative to Hypothesis 4, we redirect the reader's attention to Table 3, the matrix of inter-object affinity indices. Although casual observation of that matrix reveals the clothing items to be similar, the food items to be similar, and little meaning similarity between objects in different categories, a statistical test is necessary to establish the existence of our natural categories. Accordingly, a Mann-Whitney U test was used, with the null hypothesis that affinity indices of pairs of objects within a category are from the same distribution as affinity indices of pairs of objects from different categories. Comparing either the three within-clothing cells to the nine between-category cells or the three within-food cells to the nine between-category cells, the null hypothesis must be rejected (U = 0, p < .01). This result, supportive of Hypothesis 4, indicates that MOCOM recovered the two natural categories nicely. Even the hat is indicated to be more similar to other clothing items than it is to any of the food items. In this respect, our proposed measure has out-performed the semantic differential.

Yet the nature of inter-object similarity remains to be established. The semantic differential reveals, for example, that the sweater and the shoe (the two objects most similar in meaning) are moderately high on activity and low on potency. We could extend this investigation by examining the respective factor scores for these objects, but this is a cumbersome procedure that guarantees little by way of interpretable information. In contrast, we can use the lists of common responses from which MOCOM's affinity indices are derived and discover a richness the semantic differential cannot approach. The sweater and the shoe, for example, share these elements: casual, clean, comfortable, conservative, fall, L. L. Bean, man's, nice, plain, preppy, soft, stylish, ugly, warm, and worn. Thus, these two objects share warmth, conservativeness, and preppiness, and are worn by men in the autumn. Whereas the semantic differential requires researcher specification of scales, the MOCOM "provides" the researcher with scales -- that are texture-laden with qualitative interpretability in the bargain.

But MOCOM does not restrict us to qualitative analysis. By separating subjects' associations into their attribute? performance, and "other" dimensions we can compute affinial relations (shared dimensions) among the objects. Table 7, which displays such relations, reveals that meaning similarity within a category is dominated by performance while such similarity as exists among objects from different categories is largely a function of attribute. In other words, "natural" categories seem to consist of objects that do the same thing.

A series of x2 tests supports this interpretation. The distribution of attribute and performance does not differ across the three objects representing each natural category (food category: X2(2) = 6.75, p > .05; clothing category: X2(2)= 2.34, p > .05) nor do the distributions of attribute and performance differ between the two natural categories (x2(l)= 1.70, p > .05). This indicates that the six cells representing the two categories can be pooled. A x2 test to explore homogeneity of the distributions of attribute and performance in the nine between-category cells could not be performed because all cells have expected values less than five. Thus, those nine cells were collapsed into a single between-category group. The dramatically significant, but hardly surprising difference (X2(1) = 262.99, p < .01) between the distributions of attribute and performance in the pooled between-category cells and the pooled within-category cells is illustrated in Figure 3.

TABLE 7

DECOMPOSITION OF INTER-OBJECT AFFINIAL RELATIONS INTO THEIR DIMENSIONS ATTRIBUTE, PERFORMANCE, AND OTHER

Thus, Hypothesis 4 seems supported. MOCOM not only recovered our a priori defined categories, it did a better job of reproducing them than did the semantic differential. We also explored the insight that each measure can yield into the nature of inter-object meaning similarity. In this regard we found MOCOM to provide richer information than the semantic differential. Exploring the inter-object similarities revealed by our proposed measure further, we assert tentatively that similarities between objects within a natural category lie along the performance dimension of meaning. In contrast, meaning similarity, if any, between objects from different categories derives from the attribute dimension of meaningCwhat physical attributes the objects appear to share.

DISCUSSION

Although this exploratory effort encourages us that our definition and measure of consumption-object meaning is right-headed, we recognize that much remains to be done. Indeed, the reader might muse that we have raised more questions than we have answered. And we would agree. For example, we have not tested branded products -- some of which are extraordinarily rich in symbolic meaningCor services, and we have not addressed the complex issue of how object meaning (however generated) relates to affectCand other reactions deeper in the consumer's response hierarchy. And we have not dealt with the tenuous relationship between object meaning and that which attends consumption experiences (particularly those accompanied by aesthetic responses) where no physical entity can be regarded as focal. But theseCand many other critical issues -- must await more mundane developmental work.

FIGURE 3

BREAKDOWN OF AFFINAL RELATIONS INTO PERFORMANCE, ATTRIBUTE, AND OTHER

Our current program of research is focusing on two problems. First, experiments are being conducted to explicate the effect of contextual variation on an object's meaning. We believe this issue relates to both meaning creation and meaning change. Second (for all the obvious reasons), we are examining the process through which information is transformed into meaning. If we are lucky and learn something about these two problems, we shall feel confident (or foolhardy) enough to press on to the more fascinating issues.

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