What is cognitive complexity How does cognitive complexity influence peoples perceptions of others?

ABSTRACT - This study examines cognitive complexity as a personality trait evaluating its generality across three product classes. Findings indicate that individuals exhibit consistency in levels of complexity used to evaluate products irrespective of product class. Males and females appear to differ only slightly in the construct's generality. In addition, prior familiarity with a product class showed no relationship with the level of cognitive complexity utilized.

Citation:

Chin Tiong Tan and Ira J. Dolich (1980) ,"Cognitive Structure in Personality: an Investigation of Its Generality in Buying Behavior", in NA - Advances in Consumer Research Volume 07, eds. Jerry C. Olson, Ann Abor, MI : Association for Consumer Research, Pages: 547-551.

Advances in Consumer Research Volume 7, 1980     Pages 547-551

COGNITIVE STRUCTURE IN PERSONALITY: AN INVESTIGATION OF ITS GENERALITY IN BUYING BEHAVIOR

Chin Tiong Tan, University of Singapore

Ira J. Dolich, University of Nebraska-Lincoln

ABSTRACT -

This study examines cognitive complexity as a personality trait evaluating its generality across three product classes. Findings indicate that individuals exhibit consistency in levels of complexity used to evaluate products irrespective of product class. Males and females appear to differ only slightly in the construct's generality. In addition, prior familiarity with a product class showed no relationship with the level of cognitive complexity utilized.

INTRODUCTION

Many marketers continue to believe that personality theories can enrich our understanding of consumer behavior. To this end, a variety of approaches and techniques have been borrowed from Psychology to investigate how personality may be linked with a host of consumer's buying responses. Attempts to identify specific personality characteristics from personality inventories have generally yielded weak or nonexistent statistical relationships, but such efforts persist. Some new directions based on individual differences and the concept of cognitive complexity offer greater promise.

In psychology, treating a person's cognitive structure as a personality attribute is not new. However, such an approach is a relatively recent phenomena in marketing. This study utilizes the concept of cognitive complexity and investigates its generality as one aspect of cognition relevant to consumer behavior. Cognitive complexity has such a rich theoretical and empirical foundation in the psychological literature and holds great promise for improving explanation of buying behavior.

THEORETICAL BACKGROUND

Cognitive Structure of a person is viewed as a hypothetical link between stimulus information and an ensuing judgement. Kelly (1955), Bieri et al. (1966) and Schroder et al. (1967) have all indicated that individuals differ in their cognitive structural characteristics and such differences are in part reflected in the variation of responses among individuals. It is suggested that cognitive structure is a system of elements and relationships consisting of attributes, dimensions, constructs, and so forth, the specifics of which vary depending on how one chooses to label them. Cognitive characteristics frequently researched include:

(1) Dimension -- the number of salient or important dimensions (attributes) one uses in decision making (Schroder, 1971)

(2) Discrimination -- the articulation or refine-ness of the dimensions. (Bieri, 1966)

(3) Differentiation -- the extent to which the system of dimensions is used in an identical fashion. (Bieri, 1971)

(4) Integration -- the ways the dimensions are related and organized together. (Schroder, 1971)

The theoretical orientation of Kelly (1955) and Bieri et al. (1966) is adopted, and cognitive complexity is defined as the extent to which an individual uses Bieri's (1966) system of cognitive dimensions in a differentiated manner to construct cognitions of stimulus objects. A complex person should utilize a differentiated system of more numerous dimensions than does a less complex individual.

Empirical Studies

Cognitive complexity has been used as an explanatory construct for a wide range of behavior. Bieri (1955) found that persons who rate high on complexity are more variable in their perceptions of others and consequently manifest greater accuracy in predictions of other person's behaviors. Lundy and Berkowitz (1957) demonstrated that greater attitude change occurred from persons with low complexity scores. Other research findings have shown cognitive complexity to be related to information processing behaviors (Petronko and Perin, 1970, Tripodi and Bieri, 1964). Other psychological constructs found to be related to cognitive complexity include confidence of judgements (Tripodi and Bieri, 1964), probability preferences (Higgin, 1959), saliency of dimensions (Mueller, 1974), and stereotyping and prejudice (Koening and King, 1962).

Complexity of cognitions is a rather recent phenomenon in the marketing literature. Stiles (1974), studied integrative complexity in an industrial organization decision making setting and produced findings supportive of Schroder's with regard to task complexity, conceptual complexity, and levels of information processing (Schroder et al., 1967). Park and Sheth (1975), found dimensional complexity to be related to usage of judgmental rules. Wilson and Tan (1977) also found that dimensionally simple and complex subjects differed in several other personality traits such as need for certainty, need to achieve, self-confidence and risk style. Kasulis and Zaltman (1976), on the other hand, found mixed results between integrative complexity and message reception for two different products. Also, Menasco (1976) found a lack of difference between differentiatively simple and the complex subjects in consumer choice behaviors.

Cognitive Complexity as a Personality Style

Treating cognitive complexity as a generalized personality style is still an unresolved issue among psychologists, Those convinced of its generality treat it as a consistent personality trait which operates across different behavioral realms. However, researchers like Scott (1962, 1963) and Zajonc (1968) have argued otherwise. They consider cognitive complexity to be a somewhat less enduring state relevant to a particular domain which has become salient. They stress actual experience and familiarity with the stimuli of a domain as an explanation of the degree of complexity.

Research on the generality of cognitive complexity have centered on stimulus realms and sex differences with inconclusive results. Bieri and Blacker (1956) and Allard and Carlson (1963) found cognitive complexity to correlate across different stimulus domains, while Scott (1963) and Signell (1966) found it to be less general and more like a domain specific construct. Interestingly, psychologists (Hall, 1966, Bieri, 1966) have warned of the possibility of a sex difference, indicating that cognitive complexity may be a more consistent personality characteristic for males than for females. Hall (1966) had in fact demonstrated that males were consistent in cognitive functioning while females showed a more stimulus specific functioning.

An individual may alter his style of operation in different contexts. However, it seems reasonable to theorize that this same individual would be quite consistent in cognitive functioning within a single domain.

This research investigates the generality issue in the domain of consumer buying behavior. The major research objectives are to empirically test the following:

(1) Among a set of consumers, each person utilizes the same relative level of differentiative cognitive complexity for three product classes.

(2) Male and female consumers utilize the same relative level of differentiative cognitive complexity.

(3) Consumers utilize the same relative level of differentiative cognitive complexity regardless of prior familiarity with the product class.

RESEARCH METHODS

Product Selection

From a large list of products, pretests indicated three products (automobiles, rental apartments and toilet soaps) to be well known, to have multiple brands which were also generally known and to be of differential importance to the respondents.

Research Instruments

Kelly's Repertory grid method (Kelly 1955) was selected to measure cognitive complexity. The grid originated in a clinical setting and was used by patients first to elicit cognitive dimensions and then use the dimensions to rate stimulus objects. The grid is a matrix which captures a person's repertoire of self-generated dimensions used in the evaluation of objects. Various structural relationships and evaluation patterns are used to infer individual's cognitive properties.

Cognitive complexity is defined in terms of the number of dimensions used in a differentiated manner to evaluate objects. A person who provides few differences in ratings of brands on his repertoire of dimensions is classified as cognitively simple. Conversely, a cognitively complex person provides many differences in ratings of brands for many dimensions.

Cognitive complexity is computed from the Repertory grid using a matching of dimensions procedure. In brief, a cognitively simple person, when using the grid, would not be able to use the dimensions in a differentiated manner, and hence would evaluate the objects identically. When the ratings in the grid are compared with one another for exact agreement of ratings on objects to determine the number of identical ratings, a simple person will have a high number of matches. Every dimension in the grid is compared with all other dimensions. In such a manner, a person's entire repertoire of dimensions is examined to determine his relative complexity. A low score therefore denotes a more differentiated structure and cognitively more complex. A representative grid is presented in Figure 1 and scoring in Figure 2.

A person's familiarity with a product class is considered to be a function of several factors such as (1) awareness of different brands in the product class; (2) knowledge about the brands; and (3) actual usage of brands of the product. Therefore, three instruments were used to measure (1) proportion of brands heard or aware of; (2) proportion of brands known about; and (3) proportion of brands previously used or purchased. A pre-selected list of brands was provided for each product class and product familiarity was established in terms of the percentage of brands checked.

Data Collection

Respondents were upperclass undergraduate students attending a large Eastern university and each was paid a nominal amount for participation. Ninety-eight persons with an equal number of males and females participated.

Subjects were arranged in small group settings and administered the questionnaires. Detailed instructions were presented verbally and in writing with special care taken to explain the Repertory grid routines. A repeated measure design was used for the study (each person evaluated all three product classes). Product class presentation in the questionnaire booklets was randomly distributed to prevent order effects. Three 10 X 10 Repertory grids were included in each booklet.

From a list of twenty-two brands, each person was instructed to pick the ten which were most familiar and to write these names at the column headings of a Repertory grid. Starting from row one of the grid to row ten, the individual was instructed to list ten different dimensions he/she commonly used to evaluate brands of that product. Each dimension was then to be used like a six-point Likert type bipolar scale with a range of +3, +2, +1, -1, -2, -3 to rate all ten brands on the grid. To assist in the generation of dimensions, three randomly pre-selected cells were circulated on each row of the grid. The person was told to look at the three brands and to consider a way, dimension, or characteristic for which two of them were similar and yet different from the third. Each dimension generated was written down by the side of the row and the procedure continued until ten bipolar dimensions were elicited (See Kelly, 1955, and Bieri, et al., 1966, for details on the Repertory grid procedures). Pretesting had ensured that nearly all respondents were able to select ten names and ten dimensions for each grid. No difficulties were found during the final data collection process. The sequence of tasks was identical for each product class.

ANALYSES AND FINDINGS

Pearson product moment correlations were used to evaluate the strength of relationships across the three product classes (Bieri and Blacker, 1956, Hall, 1966). Intercorrelations of the subjects' cognitive complexity scores for all pairs of the product classes are presented in Table 1. Results of the analyses for each sex group were also presented in the same table.

TABLE 1

INTER-CORRELATIONS OF SUBJECTS' COGNITIVE COMPLEXITY FOR ALL PAIRS OF PRODUCT CLASSES

FIGURE 1

A COMPLETED REP GRID FOR AUTOMOBILES

FIGURE 2

COMPUTATION OF COGNITIVE COMPLEXITY SCORE FROM THE COMPLETED GRID

Results from Table I show that cognitive complexity of the subjects is positively correlated for each pair of product classes. Although the correlation coefficients are not exceptionally high, they are typical for personality research, and they are statistically significant.

The results indicate that a person who is cognitively complex in his evaluation of one product class tends to be relatively complex in his evaluation of the other product classes as well. When each sex group was examined separately, correlations for the male sample improved slightly, and those for the female sample were somewhat weaker. Again, the results indicate that cognitive complexity appears to be fairly consistent for each group. However, it is essential to point out that generality of the construct appears to be somewhat weaker for the female subjects.

The three measures of awareness, knowledge, and usage were used as independent variables in a multiple regression analysis with cognitive complexity as the dependent variable to evaluate the relationship between cognitive complexity and the subjects familiarity with product class. These results are presented in Table 2. Observe that the F-values of the analyses for all three product classes are not significant. The R-square statistics are also provided in Table 2 which also indicate the lack of relationships between complexity and familiarity with product class.

TABLE 2

REGRESSION ANALYSES FOR THREE PRODUCT CLASSES: COGNITIVE COMPLEXITY, AWARENESS, KNOWLEDGE AND USE AS THREE MEASURES OF FAMILIARITY

The findings of this research although exploratory in nature, can be viewed as additional support for consideration of cognitive complexity as a personality trait. A person's prior familiarity with a product class is not particularly useful toward explanation of one's level of complexity in cognitive functioning. The way a person's cognitive structure operates appears to be more a function of unique cognitive developments and/ or styles than familiarity with these consumer oriented stimuli. Cognitive complexity as a consistent trait of one's cognitive functioning in a marketing context seems to be a realistic hypothesis.

DISCUSSION AND CONCLUSIONS

The finding of a consistent mode of cognitive functioning across three product classes suggests that cognitive complexity may be viewed as a person's personality characteristic and therefore capable of mediating various buying behaviors. Because of the nature of the population and products examined the results should only be interpreted in that consumer behavior realm as there presently is insufficient evidence to indicate generality of the construct in other domains. For example, it is not known whether a person classified as complex in this consumer behavior context would also be complex in his or her social encounters.

Psychologists (Bieri, 1966, Hall, 1966) warnings of possible differences between males and females in their general cognitive and personality functioning was not resolved in this study. Both sexes exhibited fairly consistent modes of complexity, however, the male subjects exhibited slightly stronger relationships.

A counter argument for the generality hypothesis was Zajonc's (1968) domain specific proposition. He and other advocates of this proposition are less convinced of the consistency of cognitive complexity and claim that familiarity, experience, and knowledge of a realm is necessary to achieve high levels of complexity in evaluation. This study found the relationship between cognitive complexity and familiarity with product class to be nonexistent. These students' previous knowledge and experience with the products appeared to have little to do with the level of complexity used to evaluate them.

The application of the construct in marketing can be extensive. Based on the research already accomplished by psychologists, it can be anticipated that the construct has explanatory or predictive power for many of the following marketing related behaviors:

(1) processing of marketing information in terms of both the amount and of types of information

(2) attitude change with respect to direction and magnitude

(3) reception of media messages

(4) prejudicial or stereotype perception of brands, products and stores

(5) decision making styles and strategies

(6) a basis for market segmentation

Since the construct is relatively new in marketing, it is obvious that much more research is needed before it can be of immediate practical value. One obvious opportunity is in the area of information processing and the use of information in decision-making.

REFERENCES

Allard, M. and Carlson, E. R. (1963), "The Generality of Cognitive Complexity," Journal of Social Psychology, 59.

Allport, G. W. (1937), Personality: A Psychological Interpretation. New York: Henry Holt and Co.

Bannister, D. and Mair, J. M. (1968), The Evaluation of Personal Constructs, London: Academic Press.

Belk, R. (1975), "Situational Variables and Consumer Behavior," Journal of Consumer Research, December.

Bieri, J. (1955), "Cognitive Complexity-Simplicity and Predictive Behavior," Journal of Abnormal and Social Psychology, 51

Bieri, J. (1971), "Cognitive Structures in Personality," in H. M. Schroder and P. Suedfeld, (ed.) Personality Theory and Information Processing, New York: Ronald Press.

Bieri, J. and Blaker, E. (1956), "The Generality of Cognitive Complexity in the Perception of People and Inkblots," Journal of Abnormal and Social Psychology, 52.

Caracena, P. F. and King, G. E. (1962), "Generality of Individual Differences in Complexity," Journal of Clinical Psychology, 18.

Hall, M. F. (1966), The Generality of Cognitive Complexity-Simplicity. An unpublished Ph.D. Dissertation, Department of Psychology, The Vanderbilt University.

Higgins, J. C. (1959), "Cognitive Complexity and Probability Preference," unpublished manuscript, Department of Psychology, University of Chicago.

Kasulis, J. and Zaltman, G. (1976), "Message Reception and Cognitive Complexity," in Perreault, W. (ed.) Advances in Consumer Research, Vol. IV.

Kelly, G. A. (1955), Psychology of Personal Constructs, New York: Norton Press.

Koening, F. W. and King, M. (1962), "Cognitive Simplicity and Prejudice," Social Forces, 40, March.

Koening, F. W. and King, M. (1964), "Cognitive Simplicity and Out-Group Stereotyping," Social Forces.

Lundy, R. and Berkowitz, L. (1957), "Cognitive Complexity and Assimilative Projection in Attitude Change," Journal of Abnormal and Social Psychology, 55.

Meansco, M. (1976), "A Further Exploration of the Moderating Effects of Cognitive Complexity Upon Consumer Choice Behavior." Working Paper on the Bureau of Business and Economic Research, University of Iowa, July.

Mueller, Walter W. (1974), "Cognitive Complexity and Salience of Dimensions in Person Perception," Australian Journal of Psychology.

Park, W. and Sheth, J. (1975), "Impact of Prior Familiarity and Cognitive Complexity on Information Processing Rules," Communication Research, Vol. 2, no. 3, July.

Park, W. (1976), "The Effect of Individual and Situation Related Factors on Consumer Selection of Judgmental Models," Journal of Marketing Research, May.

Petronko, M. and Perin, T. (1970), "A Consideration of Cognitive Complexity and Primary Recency Effects in Impression Formation," Journal of Personality and Social Psychology, 15.

Schroder, H. M. (1971), "Conceptual Complexity and Personality Organization," in Schroder and Suedfeld, eds., Personality Theory and Information Processing, New York: Ronald Press.

Schroder, H. and Suedfeld P. (1971), Personality Theory and Information Processing, New York: Ronald Press.

Schroder, H., Driver, M., and Streufert, S. (1967), Human Information Processing, New York: Holt, Rinehart and Winston.

Scott, W. A. (1962), "Cognitive Complexity and Cognitive Flexibility," Sociometry, 25.

Scott, W. A. (1963), "Cognitive Complexity and Balance," Sociometry, 26.

Sechrest, L. B. and Jackson, D. N. (1961), "Social Intelligence and Accuracy of Interpersonal Predictions," Journal of Personality, 29.

Signell, K. A. (1966), "Cognitive Complexity in Person Perception and in National Perception: A Developmental Approach," Journal of Personality, 34.

Stiles, G. (1974), "Determinants of Industrial Buyer's Level of Information Processing: Organizations, Situations and Individual Differences," in D. Hughes and M. Ray (eds.) Buyer/Consumer Information Processing, Chapel Hill, North Carolina: University of North Carolina Press.

Tripodi, T. and Bieri, J. (1966), "Cognitive Complexity, Perceived Conflict, and Certainty," Journal of Personality, 34.

Tripodi, T. and Bieri, J. (1963), "Information Transmission in Clinical Judgements as a Function of Stimulus Dimensionality and Cognitive Complexity," Journal of Personality, 31.

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Wilson, D. T. and Tan, C. T. (1977), "Dimensional Complexity of Cognitive Structure: A Personality Trait in Decision Making," in Stolen, J. D. and Conway, J. J. eds. Proceedings of the American Institute of Decision Sciences.

Zajonc, R. B. (1968), "Cognitive Theories in Social Psychology," in The Handbook of Social Psychology, Vol. I, Reading, Mass: Addison-Wesley.

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Authors

Chin Tiong Tan, University of Singapore
Ira J. Dolich, University of Nebraska-Lincoln

Volume

NA - Advances in Consumer Research Volume 07 | 1980

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