Thinking And/Or Feeling: an Examination of Interaction Between Processing Styles

Jane Z. Sojka, Ohio University
Joan L. Giese, Washington State University
ABSTRACT - The purpose of this research is to examine the relationship between affective and cognitive processing styles. Using a combination of situation-invariant affect and cognition measures, evidence suggests that individuals differ in their propensity to rely on affective, cognitive, or both systems to process information. Rather than viewing affect and cognition as a dichotomy on a continuum, an independent but interactive relationship between affect and cognition is conceptualized and supported.
[ to cite ]:
Jane Z. Sojka and Joan L. Giese (1997) ,"Thinking And/Or Feeling: an Examination of Interaction Between Processing Styles", in NA - Advances in Consumer Research Volume 24, eds. Merrie Brucks and Deborah J. MacInnis, Provo, UT : Association for Consumer Research, Pages: 438-442.

Advances in Consumer Research Volume 24, 1997      Pages 438-442

THINKING AND/OR FEELING: AN EXAMINATION OF INTERACTION BETWEEN PROCESSING STYLES

Jane Z. Sojka, Ohio University

Joan L. Giese, Washington State University

[The authors wish to thank Joseph A. Cote and Ayn Crowley for their helpful comments.]

ABSTRACT -

The purpose of this research is to examine the relationship between affective and cognitive processing styles. Using a combination of situation-invariant affect and cognition measures, evidence suggests that individuals differ in their propensity to rely on affective, cognitive, or both systems to process information. Rather than viewing affect and cognition as a dichotomy on a continuum, an independent but interactive relationship between affect and cognition is conceptualized and supported.

Marketing researchers have long been intrigued by the relationship between affect and cognition as well as the roles they play in preference formation and decision processing. According to traditional approaches, affect in preferences is an outcome of cognitive representations of the object; i.e., before you can say you like something, you must know what it is. Zajonc (1980) and Zajonc and Markus (1982), however, refuted the traditional approach. They suggested that the cognitive and affective processes may proceed independently, as well as work together. For understanding the consumer decision process, it is more useful to emphasize the interaction between the affective and cognitive systems than to debate about which system is more important or dominant (Peer and Olson 1996).

Recent studies on preference formation and attitude change have focused on how cognition and affect work together. Building on Zajonc’s research, both Edwards (1990) and Millar and Millar (1990) investigated affect-based attitudes: intentional responses based on affect. Edwards’ (1990) findings that affect-based attitudes were more susceptible to affective means of persuasion directly conflict with Millar and Millar’s (1990) findings that affective-based attitudes were more susceptible to rational arguments. Yet, perhaps Edwards’ (1990) newly formed attitudes were susceptible to affective persuasion because cognitions had not yet formed. In contrast, the attitudes studied in Millar and Millars’ (1990) research had been sufficiently questioned to produce cognitions about the product. Hence, seemingly conflicting results actually support the Zajonc and Markus (1982) views of situational dependencyCand possibly individual processing tendenciesCof affective or cognitive preference formation.

As a result, Edwards (1990) concluded that individuals most likely use a combination of affective and cognitive processing. Furthermore, that lack of an either/or, affect/cognition dichotomy suggests the two constructs may interact but remain separate. The purpose of this research is to explore the possibility that individuals may process information based on three modes: processing cognitions, processing affective responses, or using both cognition and affect in independent but interactive processing systems.

Cognitive and Affective Processing

Conceptual Relationship. Whereas other means of exploring cognition and affect, such as the Briggs and Meyers Personality Inventory (1984), view these constructs as negatively correlated (as points along a continuum), our distinction between affective and cognitive processing is not a dichotomy; it is unlikely that individuals rely solely on cognitions or affect for all decision processing. Rather, the relationship between affect and cognition is conceptualized as a biaxial grouping of four quadrants as depicted in Figure 1.

Individuals in the lower right quadrant are high cognitive processors and low affective processors. These individuals, Thinking Processors, generally prefer to think rationally and rely heavily on cognitive information. In terms of consumer purchases, they would likely be oriented towards tangible, quantifiable product attributes such as price or length of warranty. At the other end of the spectrum are people in the upper left quadrant. These are the Feeling Processors who rely on affect; they like the product and it feels good. The cues used to arrive at a decision are affective in nature such as "like" the product or the "feeling" it evokes (Booth-Butterfield and Booth-Butterfield 1990). Although they are not exclusively high on affect intensity, their propensity to use an affective processing style would suggest they experience more affective highs and lows than a cognitive processor (Larsen, Cropanzano, and Diener 1987).

People in the upper right quadrant, Combination Processors, are high on both affect and cognition. Similar to sociological interpretations of androgyny (Bem 1974), these people are comfortable using either processing style. This quadrant is consistent with research on promotion where both cognitive and affective responses were found to be intertwined (Burke and Edell 1989; Kahn and Isen 1993; Munch, Boller and Swasy 1993). Finally, the lower left quadrant exists where individuals are low on both affective and cognitive processing. The type of processing used by these individuals, Passive Processors, is unclear.

Conceptual Definitions. While cognition has been clearly distinguished from affect, researchers have been less than specific in defining affect and distinguishing it from the closely related, although not identical, concepts of attitude and emotion. Eagly and Chaiken (1993) define affect as experiential feelings directed toward attitude objects. Yet, emotions are unique from affect in that they are valenced and can therefore be classified as positive or negative (Abeele and MacLachlan 1994); they are spontaneous, temporary states (Murry, Lastovicka, and Singh 1992); and they can be classified by individuals according to a number of directions or orientations (Oliver 1992) such as happy, sad, angry, or mad. Raman, Chattopadhyay and Hoyer (1995) further distinguish emotions from moods. They conceptualize emotions as longer affective states than moods which are more general and less intensive (Gardner 1985).

In contrast, attitude is defined as an individual’s general affective, cognitive, and intentional responses toward a given object, issue, or person. Attitude includes a behavioral and cognitive component not present in the conceptual definition of emotion (Fishbein and Ajzen 1975). AffectCas used in this researchCcontains the feeling element present in both the emotion and attitude constructs but is viewed as a processing mechanism (Oliver 1993; Peter and Olson 1996). Hence, in this paper, affect is conceptualized and defined as a processing mechanism for feelings.

Cognitive processing, as defined by Engel and Blackwell (1982), involves "interpreting present perceptions in light of past information to reason our way through unfamiliar problems" (p. 237). The key feature in this definition which distinguishes it from affect is the emphasis on reason or logic: feelings or emotions are not included in cognitive processing. Consequently, thinking is to cognitive processing as feeling is to affective processing.

FIGURE 1

Affect and Cognition Scales. There are several scales designed to measure affect. Both the Leigh (1984) and Obermiller (1985) scales measure affect as a valenced construct suggesting that the scales are not measuring affect but emotion according to the distinctions suggested previously in this paper.

The Feeling Belief Measure (Haddock and Zanna 1993) is designed to assess individual differences in preferences toward using affect or cognition to process environmental stimuli. This scale examines the affect processing preference within context-specific situations and is most appropriate for measuring situations which are likely to evoke affective processing.

The Need for Emotion Scale (Raman, Chattopadhyay and Hoyer 1995) measures individuals’ needs to seek out emotional stimuli and is intended to be analogous to the Need for Cognition scale (Cacioppo, Petty and Kao 1984). The scale items, however, are situationally bound suggesting that, like the Feeling-Belief Measure, affect processing is a function of the situation as opposed to an individual processing trait which is relatively stable with respect to situations.

The Affective Orientation Scale (Booth-Butterfield and Booth-Butterfield 1990) attempts to measure awareness and use of emotional cues. While they too coneptualize affect as information in an information processing model, the focus is on the effect of affect processing on communication and message retention.

The Need for Cognition scale (Cacioppo, Petty and Kao 1984) is an 18-item scale which measures the extent to which individuals seek out and use cognitive information when making decisions. The Need for Cognition scale is used to measure cognitive processing across all situations. In contrast, published affect scales were typically situation bound.

METHOD

Measures

A situation-invariant affective processing scale analagous to the cognitive processing scale (Need for Cognition) was developed for the purpose of this research. The steps involved in developing the proposed scale were based on those suggested by Churchill (1979) and Gerbing and Anderson (1988). Using the conceptual domain of affect, as outlined in previous research, and comments generated by a focus group, 108 sample items were generated. The large number of items represented the breadth of the affect domain as well as the special attention accorded to the wording of statements (Dillman 1978). For example, one item may be reworded four different ways using the terms "vibes," "intuitions," "feelings," or "gut feel" interchangeably.

A panel of nine experts familiar with affect research reviewed the list of sample items and eliminated inappropriate statements. As a result, a total of 62 items remained. These 62 items were randomly interspersed with the 18 items from the Need for Cognition scale (Cacioppo, Petty, and Kao 1984). The Need for Cognition scale, complete with response categories, was reproduced verbatim as a nine-point Likert scale. Scale endpoints were "very strong disagreement" (-4) to "very strong agreement" (+4). The same type of scale and endpoints were used for the affect scale.

Exploratory and confirmatory factor analysis supported the retention of 17 items. Using exploratory factor analysis, all 17 items loaded on the first factor. Of those 17 items, 13 exhibited loadings of .4 or greater and were retained. The four items discarded due to factor loadings of less than .2 shared one quality in common: they were all situationally bound (e.g. Sometimes it feels good to cry during a sad movie.). Confirmatory factor analysis using the 13 items from the exploratory analysis resulted in a good fit for a one-factor model (c2=127.809; df=65; CFI=.910). (The scale items and respective standardized parameter estimates appear in the appendix.)

Samples

Using the Need for Cognition scale to measure cognitive processing and the Preference for Affect scale to measure affective processing, two samples were used to examine the relationship between the processing styles. In an effort to avoid extensive cognitive processing of statements, respondents were encouraged to answer each question carefully but were told not to deliberate over any one particular question.

The first sample consisted of 194 students from four undergraduate business and anthropology classes at a large northwestern university. After analyzing responses for inconsistencies and missing data, 176 surveys were usable. The second sample consisted of 191 students from different undergraduate business, communication, and engineering classes at the same university. One hundred sixty-seven surveys were usable.

TABLE 1

DESCRIPTIVE STATISTICS FOR AFFECT / COGNITION QUADRANTS

RESULTS

Sample 1

Coefficient alpha for the Need for Cognition scale and the newly developed Preference for Affect scale were .8453 and .9136 respectively. There was no significant correlation between the scales (r=-.0267; p=.723). Using a median split of the actual data, results indicated that respondents could be categorized as high on cognition but low on affect (thinking processors); high on both the affect and cognition scales (combination processors); low on cognition but high on affect (feeling processors); or low on both the affect and cognition scales (passive processors). (See Table 1).

Sample 2

As a verification of the results from Sample 1, data were analyzed from another sample. Coefficient alpha for the scales were .8591 (Need for Cognition) and .8721 (Preference for Affect). Again, there was no significant correlation between the scales (r=-.0836; p=.283). (See Table 1.)

DISCUSSION AND FUTURE RESEARCH

These results suggest that affective and cognitive processing systems are independent, yet can operate interactively. Individuals, unbounded by a specific situation, demonstrate a propensity to process information using affect (feeling processors), cognitions (thinking processors), or both (combination processors). Furthermore, some individuals indicate a propensity to not rely on either processing style (passive processors).

Previous research indicates similar results pertinent to combination processors. Booth-Butterfield and Booth-Butterfield (1990) found that individuals high on the need for cognition were as likely to process feelings as they were statistical data suggesting that an affective orientation is not the polar opposite of need for cognition. In addition, Ramon, Chattopadhyay and oyer (1995) found a moderate correlation between the Need for Cognition and Need for Emotion scales causing them to conclude that the affective and cognitive systems were interacting.

If, in fact, affect and cognition are simultaneous processes operating at different levels in different situations, several interesting issues for further research should be considered. First of all, much of previous affect/cognition research has assumed a causal order of the two constructs. The critical issue may not be which comes firstCaffect or cognitionCbut rather under what situations, or with which personality types, is a combination, affective, or cognitive processing style likely to dominate. It is conceivable that situational variables, such as product involvement, risk level, or spousal processing style, may impact an individual’s processing style. For example, purchasing an automobile is most likely more emotionally laden than purchasing paper towels. Likewise, in a family situation, one spouse may take a cognitive approach to purchasing an automobile while the other spouse utilizes an affective process; the sum of which results in two different processes used to arrive at a particular decision. Additional research is needed to examine situational effects on individuals’ processing styles and the interaction of affective and cognitive processing styles in specific decision making or choice situations. With dependent decision variables, the influence of processing style and the causal sequence of that influence could be examined.

This simultaneous approach to affect/cognition also raises the issue of information overload. Research in decision processing suggests that in cases of information overload, respondents are likely to either switch heuristics or resort to an affect-referral strategy (Wright 1975). If the affective and cognitive systems respond to cues in a similar fashion, then perhaps affect overload would result in a cognitive processing approach.

In addition, future research should focus on the passive processors, i.e., those who are low on both the cognition and affect scales.

APPENDIX

LIMITATIONS

This research was conducted using traditional undergraduate students. Previous research suggests that affective decisions may be more prominent in early years and will decrease as the individual grows older (Larsen and Diener 1987). In addition, the use of student samples may result in an upward bias of results (Brown and Stayman 1992), as well as inhibiting the scale’s external validity (Lynch 1982). While some researchers argue that student samples are appropriate particularly when testing theory (Calder, Phillips and Tybout 1981), additional testing with a more diverse population is needed to enhance the generalizability of the results.

The nonverbal nature of affect coupled with research on hemisphere lateralization suggests that it might be difficult to capture affective processes via cognitive methods. Note that there are no reverse-coded items in the final scale. The lack of reverse-coded items, however, is somewhat theoretically consistent since a reverse-coded item requires more cognitive processing to accurately interpret the question. Furthermore, research has shown that scale dimensionality is not compromised in scales lacking reverse-coded items (Obermiller and Spangenberg 1996).

CONCLUSION

Preliminary evidence suggests an interaction between affective and cognitive processing styles in which both processes may operate simultaneously yet separately. While additional research is needed to offer conclusive empirical evidence supporting this conceptualization, the concept is intuitively appealing and is potentially able to accommodate previous research in the field. Clearly, the relationship between affect and cognition holds great promise for future research.

REFERENCES

Bem, D. (1974), "The Measurement of Psychological Androgyny," Journal of Counseling and Clinical Psychology, 42, 155-162.

Booth-Butterfield, Melanie and Steve Booth-Butterfield (1990), "Conceptualizing Affect as Information in Communication Production," Human Communication Research, 16 (Summer), 451-476.

Brown, Stephen P. and Douglas M. Stayman (1992), "Antecedents and Consequences of Attitude Toward the Ad: A Meta-Analysis," Journal of Consumer Research, 19 (June), 34-51.

Burke, Marian Chapman and Julie A. Edell (1989), "The Impact of Feelings on Ad-Based Affect and Cognition," Journal of Marketing Research, 26 (February), 69-83.

Cacioppo, John T., Richard E. Petty, and Chaun Feng Kao (1984), "The Efficient Assessment of Need for Cognition," Journal of Personality Assessment, 47 (3), 306-307.

Calder, Bobby J., Lynn W. Phillips, and Alice M. Tybout (1981), "Designing Research for Application," Journal of Consumer Research, 8 (September), 197-207.

Churchill, Gilbert A., Jr. (1979), "A Paradigm for Developing Better Measures of Marketing Constructs," Journal of Marketing Research, 16 (February), 64-73.

Dillman, Don A. (1978), Mail and Telephone Surveys: The Total Design Method, New York, NY: John Wiley.

Eagly, Alice H. and Shelly Chaiken (1993), The Psychology of Attitudes, Fort Worth, TX: Harcourt Brace Jovanovich College Publishers.

Edwards, Kari (1990), "The Interplay of Affect and Cognition in Attitude Formation and Change," Journal of Personality and Social Psychology, 59 (2), 202-216.

Engel, James F. and Roger D. Blackwell (1982), Consumer Behavior, New York, NY: The Dryden Press.

Fazio, R. H. and Mark Zanna (1981) "Direct Experience and Attitude-Behavior Consistency," in Advances in Experimental Social Psychology, Vol. 14, ed. L. Berkowitz, Orlando, FL: Academic Press, 161-202.

Fishbein, Martin and I. Ajzen (1975), Beliefs, Attitudes, Intentions, and Behavior, Reading, Mass: Addison-Welsley.

Gardner, Meryl P. (1985), "Mood States and Consumer Behavior: A Critical Review," Journal of Consumer Research, 12 (December), 281-300.

Gerbing, David W. and James C. Anderson (1988), "An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment," Journal of Marketing Research, 25 (May), 186-192.

Haddock, Geoffrey and Mark P. Zanna (1993), "Predicting Prejudicial Attitudes: The Importance of Affect, Cognition, and the Feeling-Belief Dimension," in Advances in Consumer Research, Vol. 20, eds. Leigh McAlister and Michael Rothschild, Provo, UT: Association of Consumer Research, 315-318.

Kahn, Barbara E. and Alice M. Isen (1993), "The Influence of Positive Affect on Variety Seeking Among, Safe, Enjoyable Products," Journal of Consumer Research, 20 (September), 257-270.

Larsen, Randy J. and Ed Diener (1987), "Affect Intensity as a Individual Characteristic: A Review," Journal of Research in Personality, 21, 1-39.

Larsen, Randy J., Russell S. Cropanzano, and Ed Diener (1987), "Cognitive Operations Associated with Individual Differences in Affect Intensity," Journal of Personality and Social Psychology, 53 (4), 767-774.

Leigh, James H. (1984), "Recall and Recognition Performance for Umbrella Print Advertisements," Journal of Advertising, 13 (4), 5-18.

Lynch, John G. Jr., (1982), "On the External Validity of Experiments in Consumer Research," Journal of Consumer Research, 9 (December), 225-239.

Millar, Murray G. and Karen U. Millar (1990), "Attitude Change as a Function of Attitude Type and Argument Type," Journal of Personality and Social Psychology, 59 (2), 217-228.

Munch, James M., Gregory W. Boller, and John L. Swasy (1993), "The Effects of Argument Structure and Affective Tagging on Product Attitude Formation," Journal of Consumer Research, 20 (September), 294-302.

Murry, John P. Jr., John Lastovicka, and Surendra N. Singh (1992), "Feeling and Liking Responses to Television Programs: Examination of Two Explanations for Media-Context Effects," Journal of Consumer Research, 18 (March), 441-451.

Obermiller, Carl (1985), "Varieties of Mere Exposure: The Effects of Processing Style and Repetition in Affective Response," Journal of Consumer Research, 12 (June), 17-30.

Obermiller, Carl and Eric R. Spangenberg (1996), "Development of a Scale to Measure Consumer Skepticism toward Advertising," Working Paper, Seattle University.

Oliver, Richard (1992), "An Investigation of the Attribute Basis of Emotion and Related Affects in Consumption: Suggestions for a Stage-Specific Satisfaction Framework," in Advances in Consumer Research, Vol. 19, eds. John F. Sherry and Brian Sternthal, Provo, UT: Association for Consumer Research, 237-244.

Oliver, Richard (1993), "Cognitive, Affective and Attribute Bases of the Satisfaction Response," Journal of Consumer Research, 20 (December), 418-430.

Peter, J. Paul and Jerry C. Olson (1996), Consumer Behavior and Marketing Strategy, Chicago, IL: Richard D. Irwin.

Raman, Niranjan V., Prithviraj Chattopadhyay, Wayne D. Hoyer (1995), "Do Consumers Seek Emotional Situations: The Need for Emotion Scale," in Advances in Consumer Research, Vol. 22, eds. Frank R. Kardes and Mita Sujan, Provo, UT: Association for Consumer Research, 537-542.

Wright, Peter(1975), "Consumer Choice Strategies: Simplifying vs. Optimizing," Journal of Marketing Research, 12, 60-67.

Zajonc, Robert B. (1980), "Feeling and Thinking: Preferences Need No Inferences," American Psychologist, 35 (February), 151-175.

Zajonc, Robert B. and Hazel Markus (1982), "Affective and Cognitive Factors in Preferences," Journal of Consumer Research, 9 (September) 123-131.

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