Longitudinal Analysis of Consumer Attitude, Intention, and Behavior Toward Beer Brand Choice

Beliefs, Attitudes, and Intentions

The summated evaluative belief measure as shown in Figure 1 is hypothesized to have a direct impact on individual attitudes with respect to each brand for both time periods. The premise of employing product attribute beliefs as predictors of consumer attitudes, preferences, and behavior has been well received in the marketing and consumer behavior literature. Wilkie and Pessemier (1973) and Lutz and Bettman (1976) have provided exhaustive reviews of more than 90 marketing articles dealing with multiattribute studies based in part upon the familiar conceptualization of Fishbein (1963). This relationship may be expressed mathematically as in equation (1). A subject's attitude (A) toward a stimulus object (0) is expressed as a summed function of the number (1...n) of his associative beliefs (B_i)about the exposed stimulus multiplied by-the evaluative aspects of (a_i) of those beliefs:

EQUATION   (1)

Day (1972, p. 279) has emphasized the importance of the effective nature of attitudes by asserting that the individual's overall feelings of like or dislike for an object represent the core of the attitude concept because of its derivation from the more basic cognitive components. The attitudinal variables (A_ot and A_ot+1) shown in Figure 1 are actually two measurements of a brand specific affective construct reflecting each individual's overall liking or disliking tendency with respect to each brand. Heberlein and Black (1976) have demonstrated that attitudes are better predictors of specific behavior toward subunits of a class of objects when the prediction is based upon more specific constructs than when based upon general attitudes about classes of objects.

Implicit in most attitudinal research in both social psychology and consumer behavior is the notion that individual attitudes are significant determinants of both behavioral intentions and specific behaviors (Ajzen and Fishbein, 1973; Norman, 1975). Overall affect toward a multi-attribute object as a measure of attitude is posited to reflect the individual's belief structure as to the degree to which individual brands possess certain attributes weighted by the evaluation of each attribute (Wilkie and Pessemier, 1973, p. 428). The affective measures are depicted in Figure 1 as being direct influences on intentions, behavior, and subsequent attitudes.

Behavioral Influences

Previous brand choice behavior is depicted in Figure 1 as directly influencing the formation of intentions and ensuing brand choice decisions. The purchase of many convenience items may not involve decision processes which are based upon well-founded belief systems and attitudes of high centrality. The perspective of "low-commitment" consumer behavior suggests that consumers for many products may not be particularly committed in their brand selection processes. When commitment is low and beliefs are not strongly held, brand purchase may reflect only the convenience inherent in repeat purchases rather than commitment to the brand purchased based on a well-developed attitudinal structure (Robertson, 1976). When individuals engage in purchase situations characterized by low-involvement (e.g., the purchase of many low-priced convenience goods), behavior may take precedence over attitudinal influences. Consequently, the initial behavioral measure is depicted as influencing current intentions and subsequent attitudes and brand selections.

Situations

The possibility of situations acting as a mediating influence between attitudes and individual behavior is being increasingly examined in the behavioral literature (e.g., Belk, 1974; Belk, 1975; Bowers, 1973; Ehrlich, 1969; Endler and Hunt, 1968; Kakkar and Lutz, 1975; Miller, 1974; Rokeach and Kliejunas, 1972; Sandell, 1968; Snyder and Monson, 1975; and Wicker, 1971). Generally, situational variables have been suggested for reducing the inconsistency between attitudes and overt behavior. An independent anticipated situational construct is depicted in Figure 1 as directly influencing the formation of intentions and reported brand choice for both measurements. The use of situational variables as independent predictors of individual behavior has been proposed by Sheth (1974a; 1974b) in two attempts to isolate situational factors which systematically intervene between attitudes and behavior. Investigations of consumer behavior which ignore situational effects are likely to result in good predictions only when the characteristics of buyers or choice alternatives are intense enough to be influential across all relevant situations (Belk, 1974).

Situational influence in this analysis is considered as an independent factor affecting the formation of intentions and behavior. The situational variable is actually an anticipated construct reflecting the individual's perception of the importance of the situation for each brand's consumption. This method of considering situational aspects of consumption is not intended to reflect the situation specific nature of the attitudinal, social, and intention measures of Fishbein's extended model. The assumed independence of the situational construct is more congruent with the approach taken by the research of Rokeach and Kliejunas (1972) in which both attitudes toward the object and the situation were found to be significant predictors of behavior. This approach is consistent with the classic formulation of Lewin: behavior is a function of the person and his environment (Ehrlich, 1969, p. 32).

Situational factors may also intervene between attitudes and behavior in an unexpected sense. For example, Wicker (1971) found that unplanned and extraneous events were the best single predictor of behavior with respect to church attendance. Sheth (1973a, p. 56) suggests that situational influences, such as temporary economic conditions, organizational changes, and changes in the market place (e.g., promotional efforts, new product introductions, and price changes) may also intervene and affect industrial and durable good buying processes. However, the likelihood of such unplanned and significant events affecting purchase behavior may be greater for durable and more expensive items with limited distribution compared with brands of beer examined in this research.

METHOD AND OPERATIONAL STATEMENTS

Subjects

Consumer beliefs, attitudes, intentions, and reported behavior for four brands of beer were collected from male household heads of a regional consumer panel in the southeastern United States in February 1975. A second mailing to the 172 respondents answering all questions for each brand was made in February 1976. The results of this study are based on the response of the 105 consumers of beer answering all questions in both mailings. Panel members are selected on a quota basis and are representative of the population characteristics of the regional area.

Choice Objects

Individual brands of beer were used as the behavioral choice objects. Beer was selected because of (1) its familiarity to most panel members, (2) high frequency of purchase, (3) possession of a variety of product attributes, and (4) the existence of a limited number of well-known and distinct brands. Budweiser, Pabst, Old Milwaukee, and Schlitz were the brands examined. The combined sales volume of these brands accounted for over 60% of all beer sold in the consumer panel area during the periods of the study. [Personal communication with consumer research personnel of Joseph Schlitz Brewing Company, Milwaukee.]

Attributes

Product attributes were selected on the basis of previous in depth interviews and taste studies of informal consumer groups conducted by an independent marketing research firm. Beliefs and evaluations were obtained for 11 product attributes. The summated belief score was based on 7 of these attributes selected on the basis of factor analysis.

Situation

The situational variable was intended to represent the importance of the consumption situation "drinking beer while watching a sports event or some favorite TV show." This situation was selected on the basis of the actual transcripts of a further series of in depth interviews with regular beer drinkers conducted for the Joseph Schlitz Brewing Company. This particular situation selected reflected the consumption environment most frequently mentioned during the recorded conversations. [Conducted by Conway-Milliken Corporation, Chicago, Illinois, June, 1973, for Joseph Schlitz Brewing Company, Milwaukee.] The situational variable was constructed as a multiplicative score reflecting three environmental aspects felt necessary for a particular consumption situation to affect brand usage. The three situational considerations assessed were: (1) the likelihood of the situation occurring as part of his normal environment, (2) the appropriateness of the product for use in the situation, and (3) the likelihood of each brand being suitable for use in that particular situation. [For a more detailed description, see Bearden and Woodside (1976b).] This is consistent with the assumption that environmental information is relevant to a person's behavior only when it is conceptualized by the individual (Russell and Mehrabian, 1976, p. 62).

Variables

[Response measures and scaled operational statements were developed on the basis of the research needs of Joseph Schlitz Brewing Company for use in exploratory -efforts directed at obtaining a better understanding of the formation of consumer preferences and intentions toward their products and competing brands.]

Brand attitudes were operationalized by means of seven-point bipolar scales ranging from "strongly disagree" to "strongly agree" reflecting each individual's overall affect toward each brand. The behavioral variable was brand most often purchased for personal consumption. The scoring was in dummy variable form, with a score of one for the brand used most often by the respondent and zero for all other brands.

Behavioral intention with respect to each brand was assessed by means of the following operational statement:

I will buy some Brand X during the next four weeks.

Likely  __:__:__:__:__:__:__: Unlikely

Respondents' beliefs toward the brands were measured across attributes sequentially both to limit the influence of brand "halo effects" and to prevent excessive questionnaire length. Beliefs with respect to each product attribute were measured for all brands as shown in the following example:

Please indicate how well you think each of the following phrases describes each of the brands listed below. Do this by putting the letter shown for each brand on one of the spaces provided. From what you may know or have heard about each brand, indicate how well you believe the phrase describes the brand.

Not for Young People  __:_"_:__:__:B,C__:_D_:  For Young People

This example would indicate that you believe brand D is more for young people than other brands. Notice that you can place more than one brand in one space.

Respondents indicated their evaluations for each product attribute using seven-point "strongly disagree" to "strongly agree" to stated preferences, e.g., "I prefer a lively beer." Both beliefs and evaluations were scored -3 to +3. (All other seven-point scaled responses were scored 1 to 7.)

The likelihood of a given situation arising for a consumer was operationalized in the following manner:

Not Very Often  __:__:__:__:__:__:__:  Very Often

Consumers responded to the likelihood of drinking beer for each situation by responding to statements such as:

Having beer while entertaining close friends at home.

Unlikely  __:__:__:__:__:__:__:  Likely

Panel members were requested to place a letter for each brand on a scale reflecting the likelihood of having that brand in each situation:

The following series of statements assumes that you are willing to use beer, as a product in general, in the following situations. Please indicate how likely you are to have the following brands of beer in the following situations. Please do this by putting the letter shown for each brand on one of the spaces provided.

The instructions were followed by an example and a series of situational statements scaled from "Unlikely" to "Likely".

ANALYSIS

One way of looking at the relationships shown in Figure 1 among the variables examined and hypothesized to underlie brand choice behavior is to formulate the relationships as a series of explicit equations. Regression analysis can then be used to examine internal consistency among the relationships across both dependent variables and brands. Cross-lagged correlations can also be employed to examine causal implications over-time (Lehmann, O'Brien, Farley, and Howard, 1974, p. 44). The assumption of asymmetrical causation enables ease of data handling and assumes that each endogenous variable is defined recursively only in terms of the previous variables. If standardized regression coefficients are used as measures of influence, a matrix of regression coefficients results for the seven variables as shown in Figure 2 (Kirkpatrick, 1974, p. 156).

FIGURE 2

MATRIX OF ESTIMATED STANDARDIZED REGRESSION COEFFICIENTS (b_i)

For example, X₁ is regressed on X₃ (b₃₁), but X₃ is not regressed on X₁. This kind of analysis requires the simplifying assumption that the error terms are un-correlated and that major outside causes of a variable in the system operate only on one variable in that system (Blalock, 1969, p. 84). Strict interpretation of Beta coefficients should be tempered by the realization that other factors may affect the relative size of each coefficient. Operational measurement, intercorrelations among explanatory variables, and the representativeness of the sample employed may limit both the validity and reliability of any estimated regression equation (Darlington, 1968).

Panel data can be analyzed by cross-lagged correlation analysis to indicate which of two variables each measured at two points in time is more likely to have causal priority over the other (Arlin, 1976). Since the affective variable and actual behavior were both measured simultaneously at two points in time, cross-lagged correlations may be used as a further means of examining some of the relationships for likely paths of influence. If attitudes have priority over behavior such that changes in attitudes precede changes in behavior, then A_t should be more closely associated with B_t+1 than B_t is associated with A_t+1. Or the correlation A_t-B_t+1 should be significantly greater than the correlation A_t+1-B_t (Monroe and Guiltinan, 1975, p. 24). While cross-lagged correlations are useful for implying causal priority among sets of variables, only inferences can be drawn since correlation is only one condition necessary for proof of causation. [Since the four measures (attitude and behavior in two time periods) lack independence, a statistical test of the significance of the difference between nonindependent correlation networks is inappropriate. Therefore, formal hypothesis testing was not used. The networks of cross-lagged correlation coefficients for the four brands may be examined for patterns which do or do not support the relationships suggested (Arlin, 1975; Bearden and Woodside, 1976a).]

RESULTS

The results of the regression analyses were generally stable across all four brands. The standardized regression coefficients are shown in Figures 3 and 4 for Budweiser and Schlitz as indicators of possible causal influence along each of the paths among the attitudinal and behavioral variables considered.

FIGURE 3

STANDARDIZED REGRESSION COEFFICIENTS AMONG BRAND ATTITUDES, INTENTIONS, AND BRAND CHOICE BEHAVIOR OVER TIME FOR BUDWEISER

FIGURE 4

STANDARDIZED REGRESSION COEFFICIENTS AMONG BRAND ATTITUDES, INTENTIONS, AND BRAND CHOICE BEHAVIOR OVER TIME FOR SCHLITZ

Further, the independent variables significant in each of the five equations have the expected positive sign (e.g., attitudes are positively related to brand choice). The resulting coefficients of determination and all standardized regression weights are depicted in Table 1 for each equation and brand. The overall  variance explained for each of the twenty regression equations was significant (p < .01). A substantial portion of the variance (R²'s > .50) in the two dependent variables measured at time t + 1 (A_t+1 and B_t+1) was explained for all four brands.

TABLE 1

BRAND SPECIFIC REGRESSION MODELS EMPLOYED IN LONGITUDINAL ANALYSIS

The situational variable (SSS_t) was found to be significant in its impact only in the time period in which the variable was measured. The Beta coefficient associated with the situational measure and behavior measured at t + 1 was significant (p < .01) for only the Schlitz results. B_t+1 was consistently found to be significantly influenced by both previous behavior (B_t) and current attitudes (A_t+1). Previous attitudes appear to have limited impact as a direct influence on behavior. However, the impact of A_ot on B_t+1 is probably felt indirectly through its direct influence on previous behavior and subsequent attitudes.

The insignificance of the coefficient associated with BI_t and B_t+1 is likely attributable to both the correlation of Bt with previous behavior, the length of time between measurements, and the anticipated nature of the situational construct. The insignificant coefficient associated with the summated attribute score and A_ot+1 may be attributed to the strength of the co-variation between the affective measures over time. This lack of statistical significance may be interpreted as an indication of the indirect influence of individual evaluative criteria as felt through previous attitudes to current affective tendencies. Each independent variable depicted as having direct influence on the formation of behavioral intentions possessed significant standardized regression coefficients in the brand specific equations.

The cross-lagged correlations between the affective measures and-brand choice each measured at t and t+1 were all significant as shown in Table 2. The correlations of B_t-A_t+1 were larger than the cross-lagged correlations A_t-B_t+1 for the Budweiser and the Old Milwaukee results. The cross-lagged correlations A_t-B_t+1 were only marginally larger than the corresponding correlations A_t+1-B_t for the other two brands. These results imply limited support of attitude causal priority over behavior for two beer brands examined in this study. The Pearson-Filon test of the difference between correlational patterns based on only the cross-lagged correlations was not significant (p < .10) for any of the brands.

TABLE 2

CROSS-LAGGED CORRELATIONS BETWEEN CONSUMER ATTITUDES AND BRAND CHOICE RESPONSES

DISCUSSION

A number of cautions should be kept in mind when interpreting these results. First, the analyses were based upon four brands of a single product and should be replicated for other brands and consumer groups. Given the diversity inherent in individuals and the range of variables that affect the judgmental process, the nature of the relationships described in this study must be tested under varying conditions before any firm generalizations can be offered. Second, the use of multiple item scales to reflect individual attitudes and beliefs would further insure the validity and reliability of the operational statements. Third, the level of involvement of consumers with the products and brands should be considered. When individuals are highly involved with a particular choice object, attitude change may precede behavior change. However, when low involvement is characteristic of the purchase situation; behavior change may precede attitude change (Pinson and Roberto, 1973; Bearden and Woodside, 1976a). This may be particularly relevant when a low-priced convenience brand is purchased on the basis of limited information search, e.g., such as a purchase on the advice of a friend or an individual impulse purchase. Fourth, the measurement of attitudes, intentions, and actual behavior within a particular situation may more accurately reflect the relative influences and strength of relationships among variables underlying consumer choice over time. Fifth, care must be exercised in drawing conclusions from any study concentrating on a small number of variables due to the possibility of bias resulting from omitted variables (Lehmann, O'Brien, Farley and Howard, 1974).

The consistency of the results across brands, the degree of variance explained, and the direction of influences support the possibility of the existence of similar findings among variables underlying choice behavior for low involvement products. Additional longitudinal analyses with repeated measurements for different products and situations are needed before more definitive answers can be provided concerning structural relationships underlying brand choice decision processes.

These results also underscore the ability of previous behavior to predict both subsequent individual affective tendencies and behavioral intentions. The implied question of whether attitude change precedes or follows behavior is perplexing (Ginter, 1974). Post-choice attitude change may be attributed to either additional information or cognitive dissonance. However, for low-priced convenience products, modifications in existing attitudinal structure are likely to occur in the form of either changes in existing attitudes or further refinement of less developed currently held beliefs on the basis of additional information acquired from trial usage.

The results of the cross-lagged correlation analyses also support the possibility of purchase behavior affecting attitudes and behavior measured in later time periods. Of the brands considered, the cross-lagged correlations B_t-A_t+1 exhibited marginal causal priority over the A_t-B_t+1 relationship for Budweiser and Old Milwaukee. The cross-lagged correlations for the remaining brands were approximately equal. There may be subsets of individuals in which the relationships between attitude change and behavior will vary (Ginter, 1974). The identification of these groups and further analysis employing experimental designs to assess change processes may be worth further research.

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