Influences of Brand Name and Packaging on Perceived Quality

ABSTRACT - Using an experimental design on the Belgian coffee market, the present research investigates the combined effects of brand names and brand packaging on the consumers' perceptions of quality. As evidenced by the empirical results, both extrinsic cues do influence the consumers' quality evaluation, not only separately but also interactively. Managerial and consumer research implications are briefly described.


Benny Rigaux-Bricmont (1982) ,"Influences of Brand Name and Packaging on Perceived Quality", in NA - Advances in Consumer Research Volume 09, eds. Andrew Mitchell, Ann Abor, MI : Association for Consumer Research, Pages: 472-477.

Advances in Consumer Research Volume 9, 1982      Pages 472-477


Benny Rigaux-Bricmont, Universite Laval


Using an experimental design on the Belgian coffee market, the present research investigates the combined effects of brand names and brand packaging on the consumers' perceptions of quality. As evidenced by the empirical results, both extrinsic cues do influence the consumers' quality evaluation, not only separately but also interactively. Managerial and consumer research implications are briefly described.


Since quality perception seems to be strongly related to actual purchasing behavior, especially brand loyalty (Jacoby 1971), perceived quality has generated considerable experimental interest (cfr. Olson and Jacoby 1972). A better understanding of the quality perception process requires knowledge of the cues used by the consumer in his alternative quality evaluation. From an information theoretic perspective, products and brands themselves are conceived to consist of an array of cues (e.g., price, brand name, packaging, color, etc...), each of these cues providing a basis for developing various impressions of the product (Cox 1962 Jacoby, Olson and Haddock 1971). Among those extrinsic [Olson and Jacoby (1972) refer to them as extrinsic cues for they are not parts of the physical product. They define intrinsic cues as product attributes which cannot be changed or experimentally manipulated without also changing the physical characteristics of the product itself (e.g. nature of the fiber, taste, special ingredients, etc...).] cues the relation between price and quality has been the most investigated during these last twenty years (Gabor and Granger 1964, McConnell 1968, Cooper 1970, Peterson 1970, Rao 1970, Monroe 1973, Woodside and Sims 1974, Olson 1977). This relation is now accepted as a positive non-linear one. Research has also shown the important role of brand names and brand packaging on quality perception. Brand reputation can be either a common surrogate indicator of product quality (Allison and Uhl 1964, Larzelere et al. 1965, Smith and Broome 1967, Myers 1967, Gardner 1971, Valenzi and Eldridge 1973, Freidman and Dipple 1978), or an effective strategy to reduce risk when ease of evaluation is low (Bauer 19609 Engel, Knapp and Knapp 1966, Lambert et al. 1980). Being almost a part of the product, packaging does not only act as a means of communication (Lincoln 1965, Gardner 1967) but may also interact closely with the evaluation of the product itself (Banks 1950, Brown 1958, McDaniel and Baker 1977, Miaoulis and d'Amato 1978).

When more than one extrinsic cue is investigated in studies, price and brand name are almost invariably included (Gardner 1970, Peterson and Jolibert 1976, Wheatley, Walton and Chiu 1977, Raju 1977). It is not the case in the present research which investigates through experimentation the combined effects of brand names and packaging on the perceived quality of coffee, a very popular food item daily consumed by 95% of the Belgian householders. The data used in this paper, were collected in an experiment conducted in June 1974 for one of the three most important firms competing in a particular variety submarket. At that time, the marketing managers were interested in determining the consumer attitudes for both their product and those of their two major competitors. Witnessing different patterns of market shares in the three typical regions of Belgium, they suspected the market to be heterogeneous in terms of attitudes.


The experimental design was a 3 x 3 x 3 factorial, consisting of three levels of packaging (i.e., blind test, brand disclosure, and regular retail presentation), three levels of regions (i.e., three representative cities of these regions), and three levels of product samples (i.e., three physically different samples of the product variety). Repeated measures were taken across the third factor. Thirty subjects were used in each of the nine experimental conditions.

The test group was composed of 270 variety users who agreed to participate in the study after having been randomly selected. After a brief interview on her consumption habits, each participant in the experiment was given free samples of the three brands, and a questionnaire to be picked up one week later.

Packaging information was manipulated by presenting the samples either in white bags with the variety name and a six-digit random number in place of the brand name, or in white bags with both the variety and the brand names, or in their regular retail packaging. A six-digit random number was selected in order to avoid any preference formation related to single figures (i.e. 7).

Brand perceived quality, the dependent variable for this study, was measured with a seven-point semantic differential scale using "good taste" and "bad taste" as pair of antonyms (similar to an "hedonic scale"). The selection of this measure was based on some findings in the field of multi-attributes attitude models, which show that the best way to find out what is a person's attitude toward a product or a brand, is to ask him a straightforward question about his overall satisfaction (Perry no date).

The effects of brand identification and brand packaging on these "overall perceived taste" ratings were investigated through an analysis of variance.

The appropriate model of analysis of variance (Three-factor experiment with repeated measures on only one of the three factors):

The form of the structural model which corresponds to the present experimental design is:

E(Xijkm) = m + ai + bj + abij + pm(ij) + gk + agij

                                    + bgjk + abgijk + gpkm(ij),


E(Xijkm) = Expected value of overall perceived taste rating i,j,k = 1, 2, 3 (three-factor experiment with three levels for each factor)

                 m = 1, ..., 30 (replications on 30 subjects);

aii, bj, gk = main effect terms respectively for regions (factor A), packaging (factor B) and brands (factor C);

abij, agij, bgjk = first order interaction effect terms;

abgijk = second order interaction effect term;

nm(ij) = subjects within groups;

gpkm(ij) = Brands (repeated measures) x subjects within groups;

m = overall mean.

The model states that the total sum of squares can be partitioned in the 9 enumerated quantities. Since the subject factor is nested under both factor A and B, there can be no interaction between these latter factors and the subject factor. This model has implicit in it homogeneity assumptions on variance-covariance matrices associated with the repeated measures. The appropriate analysis of variance for this plan is described in Winer (1971). The expected values are computed according the special case in which A, B and C are considered fixed factors. As complete assumptions about the variance-covariance matrices are not tested, the analysis uses the Greenhouse and Geisser procedure (1959) for all tests involving the brands factor. This procedure is negatively biased in that it uses conservative degrees of freedom [In this case, the degrees of freedom for numerator and denominator are each divided by 2.] leading to errors in the direction of not rejecting false null hypotheses.



Data analysis of the overall perceived taste ratings

Before performing the described analysis of variance, a check was made on the importance of the bias due to the fact that some consumers found among the samples the brand they actually buy. In the blind test situation, the probabilities of having the highest score on a brand [Cases with ties were disregarded.], knowing this brand is frequently purchased in the household, were respectively 18% for Brand 1, 10% for Brand 2 and 0% for Brand 3. In the cases where the brands were revealed, these conditional probabilities became 31> for Brand 1, 25% for Brand 2 and 24% for Brand 3. While the loyalty of the participants toward "their" brands increased when positive brand identification was possible [The same phenomenon is reported by Allison and Uhl (1964).], the observed-bias appears to be very moderate.

The means and standard deviations of the overall perceived taste ratings for each experimental cell are presented in Table 1.

The normality assumption of the analysis of variance is challenged by the results: the information gathered along a discrete scale from 1 to 7 gives an overall mean of 5.56 and a variance of 2.03. Furthermore, a Bartlett test rejects the hypothesis of homoscedasticity. In such a case, it is recommended to consider a mathematical transformation on the scale of measurement which should improve equal variances and normality. Taking into account the shapes of the observed histograms, the following transformation was selected: in (8-x), where in stands for natural logarithms and x for the individual taste ratings, 8 being the smallest number that assures values equal to or greater than 1. As shown in appendix 1, the transformation satisfies the hypothesis of homoscedasticity.

The analysis of variance was performed on both the original ratings and the transformed ones [Using the BMD08V program (Dixon 1968).]. The results are respectively summarized in Table 2 and in appendix 2. Their similarity is not surprising if one remembers Green and Tull's statement (1978, p. 355) that "... research has indicated that moderate departures from normality and equality of variances (homoscedasticity) do not seriously affect the validity of the tests". For practical purposes of interpretation, the following development is based on the analysis of variance performed on the original ratings (Table 2).



A Brands main effect is obtained (F = 13.80, df = 1,261, p < .01) and a multiple comparisons "t" test indicates that among the differences between the pairs of means for the three brands X1 = 5.78, X2 = 5.71, X3 = 5.18), the difference between X1 and X3, and between X2 and X3 are significant beyond the .001 level. The analysis also indicates a packaging main effect (F = 9.99, df = 2,261, p < .01). The difference between the means for the PACK 1 (X1 = 5.25) and the PACK 3 (X3 = 5.83) conditions is significant beyond the .001 level, and the one between the means for the PACK 1 and the PACK 2 (X2 = 5.59) conditions, beyond the .01 level. 2

Furthermore, the analysis shows a significant first order interaction effect between Packaging and Brands (F = 3.65, df = 49522, p < .01). Because of the large number of multiple comparisons involved (36), the differences between the pairs of the nine following means are LSD tested using Fisher's least significance difference procedure (Winer 1971, pp. 199-200).


At the .05 level, the critical lsd value is 0.42 in this case. Among the 36 differences, 19 appear to be significant.

Finally, the second order interaction effect term is significant beyond the .05 level. In the perspective of the previous effects, this result merely accentuates the importance of the Packaging x Brands interaction.

This implication of the main effect results can be summarized as follows:

The taste of brand 1 or brand 2 is more popular than the one of brand 3.

Brand name disclosure induces a psychological added value on the perceived quality. Knowledge that the free samples are from well known national brands probably reduces or suppresses the respondents' anxiety level associated with a blind test situation. Similar evidence is reported by Allison and Uhl (1964).

Quality perception is homogeneous across the total market. Thus, the market segment shares and consumer attitudes do not seem to be related,at least for two of the three brands.

In order to grasp the complexity of the first order interaction effect between packaging and brands, table 3 is built. In the lower half-matrix, a star marks a significant difference between two means and an arrow points to the "winning combination".

In a first step, the intrabrands variations are considered across the packaging conditions. Brand 1 reveals itself as superior in its regular packaging than in the two other presentations. For Brand 2, the brand name image overcomes the blind test situation as does the regular packaging (See Fig. 1). For brand 3, no situation improves significantly its taste perception. Thus, Brands 1 and 2 differ from Brand 3 by improving themselves across the packaging levels. But, if for Brand 2 the main change is due to its brand name, for Brand 1 it appears to be due to its retail packaging. It seems that Brand 2 benefits from a better brand image than Brand 1, at least for this specific variety; but the converse being true in terms of retail packaging, the final situation places them at the same level of perceived quality.

The second step considers the intrabrands variations. If one looks just at Brands 1 and 2, one finds that their mean scores in the blind test are surpassed by the scores of the other in the remaining situations. As soon as the brand name of Brand 2 is revealed, it gets a better position than Brand 3. The same is true for Brand 1 except that its name alone has not enough impact for differentiating it from Brand 3 in its regular packaging [The analysis of the transformed ratings yields to the same results except that, in table 3, BlPl is significantly greater than B3P2 and B1P2 significantly greater than B3P3.].





As evidenced by the present study, both brand names and brand packaging do influence the consumers' quality evaluations. These are certainly not the only extrinsic cues influencing the perception of coffee quality. For example, in a study conducted in Michigan, Roberts and Taylor (1975) investigated with mixed results the effects of the visual cue of granule size on ratings of various coffee types. But here, only the first two cues were suspected to be potential troublemakers for the client firm.

In a managerial perspective, the finding that-brand and packaging images help the consumer in differentiating the brands, accentuates the importance of the various firms' marketing efforts, and more particularly, their interdependence. Furthermore, such an experiment determines the relative performance of the major competitors' brand image and packaging on the market. The fact that, in this case, the performance is not directly associated with the market shares of two brands, can be explained by the high level of satisfaction they both develop. In a situation of equivalent perceived quality, the "elder" firm benefits from the consumer "inertia". Extended promotional sales are probably a potential strategy for switching brand loyalty, especially for a product in the maturity phase of its cycle. Finally, this kind of analysis is useful for evaluating either the effectiveness of the advertising programs, or the adequacy of the existing forms of packaging.

In a consumer research perspective, additional results on multiple cue effects are necessary for a better understanding of the chunking phenomenon. With the growing interest in information acquisition, the chunking process appears to be a promising avenue. By selecting a limited amount of informational cues (intrinsic and extrinsic), the consumer could infer a configuration which would suffice for making his decision. Such a conceptualization corresponds to Sam Becker's "mosaic" model of human communication (1968) where numerous message bits are organized into a unitary whole which is never "final". Moving within the informational environment, the consumer is constantly adding, deleting, strengthening, selecting, and substituting message bits comprising the mosaic (Fisher 1978). How many cues (relatively meaningless isolated pieces in the mosaic) does an "expert" consumer need to form an organized whole? The identification of those "anchor" cues could be crucial for advances in consumer information processing.






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Benny Rigaux-Bricmont, Universite Laval


NA - Advances in Consumer Research Volume 09 | 1982

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