Track: Branding. Keywords: Brand Image ... attributes will be mentioned more frequently across all brands than other attributes. (Romaniuk and Sharp 2000).
EXPECTED PATTERNS FOR NEGATIVE IMAGE ATTRIBUTES Maxwell Winchester and Jennifer Romaniuk University of South Australia Track: Branding Keywords: Brand Image, Negative Brand Image Attributes, Prototypicality, Brand Size, Replication Abstract Substantive research has uncovered generalised patterns in positive (or at least nonnegative) brand image responses. However there has been little systematic research as to what extent these patterns also hold for negative (i.e., undesirable) image attributes. In this paper we report on two such patterns. The first of these is that negative attributes that rank highly for one brand typically do so for all brands. This is analogous to research on prototypicality (Rosch and Mervis 1975). It appears that association with a negative image attribute may generally be a characteristic of the category (eg, all fast food brands are considered to be ‘high in fat’) rather than specific to any brand (eg, McDonalds is considered ‘high in fat’). The second of these patterns is related to brand usage and negative image attributes. It has been long known that there is a relationship between positive image attributes and market share (number of users). This study presents the surprising result that often, larger brands (rather than smaller brands) received more negative attribute responses. This insight into generalised patterns allows us to set benchmarks for what to expect from negative image attributes. However, further work needs to be conducted to uncover any generalisable patterns between brand size/usage and propensity to give a negative attribute response. Introduction The prevalence and costs associated with brand image measurement suggests that, at least in a Marketing Manager’s eyes, this area is one of the most important research areas that a firm can undertake (DiMingo 1988; Light 1998). A number of studies have discovered underlying patterns in brand image responses, that when combined and understood, can be used to establish expected values for a brand on any attribute. Two of these key patterns are (1) big brands will be more commonly associated with any image attribute than small brands (Bird and Channon 1970) and (2) some attributes will be mentioned more frequently across all brands than other attributes (Romaniuk and Sharp 2000). The majority of this research has been conducted on non-negative attributes. This is not surprising, given that the majority of image building activities and image measurement is focused on building positive aspects of the brand. However, there have been recent calls for the need to investigate negative brand image attributes further (Hoek, Dunnett et al. 2000; Winchester and Fletcher 2000). Companies have been generally measuring attributes they are trying to achieve, using attributes such as “produces products of the highest quality” and/or “offers worldwide support”. Negative Image Attributes
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A ‘negative’ brand image attribute is one that represents qualities of the brand considered to be undesirable. An example of this would be in financial services in the attribute of “high fees and charges”. In practice, very few companies bother to measure negative attributes. This is possibly due to a fear of having their brand being revealed from a negative point of view from their customers and/or the market. The lack of knowledge of how to interpret negative image attribute information is another possible contributing factor. Without guidance about what to expect there is the risk that all negative attribute responses will be considered alarming and cause undue concern. Recently, however, attention in other areas of marketing have recognised that the negative aspect of a construct may need separate consideration. For example dissatisfaction is considered to be separate from a lack of satisfaction (eg, LaBarbera and Mazursky 1983) and ad irritation considered distinct from likeabilty (eg, Greyser 1973; Aaker and Bruzzone 1985). Therefore it is timely to consider negative brand perceptions and examine the extent to which they are diametrically opposite to nonnegative brand perceptions or a separate construct. One way to gain some insight into this is by drawing on prior knowledge for non-negative image perceptions and seeing if the same pattern holds for negative image perceptions. Exploratory prior research suggests that negative responses follow different patterns to positive responses (Bird, Channon et al. 1970; Riquier and Sharp 1997; Romaniuk and Sharp 1999). However, given the comparative weight of prior knowledge in non-negative brand perceptions, our hypothesis is a null hypothesis. The patterns for negative attributes will replicate those found with positive attributes. Typicality One of the identified attribute-based patterns in non-negative image responses is that an attribute that gains a higher response level than other attributes for one brand, will generally gain a higher response level than other attributes for all brands. This pattern, based on frequency of mention of an item, has been referred to as a measure of the extent to which the attribute contributes to category membership or prototypicality (Rosch 1978). Prototypicality is the ‘belongingness’ of a brand attribute to a certain market. For example, the brand image statement “low fat” would be an attribute that could be prototypical to the yoghurt market, but not fast food; in that we expect brands in the yoghurt market to have that quality, but have less of an expectation in fast food. Consumers deem what is prototypical, by what they are familiar with in a category; when they experience a new brand, they categorise it on what they think is prototypical, based on their previous experiences in that market (Ward, Bitner et al. 1992; Romaniuk and Sharp 2000). The value of establishing this pattern is that it allows us to determine to what extent association with a negative attribute is category, rather than brand, determined. This knowledge will allow us to determine when responses to negative attributes are unusual in any given market.
Usage It has long been acknowledged that big brands gain higher response levels in image studies than small brands (Bird and Ehrenberg 1970). This is because big brands have more users and users are more likely to respond positively about a brand (or indeed respond at all) than non-users. However little systematic study has been undertaken
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to determine if the same usage bias is evident for negative brand attributes, and what has been done provides conflicting evidence. Are users, by virtue of their knowledge of the brand, also more likely to respond negatively about a brand than non-users? Or is it that non-users have negative perceptions about a brand, which can be taken as an indicator of rejection? Top of mind association with a negative attribute (eg, “most expensive”) has been found to be linked to least favourite store (Woodside and Trappey 1992). Such a finding is in line with the common belief of brand evaluation during the purchase process. In terms of this study, we would expect to see the reverse pattern occur for negative image attributes than has been seen for positive image attributes (ie. That small brands would get higher levels of response because there is a larger number of people ‘rejecting’ them). Results from a study by Bird and Channon (1970) indicate that while there were notable differences in positive image attribute response levels between respondents who had used, or never tried a brand, there was little difference across groups in response levels to negative brand image attributes. Usage in their study was determined by claimed usage within the past four weeks. We plan to extend these studies to better understand the relationship between the number of users a brand has and the response levels to negative image attributes. Romaniuk & Sharp (1999) confirm this finding. They found that negative attributes acted similarly to descriptive attributes, in that users and non-users were equally likely to mention the brand, suggesting there would be little difference in response patterns for each users and non-users. Research Method To identify the patterns under investigation, we have ordered the table of brand and attribute responses for each market, and subsequently conducted Spearman’s correlations on the ranked scores (both brand order and attribute order). A key criticism that has been put forward of many studies conducted in the marketing discipline is that there is very little replicated, generalisable research conducted (Hubbard and Armstrong 1994). The absence of replication studies is seen to be impeding knowledge development in marketing (Hubbard, Brodie et al. 1992). Hubbard et al (1992) outline a number of consequences that can arise from not replicating studies in marketing. These consequences, including type one error bias, perpetuate erroneous results. To triangulate findings and avoid the possibility of exceptional one-off results, in this study we have investigated the patterns in three different industries; in both repertoire and subscription markets; in business to business and business to consumer markets; and using different methodologies to elicit brand images. To avoid errors associated with sample size, brands with market shares lower than 5% were removed from the analysis.
Results To assess the patterns of negative image attributes, we ranked attributes and brands for three markets in order of magnitude. The results from the business banking market are outlined below in Table 1.
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Table 1: Order of prototypicality and brand ranking in the Business Banking Market (n=525) Province Regional Empire Bank Bank Bank Bureaucratic Impersonal bank Old fashioned High risk bank
Country Western Bank Bank
Local Bank
Large Intern.
18 21 9
31 27 6
29 32 6
35 34 5
32 31 4
14 12 6
16 13 1
5
4
2
3
3
3
5
Brand Ranking 0.32 (p=0.34) 0.36 (p=0.36) 0.63 (p=0.13) -0.03 (p=0.94)
Attribute Ranking Spearman’s Rho 0.80 1.0 0.80 1.0 1.0 1.0 1.0 (p) (p=0.20) (p
