Analysing the impact of buyers' personality constructs on the market structure of brands.

Transcription

1 University of Aarhus From the SelectedWorks of Polymeros Chrysochou 2008 Analysing the impact of buyers' personality constructs on the market structure of brands. Polymeros Chrysochou Athanasios Krystallis Cam Rungie, University of South Australia Available at:

2 Analysing the impact of buyers' personality constructs on the market structure of brands Polymeros Chrysochou & Athanasios Krystallis, MAPP, Aarhus School of Business Cam Rungie, Ehrenberg-Bass Institute, University of South Australia Abstract In order to operationalize brand loyalty, various models have been applied that estimate brand measures and further describe patterns and the structure of the markets. A well known model in this area is the Dirichlet-NBD model. Despite major advancements to those models, how buyers' characteristics and psychographics influence actual brand measures and the overall market structure in repeat purchase occasions is still under-researched. Moreover, measuring the type and magnitude of buyer-related effects on brand loyalty could provide additional valuable information to brand managers. Aim of this paper is to provide an approach of estimating the effect that various personality constructs have on brand measures and overall market structure through revealed preference data. Introduction Research on brand loyalty from a repeat purchase approach has extensively aimed at describing the structure of the market and defining loyalty patterns. Various models, such as the Dirichlet-NBD model, have been applied and have been proved to explain reasonably well patterns and regularities of repeat purchase behaviour, as well as the overall market structure of brands (Ehrenberg et al., 2004). A criticism on these models is their inability to identify and explain the actual causes of loyalty. On the other hand, brand managers are anxious in getting a deeper understanding of such determinants that will further help in obtaining higher loyalty from their buyers. On the basis of such determinants, the concept of polarization has been used to explain the loyalty structure of brands based on various product attributes (Chrysochou and Giraud, 2007; Fader and Schmittlein, 1993; Jarvis and Goodman, 2005). This stream of research considers that a product category is formed of subcategories according to product attributes, and therefore each subcategory obtains different attribute-based loyalty levels. Implications from this type of approach have been relatively useful for exploring the effect of various product attributes on repeat purchase. A drawback of the above mentioned approach has been said to allow only the use of extrinsic (e.g. brand name, price) or even intrinsic (e.g. organoleptic characteristics) product attributes as determinants of repeat purchase. In other words, they lack in their ability to incorporate buyers characteristics for interpreting repeat purchase. The reason to this is that such studies are based on scanner data that do not allow for further exploring of such hypotheses. One way of overcoming this weakness has been provided by the use of Juster Probability Scale (JPS) estimates (Wright and MacRae, 2007; Wright et al., 2002). This scale has been shown to be a reliable alternative way of estimating brand performance measures through revealed preference data. Based on this approach, various demographic and psychographic characteristics could be used to explore repeat purchase. For instance, Uncles and Lee (2006) explored the impact of socio-demographic differences (i.e. age) in obtaining loyalty behaviour. The present study goes one step further by measuring the impact of psychographics on brand repeat 1

3 purchase. To achieve this, the Repeated Binary Logit (RBL) model is used (Rungie and Laurent, 2005). The RBL is an extension to the traditional logistic regression that is constructed from the Negative Binomial Distribution, on which a generalized linear model estimates the impact of covariates (for a detailed review of the model and its estimations see Rungie and Laurent, 2005). Aim of this paper is to provide an approach of estimating the effect that various personality constructs might have on loyalty measures and overall market structure through revealed preference data. The fruit juice category was selected as an exemplary one for the aims of the present study. Personality constructs tested are product category involvement, familiarity and variety seeking tendency, as well as overall loyalty proneness and innovativeness. Such psychographic measures are hypothesised to have a potential to influence brand loyalty behaviour. Moreover, as buyers become more health conscious in their dietary choices (Grunert and Wills, 2007), extrinsic food brand attributes related to health (i.e. freshness and enrichment) that may have an impact on repeat purchase behaviour are further investigated. Method and Data For the purpose of the study, a survey is conducted on a convenience sample (N=257) drawn in the metropolitan area of Attika, Greece, in Market structure (i.e. the top 13 brands) of the fruit juice category is analysed through JPS. Furthermore, the brands measured are categorized according to two health brand related cues, namely freshness and enrichment. Same way of analysis is followed for both attribute categories. In the next step, the Juster estimates are used as inputs to derive theoretical Dirichlet predictions of brand performance and test their goodness of fit. For this purpose, the DIRICHLET excel spreadsheets is used (Kearns et al., 1998). Overall, the Mean Absolute Deviation in Penetration of all brands of is considered to indicate an acceptable fit (Ehrenberg et al., 2004). The description of each brand and the extracted market descriptive results as depicted from the Juster estimates are shown Table 1. In brief, the market can be characterized as a repertoire market, with an average penetration of 15.0% and purchase frequency of 2.0 times for the selected period of 4 weeks. In the second part of the study, personality constructs (covariates) are measured, following the aims of the study described above. The constructs used as examples are involvement in the product category (5-items; e.g. "I generally have a strong interest in this product category"; Beatty and Talpade, 1994); familiarity with the product category (3-items; e.g. "In general, I consider myself very familiar with the product category"; Oliver and Bearden, 1985); variety seeking within the product category (2-items; e.g. "I enjoy buying another brand of the product category just to get some variation in my purchases"; Jensen and Hansen, 2006); as well as: overall buyer loyalty proneness (5-items, e.g. "I generally buy the same brands I have always bought"; Burton, 1998); and innovativeness (3-items, e.g. "I am often among the first people to try a new product"; Ailawadi et al., 2001). All covariates are measured on a 7-point Likert type scale (1 = totally agree to 7 = totally disagree). Descriptive statistics for each scale are as follows: involvement (M = 3.20, SD = 1.28, α = 0.891); familiarity (M = 3.54, SD = 1.42, α = 0.873); variety seeking (M = 4.22, SD = 1.47, α = 0.693), 2

4 innovativeness (M = 3.06, SD = 1.19, α = 0.836), and loyalty proneness (M = 3.88, SD = 1.24, α = 0.919). Table 1 Brand description and market structure analysis Market a/a Enrichment Freshness Share Purchase Frequency Penetration Repeat Rate Juice 1 Functional Long life Juice 3 Conventional Fresh Juice 6 Conventional Fresh Juice 7 Conventional Fresh Juice 2 Conventional Long life Juice 10 Conventional Fresh Juice 9 Conventional Long life Juice 11 Conventional Fresh Juice 5 Conventional Fresh Juice 12 Conventional Long life Juice 8 Functional Long life Juice 13 Functional Fresh Juice 4 Conventional Long life Average Brand Functional (3 brands) Fresh (7 brands) Results and Discussion In the following tables, the RBL model results are presented. Table 2 includes the changes in market share when each covariate changes from one standard deviation below the mean to one standard deviation above the mean. In Table 3, the changes on repeat rates are presented and interpreted accordingly. For example, for Juice 1 involvement has a significant positive effect on market share of 6.4% and on repeat rate for 13.6%. In other words, the less involved buyers are in the product category (i.e. as involvement decreases from one standard deviation below the mean to one standard deviation above the mean) the market share and repeat rate of Juice 1 will increase significantly (i.e. from 3.2% below the mean to 3.2% above the mean, that is from 32.7% to 39.1%). It is worth noting that involvement has an opposite effect on small share brands - except for Juice 12. This result could be interpreted as an alternative way of exploring the natural monopoly effect (McPhee, 1963), which suggests that big brands monopolize buyers who buy less, therefore being less involved in the category. Some general conclusions could be drawn for the category. Overall, each construct has a significant effect on market share and repeat rate on at least one brand, indicating the accuracy of their selection as exemplary personality constructs with an impact on loyalty behaviour. Loyalty proness and variety seeking have inversed effects on market share and repeat rate, something expected as those constructs are negatively correlated (r = ; p = 0.000) and are personality traits of 3

5 opposite nature. On the other hand, involvement and familiarity have the same effects, as they are positively correlated (r = 0.692; p = 0.000) and have the similar conceptual basis. Table 2 Changes in market shares Market Brand Involvement share Familiarity Variety seeking Loyalty proness Innovativeness Juice * * -11.5** 13.0** Juice *** * 4.6*** Juice * -0.5 Juice ** *** -0.5 Juice ** -2.0** -1.5** Juice * 2.8*** -0.1* -2.2 Juice * Juice * -1.0* * Juice ** -0.8* -3.8** 2.4** -2.2** Juice *** 2.2** -4.3*** * Juice *** *** Juice * -0.6 Juice *** *** Functional 4.0** ** -13.7** 13.7*** Fresh -3.8** * 6.6* -6.0** Note: * p < 0.05; ** p < 0.01; *** p < The impact of each construct on market share is not consistent across all brands. This means that each brand behaves differently within the category. However, some patterns can be identified in the case of variety seeking, where, as buyers become less variety seekers, the influence on small share brands is negative and on big share brands is positive. In other words, the more buyers look for different brands within the product category, the more chances there are that they will buy smallshare brands. In the case of repeat rate, the impact of the constructs seems to be more consistent across brands. Variety seeking and familiarity have a positive effect, whereas loyalty proneness has a negative effect. This could be interpreted as follows: the less involved and familiar buyers of the category are, the more loyal they will become to certain brands. Moreover, loyalty proneness could stand as a study s validity measure, since its effect across all significant brands is the same (i.e. the less loyal, the smaller the market share and the lower the repeat purchase rate). Therefore, the more loyaltyprone buyers are towards a brand, the higher loyalty levels this brand will obtain. When it comes to attribute-based sub-categories (fresh and functional juice brands), results are also quite appealing (see last two lines in Tables 2 and 3). The impact of the personality constructs is different in changes of market share between the two sub-categories and the same in changes on repeat rate. Therefore, the behaviour of those two categories can be explained differently by means of buyers personality traits. In the case of market share, the more buyers are involved and seeking variety within the functional sub-category, the less they buy such brands, thus switching to conventional ones. Moreover, the 4

6 more innovative they are, the less they buy functional brands. Opposite results can be drawn for the fresh brands. Table 3 Changes in repeat rate Brand Repeat Variety Loyalty Involvement Familiarity Rate seeking proness Innovativeness Juice * * -16.7** 17.2** Juice ** -27.2** 10.2** Juice *** * 29.5*** Juice *** *** Juice ** 10.7* -1.2** -8.6** 7.2** Juice * 9.2 Juice ** *** 13.3 Juice *** *** Juice * Juice * 34.1*** -16.9* -5.1 Juice * 10.0* * Juice *** 24.3** -22.6*** * Juice * 6.5 Functional 14.9** ** -16.9** 19.7*** Fresh 5.6** * -2.0* 3.6** Note: * p < 0.05; ** p < 0.01; *** p < Finally, in the case of repeat rate, the effect of the personality constructs is the same between both attribute sub-categories. However, the effect is stronger in the case of functional brands across all significant constructs. If we consider that both categories have equal repeat rates (see Table 1) it seems that functional brands are more sensitive in changes of personality traits of their buyers. Conclusion In this paper, a way of measuring the effect of buyers psychographic constructs on repeat purchase behaviour is presented. From a theoretical perspective, this approach provides an alternative and rather straightforward way of measuring the impact that buyers personality traits have on the market structure of product categories. From a managerial perspective, this approach provides further insight to brand managers about their customers loyalty behaviour. In this respect, it allows for drawing marketing strategies based on characteristics of consumers that may have a greater impact on their brands performance. Limitations of the present study also exist that pose recommendations for further research. First of all, there is a need of bringing in more product categories so that to explore the consistency of each covariate s impact on repeat purchase behaviour. Moreover, the assumption of unsegmented market, which the Dirichlet model rests on (Fader and Schmittlein, 1993), could be further explored, as the effect of each covariate might differ across segments. Therefore, future research based on this approach could investigate the role that such personality constructs play on different segments and especially among buyer target groups. 5

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