Table
2 shows the parameter estimates for the model outlined before.
Pre-crisis loyalty has a significant (
p < 0.01) positive impact on trial for both Eta and Kraft. This supports earlier experimental findings that loyal customers are less sensitive to negative news (Ahluwalia et al.
2000), and is in line with Campo et al. (
2000) that loyal customers switch less in an out-of-stock situation due to higher substitution and search costs. This protection is found to gradually erode, however, as indicated by the negative
interaction between loyalty and time (
p < 0.01). The parameter estimates for
pre-crisis brand familiarity are significantly negative (
p < 0.01 and
p < 0.05 for Eta and Kraft, respectively).
9 This finding confirms that product experience can trigger defensive strategies against negative information on the brand (Ahluwalia et al.
2001), although this applies mostly for recent purchases because of forgetting (Mehta et al.
2004). The effect of
pre-crisis category usage on the probability of trial is significantly positive (
p < 0.05) for both Eta and Kraft. Heavy users are less inclined to cancel their purchases, as they are more familiar with the benefits of the product (Lim et al.
2005), and have lower perceived risks than light or medium users (Goering
1985). Apart from the category usage before the crisis, also the
change in category usage during the crisis is important. A reduction is indicative of the extent to which trust in the category as a whole is lost. A positive effect (causing a delayed trial if the usage rate is reduced) is obtained for both brands, even though statistical significance is only obtained for Kraft (
p < 0.05).
10 In terms of the
cross-purchase effects, an interesting asymmetry is observed. While a purchase for the stronger brand (Kraft) delays (
p < 0.05) the subsequent trial of the smaller brand (Eta), no such effect is observed when Eta was first purchased. Strong brands are known to impact competitors extensively, while their vulnerability is typically low (Kamakura and Russell
1989).
Competitive purchases did not (
p > 0.10) delay the purchase of either brand. As such, the two opposing forces (i.e. a negative feedback and a positive trust effect) seem to result in a non-significant net effect. While
own advertising has a significant positive effect on the trial probability of Kraft (
p < 0.05), advertising expenditures for Eta are not effective in stimulating Eta’s post-crisis trial rate (
p > 0.10). Using aggregate analyses, and focusing on the total sales impact rather than trial, van Heerde et al. (
2007) also obtained a non-significant own advertising effect for Eta, and a positive post-crisis advertising effectiveness for Kraft. Not surprisingly, as cross-effects tend to be smaller than own effects, Eta was not helped by Kraft’s advertising either, while it also did not have enough clout to create a positive spill-over to Kraft. With regard to
competitive advertising from non-affected competitors, we find a negative effect for both Kraft (
p < 0.05) and Eta (
p < 0.10). This implies that competitors probably used their advertising more to persuade consumers to purchase the advertised brands than to re-establish trust in the category. In unreported analyses, we checked for interaction effects between these advertising variables and the aforementioned individual-level characteristics. No such evidence was found.
Table 2
Empirical results
Pre-crisis brand loyalty | + | 0.015c (0.005) | 0.017c (0.004) |
Interaction between pre-crisis brand loyalty and time | – | −1.7e−05c (7.6e−06) | −1.8e−05c (7.5e−06) |
Pre-crisis brand familiarity | +/− | −0.007c (0.002) | −0.003b (0.001) |
Pre-crisis category usage | + | 0.022b (0.012) | 0.027b (0.014) |
Change in category usage | +/− | 0.050 (0.108) | 0.107b (0.052) |
Cross purchases | +/− | −0.018b (0.008) | 0.011 (0.012) |
Competitive purchases | +/− | −0.001 (0.002) | −0.003 (0.005) |
Own advertising | + | −0.261 (0.178) | 0.107b (0.055) |
Cross advertising | +/− | 0.009 (0.088) | 0.164 (0.129) |
Competitive advertising | +/− | −0.090a (0.051) | −0.063b (0.028) |
Control variables |
Area | +/− | 0.239 (0.470) | −0.210 (0.349) |
Household size | + | 0.099a (0.066) | 0.078b (0.044) |
Inventory | − | 0.013 (0.039) | −0.090c (0.032) |
Finally, two of the control variables turned out to be significant. Inventory has the expected negative sign for Kraft, while the parameter estimate for household size is significantly positive for both brands, supporting the idea that larger households purchase more frequently. The place of residence had no significant effect on the trial probabilities.