consumer confidence levels had an effect on the brand liking scores, the parameter estimates of the direct effects are added to the interaction parameter estimates. This was done to account for the direct and the moderating effect, which has separate parameters, though both include effects that influence the liking score simultaneously.
The interaction effects between hedonistic motives and the consumer confidence level were as follows:
Audi (β = .012, p < .05), Peugeot (β = .015, p < .05) and Seat (β = .007, p <
.05) showed positive results. This results in the assumption that when consumers are more interested in hedonic motives for choosing a car, during an upward period of time in terms of consumer confidence levels, the brand liking scores positively increase. The largest combined effect is for Peugeot with a positive beta of .029.
Utilitarian motives moderated by consumer confidence levels showed a positive result on the interaction effect with the following brands: Mercedes (β = .023, p < .01) and Volvo (β = .002, p < .05). On the other hand, for Suzuki (β = -.008, p <
.05) the effect is negative, indicating that during an upward period of time compared to the previous period, the brand liking score decreased with .008 points when consumers are focusing on utilitarian motives.
Ecological motives moderated with confidence levels only showed a negative result for Ford (β = -.028, p < .05). This means that Ford gets a decrease in the liking score during upward periods of time when the focus is on ecological motives. The combined effect for this is an increase of .002 points, which is a small effect on the brand liking score of Ford.
Figure 4 shows a clustered bar chart where the 18 brands are presented with their yearly average liking scores. This figure shows that especially for Ford, Renault, Toyota and Volkswagen a positive trend in the liking scores emerge. Contrary, a clear negative trend can be seen for Citroen, Fiat and Nissan. To see whether this had to do with the green trend, the annual ranking of the top 50 Global Green brands is used.
The results will be compared to the outcomes of males; it will therefore be discussed at the end of this chapter. Furthermore, to see what females see as the most popular car brands, the top 3 brands regarding their brand liking score will get a closer look when taking this green trend into account. These brands are: Opel, Volkswagen and Toyota.
4.3.3 Insights for males: direct effects
For males the same model has been estimated, however due to autocorrelation issues in some of the models an extra variable in the form of a lagged variable of the dependent variable needed to be added to account for autocorrelation. This was necessary in 5 of the models otherwise the Durbin Watson statistic gave positive autocorrelation for the residuals as an outcome of the model. To account for the extra lagged variable, the Durbin h statistic was used to see whether there was still a problem with autocorrelation. The outcome of the tests showed that the residuals were not correlating with each other. The direct effect of hedonic motives had a positive effect on the following brands: BMW (β = .012, p < .05), Hyundai (β = .007, p < .05), Mercedes (β = .008, p < .01), Seat (β = .007, p < .01) and Suzuki (β = .005, p < .05).
Figure 4: Clustered bar chart with yearly liking scores
For males the hedonic motives can also have a negative effect on the brand liking score, this was found for the brand Ford (β = -.015, p < .05). The largest effect for hedonic motives was for BMW with an increase of .012 points. In total, hedonic motives seem to have either a positive or negative effect for only 6 out of 18 brands.
The utilitarian motives showed positive effects for Audi (β = .039, p < .05), Citroen (β = .015, p < .01), Fiat (β = .007, p < .01), Hyundai (β = .011, p < .01), Nissan (β = .007, p < .01), Skoda (β = .009, p < .05) and Suzuki (β = .005, p < .05).
Also here, negative effects were present for BMW (β = -.019, p < .05). This indicates that utilitarian motives have a negative effect on the brand liking score of BMW. The largest positive effect is by far for Audi with an increase in points of .039. In total, males find utilitarian motives important for 8 brands, either positive or negative.
Ecological motives showed positive effects for Citroen (β = .010, p < .05), Fiat (β = .013, p < .01), Ford (β = .017, p < .05), Nissan (β = .007, p < .05), Renault (β
= .018, p < .05), Seat (β = .010, p < .05), Suzuki (β = .010, p < .01) and Volvo (β = .027, p < .05). For 8 brands, ecological motives showed to have positive effects on the brand liking score with Volvo having the largest effect, which is almost as large as its average liking score (.027 vs. .029).
The consumer confidence levels showed a negative effect for Ford (β = -.006, p < .05) and a positive effect for Volvo (β = .020, p < .05). When the economy is in an upward period of time, the brand liking score of Ford does not benefit from this whilst Volvo does.
To see whether the passing of time had an effect on the scores, the trend line tells if there is a significant difference over 4 years. This trend shows positive results for BMW (β = .00008, p < .05), Ford (β = .000, p < .01) and Hyundai (β = .000, p <
.05). A comment must be made here is that the effects are very small. However, the liking scores do significantly change over time, which can also be seen in figure 5.
Nevertheless a negative effect would have been expected for Ford and Hyundai since these were in a decline compared to BMW, which gained in their liking score over the years.
The lagged first preference of the consumers also showed some positive effects for Seat (β = .126, p < .05) and Suzuki (β = .115, p < .05). This indicated that the preference of the previous period had a positive effect on the liking scores of Seat and Suzuki.
4.3.4 Insights for males: interaction effects
Also here, the interaction effects for males will be added to the direct effects to interpret the combined effect of the factors during a certain period of time in the economy. Hedonic motives seemed to have a positive effect on Fiat (β = .007, p <
.05) only. Whenever the economy is in an upward period of time the brand liking score of Fiat increases with .007 points. Regarding utilitarian motives, these do not have a moderating effect in combination with the consumer confidence level. Males do not change their preferences for any of the 18 cars during a decline or upward period of time. The ecological motives showed a positive result for Volkswagen only (β = .017, p < .05). Since the direct effect of ecological motives has a negative effect and the combined effect has a positive effect, the ecological motives during certain economic periods can be seen as an important driver in the liking score of Volkswagen.
Figure 5 shows the yearly average liking scores to get a clear view on the changes per year. It can be concluded that many of the brands were very stable over the years. However, clear increases can be seen for Audi, Volvo and Volkswagen. A negative trend has been detected for Citroen, Fiat, Ford, Opel and Toyota. The 3 most popular brands for males are: Volkswagen, Audi and Ford.
Figure 5: Clustered bar chart with yearly liking scores
4.4 Added Z method: weighted betas for variables
With the individual brand estimates, advice on what factors they should focus regarding targeting can be given to the specific car brands. However, weighted betas can tell something about the effects across all brands, which could in turn give advice to the whole industry. First, the results for females will be discussed; these can be seen in table 4. Only for the direct effects, the factors, a significant p value was found and therefore a weighted beta was calculated. The associated effect size was calculated by retrieving the weighted average response parameters across the included brands. The weight that was used, is the inverse of the standard error of the estimates (Rosenthal, 1991). This results in the ability to conclude that in the automotive industry all motives had a significant effect on the brand liking scores. Taking the individual estimates into consideration, the brand specific effects can tell companies something about how to advertise their cars. For females, overall, hedonic motives had the largest effect (β = .001, p < .01). Therefore the look of a car seems to be the most important for females. After the looks, the price and quality of the car were the most important factors (β = .009, p < .01) and finally, females care the least about the environmental friendliness of a car (β = .006, p < .01).
Males showed significant effects for all 3 factors as well, however also the ecological motive in combination with the consumer confidence moderator showed a significant effect. Hedonic motives had the smallest effect on males (β = .004, p <
.01), followed by utilitarian motives (β = .005, p < .01). This led to the conclusion that the largest effect in the brand liking score is due to ecological motives (β = .008, p <
.01). Males are therefore more focused on cars that are environmentally friendly then that they have a stylish look or have a good price/quality ratio. In combination with the consumer confidence levels, ecological motives also have a significant effect across all brands (β = .05, p < .05). Moreover, time has a positive effect on the liking score across all brands (β = .008, p < .01).
Table 4: Weighted betas for females across brands
Figure 7 shows the importance of motives per gender. This visualizes the number of brands that are found important per factor in choosing a car preference. It gives a clear view on the fact that females find the look and style of a car the most important factor whilst men find a car that is good for the environment more important.
4.5 Green classification
The data of Interbrand (Interbrand, 2015) showed the yearly ranking of the top 50 global green brands in the world. To see whether an increase in brand liking scores can be related to the ranking of a green car brand, or in what way females and males differ in their top favorite car brands, a representation of 4 years of data has been visualized in figure 8. A decline in the bars is seen as a positive effect since this means a brand gets closer to the top of the ranking list. In total, over 4 years of time, 8 car brands that are used in this research are represented in the list. The top performing brand is Toyota which is very consistent being number 1 for years and has only dropped to the second place since 2014. The first place has been taken over by Ford, who has climbed from place 20 in 2011. Volkswagen on the other hand is one of the
Table 5: Weighted betas for males across brands
0 2 4 6 8 10 12 14
Hedonic
motives Utilitarian
motives Ecological motives
Number of brands
Females Males
Figure 6: Difference between females and males in importance of factors
brands that has been dropping in the list, same holds for Mercedes and Hyundai.
Brands entering the list and getting closer to the top are; Nissan, which has great improvements over the years and Kia, which has just entered the list in 2013. BMW is one of the stable brands around the top 10 of the list and has been on the same spot for two consecutive years.
When linking this data to the outcomes for females, their top three consisted out of Opel, Volkswagen and Toyota. Out of these brands, 2 are represented in the list, which means females slightly favor brands that have a focus on being green.
Looking at the outcomes of the regression analyses, the brands that had significant results for ecological motives were: Ford, Hyundai, Mercedes and Volvo. Also here, 3 brands are represented in the list which means females do favor green motives in choosing cars. Comparing this to males, their top 3 car brands were: Volkswagen, Audi and Ford. Same as for females, 2 brands are represented in the list. Remarkable here is the fact that females favor the Toyota brand which is currently number 2, though males favor Ford which is the top leader at the moment. Regarding the significant ecological motives for males, the following brands showed positive results: Citroen, Fiat, Ford, Nissan, Renault, Seat, Suzuki and Volvo. As can be seen in figure 7, 2 brands are represented in the list: Ford and Nissan. From this it can be said that women tend to focus more on green cars that also have this label in society.
Males on the other hand, favor ecological motives more, however do not seem to focus on whether this is also recognized by a ranking list.
Figure 8: Ranking Top 50 Best Global green brands according to Interbrand (2015).
4.6 Added Z method: Green brands versus brown brands
To see whether green brands as a whole were significantly preferred due to ecological motives compared to hedonic or utilitarian motives, a new approach is used. The 18 brands are divided in two segments; green versus brown car brands. The segmentation of these brands is visualized below in table 6. The green segment includes the 8 brands that are placed in the ranking list of Interbrand, whilst the brown brands are not and therefore not known in the industry for their green efforts. For these segments, two separate added Z models were estimated to analyze the effect for green and brown brands. Again here, the added Z method was calculated by recalculating the Z-score for each brand-specific p-value for the three factors (the other variables are not included in this method since they showed insignificant results before).
Subsequently the Z’s were summed and divided by the square root of the number of included brands (8 vs 10). This new Z-score was used to derive the associated p- values per variable. When this gave significant results, the associated effect size was calculated by retrieving the weighted average response parameters across the included brands. The weight that was used is the inverse of the standard error of the estimates of the three factors (Rosenthal, 1991). This gave the following results for the green and brown segment for females:
Table 6: Segments
Table 7: Weighted betas for females across green brands
Table 8: Weighted betas for females across brown brands
Table 7 shows that for green cars the largest effect on the brand liking score was not due to ecological motives, though due to utilitarian motives (β = .01, p < .01).
This is remarkable since hedonic motives were expected to have the largest effect.
However, in the results presented before, hedonic and utilitarian motives were close in the amount of effect they have. The expected effect (table 8) of hedonic motives is found in the segment of brown cars (β = .01, p < .01); here the ecological motives did not even found a significant effect. Indicating that for females the largest effect, in the green segment, for increasing the brand liking score is due to utilitarian motives.
Brown brands on the other hand still benefit the most from the focus on hedonic motives in car preferences.
For males the three factors are used as well to see the generalized effect of green and brown cars. The analysis was performed the same way as described previously. The outcomes are shown below in table 9 and 10.
The outcomes for males with regards to the green brands are shown in table 9.
Here it can be concluded that for males, indeed, it is very important to focus on the ecological motives in the green brand segment (β = .005, p < .01). The least important factor to focus on when advertising green cars is the utilitarian perspective the car has.
For brown brands, shown in table 10, it is still important to focus on the ecological features the car has, since this has the largest effect on the brand liking score (β = .012, p < .01). Here the smallest effect can be found for hedonistic motives regarding car preferences. This indicates that males definitely focus more on the green aspect of
Table 9: Weighted betas for males across green brands
Table 10: Weighted betas for males across brown brands
a car, and that the focus on this aspect significantly helps in increasing the brand liking score.
This research investigated whether it would make sense to start advertising gender specifically within the automotive industry. This study also included the effect of economic conditions, in the form of consumers’ confidence levels, and its effect on liking scores of car brands, using a data set comprising 4 years of consumer preferences during different economic conditions.
Multiple moderated time series regression models were estimated that provided insights in the direct and moderating effects of the chosen variables and its effect over time. Furthermore, these effects were generalized to give advice to the industry instead of to the separate brands. Finally, a comparison has been made between the way females and males react on the “green” trend and the environmental friendly initiatives.
The results showed that the importance in factors significantly differ according to gender. This is not only proven at a brand-individual level, also with the added Z methods significant results were found. The economic condition on the other hand, especially for females, does not give positive results. In contrary, upward conditions give negative results for a brand’s liking score. Also, the interaction effects are not present in many cases. This can be observed more for males than for females, therefore it seems that males care less about the economic conditions in combination with the factors they find important. This is in line with what was found in literature, namely that females take more decisions regarding money spending and therefore care more about the economic condition (Sandberg, 2014). Moreover, the effect of time is not the same across the two samples. Males do significantly increase in liking the brands, whilst females do not show any significant results. Finally, males show more significant results in the added Z methods, and can therefore be more generalized across the industry compared to females’ outcomes. The proposed hypotheses and whether they are accepted or not are summarized in table 10 on the next page.
5.2 Managerial implications
With the increasing demand of consumers in receiving customized products and services, firms are under pressure in delivering these demands. This is more easily to do with goods that are sold for the short term since these can be adapted sooner, whilst cars, which are not easy to adapt quickly, are sold for the long term. In order to be attractive for potential customers, a clear and appealing marketing strategy is necessary. The main difference with products for the short term is that you can buy them and try them out, whilst this is a whole other story with long-term goods such as a car. The findings in this research give guidance to managers in how to properly attract potential buyers by providing insights in what matters in an advertisement of a car. This research offers some answers to this question.
Regarding effective advertisements for females, it becomes clear that hedonic motives are by far the most important. Females tend to focus more on the looks of car, and in this research this is the case for 12 out of the 18 brands. Companies are wise to put these elements in a clear and prominent way in their advertisement. Also, when companies are aware of the economic situation, during an expansion it wise to advert these factors that relate to the look of a car even more since this increases the effect significantly. The individual brand-level results and its impact on the liking scores can be used for brand-specific advice on effective advertising. After the hedonic motives, companies should focus on utilitarian characteristics of a car since this also has a significant positive result on the liking score of females. In total, 10 brands benefit from the focus on these characteristics, thus price/quality ratios and low costs in
Table 10: Proposed hypotheses and outcomes
maintenance are elements to place in an advertisement. The least amount of importance should be on the ecological characteristics of a car since this has the least amount of effect. On the contrary, females do tend to favor green cars over brown cars regarding their top brands, however this is not significantly proven to be due to ecological motives. Companies that can be found in the top 50-ranking list of green efforts, should focus on promoting the utilitarian characteristics, whilst the cars that are not in the list should still focus on the hedonic characteristics in order to increase the liking score. Since the consumer confidence levels do not have an effect on the liking score, it is not necessary for companies to implement a cyclical changing advertising strategy. Companies are not advised to change their advertisements during economic downturns or expansions since this is not proven to be effective in this research.
Males on the other hand do benefit from a different marketing strategy. The results of males indicate that the most important characteristics of a car are in the nature of ecological characteristics. Expected was the importance for the utilitarian characteristics of a car, which does has a shared amount of importance in the number of brands with ecological motives. Effective marketing strategies should focus on the
“green” characteristic of a car combined with the utilitarian characteristics. This means that advertisements that state that their car is environmentally friendly and saves money since there is less costs, is very effective in attracting males to like that specific car. Hedonic motives are the least important for males; therefore the advertisement should not focus solely on the look or style of a car. Car brands in the green segment are wise to pay attention on prominently advertising the green aspect since this has the highest effect in increasing the brand liking score. Where the economic situation does not matter for advertising to females, it certainly does for males. During economic expansions the focus on ecological characteristics should be even higher since this enlarges the overall effect on the liking score of that brand.
This is possibly due to the fact that more money is available to buy a more expensive car and males seem to be less concerned with the expenses and costs it may bring compared to females (Sandberg, 2014). Males favor cars that can be found in the top 50-ranking list as well, therefore advertising their brand with the link to this ranking can enhance the liking score as well. The liking scores of males also differ over the
years, which means advertisements that change cyclically and are targeted well, increase the liking score of the brand as well.
The results in this research can help companies identify the right strategy for their brand. For all factors that have been analyzed, 18 brands can gain knowledge in what is the most important for them. The conclusions given here are based on the weighted effects of the added Z methods and are generalized for the industry, whilst the individual effects can give more personal advice to the brands included in this research.
5.3 Limitations and future research directions
This research has several limitations that can be used as an opportunity in future researches. First, the model that is used in this research is not complete and can be extended with different explanatory variables. For example, adding a variable that includes the competitors advertising. This gives a more realistic view on what influences the liking score of a brand since it is not only due to the companies’ own marketing efforts. Subsequently, when specific data is available for the own marketing channels that are used for each brand, a more detailed advice on what channel should be used more extensively can be given when these are included in the model. Another variable that would be interesting to add to the model is the price of a car, however in this research it is not feasible since it does not focus on specific cars of a certain brand though on the brand as a whole. A research that focuses on 1 specific car of each brand, f.e. the most sold or the most popular, could provide insights in what way the price of a durable good has an important role in the liking score.
Second, the data provided for this research did not include specific budgets for each of the marketing activities. When data is available on TV commercials, print advertisements and online advertisement, a more concise advice on how to target effectively can be provided.
Third, due to lack of data of 8 brands, these could not be used in this research.
When in the future conducting a research on this scale, it should be compulsory for all respondents to fill in the data before continuing to the next question. In this case more valuable insights can be derived from the data and all brands can be included in the research.
Fourth, the factors used in this research are not based on hard evidence that they are capable to use in estimating liking scores of a brand. However, it is very hard to factorize 23 characteristics into an acceptable amount of factors since there are many influencing characteristics in choosing a car. It would therefore be useful to already include factors in the survey, since you can link certain characteristics to the factors afterwards. This eliminates the unreliability of the factors in this research.
Fifth, instead of the liking score, it would be interesting to estimate the model with the sales of the car brand. The same variables can be used as in this research, though now you will see whether these factors also influence the actual sales number of a car.
In summary, this research provided insights for 18 car brands. Clear pointers in the way of effective targeted advertisements have been found and can be used accordingly. Females and males do differ in their preferences and therefore need gender-specific advertisements. I hope this research will help brand managers of cars to effectively target their advertisements.
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