Edited by: Ana I. Jiménez-Zarco, Open University of Catalonia, Spain
Reviewed by: Pablo Ruiz-Palomino, University of Castilla La Mancha, Spain; Lester Johnson, Swinburne University of Technology, Australia
†Joint first authors
This article was submitted to Organizational Psychology, a section of the journal Frontiers in Psychology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
This study adopted the paradigm of the self-reference effect to explore how brand preference, product involvement, and information valence affects brand-related memory by three experiments. Experiment 1 examined memory differences between positive/negative information of self-/other-preferred brands. Results showed increased memory of positive words (i.e., the effect of information valence) in the self-preferred brand group, yet memory of self-preferred brands was poorer than that of other-preferred brands. Experiment 2 examined effects of degree of brand preference and information valence, and revealed a positive association between degree of preference and memory of brand-related positive words. Experiment 3 explored the effects of brand preference and product involvement. Results showed that the memory of high-preference brands was stronger in the high-involvement group. Additionally, product involvement demonstrated a significant positive correlation with memory. The observed effects of information valence, especially in self-preference (Experiment 1) and high-preference (Experiment 2) conditions, can be explained by self-schema and mnemic neglect theories. The increased memory of highly preferred brands in a high-involvement condition can be explained by intimacy and self-expansion models (Experiment 3).
At the mention of two different cellphone brands, such as Apple and Samsung, two different adjectives are likely to come to mind that describe the brands. The reason why different memories of various brands form, and exactly how these memories differ, remains to be elucidated. The positive or negative memories consumers hold regarding various products and brands strongly contribute their final purchase decisions. As self-schemas effectively influence memory, the choice making process of consumers is actually a process of seeking psychological identity and self-expression. This is similar to a concept presented by
The “self” is a remarkably important topic in social psychology. This is especially true of the self-reference effect (SRE;
The SRE (
A number of studies have consistently demonstrated that intimacy has an important effect on SRE. Specifically, referring to highly intimate others promotes a memory effect that is almost as strong as self-reference (
Self-schema theory can explain the effect of enhanced memory of positive self-referential adjectives. The self-schema theory raised by
In addition, the mnemic neglect model (
While many empirical studies have been performed in the field of interpersonal memory, very little research has been conducted examining brand memory. It is possible that SRE paradigms can also be applied to the study of brand-related memory, in which brand preference and product involvement can play the same role intimacy plays in the SRE.
The previously discussed concept of involvement can be defined as the perceived relevance of an object based on inherent needs, values, and interests (
It is regrettable that the effects of brand preference and product involvement on the brand-related memory remain unexplored. Hence, the current study aimed to fill the research gap by adapting the R/K SRE paradigm to study brand-related memory.
In modern life of consumption, the self and brands have a close connection (
The overall goal of the current research was to provide evidence that brand preference, degree of brand preference, and product involvement would each demonstrate an impact on the memory of relevant product information by using the R/K paradigm of the SRE. Additionally, the current series of studies attempted to test differences in memory of brand-related positive and negative information under the influence of brand preference and product involvement.
According to the self-expansion model (
This research predicted an impact of brand preference on memory of related information. According to Aron’s self-expansion model, people include other people into the self (
Since intimacy, according to the self-expansion model, has a strong effect on the SRE in relationships among different people, it is possible that brand preference and product involvement will have a similar effect on memory in the relationship between people and objects. Based upon the self-expansion model (
Similarly, low-involvement products will be more weakly included into the self-concept. Because of this, relevant information will receive less processing, weakening the influence of brand preference on memory under this condition, presenting as no memory difference between the information of high- and low-preference brands.
Being analogous to the difference in memory effects between positive and negative words in the SRE (
To test the impact of brand preference, product-involvement, and information valence on memory, three experiments were performed. Experiment 1 used the R/K paradigm of SRE as the method and shampoo as the material to compare the memory effects of self-preferred and other-preferred brands. Additionally, the impact of information valence was also measured. It was predicted that the memory of self-preferred brands would be enhanced and that positive information of the brand would demonstrate enhanced memory when compared to negative information.
Experiment 2 also used the shampoo as material, exploring the impact of information valence and the different impacts of high, medium, and low brand preference on memory. It was predicted that a higher degree of brand preference would lead to better memory, and that memory differences between relevant positive and negative information would be even more obvious.
Experiment 3 added the variable of involvement to explore the impact of involvement and brand preference on memory. Specifically, this experiment used shower gels and computers as materials of low and high product involvement, respectively. It was predicted that information regarding the preferred brand with higher product involvement would demonstrate the best level of memory, with a greater difference between positive and negative words.
This experiment intended to examine whether memory of a self-preferred brand would be enhanced when compared to the memory of an other-preferred brand. Additionally, this experiment explored whether the valence of words (i.e., positive or negative) would show differing effects depending on the preference category.
Individuals have a tendency to incorporate preferred brands into their self-concepts (
It was also hypothesized that the memory of positive and negative information of these preferred brands would differ. According to self-schema theory (
In summary, the hypotheses of Experiment 1 were:
A total of 33 participants (17 males,
The experiment was a 2 (referential task: self-preferred brand vs. other-preferred brand) × 2 (information valence: positive vs. negative) within-subjects design. Dependent variables were recognition and R/K rates.
The materials of Experiment 1 consist of questionnaire and adjectives. Please see Appendix A for details.
Shampoos are commonly used objects in daily life, which are familiar to people and exhibit a high degree of market concentration (
All adjectives used in the paradigm to describe brands were chosen from the
After finishing the questionnaire, subjects completed the R/K paradigm experiment. The experiment was conducted in three phases: learning phase, interference phase, and testing phase. The first and third phases were completed on E-prime 2.0. The instructions of learning phase and testing phase are showed in Appendix A. The entire experimental protocol lasted for approximately 30 min.
Subjects were told that this was an adjective evaluation experiment, and they were to complete two kinds of judging tasks by answering the questions “Is the word xxx (e.g., ‘popular’) appropriate to describe the xxx (self/other-preferred brand chosen by participant)?” Each task involved 28 adjectives (14 positive and 14 negative), for a total of 56 adjectives. According to each participant’s own choices of self- and other-preferred brands in the questionnaire, brand names were modified in E-prime by the experimenter and appeared in the experimental instructions. The appearances of these two tasks were balanced. At the beginning of each task, there were detailed instructions, telling that after the presentation of a fixation point and a blank screen lasting for 500 ms, each adjective would be presented for 2 s. Participants’ reactions were not recorded, as the purpose of this phase was to allow them to learn the words.
At the end of the learning phase, subjects were given a 3-min break. Then they were asked to perform 64 mathematical calculations to avoid repetition of the words that appeared in the learning phase. This phase lasted for 7–9 min.
After the interference phase, subjects were asked to complete recognition tasks. They were randomly presented 56 old and 56 new words (half positive and half negative). First, subjects were asked to determine if words were “new” or “old.” When words were deemed “old,” participants were asked to judge whether they exactly “Remembered” the words or just “Knew” the words. There was no fixed presentation time for each word, as words were switched when participants pressed a button. Before each word, a fixation point and blank screen was presented for 500 ms.
Dependent variables (i.e., memory results) were the “Recognition rate” (the number of words correctly judged as “old”)/56 (the total number of words in the learning phase), the “R rate” (number of “Remember” words)/56, and the “K rate” (number of words subjects “Know”)/56.
This study used SPSS 23.0 to analyze data in the questionnaire, recognition rates, and R/K rates.
A paired-sample
Moreover, recognition rates of new words were calculated by using the number of the new words that were misjudged as “old” by participants. A within-subject one-way analysis of variance (ANOVA) performed on the recognition rates of new words and old words revealed a significant effect [
Descriptive statistics of recognition rates and R/K rates of different referential task and different information valence are presented in
The M (SD) of the recognition rate and the R/K rate of different referential tasks and information valence.
Memory indexes | Referential tasks |
|||||
---|---|---|---|---|---|---|
Self-preferred brands |
Other-preferred brands |
|||||
Positive words | Negative words | Mean | Positive words | Negative words | Mean | |
Recognition rate | 0.60 (0.18)_1 | 0.53 (0.23)_2 | 0.56 (0.17)_3 | 0.62 (0.17) | 0.63 (0.20) | 0.63 (0.15)_4 |
R rate | 0.32 (0.19)_1 | 0.24 (0.21)_2 | 0.28 (0.18)_3 | 0.35 (0.20) | 0.35 (0.22) | 0.35 (0.19)_4 |
K rate | 0.29 (0.16) | 0.29 (0.21) | 0.29 (0.16) | 0.27 (0.17) | 0.29 (0.20) | 0.28 (0.16) |
The interaction between referential task and information valence was significant [
A 2 (referential task: self-preferred brand vs. other-preferred brand) × 2 (information valence: positive vs. negative) repeated measures ANOVA on R rates also revealed a significant main effect of referential task [
The interaction between referential task and information valence was significant [
A 2 (referential task: self-preferred brand vs. other-preferred brand) × 2 (information valence: positive vs. negative) repeated measures ANOVA on K rates found no significant main effects of referential task or information valence [
Correlations among the degree of brand preference, recognition rate, R rate, and K rate are reported in
Correlations (
Recognition | R rate | K rate | Recognition | Recognition | R rate | R rate | K rate | K rate | |
---|---|---|---|---|---|---|---|---|---|
rate of all | of all | of all | rate of PW | rate of NW | of PW | of NW | of PW | of NW | |
Preference | -0.09 | -0.21† | 0.16 | -0.06 | -0.08 | -0.11 | -0.26∗ | 0.08 | 0.19 |
The results of Experiment 1 showed that memory effects of shampoo brand information were different under two different referential conditions, an effect in which information valence plays a role. ANOVA revealed that the memory of self-preferred brands was worse than that of other-preferred brands on both overall recognition and R rates. Correlation analysis showed that brand preference demonstrated a negative correlation with R rate, which was consistent with the ANOVA results, and failed to support hypotheses 1a and 1b. Overall, in recognition and R rates, the memory of positive words was better than negative words in the self-referential condition and not in other-referential condition, supporting hypothesis 1c.
Hypotheses 1a and 1b were not supported; the overall recognition and R rates of the information of the self-preferred brand was worse than that of the other-preferred brand. This may be because the familiarity of self-preferred brands was not significantly higher than that of the other-preferred brands, despite the fact that the former demonstrated higher preference than the latter.
Experiment 1 also found that, in the self-referential condition, the memory of positive information was enhanced when compared to that of negative information. However, in the other-referential condition, the difference disappeared. This result provides support for hypothesis 1c. Previous studies have suggested that it is difficult for people to remember negative words which may threat their positive self-image, and easy for them to remember positive words which may improve their self-image (
Since different memory effects of positive and negative information of self-preferred brands were found in Experiment 1, Experiment 2 would remove the other-referential group and divide the referential conditions into the groups of high, moderate, and low levels of self-preference, examining the main effect of the degree of brand preference on memory, and its interaction with information valence.
This study intended to discuss the impact of the degree of preference and information valence on the memory of brand-related information.
It has been shown that individuals tend to have a better memory of highly intimate others, because of these individuals being more deeply included into the self-concept (
To sum up, the hypotheses of Experiment 2 were:
Forty participants (20 males,
The experiment was a 3 (referential task: high vs. moderate vs. low levels of brand preference) × 2 (information valence: positive vs. negative) within-subjects design experiment. The dependent variables were recognition rates and R/K rates.
The materials, procedure, and measures were similar to those described in Experiment 1. Please see Appendix B for details. The differences were that subjects were asked to evaluate the degree of preference of shampoo brands as “high,” “moderate,” or “low,” and that the adjectives were divided into six groups.
This study used SPSS 23.0 to analyze data from the questionnaire, recognition rates, and R/K rates.
A within-subject, one-way ANOVA on preference was performed. With referential task as the independent variable, significant main effect of different brands was observed [
Moreover, a repeated measures, one-way ANOVA on the recognition rates of new and old words revealed a significant effect of word state [
Descriptive statistics of recognition rates and R/K rates of different referential task and different information valence are presented in
The M (SD) of the recognition rate and R/K rate of different referential tasks and information valence.
Memory | Information | |||
---|---|---|---|---|
indexes | valence | Referential tasks |
||
High- | Moderate- | Low- | ||
preference | preference | preference | ||
brands | brands | brands | ||
Recognition rate | Positive | 0.72 (0.27)a1 | 0.65 (0.25) | 0.61 (0.23)2 |
Negative | 0.53 (0.23)b1 | 0.62 (0.28)2 | 0.60 (0.18)2 | |
Mean | 0.62 (0.20) | 0.64 (0.18) | 0.60 (0.19) | |
R rate | Positive | 0.39 (0.24)a1 | 0.34 (0.19)a | 0.28 (0.20)2 |
Negative | 0.24 (0.16)b | 0.25 (0.18)b | 0.24 (0.17) | |
Mean | 0.28 (0.19) | 0.26 (0.17) | 0.24 (0.17) | |
K rate | Positive | 0.37 (0.28) | 0.37 (0.18) | 0.36 (0.18) |
Negative | 0.32 (0.20) | 0.39 (0.30) | 0.38 (0.18) | |
Mean | 0.34 (0.18) | 0.37 (0.17) | 0.37 (0.16) |
A significant interaction [
A 3 (referential task: high vs. moderate vs. low self-preference brands) × 2 (information valence: positive vs. negative) repeated measures ANOVA on R rates also revealed a significant main effect of information valence [
A significant interaction [
A 3 (referential task: high vs. moderate vs. low self-preference brands) × 2 (information valence: positive vs. negative) repeated measures ANOVA on K rates found no significant main effects of referential task and information valence [
Correlations between the degree of brand preference, recognition rate, R rate, and K rate were calculated, and are reported in
Correlations (
Recognition | R rate | K rate | Recognition | Recognition | R rate | R rate | K rate | K rate | |
---|---|---|---|---|---|---|---|---|---|
rate of all | of all | of all | rate of PW | rate of NW | of PW | of NW | of PW | of NW | |
Preference | 0.18∗ | 0.21∗ | -0.01 | 0.26∗∗ | 0.01 | 0.30∗∗ | 0.06 | 0.03 | -0.04 |
ANOVA revealed no significant main effect of referential task on the overall recognition rate, R rate, or K rate, indicating no difference in the memory of high-, moderate- and low-preference brands, and the degree of brand preference did not appear to have an impact on memory, failing to support hypothesis 2a. However, correlation analysis showed that the degree of brand preference demonstrated significant positive correlations with overall recognition and R rates, supporting hypothesis 2b. In general, the impact of brand preference on memory was partly supported, fitting with the theory of the self-expansion model that people will include brands they prefer into the self-concept, resulting in more complex processing. Simultaneously, according to the self-expansion model, the low product involvement of shampoo might be the cause of the current results. In other words, the weak relationship of shampoo with the self may have led to the non-significant memory differences among three brands. Since highly involved products, such as laptops might support hypothesis 2a, Experiment 3 added product involvement as an independent variable and predicted different memory effects of high-involvement products with different brand preference.
Experiment 2 also found that higher brand preference led to larger memory differences between positive and negative information. ANOVA results revealed that recognition rate, only when referring to a high-preference brand, would result in memory differences between positive and negative words. While for the R rate, this effect was seen when referring to both high- and moderate-preference brands, with the memory difference being larger when referring to highly preferred brand when compared to a moderately preferred brand. Additionally, correlation results also revealed that brand preference demonstrated significant positive correlations with recognition and R rates of positive words. These results mean that the memory difference between positive and negative information will likely increase along with an increase of brand preference, fitting with self-schema theory and the mnemic neglect model. Since the R rate was more sensitive than recognition rate, a stronger difference was noted. Therefore, similar to Experiment 1, hypothesis 2c of Experiment 2 was also supported.
This study sought to determine the impact of product involvement, brand preference, and information valence on brand-related information memory.
According to
In summary, the hypotheses of Experiment 3 include:
Hypotheses about the influence of brand preference on memory:
Hypotheses about the influence of product-involvement on memory:
Hypotheses about the interaction between brand preference and product-involvement:
Hypotheses about the interaction of brand preference, product-involvement, and information valence:
Sixty-six participants (35 males,
The experiment was a 2 (referential task: high- vs. low-preference brands) × 2 (product involvement: high vs. low) × 2 (information valence: positive vs. negative) mixed design experiment. The between-subject variable was product involvement and the others variables were the within-subject variables. The dependent variables were recognition rates and R/K rates.
The materials, procedure, and measures were similar to those reported in Experiments 1 and 2. Please see Appendix C for details. The difference was that Experiment 3 used two different types of products, one with high-involvement (laptops) and one with low-involvement (shower gels). Subjects were asked to complete a Personal Involvement Inventory (PII;
SPSS 23.0 was used to analyze the questionnaire, recognition rates, R rates, and K rates.
A higher PII score indicates lower product involvement. A repeated measures, one-way ANOVA on involvement scores, with two involvement levels (one high and one low) set as the independent variable, showed a significant main effect,
Brand preference scores were then analyzed. Subjects’ degree of preference for a brand with high involvement and high preference was 6.03 (
Moreover, a repeated measures, one-way ANOVA on the recognition rates of new words and old words revealed a significant effect of word state [
Descriptive statistics of recognition, R, and K rates of different referential task, different levels of product involvement, and different informational valence are presented in
The M (SD) of the recognition, R, and K rates of referential tasks, product involvement, and information valence.
Memory indexes | Information valence | Product involvement level |
|||
---|---|---|---|---|---|
High |
Low |
||||
High-preference | Low-preference | High-preference | Low-preference | ||
brands | brands | brands | brands | ||
Recognition rate | Positive | 0.34 (0.09) | 0.30 (0.11) | 0.37 (0.09)a | 0.35 (0.10) |
Negative | 0.32 (0.10) | 0.29 (0.10) | 0.32 (0.11)b | 0.33 (0.08) | |
Mean | 0.33 (0.10)1 | 0.29 (0.10)2 | 0.34 (0.10) | 0.34 (0.09) | |
R rate | Positive | 0.26 (0.12)a | 0.22 (0.13)a | 0.23 (0.13)a | 0.22 (0.11) |
Negative | 0.22 (0.12)b | 0.19 (0.10)b | 0.19 (0.13)b | 0.21 (0.12) | |
Mean | 0.24 (0.12)1 | 0.21 (0.12)2 | 0.21 (0.13) | 0.22 (0.12) | |
K rate | Positive | 0.08 (0.08) | 0.08 (0.09) | 0.13 (0.12) | 0.13 (0.11) |
Negative | 0.10 (0.08) | 0.09 (0.07) | 0.13 (0.13) | 0.12 (0.12) | |
Mean | 0.09 (0.08) | 0.09 (0.08) | 0.13 (0.12) | 0.12 (0.11) |
The interaction between brand preference and product involvement was marginally significant [
A 2 (referential task: high- vs. low-preference brands) × 2 (product involvement: high vs. low) × 2 (information valence: positive vs. negative) repeated measures ANOVA on R rates revealed a marginally significant main effect of referential task [
The interaction between brand preference and product involvement was significant [
A 2 (referential task: high- vs. low-preference brands) × 2 (product involvement: high vs. low) × 2 (information valence: positive vs. negative) repeated measures ANOVA on K rates found no significant main effects of referential task [
Since this experiment was a mixed design, with two groups of participants judging high-involvement laptops and low-involvement shower gels as materials, respectively, correlation analyses were separately computed. Correlations among the degree of laptop brand preference, product involvement, recognition rate, R rate, and K rate were compared and are reported in
Correlations (
Recognition | R rate | K rate | Recognition | Recognition | R rate | R rate | K rate | K rate | |
---|---|---|---|---|---|---|---|---|---|
rate of all | of all | of all | rate of PW | rate of NW | of PW | of NW | of PW | of NW | |
Product involvement | -0.04 | -0.31* | 0.41** | -0.07 | -0.01 | -0.32* | -0.25† | 0.40** | 0.34** |
Preference | 0.29* | 0.17 | 0.09 | 0.21 | 0.28* | 0.16 | 0.16 | 0.03 | 0.14 |
Correlations among the degree of shower gel brand preference, product involvement, recognition rate, R rate, and K rate were compared and are reported in
Correlations (
Recognition | R rate | K rate | Recognition | Recognition | R rate | R rate | K rate | K rate | |
---|---|---|---|---|---|---|---|---|---|
rate of all | of all | of all | rate of PW | rate of NW | of PW | of NW | of PW | of NW | |
Product involvement | -0.17 | 0.14 | -0.26* | -0.10 | -0.20† | 0.16 | 0.09 | -0.24* | -0.25* |
Preference | 0.07 | -0.07 | 0.11 | 0.20† | -0.08 | 0.03 | -0.15 | 0.13 | 0.09 |
ANOVAs revealed that the overall recognition and R rates of high-preference brands were better than that of low-preference brands, supporting hypothesis 3a. However, product involvement did not demonstrate significant main effects, failing to support hypothesis 3c. The significant interaction between brand preference and product involvement showed that memory of high-preference brands was better than that of low-preference brands, but only when the product had high involvement, supporting hypothesis 3e. Finally, the memory difference displayed in R rate between positive and negative words was larger in the high-preference condition than in low-preference condition, partly supporting hypotheses 3f1 and 3f2.
Correlation analyses showed that the preference level for laptops was positively related with recognition rate, and that the preference level for shower gels was marginally related with the recognition rate of positive words, supporting hypothesis 3b. Additionally, the preference for shower gel did not demonstrate significant correlations with overall recognition rate or R rate, again supporting hypothesis 3e. In the laptop group, higher involvement was associated with a better R rate and a worse K rate; conversely, in the shower gel group, higher involvement was associated with a better K rate, supporting hypothesis 3d.
Experiment 1 found that the overall memory of self-preferred brands was worse than that of other-preferred brand, and, Experiment 2 found that, although preference demonstrated positive correlations with recognition and R rates, it did not have a significant main effect, both of these results failing to support the referential effect of preferred brands. The materials used by the former two studies were shampoo brands that were familiar to everyone. However, subjects’ levels of involvement with the shampoos were different, possibly contributing to different levels of self-inclusion. When consumers had a close connection with a product, the results of these two experiments suggested a deeper inclusion to the self-concept.
Given this information, Experiment 3 added the variable of product involvement. Two groups of participants were selected by questionnaire, which were a high-involvement laptop group and a low-involvement shower gel group. Results showed that, in overall recognition and R rates, there were significant memory differences between high-preference brands and low-preference brands in the laptop group (i.e., the memory of high-preference brands was better). However, in the shower gel group, these memory differences disappeared, not only providing support for hypothesis 3e, but also explaining why hypothesis 2a of Experiment 2, which was that higher preference would lead to better memory, was not supported.
On overall recognition and R rates, information valence had significant main effects, indicating that the memory of positive information was always better than that of negative information. Moreover, the interaction of this variable with referential task was marginally significant on R rate, showing that, despite the memory advantage of positive information in both high- and low-preference conditions, the advantage was far more significant in the high-preference condition. Therefore, hypotheses 3f1 and 3f2 was partially supported. However, the impact of involvement in hypotheses 3f1, 3f2, 3f3, and 3c was not observed, which may be attributed to other unknown factors playing a part in influencing memory. Product involvement might not have an independent impact on memory of brand-related information, but rather, it could work together with brand preference, indicating that the formation of referential memory is a complicated process.
Based on the prior experiments, Experiment 3 additionally found that, in the laptop group, higher involvement was associated with a lower K rate, but in the shower gel group, higher involvement was associated with a higher K rate. These results suggest that individuals can easily form a precise and detailed memory for high-involvement products, but only a vague and integral memory for low-involvement products.
The memory difference between positive and negative information was only shown in recognition and R rates, which conforms to prior research suggesting that the SRE was more impactful in recognition and R responses (
Experiment 1 revealed that the memory of positive words of self-preferred brands was better than that of negative words, and that there was no significant memory difference between words with different valence of other-preferred brands. Moreover, subjects’ memory of negative words of self-preferred brands was worse than the memory of negative words of other-preferred brands. Experiment 2 revealed that, when referring to highly and moderately preferred brands, the memory of positive words was significantly better than negative words, and that the memory difference was more significant when referring to high-preference brands. When referring to low-preference brands, there was no memory difference between positive and negative words. The results on R rate in Experiment 3 revealed that, although the memory of positive words was always better than negative words, their difference was more significant in the high-preference condition than in the low-preference condition. All of the results reported are in agreement with the prior conclusion that positive and negative words had significant memory differences in the SRE. The important effect of brand preference on the memory of positive and negative words was supported, indicating that the higher preference subjects had for a brand, the more relevant positive information they could remember.
According to self-schema theory, consumers will incorporate the positive images of their preferred brands into the self-concept, and be loyal to the brand, thus reflecting the positive images of themselves. Therefore, brand-related positive information can receive more complex processing, resulting in better memory. Moreover, the higher the individual’s preference for the brand, the more likely he/she will internalize the relevant positive information and enhance his/her loyalty. Hence, the recognition and R rates of positive information will be much higher than those of negative words when the brand preference is higher, and when the product involvement is higher. The mnemic neglect model (
Many prior studies (e.g.,
Similar to previous topics, all of the results of the effect of brand preference and product involvement were only reflected in recognition and R rates. The results of Experiments 2 and 3 showed that preference demonstrated significant positive correlations with recognition and R rates, indicating that higher brand preference might lead to better memory. In the laptop group, product involvement was negatively related with R rate and positively related with K rate; in the shower gel group, involvement was negatively related with K rate. It was shown that, in high-involvement products, higher involvement made people “remember” more and “know” less, but in low-involvement products, the overall memory was worse because of the low involvement (i.e., “connection”) with the product. Further, in the case of the current results, higher involvement made people “know” more and memorize better. In addition to the results discussed above, preference and product involvement demonstrated a significant interaction (i.e., when products had high involvement, higher brand preference leaded to better memory and was positively correlated with recognition rate; when products had low involvement, brand preference had no effect on memory and no correlation with memory). The overall results showed a preferred brand reference effect.
According to the self-expansion model (
Furthermore, the intimacy between self and others was found to influence the self-referential memory advantage (
On this theoretical basis, the current study provides further evidence to support the impacts of brand preference and product involvement, as well as their interaction. Specifically, higher involvement and higher preference was associated with better memory. The effect of brand preference was more significant when product involvement was high, and it was weakened when product involvement was low. The non-significant main effect of product involvement in Experiment 3 also gave credence to the notion that consumers’ cognition of brands was not completely fair, and that the formation of brand preference is a complicated process.
According to the self-expansion model, previous research has paid most attention to subjects’ tendency to include intimate others into the self. This study moved forward a single step to provide supporting evidence that subjects would also try to include preferred brands into the self. During the process of forming a brand preference, consumers take the concept, identity, and even the image of the brands into the self. The more loyal consumers are to the brands, the deeper they will be incorporated into identity, the more the brand-related concept will overlap with the self-concept, and the more tags will be attached to a memory associated with the brand (making recall easier). The existing SRE studies have all verified that memories of self-related information are better than memories of other types of information. This is purportedly due to individuals having enhanced schemata of the self and intimate others (
Based on the paradigm of the SRE, this study presents preliminary evidence of the application of the SRE in brand preference, with different levels of product involvement. However, the current study did contain some limitations.
First,
Second, in the memory reference effect of brand preference, the influencing factors are likely far more complex than only brand preference and product involvement. For future research, it is suggested to explore the brand reference effect further. In a study by
On a final note, this study was limited by only using the SRE paradigm to perform experimental research. Future research can use methods of cognitive neuroscience, such as ERPs and fMRI, to study the cognitive process of brand information memory, further broadening the research scope of the reference effect. Moreover, new methods of “big data” collection can be adopted to gather vast quantities of information regarding brand preference and cognition on the Internet, (e.g., positive and negative evaluation of preferred brands), and related data analysis can be performed to collect more empirical evidence for this topic.
The current series of experiments has provided evidence that the higher the degree of brand preference, the better the memory of relevant positive information when compared to negative information. Additionally, brand preference and product involvement both affect brand-related memory and have an interactive effect. Furthermore, when product involvement was high, brand preference was elevated, resulting in a better the memory effect. However, when product involvement was low, there was no difference between the memory of high-preference and low-preference brands.
This study was carried out in accordance with the recommendations of “University Committee on Human Research Protection of East China Normal University” with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the “University Committee on Human Research Protection of East China Normal University.”
RF and WM were responsible for the overall design, implementation, and data analysis of the three experiments. RL and XL were responsible for part of the thesis writing and data analysis. ZZ and JX were responsible for the overall inspection and correction of manuscript. MZ, TQ, and CQ were responsible for the implementation of Experiments 3, 1, and 2, respectively.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at: