Effects of Parent-Extension Similarity and Self Regulatory Focus on Evaluations of Brand Extensions

JOURNAL OF CONSUMER PSYCHOLOGY, 16(3),272-282 Copyright O 2006, Lawrence Erlbaum Associates, Inc.

Effects of Parent-Extension Similarity and Self Regulatory Focus on Evaluations of Brand Extensions Junsang Yeo and Jongwon Park Korea University

Research has shown that a similar extension of a brand is evaluated more favorably than a dissimilar one. In this research we demonstrate that self-regulatory focus (promotion vs. prevention focus) significantly moderates the effect. Four experiments demonstrated that similar extensions were evaluated more favorably than less similar extensions when participants were chronically or momentarily prevention focused, whereas such effect was eliminated and sometimes even reversed when participants were chronically or situationally promotion focused. This discrepancy was attributed to different weights attached to the perceived risk and to the perceived hedonic value of the extension by promotion-focused vs. prevention-focused individuals.

Over the past decade, the factors that influence the success of brand extensions have been a great concern of theory and research in consumer judgment. A large number of empirical studies have shown that an extension of a brand is evaluated more favorably when it is similar rather than dissimilar to the original brand (e.g., Aaker & Keller, 1990; Barone, Miniard, & Romeo, 2000; Bottomley & Holden, 2001; Boush & Loken, 1991; Broniarczyk & Alba, 1994; Keller & Aaker, 1992; Park, Milberg, & Lawson, 1991 ; Smith & Park, 1992; Zhang & Sood, 2002). This similarity effect has typically been conceptualized within the well-known framework of category-based vs. piecemeal processing (e.g., Boush & Loken, 1991; Milberg, Park, & McCarthy, 1997). Although some boundary conditions for the effect have been identified, they are mostly limited to cognitive factors, mainly emanating from the stimuli or contexts (e.g., Barone et al., 2000; Broniarczyk & Alba, 1994; Keller & Aaker, 1992; Meyers-Levy, Louie, & Curren, 1994; Park et al., 1991). Less is known about motivational factors that might moderate the effect (see Barone, 2005; Maoz & Tybout, 2002, for exceptions). In this article we demonstrate that self-regulatory focus (a promotion vs. a prevention focus), which is a generalized motivational dimension that has been shown to be relevant in many decision-making situations, significantly moderates the effect of parent-extension similarity on extension evaluations. Specifically, in four experiments we show that similar extension products are evaluated Correspondence should be addressed to Jongwon Park, Department of Business Administration, Korea University, 1, Anam-Dong, Sungbuk-Gu, Seoul 136-701, Korea. E-mail: [email protected]

more favorably than dissimilar extensions in preventionfocus conditions. This effect is eliminated in promotion-focus conditions. This interactive pattern was found to hold across product categories (i.e., durables, nondurables, or services). Furthermore, we observed this pattern regardless of whether the regulatory focus was operationalized as a chronic individual difference or as an experimental manipulation. Finally, we show that this difference resulted from different cognitive processes by which promotion-focused vs. prevention-focused individuals evaluated an extension product. Specifically, when forming an overall extension evaluation, promotion-focused participants tended to attach a lesser weight than did prevention-focused participants to the perceived risk of an extension product. Conversely, they tended to attach a greater weight to the perceived hedonic value than did the prevention-focused participants.

THEORETICAL BACKGROUND Effects of Parent-Extension Similarity on Brand Extension Evaluations A number of factors have been proposed to influence consumers' acceptance of extensions. Much of this research has investigated the effects of an extension's physical, conceptual, or contextual similarity to the parent brand on favorableness of extension evaluations. It has been shown that an extension of a strong brand tends to be evaluated more favorably when the extended category is similar to the original brand category. When consumers perceive a lack of cate-

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gory fit, the extension is given smaller probabilities of success (e.g., Aaker & Keller, 1990; Martin & Stewart, 2001; Smith & Park, 1992; for recent reviews, see Keller 2003). The conceptual frameworks that have typically been used to account for these results include the dual-processing formulations of person impression formation postulated by social cognition researchers. These formulations are based on the distinction between category-based processing and piecemeal processing (for a recent review, see Fiske, Lin, & Neuberg, 1999; Fiske & Neuberg, 1990). That is, when an extension product is sufficiently similar to the parent brand, thus being viewed as belonging to the same brand category, it may be evaluated on the basis of the favorableness of this category independently of its specific attributes. If, however, the extension product is dissimilar to the parent, it is evaluated on the basis of a piecemeal assessment of its individual features (e.g., Boush & Loken, 1991; Meyers-Levy et al., 1994; Milberg et al., 1997). Other research has suggested the possibility that a favorable evaluation of an extension can be formed even when the extension is quite dissimilar to the original brand category. For example, a dissimilar extension was evaluated more favorably when it shared the parent brand's functional concept or symbolic meaning (Park et al., 1991) or when it had strong specific associations to the original brand (e.g., Broniarczyk & Alba, 1994) than when it did not. In addition, positive mood often enhanced the favorability of evaluations of dissimilar extensions (Yeung & Wyer, 2005). Also, based on Mandler's (1982) schema incongruity theory, Meyers-Levy et al. (1994) hypothesized and found that extension products associated with moderately incongruent brand names were preferred over ones that were associated with either congruent or extremely incongruent brand names. This effect was attributed to participants' greater elaboration of information about the moderately incongruent brand extension to resolve incongruity between the brand schema and the extension category. However, participants in those studies were given specific information about the extension (sometimes even prior to identification of the parent brand name), thereby having an opportunity to resolve incongruity by processing that information. Had such information been limited or absent, as in typical brand extension studies (e.g., Aaker & Keller, 1990; Boush & Loken, 1991; Keller & Aaker, 1992; Park et al., 1991), the moderate-incongruity effect might not have been observed. In sum, the existing literature on brand extensions has provided abundant evidence for the similarity effect on evaluations of brand extensions, and various cognitive factors have been identified as moderators for the effect. Nonetheless, our understanding of motivational variables as boundary conditions for the effect is limited. We argue that people's selfregulatory focus (a promotion focus vs. a prevention focus) leads to different cognitive processes by which brand extension evaluations are formed, thereby determining the relative favorability of a similar extension over a dissimilar one.

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Brand Extension Evaluation Processes and Regulatory Focus It is reasonable to assume that an extension of a favored brand has two basic components that are relevant for decision making: (a) hedonic attainment value (i.e., the degree to which people enjoy the new product when it is of high quality) and (b) perceived risk or uncertainty of that attainment (i.e., the likelihood that the new product lacks quality). First, a brand extension provides an additional opportunity for consumers to enjoy a favored brand in a new product category. This would be particularly true if consumers are strongly attached to the parent brand or have developed a strong relationship with the brand (e.g., Fournier, 1998; Park & Kim, 2002). To this extent, an exposure to an extension of the brand and imagery of using the extension is likely to elicit positive responses such as pleasantness, joy, or excitement. However, an extension also carries a risk (i.e., uncertainty about the product quality) for consumer decision making. The level of perceived risk would be particularly high when the extension is dissimilar to the parent brand category, in which case transferability of the parent brand's quality to the extension product would be questionable. Given the distinction between the hedonic attainment value and the perceived risk of an extension product, it seems reasonable to suppose that overall evaluations of an extension are determined by perceptions along each component (i.e., subjective values of perceived risk and hedonic value) and the weight attached to each component. This general process can be captured by the following equation: Evaluation = Wo + W1*V + W2*R where V is the perception of the hedonic attainment value of an extension, Wl is the weight attached to this dimension, R is the perception of the risk of an extension, W2is the weight attached to this dimension, and Wo is an intercept term. The overall attractiveness of the extension, which is presumably determined by both the value assigned to the extension along each dimension and the weight attached to each dimension, is reflected by the last two terms on the right side of the equation. Our contention is that parent-extension similarity and regulatory focus determine favorableness of extension evaluations by affecting perceptions along the two components (V and R) as well as the weights attached to the components (Wl and W2). Undoubtedly, parent-extension similarity exerts an influence in this evaluation process. Research has shown that parent-extension similarity increases perceptions about the extent to which the quality of the parent brand is transferable to the extension product (e.g., Aaker & Keller, 1990; Boush & Loken, 1991). Further, similarity has been shown to increase the extent to which the company has a perceived competence in manufacturing or marketing the extension product, which in turn increases favorability of extension evaluations (e.g.,

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Barone et al., 2000). These seem to suggest that parent-extension similarity is likely to determine the level of perceived risk of an extension (V). Thus, for example, a dissimilar extension, such as M&M's sports drink or Guess performance skiwear, might be perceived to be highly risky, whereas a more similar extension, such as M&M's chocolate cake or Guess casual suit, to which manufacturing capabilities or favorable images of the parent brand can be assumed to be easily transferable, would be perceived to be much less risky. Further, this difference in perceptions does not necessarily vary between promotion-focused versus prevention-focused individuals, although the subjective importance of the risk factor might vary with regulatory focus. Therefore, we state a formal hypothesis with respect to the perception of risk. HI: A similar extension will be perceived to be less risky than a dissimilar extension in terms of anticipated quality. This difference will emerge regardless of whether individuals are promotion focused or prevention focused. Parent-extension similarity and regulatory focus might influence perceptions of hedonic attainment value. Although there is no a priori basis to make a formal hypothesis, we expected that prevention-focused individuals might consider a dissimilar extension to be a nonnormative act by the parent brand (e.g., Park & Kim, 2002) and thus judge the hedonic value of a dissimilar extension less favorably than the value of a similar extension. However, promotion-focused individuals tend to focus on positive features of decision alternatives rather than negative ones (Higgins, 1997) and thus might judge the hedonic value of both similar and dissimilar extensions equally favorably, as long as they are introduced by their favorite brand. The relative weights attached to the two components (i.e., WI and WZ) in the preceding equation are also an important factor to be considered in understanding extension judgments. These weights might reflect personal, intrinsic value systems that are not specific to configurations of an extension product. To this extent, the weights are unlikely to be influenced by parent-extension similarity per se. Instead, we contend that promotion versus prevention focus in self-regulation, which reflects a generalized motivational orientation, influences the relative magnitude of weights. Briefly, promotion focus is concerned with ideals, aspiration, and accomplishment, and thus with the presence or absence of positive outcomes, whereas prevention focus is concerned with "oughts," safety, and responsibility, and thus with the absence or presence of negative outcomes (Higgins, 1997, 2002; Higgins & Spiegel, 2004). Accordingly, promotion-focused individuals tend primarily to focus on attaining positive consequences of decision alternatives (e.g., the potential advantages of owning a new product), whereas prevention-focused individuals primarily focus on avoiding negative consequences (e.g., the potential

failure of a new product). For example, research has shown that promotion-focused individuals, compared to prevention-focused individuals, showed a higher preference for products with high luxury ratings but neutral protection ratings over products with neutral luxury ratings but high protection ratings (Safer, 1998). Further, promotion-focused participants [prevention-focused participants] treated differences in luxury between products as more important [less important] than differences in protectiveness in evaluating the products. Also, promotion-focused individuals have been shown to take more risks than prevention-focused individuals, thus making more false hits and fewer misses in recognition tasks (Crowe & Higgins, 1997). Based on this, we contend that promotion-focused individuals would give more weight to the potential benefits (hedonic attainment value) of owning a new product than to the potential costs (perceived risk) associated with it. H2: In forming overall extension evaluations, people with a prevention focus will attach a greater weight to perceived risk than to hedonic value, whereas people with a promotion focus will attach a greater weight to hedonic value than to perceived risk. Finally, these considerations lead to a prediction about the effect of parent+xtension similarity and regulatory focus on the favorability of extension evaluations. That is, we hypothesize that an interaction effect of parent-extension similarity and regulatory focus would be observed in overall evaluations of extensions. That is, prevention-focused individuals are likely to consider the risk factor very seriously, view a similar extension to be less risky than a dissimilar one, and consequently, prefer a similar extension to a dissimilar one. Promotion-focused individuals however, are likely to consider the risk factor less seriously but the hedonic value factor more seriously. Consequently, the relative preference for a similar extension to a dissimilar one is likely to disappear. These expectations are more formally stated in the following hypothesis. H3: A similar extension will be evaluated more favorably than a dissimilar one (i.e., similarity effect) in the prevention-focus conditions. However, this difference will not emerge in the promotion-focus conditions. We report four experiments that evaluated these hypotheses. Results from all four experiments provided consistent evidence for H3, over different product domains (durables vs. non-durables vs, services) and over different operationalizations of self-regulatory focus (chronic vs. situational). In addition, the last experiment examined the cognitive processes by which extension evaluations were formed under a promotion versus a prevention focus and found generally supportive evidence for H1 and H2.

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EXPERIMENT 1

Method Participants and design. Sixty-three undergraduate students participated in the experiment as part of a course requirement. They evaluated one similar and one dissimilar extension of a well-known news channel service brand (CNN). The order of presenting the two extensions was counterbalanced over participants. Later, participants were divided into subgroups based on measured chronic regulatory focus scores (a promotion-focus group vs. a prevention-focus group). Thus, the experiment involved a 2 (regulatory focus: prevention vs. promotion) x 2 (extension similarity: similar vs. dissimilar) x 2 (order: similar extension-first vs. dissimilar extension-first) mixed design, with extension similarity being a within-subjects factor. Selection of parent brand and extension products. CNN, a well-known news channel, was used as the parent brand in the experiment. To select one similar and one dissimilar extension category of CNN for use for the experiment, a pretest was run with an independent sample of 20 students, in which several products were rated in terms of category-level similarity to the parent brand (CNN) along a 7-point scale from 1 (very dissimilar) to 7 (very similar). Based on their similarity ratings, "weekly news magazine" was selected for a similar extension (M = 5.65) and "movie channel" for a dissimilar extension (M = 3.35). The difference between the two means was statistically significant, t(19) = 7.45, p < .001. Procedure. The experiment was conducted in classrooms. Upon arriving, participants were randomly assigned a folder containing a particular version of the questionnaires. The study was introduced as a survey seeking consumer evaluations of various new products. Participants were then told that (a) CNN was seriously considering the possibility of expanding into various new businesses, (b) the company would like to receive feedback from college students about the ideas before the actual launch of new product development, and (c) participants in the survey would be asked to evaluate two of the business ideas. With this preamble, all participants were asked to open the booklet and pull out the survey questionnaire, labeled product evaluations. The questionnaire contained both similar and dissimilar extensions of CNN, but the order (along with corresponding questions) was counterbalanced over participants.' For each extension, no specific feature information was provided except the category label of the new product with the brand name (i.e., "CNN weekly magazine" or "CNN movie channel"). After thinking about the first extension for 'This counterbalancing variable did not influence any dependent measures, thus it will not be further discussed.

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a moment, participants responded to a series of questions about the extension. They then did the same for the second extension. In both cases, it was emphasized that there were no right or wrong answers, and participants were asked to answer the questions as honestly as possible. Participants reported their overall evaluations of the extension along three scales frequently employed in previous brand extension research (e.g., Aaker & Keller, 1990; Smith & Park, 1992), ranging from 1 (very badverypoor quality/very inferior) to 7 (very goodvery good quality/very superior). Responses to the three items were highly intercorrelated ( a = .91) and were averaged to form a composite index of extension evaluations. Finally, participants rated the perceived similarity between the parent brand and the extension along a scale of 1 (very dissimilar) to 7 (very similar). Participants were then debriefed, thanked, and dismissed. Two days later, participants returned to the classrooms and responded to a series of 7-point scale items (1 = not at all; 7 = very much) that were intended to measure their chronic regulatory focus. The items were based on the scales used in previous research (e.g., Higgins, Shah, & Friedman, 1997; Lockwood, Jordan, & Kunda, 2002) and consisted of five promotion items (e.g., "In general, I am focused on obtaining positive consequences when making a decision") and five prevention items (e.g., "In general, I am focused on preventing negative consequences when making a decision"). Participants' ratings along prevention items and promotion items (reverse coded) were averaged to form a composite index of chronic regulatory focus ( a = .74). Based on a median split of the averaged scores, participants were categorized as promotion focused (n = 33, M = 3.04, SD = .53) or prevention-focused (n = 30, M = 4.94, SD = .90).

Results Manipulation check for extension similarity. Participants perceived the extension as more similar to the parent brand when it was a similar extension (M = 4.94) than when it was a dissimilar one (M = 2.34), F(1, 61) = 71.41, p < .001. Further, this difference was true regardless of the regulatory focus conditions, F < 1. Finally, the regulatory focus factor itself did not influence the perceived similarity of the extension, F < 1. These results confirmed that the manipulation of parent-xtension similarity was successful. Evaluations of extensions. Overall, the similar extension was expected to be evaluated more favorably than the dissimilar extension (i.e., similarity effect). However, we hypothesized that the effect would be pronounced when participants were prevention focused, but not when they were promotion focused (see H3). These expectations were generally confirmed. Table 1 shows evaluations of extensions as a function of regulatory focus and extension similarity. As expected, participants overall preferred the similar extension to the dissim-

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TABLE 1 Mean Evaluations of Extensions as a Function of Regulatory Focus and Extension Similarity Prevention Focus

Experiments

Similar Extension

Promotion Focus

Dissimilar Extension

Similar Extension

Dissimilar Extension

Experiment 1 Experiments 2a & 2b Experiment 2a Experiment 2b Experiment 3 Note. Cell means in a given row without a common subscript differ from each other at p < .05

ilar extension (4.76 vs. 3.63), F(l,61) = 2 3 . 6 5 , ~<.001, confirming the similarity effect. However, this effect was qualified by a significant interaction of extension similarity and regulatory focus, F(1, 61) = 15.87, p < .001, which confirmed H3. That is, participants in the prevention-focus condition evaluated the similar extension more favorably than the dissimilar extension (5.17 vs. 3.03), t(29) = 7.90, p < .001. In contrast, the difference was negligible for individuals in the promotion-focus condition (4.39 vs. 4.18), t(32) = .55, p > .lo. In sum, this experiment provides support for H3.

Discussion Experiment 1 showed that, consistent with the existing literature, a similar extension was more favorably evaluated than a dissimilar extension. As hypothesized in H3, however, this effect was true only for prevention-focused participants. By contrast, the effect was negligible for promotion-focused participants. Before we generalize implications of these findings, however, we need to address two issues. First, the regulatory focus variable in this experiment was not experimentally manipulated. Instead, we measured participants' chronic focus and categorized participants as prevention or promotion on the basis of a median split on their scores. Therefore, it is desirable to replicate the findings while experimentally manipulating the regulatory focus variable. Second, the extension similarity variable was a within-subjects factor, which may have increased its impact. Although the order of presentation of similar and dissimilar extensions was counterbalanced across participants (and it did not influence any of the dependent measures,) it is also desirable to replicate the findings by manipulating extension similarity as a between-subject factor. The next two experiments were conducted to address these two issues.

promotion focus) as between-subject factors. While doing so, we also extended the findings from Experiment 1 over different product types (durables and nondurables), over different parent brands (i.e., Guess in Experiment 2a and M&M's in Experiment 2b), and over two methods of manipulating regulatory focus, to be explained shortly. Accordingly, two durable categories (casual suit and performance skiwear) were selected as extensions for Guess, and two nondurable categories (chocolate cake and sports drink) for M&M's. Because the methods and results of the two experiments were very similar, we report both experiments together.

Method Participants and design. Two hundred undergraduate students (98 for Experiment 2a and 102 for Experiment 2b) participated in the studies as part of a course requirement. The participants in each experiment were randomly assigned to one of the combinations of a 2 (regulatory focus: prevention vs. promotion) x 2 (extension similarity: similar vs. dissimilar) between-subject factorial design. Selection of parent brands and extension products. One durable-goods brand and one nondurable-goods brand were used as parent brands. Specifically, Experiment 2a used Guess, a well-known clothing brand, as the parent brand, whereas Experiment 2b used M&M1s, a well-known chocolate brand. In a pretest, 20 students evaluated the perceived similarity of various products to Guess and to M&M's. Results suggested that a casual suit was a similar extension (M = 4.80) and performance skiwear a dissimilar extension (M = 3.00) for Guess, tdfl(19) = 8.46, p < .001, and that chocolate cake was a similar extension (M = 5.55) and sports drink a dissimilar extension (M = 2.45) for M&M's, td,fX19) = 9.13, p < .001.

EXPERIMENTS 2a AND 2b These experiments attempted to extend findings from the first experiment by manipulating both extension similarity (similar vs. dissimilar) and regulatory focus (prevention vs.

Procedure. Participants were randomly assigned a folder containing a particular version of the experimental stimuli. They were told that (1) the experiment was about consumer decision making and (2) they would perform two

independent tasks: first, an advertising evaluation (in Experiment 2a) or a student life survey (Experiment 2b) and then a new product evaluation (in both experiments). The first task in both experiments was designed to manipulate regulatory focus in a subtle manner, as follows. Participants in Experiment 2a examined the advertisement contained in the first booklet with the objective of evaluating the editorial components. Two versions of an advertisement for a soy milk product were prepared. One version claimed the product provides energy (promotion-focus condition), whereas the other version claimed it prevents disease and aging (prevention-focus condition; see Aaker & Lee, 2001, for a similar manipulation). After processing the advertisement, participants reported their evaluations of the advertisement along two scales, ranging from 1 (very badvery unfavorable) to 7 (very goodvery favorable). The averaged scores ( a = .77) were similar regardless of the two advertisement versions (3.72 vs. 4.1 I), F ( l , 9 4 ) = 2.60, p > .lo, which indicates that the regulatory focus manipulation was not confounded with favorableness of advertisement evaluations. Participants in Experiment 2b were instead instructed to think about their life events and describe them on a blank sheet. In the prevention-focus condition, they were asked to write about things that they do not want to happen in their lives and ways to avoid them, whereas in the promotion-focus condition, they were asked to consider things that they want to happen and ways that they can achieve them (for a similar manipulation of regulatory focus, see Liberman, Molden, Idson, & Higgins, 2001). Approximately 5 min were given for completing the task. After a short break, participants in Experiments 2a and 2b were given the second task (i.e., product evaluation task), which was presented as a separate task. As in Experiment 1, participants were asked to open the booklet and think about the new product. After thinking about the product for a moment, participants reported their evaluations of the extension along the same scales used in Experiment 1 ( a = .89 in Experiment 2a and a = .91 in Experiment 2b). The remaining procedure was identical to that of Experiment 1.

Results We first analyzed the data from Experiments 2a and 2b separately and obtained substantially similar results. Thus, we report results from the combined data (n = 200) in the following.2

2To determine whether there were differences in results between Experiments 2a and 2b, we analyzed the pooled data in a 2 (similarity condition: similarldissimilar) x 2 (regulatory focus: preventionlpromotion) x 2 (study: Experiment 2alExperiment 2b) analysis of variance on extension evaluations. This analysis indicated that neither the main effect of the study variable nor interaction effect with other variables were statistically significant. Thus, the analysis of the pooled data over Experiments 2a and 2b seems justifiable.

Manipulation check for extension similarity. As intended, participants perceived the extension as more similar to the parent brand when it was a similar extension (M = 4.36) than when it was a dissimilar extension (M = 3.07), F(1, 196) = 32.55, p < .001. Further, this difference was true regardless of the regulatory focus conditions, F < 1. Finally, the regulatory focus factor itself did not influence the perceived similarity of the extension, F < 1. In sum, these results confirm that the manipulation of parent-extension similarity was successful. Extension evaluations. Table 1 shows the means as a function of regulatory focus and extension similarity in the combined data as well as by study. First, a significant main effect for extension similarity indicated that participants evaluated the extension more favorably when it was a similar extension (4.28) than when it was a dissimilar extension (3.64), F(1, 196) = 9 . 2 0 , < ~ .005. This replicates the findings from Experiment 1 and is consistent with the similarity effect that has been reported in the literature. However, this effect was qualified by a significant two-way interaction of regulatory focus and extension similarity, F(1, 196) = 7.54, p < .O1. A planned comparison revealed that, as hypothesized, the similar extension was evaluated more favorably than the dissimilar extension by participants in the prevention-focus conditions (4.56 vs. 3.34), t(196) = 4 . 2 8 , ~ < .001. The difference was negligible, however, in the promotion-focus conditions (4.02 vs. 3.96), t(196) = .19, p > .lo. In sum, Experiments 2a and 2b in combination provide support for H3.3

Discussion These experiments consistently showed that, consistent with H3, participants in the prevention-focus conditions evaluated the similar extension more favorably than the dissimilar one, whereas such a difference was not present for those in the promotion-focus conditions. This extends the findings from Experiment 1 in several ways. First, the hypothesized effect was consistently observed regardless of whether the selfregulatory focus was assessed as a chronic state (Experiment 1) or experimentally induced (Experiments 2a and 2b). Second, the hypothesized effect was obtained regardless of product type (i.e., durables in Experiment 2a, nondurables in Ex-

3This effect might also indicate that prevention-focused people simply prefer chocolate cake to sports drink (in Experiment 2b) and casual suit to performance skiwear (in Experiment 2a) in general, whereas promotion-focused people prefer both products equally. A follow-up study (n = 136) in which product categories (without a brand name) were presented for evaluation, indicated that in general participants tended to consider both chocolate cake and sports drink to be equally favorable (4.99 vs. 4.89), F < I , and that this was not contingent on whether participants were promotion- or prevention-focused, F < 1. In addition, participants in the next experiment (Experiment 3) considered both casual suit and performance skiwear to be similarly favorable in general (5.06 vs. 4.77), F < I , and this was true regardless of regulatory focus conditions, F < 1.

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periment 2b, and services in Experiment 1). Therefore, the hypothesized effect (H3) appears to be robust. The next experiment was intended to provide insights into the cognitive processes underlying this effect.

EXPERIMENT 3 Method

Participants and procedure. One hundred eight undergraduate students completed the life survey task as in Experiment 2b. After a short break, participants evaluated either a similar or a dissimilar extension product by Guess (i.e., Guess casual suit vs. Guess performance skiwear, respectively.) The experimental procedure was similar to that of previous experiments except that we added a series of questions specifically designed to tap into the cognitive processes implied by the equation mentioned earlier, to provide manipulation checks for the regulatory focus variable, and to observe mood state as a confounding check. Measures of cognitive processes. Process measures of the perceived risk and perceived hedonic attainment value of the extension were taken. First, participants rated the perceived risk associated with purchasing the extension along three 7-point scales in terms of likelihood of future regret (very unlikely/very likely), perceived level of risk (not at all risky/very much risky), and perceived uncertainty about quality (not at all uncertain/very much uncertain). These ratings were highly intercorrelated and thus averaged to form a composite index of perceived risk (Cronbach a = .84). Second, the perceived hedonic value associated with attainment of the product was assessed. To do so, participants were requested to first assume that the extension product is actually of high quality and then to rate the degree to which three adjectives accurately represented their reactions to the product along 7-point scales (1 = not at all, 7 = very much). The adjectives were joyful, pleasant, and wonderful. These ratings were highly intercorrelated and thus averaged to form a composite index of perceived hedonic value (Cronbach a = .89). The two composite indexes were moderately and inversely correlated with each other (r = -.22, p < .05). However, a principal components analysis of all six items (the three perceived risk items and the three perceived hedonic-value items) yielded a two-factor solution that accounted for 79.7% of the total variance among items. The loading pattern confirmed that the first three items and the last three items each loaded only on the corresponding risk or hedonic value factor. These results suggest that perceived risk and perceived hedonic attainment value were distinct factors and that both perceptions were measured reliably. Manipulation and confounding checks. As a manipulation check for the regulatory focus variable, participants

were provided with the following two questions: "How much did you think about ensuring achievement and success during the life survey task?'and "How much did you think about avoiding failure and negative consequences during the life survey task?" Participants responded to these questions along ?'-point scales from 1 (not at all) to 7 (very much). For mood confounding checks, participants rated how accurately happy and positive described their mood state during the experiment along 7-point scales from 1 (not at all) to 7 (very much). The two ratings were averaged to form an overall index of mood, because they were highly intercorrelated (r = .69, p < .001).

Results

Manipulation checks. First, regarding the parent-extension similarity manipulation, participants perceived the extension to be more similar to the parent brand, Guess, when it was a casual suit (M = 4.14) than when it was performance skiwear (M = 2.81), F(1, 104) = 24.00, p < ,001. Further, this difference was true regardless of the regulatory focus conditions, F(1, 104) = 1.63, p > .lo. The regulatory focus factor did not influence the perceived similarity of the extension, F(1, 104) = 1.04, p > .lo. These results confirm that the manipulation of parent-extension similarity was successful. Second, the regulatory focus manipulation was also successful. As expected, participants in the promotion-focus condition, compared to those in the prevention-focus condition, reported a higher level of promotion-related thinking (5.75 vs. 4.00) but a lower level of prevention-related thinking (2.87 vs. 4.85). Both differences were statistically significant, Fs > 42.82, ps < .001. Mood confounding checks. To rule out the possibility of any systematic differences in mood between experimental conditions, self-reported mood scores were analyzed as a function of extension similarity and regulatory focus (see the last row of Table 2). Results indicated that participants were in a neutral mood during the experiment (M = 3.88) and that this was unaffected by any of the experimental manipulations, Fs < 1.88, ps > .lo. Thus, none of our manipulations appeared to be confounded with participants' mood state. Extension evaluations. The fifth row of Table 1 shows the mean evaluations of the extension as a function of regulatory focus and extension similarity. Overall, participants evaluated the similar extension more favorably than the dissimilar extension (4.82 vs. 3.74), confirming the similarity effect, F(1, 104) = 19.69, p < .001. However, this effect was qualified by a significant interaction of regulatory focus and extension similarity, F(l,104) = 6 . 3 9 , < ~ .05. That is, the difference between similar and dissimilar extensions was large and significant when the regulatory focus was prevention oriented (4.74 vs. 3.01), t(104) = 4 . 8 8 , ~ < .001, but reduced to a nonsignificant level when the regulatory focus was promo-

REGULATORY FOCUS AND BRAND EXTENSION

tion oriented (4.89 vs. 4.42), t(104) < 1. This is consistent with the results from the previous experiments and provides further support for H3.

Cognitive process measures. According to H 1, a similar extension would be perceived to be less risky than a dissimilar extension, regardless of regulatory focus condition. Table 2 shows mean ratings of perceived risk and perceived hedonic value as a function of extension similarity and regulatory focus. Consistent with HI, participants perceived a higher level of risk about the dissimilar extension (4.36) than about the similar extension (3.63), F(1, 104) = 8.52, p < .005, and this effect was not contingent upon whether participants were prevention-focused or promotion-focused, F < 1. Second, participants perceived the hedonic value of the extension favorably (M = 5.54). However, a closer examination of the data revealed that participants in prevention-focus conditions perceived a higher level of hedonic value about the similar extension than about the dissimilar extension (5.85 vs. 5.00), whereas participants in promotion-focus conditions perceived it in the opposite direction (5.57 vs. 5.70). The interaction effect of extension similarity and regulatory focus was statistically significant, F(1, 104) = 4.18, p < .05. This will be discussed presently. Weights attached to the perceived-risk and the perceived-hedonic value dimension. According to H2, participants in prevention-focus conditions would assign a greater weight to the perceived-risk dimension (W2 in the equation mentioned earlier) than to the perceived-hedonic value dimension (WI in equation) in forming overall exten-

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sion evaluations, whereas the reverse would be true for participants in promotion-focus conditions. A regression analysis was conducted on extension evaluations as a function of self-reported ratings of perceived risk and hedonic attainment value of extensions for each condition of regulatory focus separately. The last column in Table 3 shows the magnitudes of the standardized regression coefficients (W1and W2) for the prevention-focus and promotion-focus conditions separately. In the prevention-focus condition, the coefficients for hedonic value (W] = .366) and perceived risk (W2 = -.563) were sta< .001 and t[50] = -5.67, tistically significant (t[50] = 3 . 6 9 , ~ p < .001, respectively.) However, as consistent with H2, the hedonic value coefficient was significantly smaller in magnitude than the perceived risk coefficient, F(2, 49) = 8.24, p < .05. In the promotion-focus condition, the coefficient for the perceived hedonic value (W1= ,394) was statistically significant, t(52) = 3.18, p < .005, but the perceived risk coefficient (W2 = -.224) was not, t(52) = -1 3 0 , p > .05. Further, as hypothesized, the hedonic value coefficient was significantly larger in magnitude than the perceived risk coefficient, F(2, 5 1) = 3.7 1, p < .05. A further analysis indicated that prevention-focused participants attached a significantly greater weight to the risk factor than promotion-focused participants did (W~S = -.536 vs. -.224), t(106) = 2.1 1, p < .05. In sum, these results provide support for H2. Finally, although the weight attached to the hedonic value factor in the promotion-focus conditions (Wl = .394) tended to be greater than the weight in the prevention-focus conditions (WI = .366), the difference was not statistically significant, t(106) < I. These results suggest that participants in

TABLE 2 Potential Mediators as a Function of Regulatory Focus and Extension Similarity (Experiment 3) --

-

Prevention Focus Similar Extension

Measures

Promot~onFocus

Diss~m~lar Extens~on

Similar Extension

D~ssimilarExtension

Perceived risk Perceived hedonic value Mood

Note.

Cells means in a given row without a common subscript differ from each other at p < .05. TABLE 3 Standardized Regression Coefficients for Perceived Risk and Perceived Hedonic Value in Explaining Extension Evaluations (Experiment 3)

Independent Variables/ Regression Coe@cients Prevention focus W1 (Perceived hedonic value) W2 (Perceived risk) Promotion focus W , (Perceived hedonic value) W ] (Perceived hedonic value)

Similar Extension ( I )

Dissimilar Extension ( 2 )

Total (1) + (2)

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both conditions considered the hedonic value as an important factor in evaluating extensions, but only those in prevention-focus conditions were cautious about the potential risk of the extensions.

GENERAL DISCUSSION Evidence from the existing literature on brand extensions finds similar brand extensions to be evaluated more favorably than dissimilar ones, yet investigations of motivational variables as potential moderators for this similarity effect have been limited. The present research is among the first to show self-regulatory focus to be an important moderator for the effect. On the empirical side, our four experiments provide evidence that similar extensions were evaluated more favorably than less similar ones when participants were prevention focused, whereas this effect was eliminated when participants were promotion focused. Furthermore, this tendency was replicated over different product domains (i.e., services in Experiment 1, nondurables in Experiment 2b, and durables in Experiments 2a and 3) and over different operationalizations of the self-regulatory focus variable (chronic vs. situational; Experiments 1 vs. Experiments 2a, 2b, and 3, respectively). The most important aspects of our results, however, concern the underlying processes for these effects. That is, we hypothesized that people, depending on their self-regulatory focus, would attach different weights to the perceived risk dimension and to the perceived hedonic attainment value dimension when making overall evaluations of extensions. Consistent with this, Experiment 3 showed that participants in prevention-focus conditions considered both risk perception and hedonic value perception as bases for forming extension evaluations, allocating a greater weight to the perception of risk than to the perception of hedonic value. In contrast, participants in promotion-focus conditions primarily focused on the hedonic value perceptions when forming extension evaluations, without considering risk perception to a significant extent. As such, participants in promotion-focus conditions assigned a much smaller weight to the risk factor than did participants in prevention-focus conditions, despite the fact that both participants perceived the similar extension as significantly less risky than the dissimilar extension. To our knowledge, this effect has not been previously reported. It is worth noting that participants in prevention-focus vs. promotion-focus conditions tended to make risk judgments similarly but hedonic value judgments differently. That is, participants in both conditions perceived the similar extension to be less risky than the dissimilar extension. However, participants in prevention-focus conditions perceived a higher level of hedonic value for the similar extension than the dissimilar extension, whereas the pattern in promotionfocus conditions was in the opposite direction (see Table 2).

Further, this interaction was attributable to a significant difference in the perceived hedonic value of the dissimilar extension between prevention-focus and promotion-focus conditions (5.00 vs. 5.70, p < .05). One possible explanation for this difference is that promotion-focused participants might have spontaneously interpreted the far-reaching nature of the dissimilar extension positively (e.g., "adventurous"), whereas prevention-focused participants interpreted it more negatively (e.g., "reckless"). Such interpretation might have influenced participants' hedonic value judgments independently of other considerations (c.f. Park & Kim, 2002; for a more general discussion of the effect of concept accessibility on encoding, see Park, Yoon, Kim, & Wyer, 2001, or Wyer & Srull, 1989). Future research might attempt to test this possibility empirically. One might consider the role of positive affect as an alternative explanation for our results. One possibility is that our regulatory focus manipulation elicited a more positive mood for participants in the promotion-focus than for those in the prevention-focus conditions. The enhanced mood in promotion-focused participants might have increased perceived similarity of extensions to the parent brand, particularly under conditions in which this similarity was ambiguous (i.e., extensions were moderately dissimilar), which in turn might have enhanced favorableness of extension evaluations (e.g., Barone, 2005; Barone et al., 2000). This alternative explanation, however, is unlikely to hold in our research for two reasons. First, in none of our experiments did participants in promotion- versus prevention-focus conditions perceive the similarity of extensions differently. Second, the mood confounding checks in Experiment 3 indicated that participants' mood did not vary over regulatory focus conditions. Another possibility is that a positive mood induced by the promotion-focus manipulation might have reduced processing elaboration and as a result led participants in the promotion-focus conditions to be insensitive to the manipulation of parent-extension similarity. If this were true, promotionfocused participants should have rated the perceived risk of an extension the same regardless of whether it was a similar or dissimilar extension. Yet, our data indicated that both promotion-focused and prevention-focused participants perceived the dissimilar extensions to be more risky than the similar extensions. This seems to argue against a processing elaboration explanation. Nonetheless, future research that examines the alternative hypothesis more directly by adding a manipulation of strong versus weak message arguments into the experimental design would be of value. Recently, Yeung and Wyer (2005) found that people based extension evaluations on the affect-based impression they formed when they were first exposed to the parent brand name, if the parent brand itself was affect eliciting and participants were not explicitly asked to consider similarity during evaluations. Under these conditions, brand-elicited affect had an influence on extensions even when the extension and

REGULATORY FOCUS AND BRAND EXTENSION

the parent brand were dissimilar. Thus, this could also potentially account for our results if one assumes that a promotion focus facilitates such an affective process. However, this "affect-as-information" notion should produce a main effect of regulatory focus, not an interaction effect, which we observed here. Further, we obtained the same results regardless of whether the parent brand itself was likely to be affect eliciting (e.g., M&M's in Experiments 2b) or not likely (e.g., CNN in Experiment I). Therefore, this possibility is also unlikely to hold. Nonetheless, some caution should be taken in overgeneralizing our findings. That is, the dissimilar extensions used in our experiments represent a relatively moderate level of incongruity with the parent brand. It may be worthwhile to investigate in future whether promotion-focused individuals' relatively favorable evaluations of dissimilar extensions can be generalized to situations in which extension products belong to extremely dissimilar categories, such as in the example of Guess sports drink.

ACKNOWLEDGMENTS This research was supported by the IBRE research grant of Korea University Business School to Jongwon Park. We gratefully acknowledge members of the Korea University B.E.S. 7: Marketing Group for their valuable suggestions concerning the theoretical basis for the study and the interpretation of the results. We also thank Professors Susan Jung Grant, Gangsuk Ryu, Jaehwan Kim, and three anonymous reviewers for insightful comments on earlier versions of this article.

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Received: April 25, 2005 Revision received: November 1 1, 2005 Accepted: December 9,2005