Product Samsung

The current issue and full text archive of this journal is for sale at www. emeraldinsight. com/0309-0566. htm EJM 44,7/8 Consumer responses to stag citations a comprehensive feign ? ? Eva Mart? nez and Jose M. Pina ? Facultad de Ciencias Economicas y Empresariales, The University of Zaragoza, Zaragoza, Spain Abstract Purpose This paper aims to understand the reciprocal spill-over onuss of gull flanks by testing a comprehensive nonplus that gathers both the trade name prolongation evaluation process and the later in? uence on steel look-alike. throw/methodological analysis/approach Data were obtained from 699 face-to-face interviews conducted in Spain.Structural equation modelling was apply to test the proposed hypotheses. Findings The chairs indicate that grease denotations expect feedback topic on shop estimate depending on the pose toward the tonic produce and comprehend emblem ? t. Consumer military strength depends, in turn, on initial sucker cr ossties, comprehend kin ? t, perceived image ? t and consumer innovativeness. tag knownity also shows in air personal set up. Research limitations/implications The model should be tested with extensions of the like ( position extensions) or unlike categories.It is also necessary to break non-? ctitious returns, and to take different moderating do into account. Practical implications The results suggest how to protect the tarnish image from unsuitable extension strategies. The paper shows what kind of perceived ? t is much important for consumers as well as the direct and indirect role of several(prenominal) variables. Originality/value The paper extends precedent(prenominal) look into by proposing a complete frame utilisation that lots the components that in? uence either the attitude to the extension or the attitude to the broaden crack.Samsung Distribution ChannelKeywords disfigurement extensions, Brand image, Brand equity, Consumer behaviour, Spain Paper gr apheme Research paper 1182 Received January 2008 Revised October 2008 January 2009 Accepted February 2009 Introduction Brand extension is a strategy that many companies follow with the aim of bene? ting from the taint knowledge achieved in the current markets (Aaker and Keller, 1990 Milberg et al. , 1997). When a impertinently product is marketed under a well-known brand name, failure rates and marketing costs ar reduced (Milewicz and Herbig, 1994 Keller, 2003). Keller (2003) states that much than than 80 per cent of ? ms resort to brand extensions as a appearance of marketing goods and services. The support that the brand gives to the new(a) product often leads to a change in the brand image associations. Both the affection and the speci? c knowledge associated with the brand and the new product be interchanged in the consumers mind (Czellar, 2003). European ledger of market Vol. 44 No. 7/8, 2010 pp. 1182- great hundred5 q Emerald Group Publishing Limited 0309-0566 DOI 1 0. 1108/03090561011047580 The authors would like to thank the followers sources for their ? nancial attend to CICYT (Ref ?SEJ2005-02315) and Government of Aragon (GENERES, Ref. S-09 PM0262/2006). They also gratefully acknowledge the constructive comments of the three anonymous EJM reviewers. This feedback process gage increase the memory and strength of brand associations (Morrin, 1999 Aaker, 2002) and, thus, improve the billet of the brand (Park et al. , 1986). Nevertheless, several authors indicate that the dilution of current beliefs is more than likely (Tauber, 1988 Ries and Trout, 1993 John et al. , 1998). This dilution effect can take place even though the extension is non related to disconfirming learning (Morrin, 1999 ?Ahluwalia and Gurhan-Canli, 2000 Mart? nez and Pina, 2003). Virgin, for instance, is a company that has grown with extensions into the audiovisual sector, retailing, alcoholic drinks, passenger transport (by railway and air) and space tourism, among new(prenominal)s. However, market research studies suggest that customers perceptions of the Virgin brand mainly depend on the performance of the airline, which implies a constant threat of image dilution (Hughes, 2007). The in? uence of brand extension on brand image is apologiseed by several theories, around of them coming from Psychology. tally to the associative network theory, brand image may be silent as a mental scheme formed by a network of concepts (nodes) interconnected by linkages or associations (Anderson, 1983 Morrin, 1999). Park et al. (1993) explain that extensions which atomic number 18 rational with the brand schema pass on not lead to image dilution (assimilation process). On the another(prenominal) hand, the brand schema allow for be modi? ed to accommodate examples that are cold from current brand attitudes and beliefs (accommodation process). Following Weber and Crockers (1983) ? ork, Gurhan-Canli and Maheswaran (1998) suggest that the image modi? catio n could be re? ected in the formation of a mental subcategory indoors the brand scheme (sub-typing model) or in a complete modi? cation of brand associations (conversion model). The sub-typing or conversion processes may occur when perceived ? t or typicality surrounded by the extension category and the brand is low. However, it is just possible that brand attitudes and beliefs would always change because of the new information, which is c on the wholeed the bookkeeping model (Weber and Crocker, 1983 Loken and John, ? 993 Gurhan-Canli and Maheswaran, 1998). Consumers could react according to the bookkeeping model when the information on the new product is highly accessible. Regardless of perceived ? t, higher accessibility gives drum to an image enhancement, whereas lower accessibility has a negative effect on brand evaluations (Ahluwalia and ? Gurhan-Canli, 2000). The brand extension literary works shows that brand extensions can affect both the ? ecumenical brand associations (Mart? nez and de Chernatony, 2004) and the beliefs in speci? attributes (Keller and Aaker, 1992 Loken and John, 1993). The beliefs related to the most re nonplusative product of the brand, or ? agship product, are more resistant to dilution ( John et al. , 1998 Chang, 2002), as well as the perceptions cerebrate to the brand constitution (Diamantopoulos et al. , 2005). Most previous research on brand extensions develops experimental designs, focusing on a reduced number of variables (e. g. Loken and John, 1993 John et al. , 1998 Alexander and Colgate, 2005). Some authors assimilate tested models finished structural ? equation modelling (e. g.Bhat and Reddy, 2001 Volckner and Sattler, 2006) although they concentrate on consumer attitude toward brand extensions and not on reciprocal spillover effects. According to literature, brand extensions may give rise to both a forward effect from the lift brand to the new product and a feedback or backward effect from the new product to th e parent brand (Milberg et al. , 1997 Responses to brand extensions 1183 EJM 44,7/8 1184 Balachander and Ghose, 2003). Neglecting this probable backward effect affords a limited view of consumer behaviour and may lead to inappropriate marketing actions.With the death of bankrupt understanding the way that extensions in? uence brand image, our work proposes and validates a speculative model that, according to the previous literature, integrates the most relevant variables. With the exception of the ? plowshare of Volckner and Sattler (2006), previous models only focus on a few variables, which devils it dif? cult to determine how the consumers responses to brand extensions are generated. Furthermore, the proposed model considers both the brand image in the lead the extension and the image var., which is a step forward in literature.As well as brand image, we result analyse the effects of brand acquainted(predicate)ity, attitude to the extension, extension-brand ? t (categor y and image ? t), perceived dif? culty in manufacturing the extension product and consumer innovativeness. Hence, the direct expands previous research by testing a comprehensive model that gathers both the brand extension evaluation process and the later in? uence on brand image. This model can help brand managers to protect their brands from unsuitable brand extensions by showing the main determinants of spillover effects and the direct and indirect effects of the speci? variables. Relationships that have been individu whollyy supported in previous works could be rejected when considering composite models with several dependent and independent variables. The study is organized in four sections. The next section contains a brief review of the literature to justify the theoretical model and the transaction established in the hypotheses. The third section describes the methodology use to validate the model, and the results are reported in the fourth section. Finally, we computer address the conclusions and managerial recommendations.Proposed model and hypotheses The proposed model helps us to understand the in? uence of brand extensions on brand image. For this reason, the model includes the variables with the greatest impact on extension attitude (Aaker and Keller, 1990 ahem et al. , 2003). This attitude ordain determine the development of the brand image (Lane and Jacobson, 1997), affecting the current associations. The model stems from the initial brand image and set outs to identify the main relations and interactions that follow the launching of the brand extension and its potential effects on the established associations.Generally, consumer attitudes toward brand extensions can depend on factors related to brand associations, all-embracing category, perceived ? t, and consumer characteristics (Czellar, 2003 Reast, 2005 ? Volckner and Sattler, 2006). Hence, two brand knowledge factors, brand familiarity and initial brand image, are considered. In re lation to the new product and its ? t with the parent brand, we consider perceived dif? culty in manufacturing, perceived category ? t and perceived brand image ? t. Extension attitude and consumer innovativeness are also taken into consideration. Whereas brand associations and ? have been examined in nearly every study on brand extensions, perceived dif? culty and consumer innovativeness have received lesser attention. Since Aaker and Kellers (1990) fundamental study and all attendant replications (Barrett et al. , 1999) analysed perceived dif? culty with inconclusive results, it seems necessary to study this variable more in depth. On the other hand, the whole literature on brand extensions relies on the assertion that a known brand reduces the risk associated with get new products (Smith and Park, 1992), and consumer innovativeness re? ects the consumers risk aversion.The proposed effects of these variables and the remaining peerlesss are depicted in phone number 1. The ? r st variable included in our model is brand familiarity. This variable is closely related to the dimension of brand equity labelled as awareness by Aaker (1996), since familiar brand names usually present high awareness. Moreover, it is also akin to the brand image construct, which refers to the different perceptions about a brand re? ected as associations existing in the memory of the consumer (Keller, 1993). Direct effects on extension attitude are expected for brand familiarity as well as indirect ones through brand image.First, individuals will have a better initial image of the brands they are familiar with (Low and Lamb, 2000 Lemmink et al. , 2003). By style of a ring effect, the impressions of familiar attributes are used to form precise opinions on brands (Reynolds, 1965) and develop more complete knowledge structures (Alba and Hutchinson, 1987 Grime et al. , 2002). Furthermore, familiarity in instanter re? ects the suffer with a brand (Alba and Hutchinson, 1987), presenti ng a clear relationship amongst experience and brand image (Hoek et al. , 2000).Familiarity can also have a direct effect on brand extension evaluations. Consumers are more inclined to buy products of brands they have antecedently consumed (Swaminathan, 2003) and know better, unless the experience has been unsatisfactory (Swaminathan et al. , 2001). Although several(prenominal) works have failed to prove that familiarity affects consumer attitude to an extension (Glynn and Brodie, 1998) and to the extended brand (Diamantopoulus et al. , 2005), we hypothesise H1. The greater the familiarity of the core brand, the more positive the initial brand image. H2.The greater the familiarity of the core brand, the more preferable the attitude to the extension. Brand image is an essential factor for understanding consumer attitude toward brand extensions, since the credibility of the new product increases when brand perceptions become more favourable (de Ruyter and Wetzels, 2000). If the bra nd image consists of Responses to brand extensions 1185 range 1. Proposed model to analyse the effect of brand extension strategy on brand image EJM 44,7/8 1186 associations such as a high-perceived quality, the extension attitude will be better (van ? Riel et al. 2001 Volckner and Sattler, 2006). In the same vein, the extension attitude is positively related to the perceptions of write up (Hem et al. , 2003), prestige (Park et al. , 1991) and the consumers affection for the brand (Sheinin and Schmitt, 1994). In the eccentric of corporate and service brands, a positive image also clearly generates favourable perceptions of the new products (Brown and Dacin, 1997 de Ruyter and Wetzels, 2000). given(p) that the extension leverages the current brand associations, the better the initial brand image the more positive will be the consumers response.Therefore H3. The more positive the initial brand image, the more favourable the attitude to the extension. If consumers perceive a high ? t amongst the brand and the new product, the brand leveraging increases and the potential negative effects are less likely (Czellar, 2003). Some authors state that consumers can consider a category ? t or an image ? t (Bhat and Reddy, 2001 Grime et al. , 2002 Czellar, 2003). Thus, individuals can believe that the new product is physically similar to the other products of the brand (category ? t) or dogged with the general brand associations (image ? ) (Grime et al. , 2002 Czellar, 2003). Whatever the case, the consistency between cognitive elements and the similarity among various stimuli ease and improve consumers evaluations (Aaker and Keller, 1990 Eagly and Chaiken, 1993). Brand image-perceived ? t interaction effects are propounded in the literature (Boush et al. , 1987 Aaker and Keller, 1990) as well as ? direct effects (Volckner and Sattler, 2006). The next hypotheses deal with the direct effects of perceived ? t dimensions on extension evaluation. As commented supra, perc eived category and image ? will directly affect the consumer attitude to the extension. Generally, the respectment of an extension will be more positive as perceived closeness with the brand grows (Aaker and Keller, 1990 ? Volckner and Sattler, 2006), even in the case of non-prestige brands (Park et al. ,1991). However, consumers believe that extensions to non-related categories are not very reliable and offer low quality, which causes a negative mensuratement (Kirmani et al. , 1999). According to the literature, a high-perceived category or image ? t makes success more likely (Boush et al. 1987 Boush and Loken, 1991 Park et al. , 1991). The important thing is to lounge around the consumers to relate the new product to the brand, independently of the kind of closeness. This discussion leads to the following hypotheses H4. The greater the perceived category ? t between the extension and the core brand, the more favourable the attitude to the extension. H5. The greater the perceive d image ? t between the extension and the core brand, the more favourable the attitude to the extension. Another variable included in our model is perceived dif? ulty in manufacturing or offering a new good or service. This variable has been analysed in numerous works, although it is not clear whether it in? uences consumer behaviour or not (Barrett et al. , 1999 van Riel et al. , 2001). Moreover, present research does not clarify whether this in? uence is positive (Aaker and Keller, 1990 van Riel and Ouwersloot, 2005) or negative (Semeijn et al. , 2004). This diversity of results re? ects that the in? uence of dif? culty in manufacturing might depend on the study settings and the variables interacting with such dif? culty.Generally, consumers who think that the new product category requires little manufacturing effort may question its advisability (Aaker and Keller, 1990). They could even think that high-quality brands are trying to make prompt money by overpricing trivial product s (Aaker and Keller, 1990 van Riel et al. , 2001). In a sense, easy-to-make extensions could resemble downscale extensions, where the brand stretches down by offering lower price-quality products (Kirmani et al. , 1999). Consequently, we posit H6. The greater the perceived dif? culty in manufacturing the new product, the more favourable the attitude to the extension.The last variable of our model to explain attitude to the extension is consumer innovativeness, a concept that represents the consumers longing to buy new products and consider new ideas (Roehrich, 2004). Since innovative people are more risk-prone (Klink and Smith, 2001 Hem et al. , 2003), they show a better attitude toward brand extensions, any(prenominal) their perceived ? t (Klink and Smith, 2001). In this sense, some authors have found that higher consumer innovativeness increases perceived quality and purchase intention of new services (Hem et al. , 2003 Siu et al. , 2004) and ? tangible products (Volckner and Sat tler, 2006).Rogers (1983) claims that one of the most salient traits of consumer innovators is the comfort they gain from taking risk. Unlike later adopters, highly-innovative individuals ? nd far extensions appealing (Xie, 2008) and, consequently, do not mind trying products that get away from the companys core business. As a matter of fact, they should be more prone to try new products regardless of the degree of brand knowledge or perceived ? t. Consequently, we posit H7. The greater consumer innovativeness, the more favourable the attitude to the extension. The following hypotheses relate to the feedback effect on brand image.Because of the new information, the brand schema could vary its structure of nodes and connect (Morrin, 1999). There is no doubt that most brand associations will remain stable after stretching to new categories, being the ? nal perceptions mainly determined by the ? initial ones (Lee and Ulgado, 1993 Mart? nez and Pina, 2003). However, product introductio ns in the marketplace involve providing consumers with information, which not always ? ts with the initial beliefs and feelings about the brand. As elucidated by previous research, the attitude to the extension is a major driver of spillover effects from the extension to the parent brand.Low quality or negatively ? assessed extensions will mean a detriment of brand image (Chang, 2002 Mart? nez and ? Pina, 2003), diluting both general and speci? c beliefs (Mart? nez and de Chernatony, 2004). Diamantopoulos et al. (2005) found that brand personality is more dilution-resistant, although any brand association is exposed to the risk of dilution. A way of reducing this risk is to strengthen the attitude to the extension, given that consumers who are satis? ed with the extension are usually satis? ed with the brand (Alexander and Colgate, 2005). The following hypothesis is based on these arguments. H8.The better the attitude to the extension, the more favourable the feedback effect on the extended brand. Responses to brand extensions 1187 EJM 44,7/8 1188 The literature reveals that the attitude to an extended brand directly depends on the degree of ? t with the extension (Grime et al. , 2002). The introduction of extensions far from the core business will involve losing brand differentiation and credibility, whereas extensions to related markets will avoid potential damage (Aaker, 2002). Some authors like Milberg et al. (1997) have proved that low-? t extensions generate negative feedback in wrong of attributes or image.Similarly, Lee and Ulgado (1993) ? veri? ed that ? t has a positive effect on the image of service ? rms, whereas Mart? nez and de Chernatony (2004) veri? ed the same for tangible product extensions. Other works equally suggest that the impact of brand extensions on the parent brand is ? directly related to similarity (Mart? nez and Pina, 2003) or image ? t (Loken and John, 1993 John et al. , 1998). All in all, we expect a more positive feedback eff ect provided the brand stretches limpidly with either its image or current products. H9. The greater the perceived category ? between the extension and the core brand, the more favourable the feedback effect on the extended brand. H10. The greater the perceived image ? t between the extension and the core brand, the more favourable the feedback effect on the extended brand. Methodology An empirical study was conducted to contrast the hypotheses and validate the model displayed in Figure 1. Following the usual numbers, we utilised real brands and realistic hypothetical extensions (Aaker and Keller, 1990 van Riel et al. , 2001 van Riel and Ouwersloot, 2005) that were previously selected through three pre-tests.Below, we explain these and other aspects related to the methodology applied. Pre-tests In line with previous research, a specimen of undergraduates was employed in the pre-tests (Sheinin and Schmitt, 1994 Kim, 2003). The speci? c brands and extensions were selected by means of Wilcoxon tests, which were necessary due to the lack of normality in the info. The aim of the ? rst pre-test, conducted with 91 students, was to choose brands in three sectors (fast moving consumer goods, durable consumer goods and services) that were familiar (F) to individuals and had a different image perception (I).Familiarity is an essential requisite to stock warrant that consumers have a clear image to evaluate (Low and Lamb, 2000). Two questions were thus formulated to assess those concepts in seven-point Likert scales (1 ? Totally unfamiliar/7 ? truly familiar 1 ? Bad image/7 ? Excellent image) for a total of 11 brands. According to the results, Colgate ? and Signal (FC ? 6. 38 FS ? 5. 50), Nike and jaguar (FN ? 6. 56 FP ? 5. 64), Telefonica Movistar and Amena (FT ? 6. 64 FA ? 6. 27) were elect as familiar brands. The image is signi? bevel squarely different in toothpaste brands (IC ? 5. 74 IS ? 4. 96 Z ? 2 4. 618 p , 0. 0001), sports brands (IN ? 6. 21 IP ? 5. 10 Z ? 2 5. 449 p , 0. 00001) and mobile phones (IT ? 5. 67 IA ? 4. 88 Z ? 2 4. 001 p , 0. 00001). The second and third pre-tests, where 98 and 81 students, respectively, participated, were aimed at ? nding two extensions one for apiece sector with differences in perceived ? t. Both perceived category ? t (CF) and brand image ? t (IF) were considered (Bhat and Reddy, 2001) in two Likert scales (1 ? Not at all similar/7 ? Very similar 1 ? Non-coherent/7 ? Very coherent). For the toothpaste brands, sugar-free whitening tooth decay-preventing sweets and sunglasses were selected.The ? rst showed a higher perceived ? t than the second for Colgate (CF1 ? 5. 36 CF2 ? 1. 31 Z ? 2 5. 341 p , 0. 00001) (IF1 ? 5. 69 IF2 ? 1. 54 Z ? 2 5. 339 p , 0. 00001) and Signal (CF1 ? 4. 86 CF2 ? 1. 19 Z ? 2 5. 120 p , 0. 00001) (IF1 ? 5. 19 IF2 ? 1. 25 Z ? 2 5. 019 p , 0. 00001). On the other hand, for the sports brands, we chose skis as a close extension and DVD players as a far extension, both from the pers pective of product category of Nike (CF1 ? 3. 33 CF2 ? 1. 28 Z ? 2 5. 120 p , 0. 00001) and Puma (CF1 ? 3. 32 CF2 ? 1. 14 Z ? 2 4. 910 p , 0. 00001).Similarly, there were statistical differences between the image ? t of the extensions for Nike (IF1 ? 4. 23 IF2 ? 1. 36 Z ? 2 5. 561 p , 0. 00001) and Puma (IF1 ? 3. 89 IF2 ? 1. 14 Z ? 2 5. 113 p , 0. 00001). Finally, telecommunication on-line courses and insurance were the service extensions selected. Speci? cally, the perceived category ? and image ? t were statistically different for Telefonica Movistar (CF1 ? 4. 67 CF2 ? 1. 84 Z ? 2 5. 475 p , 0. 00001) (IF1 ? 4. 72 IF2 ? 1. 72 Z ? 2 5. 543 p , 0. 00001) and Amena (CF1 ? 3. 73 CF2 ? 1. 76 Z ? 2 4. 283 p , 0. 00001) (IF1 ? 4. 27 IF2 ? 1. 84 Z ? 2 4. 61 p , 0. 00001). Sample and procedure Subsequent to the pre-tests, we elaborated 12 questionnaires with a different brand-extension combination. On the ? rst page, individuals had to indicate their consumer innovativeness and answer some questions about the corresponding brand (familiarity and image) and product category (perceived dif? culty). Then, on the second page of the questionnaire, respondents were required to imagine that the speci? c brand launched the extension. Questions then assessed the ? t, the respondents attitudes towards the extension and the brand image, supposing the existence of the new product category.No additional information about the products attributes was provided in order to avoid bias that could defeat the objective of the study (Bhat and Reddy, 2001). The surveys were answered by a total sample of 720 individuals (699 valid cases) in a Spanish city, which is sometimes considered as a test market for products aimed at Spain. The respondents were approached by a team up of interviewers in different parts of the city, on different days and at different times during May 2005. By following a quota sampling procedure, the sample was required to match the population structure by sex (50. 9 per cent women and 49. per cent men) and age (46. 5 per cent 26-45 years, 33. 3 per cent 16-25 years, 20. 2 per cent 46-64 years). These demographical variables may be strong predictors of changes in attitudes and behavior (Hansman and Schutjens, 1993) and, therefore, should be controlled to get adequate variance in the selective information. Table I shows the type of questionnaires used in our research and the speci? c number of individuals who satisfactorily responded to each. No individual answered more than one questionnaire. Measures Variables were measured through seven-point Likert scales by requesting individuals either to state their aim of agreement with the speci? statement (1 ? Totally disagree, 7 ? Totally agree) or directly assess the variable (e. g. 1 ? Not at all familiar, 7 ? Very familiar). In all cases, items were extracted or based on the literature. In order to avoid potential order effects (Klink and Smith, 2001), perceived Responses to brand extensions 1189 EJM 44,7/8 N8 Brand 49 Colgate Extension (high ? t) Sugar-free whitening tooth decaypreventing sweets Sugar-free whitening tooth decay Skis Skis Telecommunication online courses Telecommunication online courses N8 Brand 50 Colgate 48 49 49 80 Signal Nike Puma ? Telefonica Movistar 75 AmenaExtension (low ? t) Sunglasses Sunglasses DVD players DVD players Insurance Insurance 1190 Table I. Type and number of questionnaires Signal Nike Puma ? Telefonica Movistar 79 Amena 49 48 49 74 dif? culty was assessed prior to brand characteristics and ? t. For the same reason, ? nal image was measured once the individuals had formed an opinion about the brand extension. Table II shows the scales used for each factor. First, consumer innovativeness was measured with the items proposed by Roehrich (1994), who considers a dual perspective, hedonistic and social. Perceived dif? ulty was assessed through an item used by Aaker and Keller (1990) and two additional items coherent with the concept. For bra nd familiarity, we used Dawars scale (Dawar, 1996), whereas the scale validated by Martinez et al. (2004) was employed to assess initial and ? nal brand image. This scale utilises items from several works (Martin and Brown, 1990 Weiss et al. , 1999) which attempt to assess tangible (functional image) and intangible (affective image) attributes and bene? ts, as well as the global attitude to the brand (reputation). The distinction made by several authors between category ? t or similarity and image ? or consistency with brand image (Park et al. , 1991 Bhat and Reddy, 2001 Grime et al. , 2002) was used to measure perceived ? t. Thus, a series of items that assess ? t from both perspectives (Aaker and Keller, 1990 Taylor and Bearden, 2002) were chosen. Finally, extension attitude items were suggested by authors like Aaker and Keller (1990) or Pryor and Brodie (1998) considering both the general assessment of the new product and purchase intentions. Results The collected data were analy sed by means of structural equations methodology, assessing both the measurement and the structural model (Kline, 2005).The structural model allows us to know whether there is evidence to reject the proposed hypotheses, although previously the measurement model has to evaluate the psychometric properties of the scales in terms of unidimensionality, reliability and validity. Furthermore, some ? t indicators show whether the measurement and structural models explain the collected data with relative precision (Hair et al. , 1998). Scale constitution Prior to analysing all the variables as a whole, we studied whether initial brand image, ? nal brand image, consumer innovativeness and perceived ? should be considered as multidimensional or unidimensional factors, since the distinction between the Scale Consumer innovativeness. Roehrich (1994) Measured concept Hedonist innovativeness (HINN) HINN1 I am more interested in buying new than known products HINN2 I like to buy new and different products HINN3 New products excite me Social innovativeness (SINN) SINN1 I am usually among the ? rst to try new products SINN2 I try new products before my friends and neighbours SINN3 I know more than others about the latest new products DIFF1 Dif? ulty in designing and making the product DIFF2 difficult techniques or knowledge are needed DIFF3 Specialised resources are needed (personnel, facilities. . . ) FAMI1 Familiarity with the brands products FAMI2 Purchase frequency of the brands products FAMI3 Knowledge of the brands products Functional image (FUIM) (initial/? nal) FUIM1i/FUIM1f The products have a high quality FUIM2i/FUIM2f The products have better characteristics than competitors FUIM3i/FUIM3f The products of the competitors are usually cheaper Affective image (AFIM) (initial/? al) AFIM1i/AFIM1f The brand is straitlaced AFIM2i/AFIM2f The brand has a personality that distinguishes it from competitors AFIM3i/AFIM3f It is a brand that does not disappoint its customers Re putation (REIM) (initial/? nal) REIM1i/REIM1f It is one of the best brands in the sector REIM2i/REIM2f The brand is very consolidated in the market Category ? t (CAFI) CAFI1 The extension is similar to the brands products CAFI2 The ? rms resources are helpful to make the product extension type ? t (IMFI) IMFI1 The product extension ? s with the brand image IMFI2 Launching the extension is logical for the company IMFI3 Launching the extension is appropriate for the company EXAT1 good attitude towards the extension EXAT2 Perceived quality of the extension EXAT3 Likelihood of trying the extension Responses to brand extensions 1191 Perceived dif? culty (DIFF). Aaker and Keller (1990) Brand familiarity (FAMI). Dawar (1996) ? Brand image. Mart? nez et al. (2004). Based on Martin and Brown (1990) Aaker (1996) Weiss et al. (1999) Villarejo (2002) Perceived ? t. Aaker and Keller (1990) Taylor and Bearden (2002) Extension attitude (EXAT).Aaker and Keller (1990) Pryor and Brodie (1998) Table II. Scales used in the questionnaires EJM 44,7/8 1192 proposed dimensions (e. g. hedonistic and social innovativeness) could be statistically non-advisable. Through a previous analysis with SPSS 13. 0, we detected a weak item-total correlation of FUIM3i (corr. ? 0. 281) and FUIM3f (corr. ? 0. 296) with the respective dimensions of functional image. After eliminating them, we conducted an explanatory factor analysis for the unidimensional and multidimensional models using the EQS 5. b and ERLS (elliptical re-weighted least squares) adherence method.The initial image, ? ?nal image and perceived ? t scales proved to be reliable in both models (Joreskog and ? Sorbom, 1993), although it was advisable to eliminate HINN1 related to consumer innovativeness. Although the factor loadings exceeded the cut point lU ? 0540 lM ? 0673? the R 2 coef? cients ? R 2 ? 0292 R 2 ? 0453? were to a lower place those recommended in the literature (Hair et al. , 1998). Once the scales had been properly re? ned, we proceeded to compare the unidimensional and multidimensional models through several indicators (Hair et al. , 1998 Kline, 2005). Tables III and IV display the coef? ients obtained, which clearly favour the consideration of independent dimensions for all the factors analysed. The only forcees in which the unidimensional model surpasses the multidimensional one are PNFI and PGFI for the factors of initial brand image (PNFI ? 0. 511 , 0. 638 Comparative indicators initial image Unidimen. Multidimen. 126. 181 0. 047 0. 221 112. 181 0. 160 0. 638a 0. 466a 154. 181 72. 177a 0. 034a 0. 152a 61. 177a 0. 088a 0. 511 0. 377 106. 177a Final image Unidimen. Multidimen. 211. 559 0. 053 0. 343 197. 559 0. 283 0. 628a 0. 449a 239. 559 51. 082a 0. 027a 0. 122a 40. 082a 0. 057a 0. 516 0. 382 85. 082a x2RMSR (Root mean square residual) ECVI (Expected cross-validation index) NCP (Noncentrality parameter) SNCP (Scaled noncentrality parameter) PNFI (Parsimonious normed ? t index) PGFI (Pars imonious goodness of ? t index) AIC (Akaike information criterion) Table III. Indicators of the alternative models of brand image (initial and ? nal) mark off aCoef? cients that are favourable to the speci? ed model Comparative indicators Consumer innov. Unidimen. Multidimen. 195. 411 0. 079 0. 309 190. 411 0. 272 0. 453a 0. 292a 215. 411 31. 088a 0. 022a 0. 076a 27. 088a 0. 039a 0. 394 0. 261 53. 088a Perceived ? t Unidimen. Multidimen. 77. 634 0. 34 0. 140 72. 634 0. 104 0. 483a 0. 314a 97. 634 50. 164a 0. 025a 0. 103a 46. 164a 0. 066a 0. 391 0. 256 72. 164a x2 RMSR (Root mean square residual) ECVI (Expected cross-validation index) NCP (Noncentrality parameter) SNCP (Scaled noncentrality parameter) PNFI (Parsimonious normed ? t index) PGFI (Parsimonious goodness of ? t index) AIC (Akaike information criterion) Table IV. Indicators of the alternative models of consumer innovativeness and ? t Note aCoef? cients that are favourable to the speci? ed model PGFI ? 0. 377 , 0. 466), ? n al image (PNFI ? 0. 516 , 0. 628 PGFI ? 0. 382 , 0. 449), consumer innovativeness (PNFI ? . 394 , 0. 453 PGFI ? 0. 261 , 0. 292) and perceived ? t (PNFI ? 0. 391 , 0. 483 PGFI ? 0. 256 , 0. 314). Nevertheless, the parsimony indicator, AIC, which allows us to choose between models with a different number of latent variables, as in our case, presents better values in the multidimensional structure initial image (AIC ? 106. 177 , 154. 181), ? nal image (AIC ? 85. 082 , 239. 559), consumer innovativeness (AIC ? 53. 088 , 215. 411) and perceived ? t (AIC ? 72. 164 , 97. 634). After verifying the multidimensional character of initial brand image, ? nal brand image, consumer innovativeness and perceived ? , our next step was to conduct a factor analysis of all the scales. Again, we used EQS and ERLS, obtaining the results shown in Table V. We can infer from these results that the scales present good statistical properties. As can be seen in Table V, all the proposed items unidimensionally ? t the respective 13 factors or latent variables. The values obtained in composite reliability coef? cients and extracted variance analysis (EVA) are to a higher place 0. 6 and 0. 5, respectively, which guarantees the immanent consistency of the scales. Moreover, the validity criterion was satis? ed from both convergent and discriminant viewpoints.Thus, all lambda coef? cients for the observed variables are signi? huckster (t . 1. 96) and they load on the corresponding factors with standard loadings above 0. 5. The con? dence intervals of between-factor correlations were calculated to analyse discriminant validity. No intervals included value 1, which indicates the differentiated character of the factors. The main goodness-of-? t indicators for the measurement model are shown at the tin can of Table V, distinguishing between global and incremental ? t indexes. On the whole, the indicators are positive and above the minimum established by researchers (Hair et al. 1998 Kline, 200 5). With regard to global ? t, GFI is above 0. 8 (GFI ? 0. 884), whereas RMSEA and SRMR error statistics were below the maximum values of 0. 06 (RMSEA ? 0. 053) and 0. 08 (SRMR ? 0. 040) recommended by Hu and Bentler (1999). The only unsuitable indicator is the Chi-square test (x 2(417) ? 1224. 142 p , 0. 001), which often occurs in samples of over four hundred observations. On the other hand, all the incremental ? t measures were above the required 0. 8 (AGFI ? 0. 844) and 0. 9 (CFI ? 0. 973 IFI ? 0. 973 NFI ? 0. 960 NNFI ? 0. 966) levels, which proves the statistical convenience of the proposed model.The validation process concluded with the estimation of three second-order models for the dimensions of brand image (initial and ? nal) and consumer innovativeness. These models presented favourable ? t indicators for initial image (GFI ? 0. 958 SRMR ? 0. 035 NFI ? 0. 975 IFI ? 0. 979), ? nal image (GFI ? 0. 972 SRMR ? 0. 028 NFI ? 0. 985 IFI ? 0. 989) and consumer innovativeness (GFI ? 0. 978 SRMR ? 0. 022 NFI ? 0. 985 IFI ? 0. 987). Model and hypotheses contrasting After analysing the psychometric properties of the scales, we proceeded to the estimation of the structural model, which corresponds to the structure shown in Figure 1.Previously, the global effect of extensions on brand image was analysed, comparing the values of initial and ? nal image in each scenario. Responses to brand extensions 1193 EJM 44,7/8 Factor HINN SINN Items HINN2 HINN3 SINN1 SINN2 SINN3 FUIM1i FUIM2i FUim1f FUIM2f AFIM1i AFIM2i AFIM3i AFIM1f AFIM2f AFIM3f REIM1i REIM2i REIM1f REIM2f FAMI1 FAMI2 FAMI3 DIFF1 DIFF2 DIFF3 EXAT1 EXAT2 EXAT3 CAFI1 CAFI2 IMFI1 IMFI2 IMFI3 Reliability t (. 1. 96) l(. 0. 5) 22. 230 20. 993 26. 547 25. 862 19. 829 22. 534 20. 543 24. 779 24. 208 21. 076 19. 473 17. 864 21. 545 21. 680 17. 880 23. 342 18. 125 25. 834 19. 868 22. 112 19. 930 20. 822 18. 05 24. 402 18. 291 22. 956 18. 606 21. 579 22. 312 18. 837 26. 733 26. 683 24. 607 0. 861 0. 820 0. 915 0. 899 0. 744 0. 835 0. 776 0. 873 0. 859 0. 787 0. 741 0. 693 0. 798 0. 802 0. 694 0. 871 0. 706 0. 919 0. 751 0. 838 0. 771 0. 799 0. 729 0. 926 0. 725 0. 831 0. 712 0. 795 0. 839 0. 730 0. 906 0. 905 0. 859 Convergent validity * CRC (. 0. 6) EVA (. 0. 5) 0. 828 0. 891 0. 787 0. 857 0. 785 0. 810 0. 770 0. 825 0. 845 0. 839 0. 824 0. 763 0. 920 0. 707 0. 733 0. 650 0. 750 0. 550 0. 587 0. 629 0. 704 0. 645 0. 638 0. 610 0. 618 0. 793 1194 FUIM (i) FUIM (f) AFIM (i) AFIM (f) REIM (i) REIM (f) FAMI DIFF EXAT CAFI IMFITable V. Reliability, convergent validity and ? t of the measurement model Notes Fit indices Global ? t x 2 ? 1224. 142 (417) p , 0. 001 GFI ? 0. 884 RMSEA ? 0. 053 SRMR ? 0. 040. Incremental ? t AGFI ? 0. 844 CFI ? 0. 973 IFI ? 0. 973 NFI ? 0. 960 NNFI ? 0. 966 CRC Composite reliability coef? cient EVA Extracted variance analysis, GFI Goodness of ? t index RMSEA Root mean square error of contiguity SRMR assess root mean square residual AGFI Adjusted goodness of ? t index C FI Comparative ? t index IFI Incremental ? t index NFI Normed ? t index NNFI Non-normed ? t indexGiven that the Cronbach alphas exceeded 0. 7, a single measure of initial and ? nal image, obtained as the mean of all the underlying items, was considered. Figures 2-4 gather the results according to the sector. For a better understanding of the effect on image, a single initial image (IMAG * (i)), calculated as the mean of initial brand images for close and far extensions, was taken into consideration. A new ? nal brand image (IMAG * (f)), resulting from adding IMAG * (i) to the difference obtained between the ? nal and the initial image in each scenario, was also considered. In general, these Responses to brand extensions 195 Figure 2. Brand image variation (toothpaste brands) Figure 3. Brand image variation (sport brands) Figure 4. Brand image variation (mobile phones brands) graphics suggest that ? rms should avoid entering markets far from their sector, since such extensions clearl y entail brand image dilution. Once the global effect of extensions was analysed, the model hypotheses were tested. To test hypotheses related to feedback effects we created new variables based on unstandardised residuals. These residuals represent the brand image variation in such a way that higher values indicate more favourable feedback effects.They were obtained by regressing the post-test hemorrhoid against the corresponding post-test scores, and the psychometrical properties of the resulting construct were similar to those of brand image factors (Cronbachs alpha ? 0. 795). EJM 44,7/8 1196 Table VI contains the results of the model estimation and goodness of ? t measurements, which are acceptable and above the thresholds established in literature. Again, reasonable values were obtained for the error statistics (RMSEA ? 0. 044 SRMR ? 0. 077) and the global ? t GFI (0. 892). The incremental ? t indexes also met the statistical requirements (AGFI ? 0. 74 CFI ? 0. 972 IFI ? 0. 972 NFI ? 0. 952 NNFI ? 0. 969). Next, the speci? c results concerning the hypotheses are commented. First, familiarity has a direct and signi? cant in? uence on initial brand image (best ? 0. 485 t-value ? 10. 419), as proposed in H1. However, contrary to H2, familiarity seems to have no signi? cant effect on extension attitude (best ? 2 0. 052 t-value ? 2 1. 443). Consequently, the most familiar brands will lead to more favourable brand associations, although not of necessity to a better assessment of the extension. The effect of initial brand image on extension attitude is signi? ant and positive (best ? 0. 232 t-value ? 6. 351), as proposed in H3. Therefore, consumers will prefer the brand extensions of companies that have managed to build and communicate positive brand associations. Since brand image depends on brand familiarity, consumer attitude toward brand extensions seems to be the result of a cognitive-affective sequence (Fishbein and Ajzen, 1975). Supporting H4, category ? t seems to be a clear determinant of extension attitude (best ? 0. 299 t-value ? 2. 439). In the same way, extension attitude is signi? cantly dependant on image ? t (best ? 0. 587 t-value ? 4. 76), which con? rms H5. Consequently, consumers will prefer those extensions marketed in a category that ? ts the brand portfolio, especially in terms of general brand associations. The effect of perceived dif? culty on extension attitude is positive (best ? 0. 035), as expected. Nevertheless, the coef? cient relating both factors fails to reach statistical signi? cance (t-value ? 1. 186), which implies rejecting H6. This lack of statistical signi? cance reveals that consumers do not consider dif? culty of manufacturing as a heuristic of the perceived quality of the new product. Hypotheses H1 FAMI IMAG (i) H2 FAMI EXAT H3 IMAG (i) EXAT H4 CAFI EXAT H5 IMFI EXAT H6 DIFF EXAT H7 INNV EXAT H8 EXAT IMAG variation H9 CAFI IMAG variation H10 IMFI IMAG variation Standardised b (t) 0. 485 * 2 0. 052 0. 232 * 0. 299 * 0. 587 * 0. 035 0. 093 * 0. 631 * 2 0. 050 0. 159 (10. 419) (2 1. 443) (6. 351) (2. 439) (4. 876) (1. 186) (2. 924) (5. 846) (2 0. 313) (1. 004) Hypotheses validation Yes No Yes Yes Yes No Yes Yes No No Table VI. Results of the structural model Notes *Signi? cant at p 0. 05 Fit indices Global ? t x 2 ? 1131. 700 (481) p , 0. 001 GFI ? 0. 892 RMSEA ? . 044 SRMR ? 0. 077. Incremental ? t AGFI ? 0. 874 CFI ? 0. 972 IFI ? 0. 972 NFI ? 0. 952 NNFI ? 0. 969 CRC Composite reliability coef? cient EVA Extracted variance analysis, GFI Goodness of ? t index RMSEA Root mean square error of approximation SRMR Standardised root mean square residual AGFI Adjusted goodness of ? t index CFI Comparative ? t index IFI Incremental ? t index NFI Normed ? t index NNFI Non-normed ? t index Regarding H7, consumer innovativeness appears to have a clear, though reduced, effect on extension attitude (best ? 0. 093 t-value ? 2. 924).All in all, attitude towards extensions will be b asically explained by the initial brand image (H3), perceived ? t (H4 and H5) and, to a lesser extent, by other factors such as consumer innovativeness (H7). H8 to H10 indicate the factors that explain the potential feedback effects of brand extensions on brand image. With respect to H8, extension attitude has a positive and signi? cant effect on brand image variation (best ? 0. 631 t ? 5. 846). Hence, the more favourable the attitude to the extension is, the more favourable the attitude toward the extended brand will be. Because of the high coef? ient obtained, companies launching brand extensions will have to avoid damaging their brands with low quality products. Contrary to our expectations, perceived category ? t has no direct effect on brand image variation, which rejects H9 (best ? 2 0. 050 t ? 2 0. 313). Despite showing a relatively high and positive coef? cient, the effect of image ? t proposed in H10 is not signi? cant either (best ? 0. 159 t ? 1. 004). The lack of signi? c ance in both coef? cients suggests that the in? uence of ? t on brand image variation is only indirect through extension attitude (H4 and H5).To sum up, then, while perceived image and category ? t are essential factors for the success of a brand extension, it is signi? cant that extension attitude synthesises their effects. The centralising role of extension attitude was also corroborated by checking through the estimation of competitive models that neither brand familiarity nor consumer innovativeness nor perceived dif? culty have direct effects on brand image variation. Given the importance that literature attaches to perceived ? t to explain feedback effect (e. g. Loken and John, 1993 John et al. , 1998) and the lack of signi? ant effects in our model, we took a new step in the analysis. According to Czellar (2003), perceived ? t may moderate the in? uence of the attitude to the extension on the attitude to the extended brand. In the same way that high-perceived ? t increases th e transference of brand associations to the new product (Aaker and Keller, 1990 Czellar, 2003), we think that the opposite effect could take place. This possibility was explored by means of two multi-sample analyses for each of the ? t dimensions, category ? t and image ? t. Speci? cally, the sample was split into high ? t (mean . 4) and low ? (mean , 4) and the structural model were replicated without considering direct effects of ? t. The Lagrange Multiplier (LM) Test and the maximum likelihood estimation method determined whether the model coef? cients are signi? cantly different (Iglesias and ? Vazquez, 2001). The likeness between the considered sub-samples yields interesting results. Although the effect of extension attitude on image variation was similar for category ? t (x2dif ? 0. 182 p . 0. 1), the results lend support to the existence of moderating effects for image ? t at 90 per cent (x2dif ? 2. 868 p ? 0. 090). In the expected direction, the in? ence of extension attit ude was higher in the high ? t condition (best ? 0. 810 t ? 12. 740) than in the low ? t one (best ? 0. 666 t ? 11. 203). In consequence, spillover effects between the brand and the extension (forward and backward) will depend on image ? t perceptions rather than on category ? t. Responses to brand extensions 1197 EJM 44,7/8 1198 Discussion A brand is one of the most important assets for ? rms and, therefore, marketing managers must be on the alert for inadequate strategies that erode brand assets. One of this potentially risky strategies involves the launching of unsuitable brand extensions ? hat erode extended brand bene? ts and associations (Mart? nez and de Chernatony, 2004 Diamantopoulos et al. , 2005). However, so far there is no clear understanding of the main variables leading to spillover effects between brand extensions and parent brands and their relative in? uence. The present work proposes a model to ? nd out how extension strategies affect brand image, one of the major dimensions of brand equity. Unlike most previous research, this paper focuses on extension evaluation and feedback effects on the core brand as interrelated rather than independent phenomena.Moreover, it incorporates a few separate variables into an operative model instead of considering most of the potential variables that might divert the attention of researchers and practitioners alike. The estimation of this model showed positive goodness-of-? t indexes and, without considering non-validated relationships, it sheds some light on the main factors and processes explaining consumer attitude. According to the literature, core parent brand experience positively in? uences probability of extension trial (Swaminathan et al. , 2001 Swaminathan, 2003).However, our results reveal an indirect effect of brand experience or brand familiarity on consumer attitude to brand extensions. This variable has a distinctive in? uence on brand image, which, in turn, affects the assessment of the new category. These results are coherent with the behaviour models de? ned by some authors who maintain that the individuals beliefs determine attitude and this, in turn, determines purchase behaviour (Fishbein and Ajzen, 1975). From this perspective, brand image, rather than brand familiarity, would explain consumer attitude to the extension. Our ? dings validate previous results in the literature concerning the positive effects of perceived ? t, either category or image ? t, on consumer attitude. In the same way, it was con? rmed that consumer innovativeness increases likelihood of consumer ? sufferance, although to a lesser extent than perceived ? t (Volckner and Sattler, 2006). Nevertheless, we could not verify the proposed relationship between the attitude to the extension and dif? culty in manufacturing the new category. Due to the clear inconsistency of results along studies, the relevance of this variable proposed by Aaker and Keller (1990) should be questioned.In relation to f eedback effects, our results suggest that perceived ? t (category and image) has no direct effect on the extended brand image, though an indirect effect occurs through attitude to the extension. Previous works focusing on the in? uence of perceived ? t on parent brand associations have mostly resorted to experimental settings (e. g. Loken and John, 1993 Milberg et al. , 1997 John et al. , 1998) rather than SEM models. Therefore, this relationship cannot be taken for granted in complex models where several constructs are interrelated. The estimation of the model also revealed that image ? moderates the effect of extension attitude on image variation. In the light of the results, consumers that perceive the extension as coherent with the brand image will modify their brand associations mainly on the basis of their resulting attitude. A high ? t perception usually entails a categorisation process where the extension is associated to the brand category and leverages the current beliefs and attitudes (Monga and Houston, 2002). According to our results, this process occurs in the opposite direction in such a way that a high ? t will involve the leveraging of the attitude to the extension.The results obtained are thus in line with those works that indicate that consumer attitude toward brand extensions mainly depends on perceived ? t (Aaker and ? Keller, 1990 van Riel et al. , 2001 Volckner and Sattler, 2006). Moreover, it contributes to the body of knowledge by showing that the effect of perceived category and image ? t on the extended brand image is not direct. On the contrary, it occurs an indirect effect through extension attitude and, in the case of image ? t, a come along moderating effect on the relationship between extension attitude and image variation. To sum up, the coef? ients obtained indicate that extension attitude is especially determined by perceived category ? t, image ? t and initial brand image, which, in turn depends on familiarity. Consumer inn ovativeness is also a factor that explains consumer response to brand extensions. Furthermore, the results reveal that the existence of positive feedback effects will be an immediate consequence of the attitude to the extension. These results clearly support the basic argument of our model the consumer will assess the product according to a series of variables and, as a result, the consumers will modify the initial brand schema.Implications Considering all the results obtained as a whole, we can make some recommendations for ? rms launching brand extensions. There is no doubt that the most important aspect for the success of an extension is coherence with the image of the extended brand. though positive, it is not essential that the new product or service belongs to a new category, but the ? rm has to be able to communicate the brand essence to the different markets (Kim, 2003). Once the new product is ? rmly associated to the current brand image, consumers will perceive a high qual ity of the new product and the risk associated to purchasing it will be lowered.Although innovative consumers are expected to prefer low-? t products (Xie, 2008), consumer innovativeness is a factor with a weak effect on the attitude to the extension. In comparison to introducing a new brand name, brand extensions will increase consumer trust and reduce the weight of consumer innovativeness as a risk reliever. Since consumer behaviour will be relatively similar regardless of consumer predisposition to new products, this factor should not be used for potential market segmentation. In consequence, companies must identify other consumer characteristics able to alter perceptions of quality and purchase ntentions of speci? c product categories. A favourable initial image will also be positive for consumer acceptance increasing the appeal of the new product. This image is hard to obtain in the short term, although our model suggests that increasing familiarity through communication or bra nd trials is an efficient way of building brand associations. Since brand familiarity does not directly in? uence extension attitude, companies do not have to worry when their brands are not familiar enough or the current market share is scarce.Whenever they are capable of transmitting a positive brand image and ? t is high, success should be easy to obtain. Moreover, launching products perceived as trivial or very easy to make will not prevent consumers from trying the new product, a concern highlighted by Aaker and Keller (1990). Responses to brand extensions 1199 EJM 44,7/8 1200 Once consumers have developed a favourable attitude toward the new product, the brand associations might not be thin but even strengthened. Provided perceived ? between the extension and the core brand is high, especially on the basis of image ? t, the attitude to the extension will be the main driver of feedback effects. Consequently, increasing the success of brand extensions and protecting the levera ged image are not con? icting but complementary goals. Companies should thus address their efforts towards the success of the extension by building a bundle of coherent and strong brand associations. This is the best way to avoid the risk of image dilution. afterlife research Our ? ndings raise several issues for future research. The ? st issue refers to the lack of time between the extension stimulus and the subsequent measurement of brand image, which is the common procedure in most studies. The fact of the matter is that higher experience reduces the likelihood of negative feedback effects (Sheinin, 2000 Swaminathan, 2003), since the mere exposure to the new product affords consumers to establish links with the brand that, otherwise, would not exist (Klink and Smith, 2001). However, experiments requiring the cooperation of respondents over time are likely to suffer from a history problem caused by the in? ence of external events (Campbell ? and Stanley, 1963). By analysing FMCG through a longitudinal study, Volckner and Sattler (2008) show that feedback effects diminish over time, although they also admit the possibility of confounding effects. Taking into account the advantages and disadvantages of the different procedures, the present study opted to exclude extraneous variables by minimising the time between pre and post-test scores. Since we aimed to test the interrelationships between factors, the setting of the study was designed to reinforce internal validity as much as possible.Consequently, it must be observed that the paper generates a picture of feedback effects in the short-term and these effects should be checked through a long period of time. It would be also advisable to verify whether the validated relationships are consistent when consumers are exposed to all the market signals (competitors action, distribution support, etc. ) by using real extensions. Another issue to consider is whether the model can be applied to extensions of the same category or line extensions. Since line extensions are products with a higher perceived degree of ? t (Grime et al. 2002), there is a possibility that the relationships are sustained. It might be even more interesting to study whether service companies can successfully extend to the goods markets and vice versa. Indeed, it would be worthwhile to examine the brand and extension conditions that lead to higher effects of perceived ? t dimensions on the extension attitude toward the brand. Given that the in? uence of consumer innovativeness on extension attitude was less than expected, further research could also explore whether consumer innovativeness has moderating effects rather than mediating ones.Klink and Smith (2001) proved that the in? uence of perceived ? t on extension attitude is lower among innovative consumers, who are more receptive to new products. The in-depth study of other variables related to personality, such as sensation-seeking or impulsive decision-making, also de serves attention Finally, it would be convenient to revise other measurement scales for brand image, which include a higher number of items. Brand image is a complex construct that sums up every association linked to the brand and may involve attributes, bene? ts, and attitudes (Keller, 1993).Although the proposed scale can be a suitable proxy, further research should deal with the limitations derived from the items used for measuring brand image and the remaining factors as well. References Aaker, D. A. (1996), Measuring brand equity across products and markets, California Management Review, Vol. 38 No. 3, pp. 102-20. Aaker, D. A. (2002), Brand Portfolio Strategy, The Free Press, New York, NY. Aaker, D. A. and Keller, K. L. (1990), Consumer evaluations of brand extensions, journal of Marketing, Vol. 54 No. 1, pp. 27-41. Ahluwalia, R. and Gurhan-Canli, Z. 2000), The effects of extensions on the family brand name an accessibility-diagnosticity perspective, Journal of Consumer Researc h, Vol. 27 No. 3, pp. 371-81. Alba, J. W. and Hutchinson, J. W. (1987), Dimensions of consumer expertise, Journal of Consumer Research, Vol. 13 No. 4, pp. 411-54. Alexander, N. and Colgate, M. (2005), Customers responses to retail brand extensions, Journal of Marketing Management, Vol. 21 Nos 3/4, pp. 393-419. Anderson, J. R. (1983), A spreading activation theory of memory, Journal of Verbal Learning and Verbal Behavior, Vol. 22 No. 3, pp. 61-95. Balachander, S. and Ghose, S. (2003), Reciprocal spillover effects a strategic bene? t of brand extensions, Journal of Marketing, Vol. 76, January, pp. 4-13. Barrett, J. , Lye, A. and Venkateswarlu, P. (1999), Consumer perceptions of brand extensions generalising Aaker and Kellers model, Journal of Empirical Generalisations in Marketing Science, Vol. 4, pp. 1-21. Bhat, S. and Reddy, S. K. (2001), The impact of parental brand attribute associations and affect on brand extension evaluation, Journal of Business Research, Vol. 53 No. 3, pp. 111 -22. Boush, D. M. nd Loken, B. (1991), A process-tracing study of brand extension evaluation, Journal of Marketing Research, Vol. 28 No. 1, pp. 16-28. Boush, D. M. , Shipp, S. , Loken, B. , Genturck, E. , Crockett, S. , Kennedy, E. , Minshall, B. , Misurell, D. , Rochford, L. and Strobel, J. (1987), Affect generalization to similar and dissimilar brand extensions, Psychology and Marketing, Vol. 4 No. 3, pp. 225-37. Brown, T. J. and Dacin, P. A. (1997), The company and the product corporate associations and consumer product responses, Journal of Marketing, Vol. 61 No. 1, pp. 68-84.Campbell, D. and Stanley, J. (1963), Experimental and Quasi-experimental Designs for Research, Rand McNally, Chicago, IL. Chang, J. W. (2002), Will a family brand image be diluted by an unfavorable brand extension? A brand trial-based approach, Advances in Consumer Research, Vol. 29, pp. 299-304. Czellar, S. (2003), Consumer attitude toward brand extensions an integrative model and research propositions, In ternational Journal of Research in Marketing, Vol. 20 No. 1, pp. 97-115. Dawar, N. (1996), Extensions of broad brands the role of retrieval in evaluations of ? , Journal of Consumer Psychology, Vol. 5 No. 2, pp. 189-207. de Ruyter, K. and Wetzels, M. (2000), The role of corporate image and extension similarity in service brand extensions, Journal of Economic Psychology, Vol. 21 No. 6, pp. 639-59. Responses to brand extensions 1201 EJM 44,7/8 Diamantopoulos, A. , Smith, G. and Grime, I. (2005), The impact of brand extensions on brand personality experimental evidence, European Journal of Marketing, Vol. 39 Nos 1/2, pp. 129-49. Eagly, A. H. and Chaiken, S. (1993), The Psychology of Attitudes, Harcourt Brace Jovanovich, Fort Worth, TX. 202 Fishbein, M. and Ajzen, I. (1975), Belief, Attitude, Intention and Behavior An Introduction to Theory and Research, Addison-Wesley Publishing, Reading, MA. Glynn, M. S. and Brodie, R. J. (1998), The importance of brand-speci? c associations in brand extension further empirical results, Journal of Product & Brand Management, Vol. 7 No. 6, pp. 509-18. Grime, I. , Diamantopoulos, A. and Smith, G. (2002), Consumer evaluations of extensions and their effects on the core brand key issues and research propositions, European Journal of Marketing, Vol. 36 Nos 11/12, pp. 415-38. Gurhan-Canli, Z. and Maheswaran, D. (1998), The effects of extensions on brand name dilution and enhancement, Journal of Marketing Research, Vol. 35 No. 4, pp. 464-73. Hair, J. F. , Anderson, R. E. , Tatham, R. L. and Black, W. C. (1998),