Social vs traditional media communication: brand origin associations strike a chord

Maria Cristina Morra (University of Milano-Bicocca, Milano, Italy)
Francesca Ceruti (University of Milano-Bicocca, Milano, Italy)
Roberto Chierici (University of Milano-Bicocca, Milano, Italy)
Angelo Di Gregorio (University of Milano-Bicocca, Milano, Italy)

Journal of Research in Interactive Marketing

ISSN: 2040-7122

Publication date: 12 March 2018

Abstract

Purpose

The purpose of this study is to develop an analytical comparison between the impact of social media communication (both user-generated and firm-created) and the effects of traditional media communication. In particular, the components of customer-based brand equity and any difference in the effects according to brand origin associations are investigated. The target group consisted of fans and followers of beer brands on social media.

Design/methodology/approach

In all, 192 questionnaires were collected a survey link that was posted on beer brand pages that operate in the Italian market. Structural equation modeling was developed to investigate the impact of social and traditional media communication on brand equity and a multi-group analysis to examine the differences according to the brand names’ origin associations.

Findings

Results show that fans and followers cannot be considered as a collective unit. Additionally, consumers make a clear distinction between firm-created/user-generated social media and traditional media communication. Specifically, they distinguish how the effects of the two media outlets differ in relation to the brand origin associations. International brands should concentrate on both firm-created and user-generated communication, whereas national (Italian) brands should foster their firm-created communications. In both cases, however, traditional media communication loses its effectiveness on the brand equity components.

Originality/value

Contrary to existing literature, this project compares the effect of 2.0 and traditional media on various social media platforms, pointing out two different models according to the brands’ origin associations. This study develops interesting insights both for international companies with huge brand portfolios and for national firms in a complex market like those for beer.

Keywords

Citation

Morra, M., Ceruti, F., Chierici, R. and Di Gregorio, A. (2018), "Social vs traditional media communication: brand origin associations strike a chord", Journal of Research in Interactive Marketing, Vol. 12 No. 1, pp. 2-21. https://doi.org/10.1108/JRIM-12-2016-0116

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Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited


Introduction

Due to the complexity of the current socioeconomic landscape in which firms operate, and in light of the modern information and communication technologies, the topic of brand management is still widely debated, both academically and at a managerial level. In fact, the introduction of social media into the everyday lives of consumers has completely changed the way they collect information about products and services along with the way they interact with brands, due to the fact that they consider social media to be both an essential and useful communication channel (Boateng and Okoe, 2015; Lee and Ma, 2012). As a result, the communication paradigm has changed and firms must deal with many managerial challenges, such as organizational structure, multi-channel management and assessment of the effectiveness of marketing and communication strategies, all of which appear to be an increasingly difficult activity (DiStaso et al., 2011; Milewicz and Saxby, 2013).

In the academic literature, brand equity is discussed as a parameter, which allows assessment of the performance of marketing and communication activities (Aaker, 1991; Baldinger, 1992; Farquhar, 1989). Brand equity in fact, represents the output of the efforts invested by the firms in the creation of a set of symbolic and emotional associations around the brand (Anderson, 2011; Fornerino and d’Hauteville, 2010; Johansson et al., 2012; Kamakura and Russell, 1993; Moradi and Zarei, 2012; Raggio and Leone, 2007). Moreover, a positive brand equity allows achievement in a variety of competitive advantages, such as increased loyalty from customers (Aaker, 1997; Pappu et al., 2005), premium price (Ailawadi et al., 2003; Lassar et al., 1995) and higher profit margins (Hakala et al., 2012; Morgan et al., 2009). Also, a strong brand equity capitalizes on further marketing and communication activities, for instance, increased opportunities for brand extension (Farquhar, 1989; Kim and Kim, 2004; Moradi and Zarei, 2012; Vukasovic, 2009).

On closer examination, brand equity has been studied in both a financial-based perspective and in a consumer- or customer-based perspective (CBBE). The first term refers to the incremental cash flow that branded products or services received compared to similar not branded products (Johansson et al., 2012; Koçak et al., 2007; Simon and Sullivan, 1993; Wang, 2010), whereas the second one emphasizes the relationship between consumers and firms (Schivinski and Dabrowski, 2015; Yoo et al., 2000).

Furthermore, many authors studied some measurement models to investigate how marketing efforts affect the components of CBBE, such as the country-of-origin effect (Moradi and Zarei, 2012; Pappu et al., 2005), distribution intensity, advertising spending and price promotions (Yoo et al., 2000). Also, digital media like electronic word-of-mouth (eWOM) (Jalilvand and Samiei, 2012) and customer experience online have been investigated regarding their effect on the overall brand equity (OBE) (Biedenbach and Marell, 2010).

Moreover, the existing literature about social media discusses a wide range of topics such as the motives that drive people to interact with brands and to spread word-of-mouth (WOM) or the impact of peer reviews on brand preferences. Nevertheless, the effect of digital media 2.0 on brand equity components has been little investigated (Coyle et al., 2012; Logan et al., 2012; Mortazavi et al., 2014; Rios and Riquelme, 2010; Rohm et al., 2013). In particular, some authors investigated the effects of user-generated contents (UGC) (Christodoulides et al., 2012; Severi et al., 2014) or social media marketing activities created directly by firms (FCC – firm-created content) (Kim and Ko, 2012; De Vries and Carlson, 2014) on brand equity. However, none of these works takes into account UGC and FCC simultaneously, apart from Bruhn et al.(2012) and Schivinski and Dabrowski(2015). The first work studied the impact of FCC and UGC social media communication on brand awareness and functional and hedonic brand image (Bruhn et al., 2012) comparing their effects with advertising. The second one studied the dynamics of social media communication on the components of CBBE examining industry-specific differences about non-alcoholic beverage, clothing and mobile network providers sectors (Schivinski and Dabrowski, 2015).

Taking these considerations into account, there is an identifiable gap in the academic literature, not only about the effect of social media communication in comparison with traditional ones but also between FCC and UGC on the different components of consumer-based brand equity. The present paper tries to illuminate some insights on this topic, as the main purpose is twofold:

  1. to understand the impact of social media (UGC and FCC) and traditional media communication on CBBE’s components of fans and followers on social media; and

  2. to investigate any differences according to the brand origin associations.

The first part of this paper is dedicated to a literature review about the components of CBBE and the effect of both traditional and social media on them, concordant with the relative research hypothesis. The research methodology is illustrated, whereas results and managerial implications conclude the study.

Conceptual framework and hypotheses

Customer-based brand equity and marketing and communication mix

In the existing literature, CBBE is represented in four components, namely, brand awareness, brand associations, perceived quality and brand loyalty (Aaker, 1991). The first dimension refers to the strength of the presence of a brand in the consumers’ mind, and it has a role in purchasing decisions, as it represents the familiarity obtained from experiences with the brand (Aaker, 1991; Keller, 1993). Indeed, recognition is the main purpose of marketing and communication strategies, because firms need to orient the brand in a way that the customers will take acknowledge and consider it (Keller, 2008).

The second dimension, brand associations, indicates the connections tied to a specific brand as perceived by consumers and it represents the meaning of the brand for customers (Aaker, 1996). Through marketing and communication activities, firms create specific associations that help to create value for customers, serving as a reason to buy. High levels of awareness and unique and positive associations toward the brand are the conditions to create a strong brand equity (Aaker, 1991; Tong and Hawley, 2009). Nevertheless, associations are created either by actions directly controlled by the firm or by information circulating in the environment, such as direct experience, WOM, country-of-origin and, finally, places or events (Keller, 1993).

The level of perceived quality associated with the brand is one of the core factors of brand equity (Aaker, 1996; Farquhar, 1989; Tong and Hawley, 2009). In particular, this dimension does not represent the real quality of products, rather it is the customers’ perceptions of the overall quality or superiority of the offer/product compared to the/a competitors’ (Zeithaml and Bitner, 1996). It is important for the company to understand which elements consumers use to make a positive quality judgment and to reach this position through appropriate marketing and communication strategies (Aaker, 1996).

Finally, brand loyalty can be analyzed both at the behavioral level and perceptual level (Aaker, 1991). Marketing and communication activities are supposed to leverage this dimension of brand equity, as it helps to maintain a greater amount of purchases over the same period in comparison to non-loyal consumers. It also has a great impact on marketing costs, in terms of reduction of expenses’ in customer retention (Aaker, 1996).

Many authors have already analyzed the effects of marketing and communication strategies on the components of CBBE, such as advertising, store image, distribution, pricing, brand community or celebrity endorsement (Laroche et al., 2012; Spry et al., 2011; Yoo et al., 2000). In Table I, a review of the literature about marketing and communication tools with positive impact on CBBE’s dimensions is shown.

The large amount of academic contribution and the great attention devoted by practitioners is due to importance of understanding the role of marketing and communication activities in the brand equity creation process to derive managerial implications for integrated marketing communications strategies (Mulhern, 2009).

Social media communication and brand equity

Recent studies emphasized the importance of social media in the process of brand equity creation (Vanden Bergh et al., 2011; Goh et al., 2013; Laroche et al., 2012; Leung et al., 2013). In fact, the 67 per cent of people who have access to the internet are also active users of social media because they enjoy spreading and collecting information, as well as sharing emotions or ideas on these channels (Audiweb Trends, 2015; Kemp, 2016). Social media, therefore, has developed new touchpoints between consumers and brands on a global scale, developing a twofold effect, as digital media has revolutionized both the roles of customers and of firms.

From the consumers’ perspective, many authors suggest that UGCs are evaluated by users as a more reliable source of information rather than contents published through traditional channels by the firm (Logan et al., 2012; Mangold and Faulds, 2009). As a result, consumers play an increasingly active role in the communication process as the main creators of content and interactions for brands (Hanna et al., 2011; Okazaki and Taylor, 2013). The consumer-to-consumer communication tends to dominate the social media landscape and it influences the tone and availability of information spread by firms. This type of information is called “UGC”, and it indicates the involvement of consumers in the content creation due to a variety of reasons, such as self-promotion, complacency or hope to change their own brand image (Mangold and Faulds, 2009; Milewicz and Saxby, 2013; Schivinski and Dabrowski, 2015). Moreover, both academics and practitioners are interested in understanding the reasons that encourage people to interact with brands, for instance, entertainment, brand engagement, searching information about products and promotions (Rohm et al., 2013). In fact, eWOM has a crucial role in the phase of attitude creation and in the definition of purchase intentions and in the formation of brand equity. The worldwide spread of the internet allows peer information to be more easily accessible and users’ product reviews are perceived as one of the most important sources of information in the pre-purchase phase. Specifically, reviews have an impact on brand preference and purchase intentions (Bambauer-Sachse and Mangold, 2011; Coyle et al., 2012; Mortazavi et al., 2014).

Because the customers’ role within the communication process has changed from passive to active, it causes a progressive loss of control on brand building and management activities by the firms (DiStaso et al., 2011; Valos et al., 2014). Information defined as “FCC”, however, remains under the companies’ control (Bruhn et al., 2012). Firms, therefore, are facing a variety of challenges, such as understanding the level of integration of social and traditional media, internal organization and monitoring of UGC (DiStaso et al., 2011; Hanna et al., 2011; Schivinski and Dabrowski, 2015). It is also necessary to check peer-to-peer communication to collect information about strengths and weaknesses perceived by consumers, as market trends, in a quick and efficient way (DiStaso et al., 2011; Godes and Mayzlin, 2009; Hanna et al., 2011). In addition, firms can understand the dynamics of social networking sites through social media analysis and to determine what information is important for customers and the correct strategies that engage users (Diga and Kelleher, 2009). Finally, it is fundamental for marketers to investigate consumers’ attitude toward advertising on social and traditional media and the level of their effectiveness on business performance (Boateng and Okoe, 2015; Logan et al., 2012; Valos et al., 2014). In fact, understanding the impact of social media on firm performance appears to be an element of great importance to determine the correct mix of media and branding strategies (DiStaso et al., 2011; Hanna et al., 2011).

Likewise, this paper examines the effects of user-generated social media, firm-created social media and traditional media communication, according to the brand origin associations of fans and followers on social media.

Effects on overall brand equity

The main purpose of this research is to investigate the impact of digital media 2.0 on CBBE in comparison with traditional media and to study whether there are any differences according to the brand origin associations. To answer the aims of the analysis, three main studies are identified, namely, Bruhn et al. (2012), Schivinski and Dabrowski (2015) and Yoo et al. (2000).

According to existing literature, brand awareness along with unique and positive associations forms a specific brand image, which is derived from a variety of touchpoints between brands and consumers (Aaker, 1996; Atilgan et al., 2005; Calvo Porral et al., 2013; Keller, 1993; Kladou and Kehagias, 2014; Moradi and Zarei, 2012). Therefore, brand awareness/associations support customers in their decision buying process:

H1.

Brand awareness/associations positively influences brand equity.

Moreover, a high level of perceived quality means that consumers recognize a sort of differentiation and superiority through the long-term experience with a brand (Atilgan et al., 2005; Calvo Porral et al., 2013; Kladou and Kehagias, 2014; Moradi and Zarei, 2012; Zeithaml, 1988). As a result, the higher level of perceived quality increases the brand equity:

H2.

Brand perceived quality positively influences brand equity.

Finally, brand loyalty makes consumers buy the same product over a long period of time without turning to the competitors’ one (Atilgan et al., 2005; Calvo Porral et al., 2013; Kladou and Kehagias, 2014; Moradi and Zarei, 2012; Srinivasan et al., 2004). Therefore, brand equity will increase to the extent that consumers are loyal:

H3.

Brand loyalty positively influences brand equity.

Effects on brand awareness/associations

Many studies suggest that marketing activities, along with the environmental market conditions, have an impact on CBBE (Park and Srinivasan, 1994; Schivinski and Dabrowski, 2015; Yoo et al., 2000). In fact, a lot of relations between marketing and communication activities and the dimensions of brand equity are analyzed, such as slogans, public relations and advertising (Aaker, 1997; Keller, 1993; Simon and Sullivan, 1993). If a marketing and communication action leads to a more favorable behavioral response to the firm’s product compared to similar competitors’ ones, it will be positively related to brand equity. Therefore, to create and maintain a strong brand equity, the links between marketing tools and brand equity dimensions need to be investigated (Yoo et al., 2000).

Specifically, in the present study, particular platforms were selected from firm-crated, user-generated social media and traditional media, such as TV, radio, print and billboards. In fact, communication activities simplify the decision-making process increasing the probability of being included in the customers’ set of considerations. In other words, a positive assessment of traditional and social media leads to increased brand awareness/associations:

H4.

A positive evaluation of user-generated social media communication positively influences brand awareness/associations.

H5.

A positive evaluation of firm-created social media communication positively influences brand awareness/associations.

H6.

A positive evaluation of traditional media communication positively influences brand awareness/associations.

Effects on perceived quality

Some authors investigated how consumers who have experienced a frequent form of advertising perceive the brand to be of higher quality than other similar offers that were less promoted (Villarejo-Ramos and Sánchez-Franco, 2005; William et al., 2001; Yoo et al., 2000). Even in the context of social media communication, some works show that peer reviews have a considerable impact on the dimension of perceived quality (Schivinski and Dabrowski, 2015; Triche et al., 2013). As a result, it is assumed that UGC affects users’ quality perceptions. Despite the work of Schivinski, who does not confirm the same relationship from FCC to brand equity, in this work, it is assumed to be a positive effect because the context of analysis takes into consideration also the variable of traditional media communication changing the framework of the model:

H7.

A positive evaluation of user-generated social media communication positively influences perceived quality.

H8.

A positive evaluation of firm-created social media communication positively influences perceived quality.

H9.

A positive evaluation of traditional media communication positively influences perceived quality.

Effects on brand loyalty

Previous studies suggest that communication activities can have a positive or negative effect on brand loyalty, depending on the personal’s consumer exposure circumstances (Schivinski and Dabrowski, 2015). In the context of social media communication, the study of Schivinski and Dabrowski stressed that the quality of peer interactions has a positive impact on brand loyalty. In fact, UGC is considered to be more credible and reliable, acting as a catalyst for the brand loyalty dimension (Schivinski and Dabrowski, 2015). Nevertheless, given the justifications provided for the group of previous hypotheses, it is assumed to be a positive impact of FCC on the loyalty dimension:

H10.

A positive evaluation of user-generated social media communication positively influences brand loyalty.

H11.

A positive evaluation of firm-created social media communication positively influences brand loyalty.

H12.

A positive evaluation of traditional media communication positively influences brand loyalty.

Brand origin associations and brand equity

According to the literature the term “brand origin” means the “country where a brand is perceived to belong by its target customers” (Bruhn et al., 2012; Calvo Porral and Levy-Mangin, 2015; Schivinski and Dabrowski, 2015; Thakor and Kohli, 1996, p. 27).

According to the industry-specific features, the brand-related origin cues may be extremely salient for customers because it has an impact on the perceptions of quality (Thakor and Lavack, 2003). As some authors suggest, consumers may report a bias toward national origins of brands, which drives judgments of product quality and brand attitudes (Samiee et al., 2005). In fact, the brand origin may be perceived in an inaccurate association and can be used by customers to frame their evaluation process (Samiee et al., 2005).

In particular, customers make a distinction between global and local brands, and according to the product category, firms may exploit the brand origin associations cues to guide the customers’ evaluation process (Winit et al., 2014). If this is true, then it is possible to assume the following research hypothesis:

H13.

According to the brand origin associations (international vs national brands), social and traditional media have different effects on CBBE.

Methodology

Procedure and sample

The variables used in the present study consist of three dimensions of CBBE, OBE, UGC and FCC social media communication and, finally, traditional media communication. The items variables were extrapolated from previous studies (Bruhn et al., 2012; Porter and Donthu, 2008; Schivinski and Dabrowski, 2015; Yoo et al., 2000). The items and the relative references are reported in Appendix. The questions were translated in Italian and were formulated on a Likert scale ranging from 1 to 7, and a small introduction of the research and a disclaimer were added at the beginning of the survey (Yoo et al., 2000, p. 202).

Several criteria were followed to identify a suitable product category to test the model. First, fast moving consumer goods were selected as suggested by Bick (2009). Second, some future research suggestions were followed to include non-durable products like beer (Pappu et al., 2007). Third, products usually used by a large target and for which known brands easily exist were researched, to simplify the data collection phase (Vazquez et al., 2002). Finally, an active presence on social media, both from the firms’ point of view (weekly posted) and from the users’ was identified.

In light of the characteristics above, the product category of beer was selected. The beer sector represents an ideal market where the impact of marketing and communication activities can be tested, for example, via social and traditional media and brand origin associations (Fontanella, 2015).

To investigate whether or not the questionnaire was in line with the real dynamics and consumers’ behaviors of the beer sector, interviews with seven marketing managers of industry leaders were developed (Vazquez et al., 2002). In addition, they allowed identification of the brands to be included in the survey, covering different value propositions, various brand origin and levels of perceived craftsmanship of the beer. The questionnaire was administered in ten different versions, utilizing the same questions but changing the brand name (Yoo et al., 2000). Nevertheless, analyses were developed without considering the individual brand, as the main objective of this paper is to identify the relationships between the constructs according to the perceptions of consumers (Yoo et al., 2000). Specifically, the survey was loaded onto a Web platform, which provided easy access from a single online link, without the risk of overwriting the responses and protecting the anonymity of the respondent. After a pre-test, the questionnaire was disseminated posting the survey link every two weeks from early December 2015 until late January 2016 on main social media of beer brands, such as Facebook, Instagram, Twitter and similar forums. The brand attribution on which to compile the questionnaire was handled in an automated way by conditioning the questions related to the brand followed on social media.

Respondents who do not follow any beer brand on social media were excluded from the analysis, as the objective of the study is to investigate the effect of social and traditional media on CBBE, according to fan and followers’ brand origin associations. In other words, only fan and follower of different beer social media pages were taken into consideration for the analysis. In all, 192 completed questionnaires were collected, but after the data cleaning phase, 183 complete responses were obtained. A sample composition is presented in Table II.

The sample perfectly reflects the description of users with greater access to the internet, which were predominantly students with a monthly income of up to €3,000 (Audiweb Trends, 2015). Moreover, the sample is optimal for investigation of the product category of beer, as much as 92.3 per cent of the interviewed had experience with beer. In addition, interviewees were both active consumers of beer and active participants on social media. Finally, the construct about the involvement with the product category presents a reliability of 0.907 for the items related to the attention, use and self-assessment in declaring’s themselves an expert about the product category (Yoo and Donthu, 2001).

Measurement procedures

Exploratory factor analysis (EFA) was performed to determine the convergent and discriminant validity of the model. Through the use of the IBM SPSS, with a maximum likelihood method and Promax rotation, it was identified iteratively as a model with seven factors. Specifically, the EFA identified 29 items. The set of items presents an excellent indicator for the KMO test (0.882) and a perfect significance level (0.000). Also, the levels of commonality of the items show a higher than acceptable level on an extraction index of 0.3 (Schivinski and Dabrowski, 2015; Yoo et al., 2000).

The seven extracted factors reach a cumulative variance explained of 75.61 per cent (Yoo et al., 2000). From the pattern matrix model, every single item proposes a loading factor greater than 0.5 (and greater on average for each construct 0.7), thus confirming the convergent validity of the model. Moreover, items loaded on a multiplicity of factors are absent, thus achieving discriminant validity (Schivinski and Dabrowski, 2015). In the end, the factor correlation matrix shows that all correlations between factors are below the acceptance threshold of 0.7, providing further discrimination of the measured constructs (Yoo et al., 2000).

Furthermore, Cronbach’s alpha of every construct is between 0.884 and 0.949, which is above the threshold limit of 0.7, confirming excellent reliability of the items (Anderson and Gerbing, 1988). In addition, all independent and dependent variables were included in a single model of multifactorial confirmatory factor analysis (CFA) with IBM SPSS – Amos, as presented in Figure 1.

The composite reliability (CR) indexes are between 0.889 and 0.941 surpassing 0.7 recommended, whereas the values of the average variance extracted (AVE) cover the range between 0.725 and 0.823 passing 0.5 recommended (Schivinski and Dabrowski, 2015). In addition, all the CR values are higher than those of AVE for each construct, and the MSV and ASV values are lower than those of the AVE (Schivinski and Dabrowski, 2015; Yoo et al., 2000). Next, the constructs demonstrate low levels of correlation.

Finally, the model shows adequate goodness fit indices because the CMIN/DF is 1.852, the CFI is 0.949, the TLI is 0.940 and the RMSEA is 0.068. Thus, all values are in line with the same indices of the models taken as a reference from the analyzed literature (Bruhn et al., 2012; Schivinski and Dabrowski, 2015). Through the attribution of composite variables calculated with the CFA, IBM SPSS – Amos derived latent variables to be used for structural equation modeling (SEM).

Even the structural equation modelling analysis suggests a proper level of goodness fit indices with:

  • CMIN/df: 1.214;

  • CFI: 0.994;

  • TLI: 0.987; and

  • RMSEA: 0.034.

Results and implications

Main effects of the study (structural equation model)

The standardized coefficients obtained through the analysis are shown in Table III, with the relative levels of significance and the corresponding research hypothesis.

First, the relations between the components and OBE are analyzed (H1, H2, H3). The impact of perceived quality and brand loyalty on CBBE is supported (H2, H3). As previous studies pointed out, the strongest impact between components and OBE is represented by perceived quality (β = 0.326; p = 0.001) and brand loyalty (β = 0.275; p = 0.003) (Calvo Porral et al., 2013; Moradi and Zarei, 2012; Yoo et al., 2000). In particular, in the Italian beer industry, the dimension of perceived quality is the key determinant of brand equity, suggesting that firms have to develop this components to achieve a competitive advantage (Pappu et al., 2006). On the contrary, H1 is not supported, implying that the awareness/association does not contribute in the brand equity creation process. The same results are suggested by other studies about the beer industry (Calvo Porral et al., 2013).

Second, the effects of three marketing and communication activities are investigated: UGC (H4, H7, H10), FCC (H5, H8, H11) and traditional media (H6, H9, H12). Related to the impact of social UGC on the main components of CBBE, a significant relation is identified on perceived quality (β = 0.436; p = 0.000) and brand loyalty (β = 0.585; p = 0.000), thus supporting H7 and H10. Conversely, UGC does not influence the dimension of brand awareness/association (H4 is not supported). These results, in line with former literature, advise that peer-to-peer contents posted on social media have a very positive effect on CBBE, even in the Italian beer industry (Bruhn et al., 2012; Schivinski and Dabrowski, 2015).

Conversely, FCC social media communication positively affects the component of brand awareness/associations (β = 0.584; p = 0.000), without involving effects on the other dimensions of CBBE (H5 is supported, whereas H8 and H11 are not). Even this relation is reported by previous academic studies, thus suggesting that the two types of social media communication can have a complementary effect on brand equity (Bruhn et al., 2012; Schivinski and Dabrowski, 2015).

With reference to the actions of traditional media on CBBE, although H6, H9 and H12 are statistically significant relations, the directions of the impact are the opposite of the hypothesized ones. In details, traditional media have a negative effect on brand awareness/association (β = −0.203; p = 0.002), perceived quality (β = −0.321; p = 0.000) and brand loyalty (β = −0.236; p = 0.000), thus rejecting H6, H9 and H12. Somewhat conversely to Bruhn’s findings, this output means that active users of social media are quite annoyed by traditional media communication (Bruhn et al., 2012).

Results of brand of origin associations (multi-group analysis)

To investigate whether social and traditional media have different effects on CBBE according to the brand origin associations (international vs national brands) (H13), a multi-group analysis was performed. Specifically, the dummy moderator variable was obtained by sorting the brands by their beer brand name (Italian or international). The indexes of goodness fit of the multi-group model are better than the first model presented in this study, indicating an adequate choice of the moderator variable: CMIN/df 1.242, CFI 0.989, TLI 0.976 and RMSEA 0.021.

The results of the multi-group analysis reveal that the impact of the communication variables (social UGC, social FCC and traditional media) on CBBE, changes according to the nationality of the beer brand, as shown in Figure 2. Thus, H13 is supported.

Talking about international beer brands, the only component of perceived quality impacts on OBE (β = 0.842; p = 0.000). In comparison with the first model, perceived quality has increased its effect on CBBE. Therefore, it is possible to state that perceived quality is the essential dimension through which enhancing international beer brand equity. Regarding the roles of marketing and communication activities on the components of brand equity, social UGC influences perceived quality (β = 0.716; p = 0.000) and brand loyalty (β = 0.802; p = 0.000), whereas social FCC affects brand awareness/association (β = 0.548; p = 0.000), in line with the findings of the first model. On the contrary, traditional media have no effects on the all dimensions of CBBE, underlying another difference between the two models.

Moving to national (Italian) beer brands, the only component of brand loyalty impacts on OBE (β = 0.645; p = 0.004). This result outlines the major difference with the first model, as brand loyalty is the key driver in the brand equity creation’s process rather than perceived quality. With reference to the impact of social media communication on CBBE, a different model is outlined: social UGC has no impact on none of the dimensions, whereas social FCC influences brand awareness/associations (β = 0.975; p = 0.000), perceived quality (β = 0.671; p = 0.000) and brand loyalty (β = 0.341; p = 0.013). Finally, traditional media have a negative effect on perceived quality (β = −0.371; p = 0.000), thus restricting the negative effects of the main output model.

Summary and discussion

Social media has already been incorporated into the marketing and communication strategies of many firms. Nevertheless, the effect of digital media 2.0 is neither fully understood nor capitalized by companies. Due to the increasing number of touchpoints and different targets to be managed, communication activities are more and more challenging for marketers. In this landscape, brand equity can represent a suitable fil rouge for managing marketing strategies. Up to now, managers do not have specific guidelines in relation to how social and traditional media affect brand equity. This study contributes to the current body of literature in this direction, giving some insights about the reactions of fan and follower of beer brands in the Italian market.

In particular, through the multi-group analysis, it was possible to identify different reactions of fan and follower of beer brands on social media, according to the brand origin associations (international vs Italian). In details, social UGC has effects on perceived quality and brand loyalty in the case of international beer brands. On the contrary, peer-to-peer contents do not influence the dimensions of brand equity of “Italian” brands. With reference to social FCC, their greater impact is identified for national beer brands, where this type of communication affects all the three components of CBBE. Surprisingly, findings outlined that traditional media have no effects on brand equity of international beer brands and even a negative impact on national ones.

The present study can have interesting implications for marketers on three different level: budget allocation, social media marketing and brand management strategies.

First, results have important implications for firms investing in communication activities through social and traditional media. As results clearly show, traditional media have a negative impact on fan and follower’s CBBE, stressing that for users who are already engaged with the brand on social media, traditional communication loses its power. In fact, it seems that users consider traditional media just as a way to sell them an offer/product instead of interacting with them and establishing and cultivating relationships. Also, findings show that social media can be a partial substitute for traditional media communication as active users of social media still rely on traditional media to fulfill many of their needs (Kilian et al., 2012). Due to this, brands operating in Italy’s beer market, which aim to reach millennials, should reinvent their traditional media communication strategies if they want to effectively manage these channels. Otherwise, these firms should develop their traditional media communication strategies on other targets. Moreover, brand origin associations strike a chord in determining the absence of effect or the deleterious impact on the components on CBBE.

Second, the research sheds light on how to strategically promote beer brands according to their different brand origin associations, drawing managerial implications both for multinational firms with complex brand portfolios, both for Italian firms. More in details, the target of fans and followers on social media accounts is not a single unit, but it makes a clear distinction between the two types of communication on digital media 2.0 according to the brand origin associations. Based on the outputs of the study, marketers are encouraged to promote international beer brands through contents posted by peer-to-peer (UGC). Specifically, managers should focus on developing quality perceptions thanks to user-generated social media communication. Indeed, firms should be able to stimulate the production of UGC through FCC communication, for instance using influencers (Godes and Mayzlin, 2009; Mangold and Faulds, 2009). In addition, it is important for firms to monitor UGC social media for two reasons:

  1. Monitoring improves branding strategies.

  2. It allows checking any reviews, comments and negative WOM, which can have deleterious effects on brand equity (Bambauer-Sachse and Mangold, 2011).

On the other hand, firms should foster brand loyalty programs through FCC for national beer brands. The reason could stem from the effect of the strategies adopted by “Italian” brands on social media, as they communicate frequently and receive good feedback from users, but the focus remains in the hands of firms, as confirmed by sentiment analysis. This type of impact can represent two sides of the same coin. On the one hand, Italian fans and followers do not trust the contents posted by other peer users about “Italian” beer brands, meanwhile these beer brands have achieved a precise tone-of-voice that affects the right levers of CBBE. In particular, even though the product category of beer is not perceived as a typical Italian offer/product, in recent years, a lot of Italian craft beers have been produced. Precisely, these types of beers have reached a position in a high-end market, as they are characterized as the beer of “real connoisseurs”. Due to this, UGC can be seen as the voice of non-expert people, whereas FCC can represent interesting insights and source of precious information about an elite product.

The third managerial implication of the research is that by prompting peer-to-peer interactions for international beer brands, firms can convince fan and follower of the perceived quality of their brands and enhance brand loyalty. Consequently, these activities are translated into greater brand equity. With respect to national beer brands, managers have been encouraged to focus on FCC to achieve improvement in brand equity, especially through the brand loyalty dimension. Findings show that social media communication can foster consumer-based brand equity through its components and that traditional media can have deleterious effects on them according to the brand origin associations. Beer brand managers should incorporate social media into their communications mix and they should develop communication strategies that take into account the differences according to the brand origin associations with a glocal attitude (Di Gregorio, 2004).

The present study contains limits useful for the implementation of future research. First, the work is based on a survey, but preliminary analysis demonstrates robust reliability and validity tests (Park and Srinivasan, 1994). Second, social media is analyzed as a single component. It is suggested for future research to consider the specific features of the platforms to better understand their peculiarities. Finally, future analysis should replicate the study in countries with greater vocation against beer (Schivinski and Dabrowski, 2015). In addition, it would be interesting to investigate further industries, as well as to develop the analysis at individual brand level, to understand the differences between business strategies.

Figures

CFA Model

Figure 1.

CFA Model

Results of multi-group analysis

Figure 2.

Results of multi-group analysis

Effects of marketing and communication mix on consumer-based brand equity

Component Tools with positive impact on consumer-based brand equity
Brand loyalty Distribution intensity (Yoo et al., 2000) Brand’s age (Ries and Trout, 1986)
Country of origin (Pappu et al., 2006, 2007; Moradi and Zarei, 2012 [COB and COM]; Murtiasih et al., 2014) Order of entry (Schmalensee, 1982)
Brand community, impression management and brand use (Laroche et al., 2012) Customer experience (Biedenbach and Marell, 2010)
Adv spending (Yoo et al., 2000; Villarejo-Ramos and Sánchez-Franco, 2005) Social media UGC (Schivinski and Dabrowski, 2015)
Brand awareness Store image (Yoo et al., 2000) Brand’s age (Ries and Trout, 1986)
Adv spending (Yoo et al., 2000; Villarejo-Ramos and Sánchez-Franco, 2005) Customer experience (Biedenbach and Marell, 2010)
Country of origin (Pappu et al., 2006, 2007; Moradi and Zarei, 2012 [COB], Murtiasih et al., 2014) National cultural context (Hakala et al., 2012)
Social media FCC (Bruhn et al., 2012) Social media UGC and FCC (Schivinski and Dabrowski, 2015)
Brand associations Store image (Yoo et al., 2000) Country of origin (Pappu et al., 2006, 2007; Moradi and Zarei, 2012 [COB], Murtiasih et al., 2014)
Adv spending (Yoo et al., 2000; Villarejo-Ramos and Sánchez-Franco, 2005) Social media FCC (Schivinski and Dabrowski, 2015)
Brand image (attributes) Social media FCC (Bruhn et al., 2012) Social media UGC (Bruhn et al., 2012)
eWOM (Jalilvand and Samiei, 2012) Country of origin (Murtiasih et al., 2014)
Perceived quality Price (Yoo et al., 2000) Customer experience (Biedenbach and Marell, 2010)
Store image (Yoo et al., 2000) Social media UGC (Schivinski and Dabrowski, 2015)
Adv spending (Nelson, 1974; Yoo et al., 2000; Villarejo-Ramos and Sánchez-Franco, 2005) Country of origin (Pappu et al., 2006, 2007; Moradi and Zarei, 2012 [COB], Murtiasih et al., 2014)
Distribution intensity (Yoo et al., 2000)
OBE Price (Yoo et al., 2000) Adv spending (Yoo et al., 2000)
Store image (Yoo et al., 2000) Distribution intensity (Yoo et al., 2000)
Country of origin (Murtiasih et al., 2014) Destination brand experience (Boo et al., 2009)
eWOM (Jalilvand and Samiei, 2012) Celebrity endorsement (Spry et al., 2011)

Source: Authors’ elaborations

Sample composition

Anagraphic Category (%)
Gender Male 64.5
Female 35.5
Age 18-22 36.1
23-34 53.6
35-54 9.3
55-65 1.1
Qualification High school diploma 56.8
Bachelor degree 31.1
Master degree 10.9
PhD 1.1
Profession Student 66.7
Intern 3.3
Worker 1.1
Employee 13.7
Manager 8.2
Self-employed 4.4
Retired 1.1
Unemployed 0.5
Monthly income (€) <999 32.2
1,000-2,999 24.0
3,000-5,999 1.6
6,000-8,999 0.5

Source: Authors’ elaboration

Standardize structural coefficients of the model

Component Endogenous Estimate CR p-value Hypotheses Test
Awa/Ass OBE 0.049 0.669 0.503 H1 N.S
Quality OBE 0.326 3.203 0.001*** H2 Supp
Loyalty OBE 0.275 2.93 0.003** H3 Supp
Social UGC Awa/Ass −0.136 −1.396 0.163 H4 N.S
Social UGC Quality 0.436 5.015 *** H7 Supp
Social UGC Loyalty 0.585 6.437 *** H10 Supp
Social FCC Awa/Ass 0.584 5.975 *** H5 Supp
Social FCC Quality 0.145 1.665 0.096 H8 N.S
Social FCC Loyalty −0.065 −0.713 0.476 H11 N.S
Traditional Awa/Ass −0.203 −3.147 0.002** H6 N.S.°
Traditional Quality −0.321 −5.596 *** H9 N.S.°
Traditional Loyalty −0.236 −3.935 *** H12 N.S.°
Notes:

***p < 0.01;

**p < 0.05;

statistically significant but with opposite direction to the HP

Source: Authors’ elaboration on IBM Spss – Amos output

Items’ lists and references

Construct Item References
Social UGC UGC 1: I am satisfied with the content generated on social media sites by other users about [brand] Mägi (2003)
Tsiros et al. (2004)
Bruhn et al. (2012)
Schivinski and Dabrowski (2015)
UGC 2: The level of the content generated on social media sites by other users about [brand] meets my expectations
UGC 3: The content generated by other users about [brand] is very attractive
UGC 4: The content generated on social media sites by other users about [brand] performs well, when compared with other brands
Social FCC FCC 1: I am satisfied with the company’s social media communications for [brand] Mägi (2003)
Tsiros et al. (2004)
Bruhn et al. (2012)
Schivinski and Dabrowski (2015)
FCC 2: The level of the company’s social media communications for [brand] meets my expectations
FCC 3: The company’s social media communications for [brand] are very attractive*
FCC 4: This company’s social media communications for [brand] perform well, when compared with the social media communications of other companies
Traditional media Traditional 1: X is intensively advertised Yoo et al. (2000)
Traditional 2: The ad campaigns for X seem very expensive, compared to campaigns for competing brands
Traditional 3: The ad campaigns for X are seen frequently
Traditional 4: I am satisfied with the traditional media campaigns of [brand], i.e. radio, TV, print advertisements Mägi (2003)
Tsiros et al. (2004)
Bruhn et al. (2012)
Traditional 5: The level of the traditional media campaigns of [brand], i.e. radio, TV, print advertisements) meets my expectations
Traditional 6: Compared with the very good traditional media campaigns (i.e. radio, TV, print advertisements) of other brands, the traditional media campaigns of [brand] perform well
Brand awareness/associations Awa/Ass 1: I know what X looks like Yoo et al. (2000)
Awa/Ass 2: I can recognize X among other competing brands
Awa/Ass 3: I am aware of X
Awa/Ass 4: Some characteristics of X come to my mind quickly
Awa/Ass 5: I can quickly recall the symbol or logo of X
Awa/Ass 6: I have difficulty in imagining X in my mind
Perceived quality Quality 1: X is of high quality Yoo et al. (2000)
Quality 2: The likely quality of X is extremely high
Quality 3: The likelihood that X would be functional is very high
Quality 4: The likelihood that X is reliable is very high
Quality 5: X must be of very good quality
Quality 6: X appears to be of very poor quality
Brand loyalty Loyalty 1: I consider myself to be loyal to X Yoo et al. (2000)
Loyalty 2: X would be my first choice
Loyalty 3: I will not buy other brands if X is available at the store
Loyalty 4: Willing to say positive things about X to others Porter and Donthu (2008)
Loyalty 5: Willing to encourage close others to buy X
Loyalty 6: Plan to buy more X in the next few years
OBE OBE 1: It makes sense to buy X instead of any other brand, even if they are the same Yoo et al. (2000)
OBE 2: Even if another brand has same features as X, I would prefer to buy X
OBE 3: If there is another brand as good as X, I prefer to buy X
OBE 4: If another brand is not different from X in any way, it seems smarter to purchase X

Source: Authors’ elaboration

Appendix

Table AI

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Supplementary materials

JRIM_12_1.pdf (20.9 MB)

Corresponding author

Maria Cristina Morra can be contacted at: mariacristina.morra@unimib.it