From firm’s brand identity to cluster’s brand identity: a web-based analysis of Tuscan wineries

Matteo Devigili (Department of Business and Law, University of Siena, Siena, Italy)
Tommaso Pucci (Department of Business and Law, University of Siena, Siena, Italy)
Lorenzo Zanni (Department of Business and Law, University of Siena, Siena, Italy)

International Journal of Wine Business Research

ISSN: 1751-1062

Publication date: 19 November 2018



This paper aims to investigate the brand identity drivers used online by wineries and to assess cluster identity from the analysis of firms’ specific branding strategies.


Chianti, Chianti Classico and Brunello di Montalcino wine clusters (located in Tuscany, Italy) were selected as the set for this study. A total of 452 wineries websites were analyzed using a text frequency query, and the results were further examined through a discriminant analysis.


The theoretical framework was modeled after a careful analysis of the literature and is composed of three macro-areas of identity drivers: locational, product/process and social attributes. The analysis of winery websites shows the presence of all the drivers examined, which explain not only the wineries’ specific strategies but also the drivers of a particular cluster’s brand identity. A discriminant analysis highlighted that some drivers are able to explain the unique characteristics of the three clusters.


This research seeks to build a holistic investigation of all the identity drivers used by firms online. The specific brand identity focus and the holistic approach can enrich both academics and practitioners with a framework of current branding strategies.



Devigili, M., Pucci, T. and Zanni, L. (2018), "From firm’s brand identity to cluster’s brand identity: a web-based analysis of Tuscan wineries", International Journal of Wine Business Research, Vol. 30 No. 4, pp. 374-393.

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

1. Introduction

The wine sector is overcrowded with brands, and differentiation is increasingly difficult (Bruwer, 2004; Johnson and Bruwer, 2007; Brochado et al., 2015). While the wine literature has examined the relationship between brand and geographical indication (Schamel, 2006; Durrieu, 2008; Teuber, 2011), packaging/label (Rundh, 2005; Boudreaux and Palmer, 2007; Laeng et al., 2016) and wine tourism (Lockshin and Spawton, 2001; Bruwer and Lesschaeve, 2012) in affecting brand perceptions offline, the wineries’ online presence has mostly been ignored. Although some authors have highlighted a particular interest of wine literature in consumer behavior research studies (Lockshin and Corsi, 2012), the firm’s perspective on this topic has not been sufficiently investigated.

Many studies have focused on evaluating and describing website marketing strategies or content and design (Begalli et al., 2009; Taylor et al., 2010; Mills et al., 2012; Notta et al., 2013; Canziani and Welsh, 2016), without building a comprehensive examination of the drivers and attributes employed by wineries in the branding process. Moreover, to the best of our knowledge, only one study has investigated branding on a holistic basis, but only in an offline context (Vlachvei et al., 2012).

This study thus aims to build an all-inclusive framework to promote the academic/managerial discussion about online brand identity strategies. Brand identity expresses how managers and owners want the brand to be perceived and conveys the firm’s culture, physical specificities, personality and relational style (Kapferer, 2012). In the wine sector, most of the actors are SMEs which pay a careful attention to marketing and technological expenses (Canziani and Welsh, 2016). Struggling with funding, these entities often do not have the necessary resources to hire a website manager or a social media manager, adding new functions or content as time goes by (Simmons et al., 2008; Canziani and Welsh, 2016). Yet websites allow wineries to communicate with consumers and other stakeholders, thus becoming a fundamental marketing strategy (Taylor et al., 2010). In the light of these considerations, our first research question is:


What are the main brand identity drivers used by wineries to build their online brand identity?

It is generally accepted by the literature that, in many markets, the firm’s brand reputation and consumer evaluation of their products is closely related to the country of origin (Tse and Gorn, 1993; Phau and Prendergast, 2000; Pharr, 2005; Pappu et al., 2006). This is particularly true in the agri-food sector (Ozretic-Dosen et al., 2007; Anselmsson et al., 2014; Luceri et al., 2016) and even more in the wine industry, where there are three territorial levels: country, region and wine cluster (Papadopoulos and Heslop, 2002; Bruwer and House, 2003; Schamel, 2006; Yasin et al., 2007; Durrieu, 2008; Beebe et al., 2012; Dana et al., 2013; Josias et al., 2014). A cluster, defined as “geographic concentrations of interconnected companies and institutions in a particular field” (Porter, 1998, p. 73), has its specific population, mores and customs that identify a community, where each member takes part in the identity creation process consciously or unconsciously, thus influencing and being influenced by the shared identity (Staber, 2010; Staber and Sautter, 2011; Beebe et al., 2012; Zamparini and Lurati, 2012).

Beebe et al. (2012) emphasize how identity in wine clusters is linked to wine regions with legal recognition (e.g. appellation d’origine controllee in France), for which wineries receive a quality premium generating a positive effect on price. As consumers apply the perceived quality of a cluster to its members, there is a strong interest for all associates to build a common strategy to outline a positive cluster identity (CI). Given that CI has gained researchers’ attention only recently (Staber, 2010; Staber and Sautter, 2011; Beebe et al., 2012), our study aimed to answer a second research question:


How does the brand identity of firms contribute to creating a brand identity of a cluster?

The research field units selected are wineries in the wine clusters in Chianti, Chianti Classico and Brunello di Montalcino, located in Tuscany (Italy). Wine clusters are a particularly revealing setting for examining identity, as they provide a controlled environment delineated by legally stated boundaries (appellations) which are also helpful for delineating membership (Beebe et al., 2012). From the analysis of firm specific branding strategies and the subsequent comparison within and between clusters, this study formulates a set of categories and subcategories of drivers which are able to explain common identity crafting trends. The branding strategies of the three clusters are then analyzed to identify the specific driver mix used to shape CI. Several theoretical studies have shown that a well-shaped and consistent brand identity can impact positively on brand equity (Madhavaram et al., 2005; Kapferer, 2012). Indeed, brand identity strategies are the guidelines that delineate well-designed integrated marketing communication strategies, which consequently impact on a firm’s brand equity (Madhavaram et al., 2005).

Unfortunately, only a few studies have tried to bridge theory with empirical evidence, and more insights are needed (Coleman et al., 2015). Even though we recognize the relevance of brand equity to evaluate the effectiveness of branding strategies, we decided to focus on brand identity to enrich the theory by:

  • presenting a structured and inclusive framework of the main branding strategies employed online by wineries;

  • showing usage and interactions of branding drivers; and

  • opening up to possible national and international comparisons.

These comparisons can help practitioners to learn from experiences of national and foreign wineries and to enrich their branding strategies with new ideas and tools, thus building an international cross-fertilization. In addition, our findings highlight to Tuscan managers:

  • what strategy they appear to be employing, thus helping them to understand if it is in line with their initial intention; and

  • the differences or similarities with other regional or cluster fellows.

The same methodology can be replicated by other clusters to achieve similar findings.

The article is organized as follows. In Section 2, the theoretical framework introduces the main literature on branding. The selected samples are examined in Section 3, while Sections 4 and 5 present and discuss the findings. Section 6 draws some conclusions and Section 7 discusses possible limitations and further research topics.

2. Theoretical framework

A brand is essentially a name that guides consumer choices (Kapferer, 2012). The literature on wine has studied drivers that influence brand identity; however, how these drivers work together has not been investigated. Few studies have been conducted to build a framework of marketing strategies used online by wineries (Notta et al., 2013), and only one agri-food study to discover branding drivers (Vlahvei et al., 2013). Therefore, the scarce research upon branding calls for further investigation. The following analysis categorizes the literature on wine branding into three macro-areas: location, product and process and social.

2.1 Location

Geographical boundaries play an important role in the wine business and terroir becomes both a guarantee and a source of experience. As a guarantee, Geographical Indication (GI):

Both country-of-origin and region are useful branding tools to differentiate products from both foreign and national competitors (Bruwer and House, 2003). Furthermore, a territorial brand can be described as an umbrella brand, due to a strong connection between collective and individual reputation (Durrieu, 2008). As different products are branded with the same name (country or region), consumers build expectations of quality upon the umbrella that is transferred to all products branded with that name (cf Schamel, 2006). Therefore, GI can be considered a branding strategy as the umbrella brand communicates its identity to consumers who consequently conceive a brand image (Teuber, 2011). In branding, region-of-origin has acquired a greater importance than grape varieties, which can be farmed everywhere, because what is not replicable is the terroir (Huneeus, 2005; Johnson and Bruwer, 2007).

As a source of experience, terroir becomes the engine of the wine tourism industry, which can help wineries to create loyalty, to enhance brand awareness and to improve the consumers’ image of the brand (Alant and Bruwer, 2010; Byrd et al., 2016). A winery thus becomes a vehicle for communicating values, philosophy and the degree of excellence sought by the winemaker (Lockshin and Spawton, 2001). Wine tourists are interested in tasting wine and in experiencing the atmosphere and surroundings of the winery (Bruwer and Lesschaeve, 2012). In Figure 1, this macro-area is composed by territorial identification (terroir as a guarantee) and collateral experiences (terroir as a source of experience).

2.2 Product and process

The wine literature recognizes the presence of a set of brand constellation cues, associated with wine characteristics, that can influence consumers’ perceptions (Lockshin et al., 2000; Lockshin and Hall, 2003; Durrieu, 2008). Bruwer and House (2003) highlighted the role of grape variety and style of production for the Australian market, and a recent WineMonitor study underlined the increasing purchasing impact of autochthonous grapes in the Italian and US market (Pantini, 2017). Grapes and production style thus take part in the image building process of wine regions, and are always represented by one or two grape varieties (Spawton, 1999; Lockshin et al., 2000; Bruwer and House, 2003).

The method of production also plays a fundamental role in consumers’ perceptions and choices, thus proving to be a discriminant in consumers’ choices for countries such as Italy, French, UK, Germany, CA and South Africa (Maizza et al., 2017). In addition, a winery can use farming and business sustainability as tools to differentiate itself from competitors’ brands (Steinthal and Hinman, 2007; Atkin et al., 2012; Annunziata et al., 2018). In Figure 1, this macro-area is divided into two categories: product characteristics and process characteristics. The former is made up of color, grape variety, style and vintage. The latter accounts for the influence on firms’ identity of production methodologies and environmental and sustainability measures. The increasing power of product and process is highlighted by recent studies on consumer behavior (Pantini, 2017; PwC, 2017), thus becoming crucial drivers for wineries (Bernabéu et al., 2008; Santini et al., 2013).

2.3 Social attributes

Figure 1 shows this macro-area divided into two categories of drivers: governance attributes and external approval. Governance attributes, such as winemaker or family, are brand constellation cues (Lockshin et al., 2000; Lockshin and Hall, 2003). Family is a cross-sector branding strategy (Binz Astrachan and Astrachan, 2015), which increases sales, captures consumers’ attention (Craig et al., 2008), and is widely employed in the wine sector (Maguire et al., 2013; Gallucci et al., 2015). A branding strategy based on family should communicate history and heritage, balance innovation and tradition and translate family values (trustworthiness and long-term value orientation) into social actions, thus promoting local community development and improving workers’ conditions (Binz Astrachan and Astrachan, 2015). In the wine sector, family branding creates long-lasting competitive advantages (Gallucci et al., 2015).

External approval is composed of third-party certifications or reviews (Vlachvei et al., 2012) and social media influences (Kozinets et al., 2010; Vlachvei et al., 2012; Kabadayi and Price, 2014; Tsimonis and Dimitriadis, 2014; Vlachvei and Notta, 2015; Martìnez-Lopez et al., 2016). The online panorama allows wineries to use new flexible tools that enhance SMEs competitiveness on a global stage, thus decreasing the necessity for large investments (Pentina et al., 2012; Adegbuyi et al., 2015) and offering a wide variety of promotional items at a lower cost (Broekemier et al., 2015; Dehghani and Tumer, 2015). In this panorama, Word-of-Mouth (WOM) and electronic-WOM (e-WOM) can influence brands’ perceptions (Malhotra et al., 2013; Tsimonis and Dimitriadis, 2014; Wallace et al., 2014), thus becoming powerful strategic tools (Kozinets et al., 2010). Owing to social media, firms can build or maintain relationship, gather information or feedback and monitor social performances (Malhotra et al., 2013; Tsimonis and Dimitriadis, 2014). The effectiveness of social media for branding has been highlighted by several studies (Kabadayi and Price, 2014; Tsimonis and Dimitriadis, 2014; Gao and Feng, 2016), whereas the wine literature has focused mainly on quantitative evaluation of intensity, fullness and responsiveness (Vlachvei and Notta, 2015) to evaluate the social media presence of wineries. Wine Awards are consumer-oriented certifications, which can drive choices, thus lowering the amount of information that a consumer needs to make a purchase (Vlachvei et al., 2012). These certifications influence consumers’ preferences, and consequently impact on the image of the brand.

3. Research design and methodology

3.1 Tuscan wineries

In 2015, Tuscany – only seventh among a total of 20 administrative regions in Italy in terms of liters of wine produced – accounted for 16.42 per cent of all Italian wine exports, thus showing a special ability to produce high value wines (Unione Italiana Vini, 2017). Within Tuscany, three DOCG clusters were selected. Their main features are described in Table I.

These clusters thus show different brand values, market positioning, volumes of production and geographical extension, even though they are based in the same region. This characteristic enabled us to:

  • avoid biases due to different regional identities; and to

  • understand how and if different clusters employ the regional brand.

Furthermore, these clusters represent a unique case study because of their historical background and recent branding choices.

Chianti is among the oldest Italian wines and was the first to be protected with an ancestral form of denomination enacted by Grand Duke Cosimo III in 1716 (Consorzio Chianti Classico, 2016). The decree included only 70,000 hectares, which are now known as Chianti Classico. However, before gaining its desired independence from Chianti, Chianti Classico was included in the Chianti DOC in 1967 (becoming a DOCG in 1984). This DOCG includes a wide variety of Chianti producers, from different areas of Tuscany and with different qualities of products. Consequently, Chianti Classico fought to obtain DOCG status, becoming a specific denomination in 1996. In 2017, the price at source of Chianti Classico is nearly two times greater than Chianti (Ismea, 2017b). Even though Brunello is the “youngest” (it originated in the mid-nineteenth century), it became DOC in 1966 and DOCG in 1980, thus before Chianti (Consorzio del Vino Brunello di Montalcino, 2017). However, Brunello only achieved worldwide success in 1995 (Rivella, 2010). In our research, we focused on the following three clusters which are all from the same region:

  1. the oldest (Chianti Classico);

  2. the most valuable brand (Chianti); and

  3. the most expensive Italian wine in terms of price at source, Brunello di Montalcino.

3.2 Empirical setting and sample selection

We decided to use consortium firms, in line with previous studies on different features of wine CI (Zamparini and Lurati, 2012; Zamparini and Lurati, 2017). The consortiums of Chianti, Chianti Classico and Brunello di Montalcino all have a list of associated wineries which thus enabled us to focus on a large sample. The lists of members on the consortium webpages is the best and most-up-to-date system for identifying all firms that contribute consciously or unconsciously to CI creation and, most importantly, which want to be identified with that cluster. Only the websites with English translations were selected to create a database that would be able to support international comparisons in future research. In addition, as Anglophone countries represent the clear majority of Tuscan wine buyers, this restriction does not create a significant exclusion of wineries (only 6 per cent of the total sample population).

The initial list found on consortiums’ websites included 117 affiliated wineries for Chianti, 208 for Brunello di Montalcino, and 388 for Chianti Classico. Due to the absence of websites, duplicate links, websites without content, lack of English translations, firms which have hospitality as their core business, and firms (16) that belong to more than one cluster (discarded to avoid biases), the final sample was made up of 452 websites: 84 Chianti, 146 Brunello di Montalcino and 222 Chianti Classico.

3.3 Methodology

Data were gathered through N-Capture, which enables page by page downloads of the content, pictures and technical sheets of websites. The downloaded materials were checked several times to remove incomplete or corrupted files. All data were uploaded onto N-Vivo 11 divided by consortium, and a total of 7245 files were collected. N-Vivo was selected to perform a content analysis with an individual word being the measurement unit. A Word Frequency Query was run for each consortium. The top 1,000 words in terms of frequency were analyzed for each cluster and those words not useful to be employed in the analysis were discarded; the final number of words selected was 457. These words were divided into the framework categories and used in the website analysis. Thus, each website was analyzed on the basis of these categories to find their frequency weighted on the total amount of words in each website. Words belonging to more than one category were differentiated on the basis of their specific meaning.

The results were uploaded onto Stata 15.0 to perform a multiple discriminant analysis. The purpose of this analysis is to estimate the relationship between non-metric variables, clusters, and metric independent variables, categories and subcategories of identity drivers (Hair et al., 2010). This technique is particularly suited to explaining and predicting the bases of membership of different groups, represented by non-metric variables. Another advantage of discriminant analysis is the reduction of “analyst’s space dimensionality” (Altman, 1968, p. 592) which is given by number of non-metric variables (groups defined a priori) minus one. Consequently, two discriminant functions were designed where each independent variable shows a variate’s weight maximizing the differences between groups for each function (Hair et al., 2010). The function structure is Zjk = a + W1X1k + W2X2k + … + WnXnk, where Zjk is the discriminant Z score for function j and object k, a is the intercept, Wi is the discriminant weight for independent variable i and Xik is the independent variable i for object k. In this way, the independent variables are plotted in two dimensions, which represent the two discriminant functions.

4. Results

4.1 Brand identity drivers

In our sample of firms, we identified six categories and eighteen subcategories of drivers. Table II displays the mean presence per cluster of each driver, weighted by the total amount of words. The model can capture on average 23.06 per cent of words on Chianti websites, 23.87 per cent on Chianti Classico and 25.06 per cent on Brunello. These are high percentages given that, in the word count of a website, even “or”, “a”, “and”, phone numbers, etc., are included.

The 457 words identified during the analysis and divided into the categories and subcategories, were then employed to answer the second research question examining to what extent such words are found on the websites of the wineries for each consortium.

4.2 Identity drivers and wine clusters

Table III outlines descriptive statistics and Pearson’s correlation among subcategories of identity drivers for Chianti, Chianti Classico and Brunello di Montalcino. The correlation indicators do not reveal problems in terms of multicollinearity, as confirmed by low VIF scores and high tolerance for all drivers (see Appendix). A multiple discriminant analysis was performed. Table IV outlines the two features of the discriminant functions, where the first function explains the larger proportion of variance with a high significance. Table V shows ANOVA and Standard Canonical discriminant function coefficients.

The F values highlight a strong significance for region, locality, hospitality and production as discriminant factors. On the other hand, environment and sustainability, wine and food, denomination and tradition show a lower significance. The drivers’ ability to discriminate among clusters is summarized in Table VI.

The analysis revealed that region is one of the drivers that discriminates Chianti from the other two clusters, while Hospitality discriminates Chianti Classico from the other two. Production and Locality are particularities of Brunello di Montalcino. Low discriminant factors overlap single clusters: Wine and Food, Tradition, and Environment and Sustainability are drivers shared by both Chianti and Chianti Classico, while Denomination belongs to both Chianti and Brunello di Montalcino. Non-discriminant are drivers which are employed by all clusters, without substantial differences.

Figure 2 illustrates the loading plot, and Figure 3 reports the mean of standardized variables.

5. Discussion

These results confirm our framework’s ability to explain the online branding strategies of wineries.

To answer the first research question, it is interesting to note that several offline branding strategies were employed. Product and Process show the highest incidence for all clusters, thus highlighting their significance as identity drivers. Our findings regarding Production are in line with those of Maizza et al. (2017), which emphasize the influence of methods of production on consumer preferences. Therefore, production is a vehicle to communicate quality, pursuit of excellence and attention to detail, all of which help to create a firm’s identity. Even though the literature (Steinthal and Hinman, 2007; Atkin et al., 2012) highlights that environment and sustainability differentiate a brand from the mass, in our sample, this driver shows a low percentage of usage and discriminant power.

In terms of Location, territorial identifications are employed by all clusters. Within this category, the presence of Locality should be emphasized as a new identity driver able to differentiate a high-quality and well-known wine zone from broader geographic indication (e.g. region or country). The literature has evolved from considering the positive impact of country-of-origin (Yasin et al., 2007), to region (Johnson and Bruwer, 2007; Bruwer and Johnson, 2010) seen as a branding strategy able to differentiate products not only from foreign competitors but also from domestic (Bruwer and House, 2003).

However, our results show a further evolution of territorial identification, i.e. from regional to local branding. If a region is seen as an umbrella brand, each product branded with region’s name contributes to quality perceptions, therefore both high-quality and low-quality wines. Hence, if a Locality produces wines of higher-quality than those of other wineries in different locations but in the same region, it is a logical consequence to brand the name of the Locality to differentiate its particular quality, thus avoiding or limiting region-of-origin associations. A possible drawback of this strategy could be a dilution effect, thus decreasing the ability of territorial identification to act as a differentiation tool and to carry clear values in order to build a solid identity.

In addition, websites allow wine enthusiasts to gain information about winery tours, tastings and to book holidays on the farm, thus enabling wineries to reach consumers without any mediation. In fact, collateral experiences can influence brand association and perceptions (Lockshin and Spawton, 2001; Alant and Bruwer, 2010), therefore having a non-mediated communication instrument allows wineries to convey their preferred identity message.

Our analysis supports these previous findings. In fact, hospitality is widely used by wineries and discriminates between the three clusters.

Regarding Social attributes, our results highlight the presence of the family branding driver, and this in line with the wine literature (Maguire et al., 2013; Gallucci et al., 2015). Binz Astrachan and Astrachan (2015) proposed three brand themes (storytelling, tradition and innovation), which are linked with families. They also stressed the need to balance Tradition with Innovation to avoid negative customer perseptions. Our research findings show a different picture for the Tuscan wine business, where firms tend to focus on Tradition to convey their identity.

Our research reveals not only which drivers are employed, but also how wineries combine them in each consortium (Table II). As Figure 2 highlights, these drivers discriminate between the branding strategies of clusters, thus showing differential usage of drivers. However, it should be highlighted that CI is not necessarily a shared strategy of cluster’s members, but could be a silent process not founded on mutual support (Staber, 2010). Therefore, we are not saying that these results are outcomes of a cluster strategy, but that what they reveal could be useful for the winery consortiums.

The discriminant analysis highlights four drivers able to differentiate branding strategies of the three clusters. The non-discriminant (and low-discriminant) factors are unable to identify specific drivers for one cluster, as they are used similarly by all clusters (or at least by two of them). Production and Locality are what distinguish the identity strategy of Brunello di Montalcino – one of the top Italian quality wines and the highest priced at source (Ismea, 2017b). The fact that Brunello uses Locality as an identity driver supports the above-mentioned idea of differentiating high-quality clusters from the broader varieties in the same region. A small production zone can be easily linked with higher quality when compared to an entire region. In addition, highlighting production capabilities and particularities is a way to show product excellence, emphasizing the unique knowhow of the cluster. Excellence of terroir and superior knowhow are the fundamental factors in Brunello’s identity.

On the other hand, Chianti Classico – which has only recently become an autonomous DOCG – is struggling to be recognized worldwide and stresses hospitality as its main discriminant driver. The Chianti cluster – the top Italian wine in terms of brand value (WineNews, 2015) – covers a number of hectares seven times larger than Brunello and twice as large as Chianti Classico, with a production ten times larger than Brunello and twice as large as Chianti Classico. This massive production can only benefit from associations with a wine region such as Tuscany; therefore, region is the main driver used by this cluster.

6. Conclusions

This study enriches the wine literature with a framework of brand identity drivers employed online, which would be useful for future research. Indeed, the strategic mix of identity drivers presented opens up to further exploration focused on understanding the most suitable combination of drivers. In addition, this framework is a first attempt to capture online brand identity strategies and could support researchers in conducting international comparisons.

From a practitioner’s perspective, we believe that this study is valuable as it shows an:

  • up to date list of online brand identity drivers; and

  • three different strategic mixes to take into consideration in future managerial choices.

For winery managers, these findings can enrich and guide their analysis of the online competitive scenario, thus offering a road map to reach a clearer understanding of what competitors are doing and of what the winery can do to differentiate itself. In addition, managers can understand if the employed branding strategy is in line or not with their cluster or regional fellows. This can help wineries to build consistent long-term strategies, thus increasing the quality of managerial decisions regarding brand identity.

Regarding clusters, with a better understanding of firms’ strategies, consortiums can better protect and promote their members’ needs, by influencing national, regional and local legislative authorities to promote more suitable laws and interventions. Our results should help local authorities to understand what kind of identity is being communicated by the members of a cluster, thus enabling consortium managers to improve or change current strategies and avoiding individual strategies that could be detrimental for the whole cluster. In addition, we provide them with a methodology that can be easily replicated everywhere. Therefore, consortium managers will be able to plan long-term CI branding strategies at a central level, thus taking account new competitors, market conditions and consumers trends. This will:

  • enhance the coordination of the whole cluster;

  • improve the quality of its decisional choices;

  • enhance the consistency and quality of the cluster brand identity; and

  • be helpful for both SMEs and large firms.

Through their consortium, SMEs will be able to access fundamental data at a lower cost, thus increasing their managerial and marketing knowhow. This improvement will enable SMEs to adopt better quality standards, thus enhancing the whole CI and decreasing confusion and misconceptions. Large firms will gain a well-shaped cluster brand identity, thus having a qualitative source of distinction (membership of a cluster) to employ in the international competitive panorama.

Finally, individual firms and clusters can replicate this methodology of analysis to gain more insights into competitors and to monitor intra-clusters trends. Given that a well-designed and consistent brand identity can positively impact on brand equity (Madhavaram et al., 2005), a whole cluster should be able to benefit from better designed and consistent brand identity strategies for individual wineries. This, in turn, would increase the brand equity of individual wineries and consequently the brand equity of a cluster.

7. Limitations and further research

This research does not take into account those firms that are not listed on consortiums’ websites and is composed only of Tuscan firms. However, our decision to focus on consortiums means that we had access to a complete list of current members, showing those firms which identify with and wish to be members of a cluster and which take part in the identity creation process. Another possible limitation is that we focused exclusively on words rather than images which also influence brand associations. This focus on words excluded all the social media logos, which were impossible to count through the text query employed; therefore, the relevance of this driver may be underestimated. Furthermore, the word analysis does not capture concepts that are expressed with uncommon words, or that should be read between the lines, or that may be related to where (e.g. home page or peripheral page) they appear on the website. Finally, we cannot bridge our brand identity findings with any numerical inferences of brand equity improvement or deterioration, thus leaving open this topic for further investigations.

It would be interesting to investigate differences in the identity drivers pool through a cross-national comparison. Clusters such as the Napa Valley, Paso Robles, Russian River, Barossa Valley, Saint-Emilion and Pomerol will show different strategies enhancing the reliability of the identity drivers’ framework and further increasing insights for building strong CI. Additionally, governance typology (family vs non-family) and their brand identity choices should be investigated. Research could also be conducted into identity composition compared to firms’ or cluster’s performances, and also looking at the impact of drivers on consumers.


Brand identity framework

Figure 1.

Brand identity framework

Representation of the loading plot and discrimination of the clusters

Figure 2.

Representation of the loading plot and discrimination of the clusters

Mean of standardized variables

Figure 3.

Mean of standardized variables

Clusters features

Sources Feature Wine clusters
Chianti Chianti Classico Brunello di
(WineNews, 2015) Brand value € 1.833.325.000 n.a. € 794.964.000
(Ismea, 2017a) Hectare 14.304,40  6.653,00 1.920,00
Produced 720.382,00  413.213,00 69.373,00
Bottled 718.947,00 281.949,00 70.896,00
Economic value € 101.934.000 € 99.584.300 € 61.048.200
(Ismea, 2017b) Monthly average price at source (November 2017) 130,00 €/100 kg 257,50 €/100 kg 1050,00 €/100 kg
Δ% (November 2017)/(November 2016) +26,8 % +17,0 % + 12,9 %

Mean of identity drivers for each cluster

Drivers Chianti (%) Chianti Classico (%) Brunello di Montalcino (%)
Wine Characteristics 6.92 7.61 7.41
Process Characteristics 5.95 6.15 8.11
Production 5.67 5.93 7.94
Envir. and Sust. 0.28 0.22 0.17
Territorial identification 3.57 3.33 4.07
Denominations 0.69 0.44 0.49
Locality 1.44 1.75 2.67
Region 1.00 0.65 0.42
Country 0.44 0.49 0.49
Collateral Experience 3.90 4.26 2.94
Wine and Food 1.14 1.16 0.92
Hospitality 1.99 2.31 1.15
Photo Gallery 0.25 0.30 0.29
Estate 0.52 0.49 0.58
External Approval 1.49 1.35 1.41
Awards 0.65 0.58 0.62
Press 0.48 0.46 0.55
Social Networks 0.36 0.31 0.24
Governance Attributes 1.23 1.17 1.12
Family 0.27 0.27 0.29
Innovation 0.05 0.05 0.03
Tradition 0.53 0.51 0.38
Story telling 0.38 0.34 0.42
Total 23.06 23.87 25.06

Descriptive statistics and correlations

[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21]
[1] Wine charac. 1
[2] Production 0.197 1
[3] Envir. and Sust. −0.047 0.085 1
[4] Denominations 0.151 0.081 −0.048 1
[5] Locality 0.096 0.074 −0.094 0.018 1
[6] Region 0.069 −0.069 0.052 0.404 −0.000 1
[7] Country −0.002 −0.007 0.045 −0.042 0.213 0.073 1
[8] Wine and Food 0.243 0.132 −0.038 −0.008 0.007 0.210 0.022 1
[9] Hospitality −0.146 −0.269 −0.014 −0.114 0.047 0.190 0.116 0.220 1
[10] Photo Gallery −0.053 −0.004 −0.015 −0.068 0.039 0.007 0.113 0.099 0.230 1
[11] Estate 0.022 0.106 −0.028 0.043 0.077 0.046 0.078 0.013 0.030 0.108 1
[12] Awards 0.112 −0.077 −0.059 0.123 −0.013 0.023 0.037 −0.059 −0.083 0.049 0.066 1
[13] Press 0.072 0.114 −0.041 0.101 0.032 0.007 0.167 0.018 0.013 0.122 0.097 0.241 1
[14] Social Networks −0.015 −0.014 −0.024 0.108 0.022 0.116 0.053 0.039 0.104 0.032 0.033 0.056 0.268 1
[15] Family −0.026 0.026 −0.063 −0.088 0.006 −0.042 −0.019 −0.011 −0.011 0.038 0.143 −0.050 −0.046 −0.044 1
[16] Innovation −0.012 0.031 0.052 0.015 −0.073 0.017 −0.005 0.036 −0.053 −0.074 0.069 0.033 −0.018 −0.038 0.236 1
[17] Tradition 0.077 −0.054 −0.005 −0.015 −0.012 0.080 −0.023 0.010 0.179 −0.033 0.080 −0.016 −0.021 −0.089 0.227 0.203 1
[18] Story telling 0.008 0.126 0.012 −0.023 −0.025 0.000 0.094 0.100 0.015 0.152 0.170 0.004 0.067 −0.037 0.215 0.134 0.150 1
[19] Chianti −0.073 −0.115 0.106 0.132 −0.207 0.314 −0.064 0.030 0.036 −0.034 −0.005 0.034 −0.010 0.061 −0.011 0.018 0.058 −0.001 1
[20] Chianti Classico −0.013 −0.158 0.035 −0.087 −0.148 0.026 0.036 0.104 0.222 0.018 −0.043 −0.025 −0.061 0.031 −0.026 0.049 0.076 −0.071 −0.469 1
[21] Brunello 0.075 0.264 −0.125 −0.016 0.331 −0.289 0.016 −0.136 −0.268 0.008 0.050 −0.002 0.073 −0.083 0.037 −0.068 −0.129 0.077 −0.330 −0.679 1
Mean 0.067 0.065 0.002 0.005 1.970 0.623 0.488 0.011 0.019 0.003 0.005 0.006 0.005 0.003 0.003 0.042 0.466 0.004 0.186 0.491 0.323
Std. Dev. 0.070 0.039 0.003 0.007 1.506 0.596 0.535 0.010 0.021 0.005 0.007 0.012 0.006 0.005 0.004 0.088 0.502 0.004 0.389 0.501 0.468
Min 0 0 0 0 0.03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Max 1.329 0.214 0.033 0.068 10.680 4.650 3.420 0.066 0.138 0.028 0.038 0.125 0.037 0.031 0.028 0.580 5.540 0.032 1 1 1

N = 452. Correlation coefficients greater than 0.09 in absolute value are statistically significant at 95%

Canonical linear discriminant analysis

Function Canon. corr. Eigen-value Variance (proportion) F df1 df2 Prob. > F
1 0.583 0.515 0.884 6.522 36 864 0.000
2 0.252 0.068 0.116 1.726 17 433 0.036

ANOVA and std. canonical discriminant function coefficients

Variables R2 F Std. canonical discriminant
function 1 coefficients
Std. canonical discriminant
function 2 coefficients
Wine charac. 0.008 1.848 −0.091 0.263
Production 0.071 17.098*** −0.359 −0.103
Envir. and Sust. 0.020 4.676** 0.231 −0.086
Denominations 0.018 4.146* −0.046 −0.170
Locality 0.120 30.657*** −0.638 −0.109
Region 0.137 35.75*** 0.559 −0.620
Country 0.004 0.945 0.012 0.273
Wine and Food 0.019 4.295* 0.181 0.194
Hospitality 0.075 18.114*** 0.227 0.582
Photo gallery 0.001 0.256 −0.057 0.021
Estate 0.003 0.593 −0.011 −0.051
Awards 0.001 0.283 0.053 −0.060
Press 0.006 1.263 −0.095 −0.167
Social networks 0.008 1.843 0.143 0.031
Family 0.001 0.309 −0.042 −0.081
Innovation 0.005 1.041 0.067 0.196
Tradition 0.017 3.886* 0.183 0.039
Story telling 0.007 1.470 −0.138 −0.243

p < 0.05;


p < 0.01;


p < 0.001

Summary of the discriminant power for the variables used

High discriminant power Low discriminant power Non discriminant
Region Denomination Wine characteristics
Locality Tradition Country
Production Envir. and Sust. Photo gallery
Hospitality Wine and Food Estate
Social Networks
Story telling

VIF Scores and tolerances among study variables

Variables VIF scores Tolerance
Wine charac. 1.21 0.828
Production 1.24 0.810
Envir. and Sust. 1.05 0.951
Denominations 1.33 0.751
Locality 1.10 0.911
Region 1.37 0.731
Country 1.14 0.880
Wine and food 1.25 0.797
Hospitality 1.40 0.715
Photo Gallery 1.13 0.885
Estate 1.08 0.926
Awards 1.13 0.886
Press 1.22 0.822
Social networks 1.12 0.894
Family 1.18 0.850
Innovation 1.12 0.894
Tradition 1.19 0.838
Story telling 1.14 0.875

Mean VIF: 1.19. Condition number: 11.034


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Further reading

Bruwer, J. and Alant, K. (2009), “The hedonic nature of wine tourism consumption: an experiential view”, International Journal of Wine Business Research, Vol. 21 No. 3, pp. 235-257.

Lapsley, J. and Sumner, D. (2014), “We are both host napa valley, UC davis and the search for quality”, Kenney, M. and Monwery, D. (Eds), Public Universities and Regional Growth, Stanford Business Books, Standford, pp. 180-209.

Vlachvei, A., Notta, O. and Grigoriou, E. (2013), “Establishing a strong brand identity through a website: the case of Greek food SMEs”, Procedia Economics and Finance, Vol. 5, pp. 771-778.

Supplementary materials

IJWBR_30_4.pdf (11.8 MB)

Corresponding author

Lorenzo Zanni can be contacted at:

About the authors

Matteo Devigili received a master’s degree in Accounting and Management from Siena University (Italy) in 2017. In the same year, he started PhD in Development Economics and Local Systems held by Trento University in collaboration with Florence University. Hid research interests include marketing and management, international management and innovation management.

Tommaso Pucci has graduated in Economics (cum laude) from the Faculty of Economics of the University of Florence (Italy). In 2013, he obtained PhD in Economics and Management of Enterprises and Local Systems. He has carried out research and teaching activities (years 2009-2016) at the Department of Business and Law (University of Siena) as a Contract Professor and a Research Fellow. Since 2016, he has been an Assistant Professor in Management and Marketing at the Department of Business and Law (University of Siena). His research interests include management, innovation management, management and marketing of “Made in Italy”, international business.

Lorenzo Zanni is a full Professor of Economics and Business Management at the Department of Business and Law, University of Siena. His research interests are in the fields of: small businesses and entrepreneurship, economics and management of innovation, international management and marketing. At the moment, he is the Vice-Chancellor for technology transfer and university-industry relations at the University of Siena.