The Effects of Online Brand Communities on Brand Equity in the Luxury Fashion Industry

Abstract

Quoting the fashion genius Coco Chanel: “Fashion is not something that exists in dresses only. Fashion is in the sky, in the street, fashion has to do with ideas, the way we live, what is happening.” This is even more true today than it was back then. Indeed, Web 2.0 technologies have made luxury fashion more accessible to everyone. Nowadays, consumers can instantly access a wide variety of fashion goods on the Internet and share brand experiences with other consumers. In this scenario, Online Brand Communities (OBCs) allow fashion customers to communicate with each other without any restrictions of time and place. For this reason, OBCs are viewed by fashion marketers as powerful instruments to influence customers' purchasing behaviour. The aim of the current study is to analyse the effects of OBC dynamics on brand equity. The proposed research model is applied to eight spontaneous OBCs of the luxury fashion industry.

Keywords

Online Brand Communities Web 2.0 Technologies Online Marketing Brand Equity Luxury Fashion Industry

1. Introduction

The transition to a knowledge-based economy and the enormous development of Information and Communication Technologies (ICTs) are driving companies to find innovative approaches to marketing and to business in general [1 –4]. In particular, with the rise of next generation Internet technologies commonly known as Web 2.0, such as video sharing, blogging, social bookmarking and social networking, the interaction between consumers has undergone huge acceleration, facilitating their aggregation and participation. Web 2.0 describes the evolution from the Web 1.0 technologies (i.e., static websites updated only by the webmaster and closed to external editing) to participation-based web technologies (i.e., chat rooms, newsgroups, wikis, forums, social networks, etc.), that allow users to interact and collaborate with each other as creators of user-generated content in a virtual community [5–6].

In this context, it is clear that marketers need to rethink marketing strategies, using innovative approaches based on the new communication technologies, alongside the classic systems of corporate propaganda (e.g., advertising campaigns in traditional media such as TV, radio, newspaper, etc.). The most promising innovative marketing practices that leverage on Web 2.0 technologies are: viral marketing, buzz marketing, tribal marketing and social media marketing. In the last case, marketing activities exploit social media such as Facebook, Twitter and YouTube. The common characteristic of these innovative marketing techniques is the exploitation of the word-of-mouth phenomenon in an online environment (playfully renamed word-of-mouse by Internet marketers). In particular, the importance of the word-of-mouth promotion is amplified for social media users, who benefit from news, information and entertainment in an online community, and consider suggestions and recommendations from friends as an important source of information [7]. In this scenario, Internet marketers focus their attention on OBCs [8 –10], which are the web-based evolution of traditional brand communities defined by Muniz and O'Guinn [11] as a “specialized, non-geographically bound community, based on a structured set of social relations among admirers of a brand”. The main aspects of OBCs that marketers have to consider are connectivity and participation of social network members [12]. Following this lead, we analyse OBC dynamics and their implications on brand equity and, consequently, on brand management. In particular, we propose a research model to investigate OBC dynamics in the luxury fashion sector, an industry characterized by high-value brand assets [13]. Finally, the research model is applied on a sample of eight spontaneous (i.e., fan-made) fashion OBCs.

2. Literature Review on OBCs

OBCs have the potential to become a key marketing instrument and for this reason they introduce relevant managerial implications [14]. Indeed, Internet marketers should view OBCs as amazing business opportunities: they are effective means to influence customers' purchasing behaviour [15] and they allow companies to increase their understanding of customers by monitoring their opinions, information and suggestions [16–17].

2.1 OBC definitions and characteristics

OBCs are specialized brand communities that take place in a virtual setting where members' interaction is primarily Internet-mediated [10]. OBCs differ from traditional online communities because of their commercial nature and their members' common interest, admiration, sympathy and even love for a specific brand [18]. The fundamental peculiarity of OBCs resides in the ability of their members to interact with each other, exchanging information and knowledge on the brand or simply expressing their passion for it, thus influencing their relationship with the brand [19]. The trigger factor for the birth of an OBC is the brand itself, but eventually an OBC will grow due to the relationship among members [20]. Typically, OBCs present three key factors that also characterize traditional brand communities: ‘consciousness of kind’, ‘shared rituals and traditions’ and ‘moral responsibility’ [11]. The ‘consciousness of kind’ describes the feeling of OBC members of having a solid connection to the brand and an even stronger connection toward one another. The members perceive what Bender [21] calls “we-ness”, a shared feeling of belonging that creates a differentiation and separation between users of a brand and the users of other brands [11, 22 –24]. Perpetuating consciousness of kind often implies two social processes: legitimacy and oppositional brand loyalty. The former describes the behaviour by which members, who are real knowers and appreciators of the culture, history, traditions and symbols of the brand, tend to marginalize those who are not; the latter define and delimit “what the brand is not and what the brand community members are not”, characterizing the antagonism toward competitive brands [11, 25]. Through ‘shared rituals and traditions’, OBC members maintain, reinforce and diffuse, within and beyond the community, the culture, the set of values, norms, behaviours, the specific language, signs and symbols, myths, history and consciousness of the community itself [11, 26]. In addition, ‘moral responsibility’ is a sense of moral duty which leads the OBC members to feel committed toward other community members and the community as a whole [26–27]. Muniz and O'Guinn [9] note that the moral responsibility manifests itself through the OBC members' attitude toward retaining old members and toward integrating new ones - supporting them to enjoy a meaningful brand experience.

2.2 OBCs and Web 2.0 technologies

OBCs come into being in a computer-mediated environment that allows members to interact at will with each other, exchanging and sharing information and emotions in a virtual setting. The Web 2.0 technologies facilitate OBC members' participation and interaction: multiple virtual connections among members support them in building relationships and in sharing content and interests on brands [28]. Buttons such as those to “share” or “like” on Facebook, which are available to the one billion users of social media [29], testify to the enormous potential of social media for marketing purposes. From this perspective, OBCs are brand communities embedded in online social networks, characterized by ease of applicability, access to unbelievable numbers of consumers, at high speed, at low cost [30]. Actually, Web 2.0 technologies have caused market power to shift from marketers to consumers: unsatisfied consumers can easily network together, spreading negative word-of-mouth and determining a high potential risk for the brand [28].

2.3 Most relevant aspects of OBCs

OBCs are characterized by a number of relevant aspects related to the behaviour of the community members. Corporate managers should understand these aspects in order to be able to achieve desirable outcomes from the exploitation of business opportunities related to OBCs. One of the most relevant aspect of OBCs is the level of participation and interaction of members, i.e., the degree of social involvement in the OBC, that directly impact on the production of content in the community, such as comments, opinions, suggestions, etc. [31]. Another important factor is the level of identification in the OBC, that is, the degree to which a consumer feels himself or herself to be part of the community [31–32]. In addition, the quality of the communication and, consequently, the relevance of the content published in the OBC is of great importance [15]. All the previous factors influence positively the process of brand promotion and increase the brand loyalty of members [31]. Moreover, the process of participation in an OBC involves human capital exploitation in a collaborative environment leading to the creation of brand knowledge, which is positively associated with the process of brand innovation [33–34].

2.4 Critical aspects of OBCs

Customer loyalty, positive word-of-mouth and resilience to negative company news, depend on the customer perception of the company's socially responsible behaviour [35 –37] and, from this perspective, OBCs can play an important role in enhancing public awareness about the company's social commitment. Indeed, the externalities deriving from companies' activities in the local environment and in society, with respect to the regional economic growth and the local communities' interests [38 –40], can lead consumers to reconsider the sustainability of the current business approaches, making them more responsible and sensible toward environmental and social issues [27] and reinforcing the importance of OBCs in developing ethical control over companies. Moreover, OBCs have a considerable impact on company relational capital. A company's relational capital consists of, to a large extent, the quantity and quality of the company relationships with its customers (e.g., quality of services) and it involves the company image [41–42]. For this reason, OBC dynamics can have a huge influence on the enhancement or deterioration of the company's relational capital.

The previously described aspects of OBCs appear even more critical if we consider that Web 2.0 technologies allow negative consumer comments to easily spread on the network with the risk of alienating other consumers and damaging the company image [28].

3. OBCs in the luxury fashion industry

Just a decade ago, luxury fashion companies were supported by considerable brand assets and reliably regular customers. Nevertheless, the latest entries in the luxury fashion market of numerous new fashion brands have led to fierce competition and unforeseen changes in a previously sheltered market [13]. Indeed, globalization and ICT progress have made luxury fashion even more accessible. Consumers can now shop at will on the Internet, access a wide variety of fashion goods and instantaneously exchange brand experiences. Consequently, the average online fashion consumer has become well-informed, demanding and hard to get. Luxury fashion companies have undergone a technological evolution along with their consumers, leading to innovative forms of e-marketing. In particular, Web 2.0 technologies have hugely affected different aspects of fashion, beauty and luxury retail industries [43]. In this landscape, many fashion OBCs appeared and expanded on the Internet, allowing members to make comments, display designs and communicate ideas and ideals of fashion. Undeniably, OBCs are effective tools that luxury fashion brands should exploit to build stronger relationships with their consumers. There are two main typologies of OBCs: spontaneous OBCs and official OBCs. A spontaneous OBC is a fan-made online community composed of enthusiasts of a specific fashion brand. In this case, OBC members join voluntarily and often spontaneously to the fashion-related community. An official OBC is opportunely created and sponsored by the fashion company itself, with the aim to proactively enable members to exchange fashion opinions while educating them on the brand offerings [44]. The official OBC congregates users with common interests and goals in a collaborative community that thrives on serving both the consumers and the brand itself [45].

Following this lead, many luxury fashion companies created their Twitter accounts or Facebook pages and, simultaneously, many fashion enthusiasts made their own OBCs. OBCs allow fashion brands and their customers to communicate with each other without any restriction in time, place and content, revolutionizing the old one-way communication into an innovative interactive two-way direct communication. Moreover, OBCs can have a dramatic impact on brand reputation and fashion companies that do not use social media as part of their online marketing strategy are definitely missing an opportunity of competitive advantage [46].

Even though both official and spontaneous OBCs are of great interest for their managerial implications, in this paper, we are more interested in the study of fan-made OBCs. In fact, spontaneous OBCs are not managed or controlled by companies and, from this perspective, they can represent a “wild card” for fashion companies' marketing strategies.

4. The research model

The principal objective of the paper is to create a model capable of explaining the effects of OBC dynamics on brand equity, i.e., the value of the brand [47 –49].

The variables that we consider for the formulation of our model are those inherent to OBC members' behaviour and their perception of the brand. From the analysis of the scientific literature on brands and OBCs, we select six OBC and brand-related variables to analyse the relation between brand equity and OBC dynamics (Figure 1): –

“Brand community participation” takes into account the level of participation in the OBC and the degree of interaction among OBC members, i.e., the degree of social involvement in the OBC [31–32].

–

“Perceived brand quality” describes the OBC members' perception of the brand quality. It is the OBC members' opinion of a brand's ability to fulfil their expectations [32, 50].

–

“Brand community's generated content” takes into account the content generated by OBC members that can significantly influence both their perception of the brand and their subsequent purchase behaviour [51–52].

–

“Brand loyalty” describes the OBC members' commitment to repurchase or otherwise continue using the brand, which is associated to positive behaviours such as word-of-mouth advocacy [32, 53].

–

“Brand associations” describes the feelings, beliefs and knowledge that OBC members associate to the brand. It is anything which is deep-seated in the members' minds about the brand, such as symbols, images, celebrities, etc. [47–48].

–

“Brand awareness” describes the brand recall and the brand recognition by OBC members [47–48].

Figure 1.

The research model

In the current study, the purpose of the research model (Figure 1) is to verify the following hypotheses: –

H1: A greater level of participation and interaction in the OBC (‘brand community participation’) leads to a greater perception of the brand quality (‘perceived brand quality’).

–

H2: A greater ‘perceived brand quality’ determines a greater ‘brand loyalty’.

–

H3: The level of participation and interaction in the OBC (‘brand community participation’) positively influence ‘brand loyalty’.

–

H4: Greater ‘brand community participation’ pushes members to generate more brand-related content being shared in the OBC (‘brand community's generated content’).

–

H5: The ‘brand community's generated content’ positively influences the OBC members' ‘brand loyalty’.

–

H6: Greater ‘brand community participation’ determines a greater ‘brand awareness’ among the OBC members.

–

H7: Higher ‘brand awareness’ determines greater ‘brand loyalty’ among OBC members.

–

H8: Greater ‘brand community participation’ positively stimulates ‘brand associations’ among the OBC members.

–

H9: Higher ‘brand associations’ induces a greater ‘brand loyalty’ among the OBC members.

5. An application to fashion OBCs

In this paper, we consider only spontaneous OBCs, created by consumers which are driven by their common interest and their passion for a specific fashion brand and for the products marketed by the brand. Therefore, in our study we do not consider official OBCs directly influenced and managed by a fashion company.

In fact, fashion marketers are interested in understanding what motivates fashion consumers to join an OBC, where members share both a common fashion style and an emotional relationship with the fashion brand. Their involvement in the fashion OBC is so powerful that they are willing to devote their leisure time to maintain this virtual social gathering [44].

Fashion OBCs are characterized by both emotional factors, closely related to the shared passion for a brand, and socio-cultural factors, which are drivers of social integration. Potentially, spontaneous fashion OBCs are customers' aggregations that may arise around any fashion brand, even though most of them are developed around a fashion brand with a famous and established image [43]. The dialogues developed within OBCs affect the everyday lives of the individuals, are important drivers of a brand culture and help to perpetuate its history. Storytelling on fashion brands creates an independent knowledge, often very articulate, which is beyond the control of the official sources of the fashion brand companies [43 –45].

Worldwide, in 2011, 90 million people were members of OBCs, with an increasing tendency [54]. Given the importance of OBCs in modern society, fashion companies have to understand their influence on fashion consumers. It is even more crucial to identify the internal dynamics of spontaneous OBCs and their impact on brand equity, because they are not directly under the control of the fashion companies [17].

In order to study the OBC dynamics in the luxury fashion sector, a statistical survey was carried out by collecting data through structured interviews. The questionnaire was delivered electronically to a sample of users of spontaneous fashion OBCs which were established in relation to eight international luxury fashion companies (Table 1).

Table 1.

Univariate analysis of the sample.

Variable	Category	Frequency	% of the sample
Sex	Female	350	76.75%
Sex	Male	106	23.25%
Age	under 18	24	5.26%
	18-30	290	63.60%
	31-50	125	27.41%
	over 50	17	3.73%
Brand	Armani	27	5.92%
	Burberry	88	19.30%
	Chanel	40	8.77%
	Gucci	40	8.77%
	Hermes	16	3.51%
	Louis Vuitton	101	22.15%
	Prada	48	10.53%
	Ralph Lauren	96	21.05%

The questionnaire included a total of 13 questions concerning brand equity variables (brand loyalty, brand associations and brand awareness) and variables related to OBC dynamics (brand community participation, brand community's generated content and perceived brand quality). It also collected socio-demographic information (gender, age, etc.) of the respondents. Each respondent was asked to reply to the statements in the questionnaire on a one-dimensional Likert scale (a five-point scale was used).

The analysed sample is composed of 456 respondents belonging to spontaneous OBCs, of which 76.75% are female (Table 1). In fact, interest in the Haute Couture sector has always been a prerogative of the female gender. With regard to the age of the respondents, the majority of them are aged between 18 and 30 years (63.6%). Respondents aged between 31 and 50 years account for 27.41% of the total sample, while those under 18 and those over 50 represent the lowest percentages (5.26% and 3.73% respectively).

With regard to the brand distribution of the sample, the respondents belong mainly to: Louis Vuitton (22.15%), Ralph Lauren (21.05%) and Burberry (19.30%).

6. The results

Statistical analysis of the collected data was conducted by means of standard “Statistical Package for Social Science” (SPSS) packages. The questionnaire consisted of 13 multiple measurement items related to each of the six variables/constructs introduced in section 4.

The internal reliability of each construct is analysed by means of the Cronbach's α index that describes the reliability of factors extracted from dichotomous and/or multipoint formatted questionnaires or scales. In Table 2, all Cronbach's α coefficients score higher than 0.6, which is the recommended lower bound reported in the scientific literature (see [55] for details).

Table 2.

Reliability assessment.

Construct	N. items	Cronbach's alpha	Mean	Std. Dev.
Brand loyalty (BL1, BL2)	2	0.79	3.52	0.74
Brand community participation (BCP1, BCP2)	2	0.92	3.60	0.81
Brand associations (BAs1, BAs2, BAs3)	3	0.74	3.66	0.86
Perceived brand quality (PBQ1, PBQ2)	2	0.69	4.41	0.49
Brand awareness (BAw1, BAw2)	2	0.70	4.15	0.52
Brand community's generated content (BCGC1, BCGC2)	2	0.90	4.12	0.77

In this paper, the validity of the six constructs is tested by means of factorial analysis (Tables 3 and 4). In particular, a principal component analysis, using the Varimax with Kaiser normalization oblique rotation [56], is performed on the 13 items. Rotation converges in ten iterations. Data are pooled across the six constructs, for a total of 456 observations. From Table 4, it is possible to observe that the results show that each of the six items load on distinct factors (bold type evidences the relevant values). For this reason, only the first six factorial components have been fully reported.

Table 3.

Components and explained variance.

Items	Initial eigenval ues	Rotation sums of squared loadings
	Total	Variance (%)	Cumulative (%)	Total	Variance (%)	Cumulative (%)
BL1	4.41	33.96	33.96	2.76	21.22	21.22
BL2	2.56	19.66	53.62	2.13	16.41	37.63
BCP1	1.51	11.63	65.25	1.64	12.65	50.29
BCP2	1.04	7.97	73.22	1.64	12.64	62.93
BAs1	0.84	6.44	79.66	1.50	11.52	74.45
BAs2	0.78	6.02	85.68	1.46	11.23	85.68
BAs3	0.50	3.81	89.49
PBQ1	0.44	3.40	92.89
PBQ2	0.40	3.08	95.97
BAw1	0.17	1.35	97.31
BAw2	0.15	1.15	98.47
BCGC1	0.11	0.86	99.32
BCGC2	0.09	0.68	100.00

Extraction method: Principal Component Analysis.

Table 4.

Rotated component matrix.

Items	Component
	1	2	3	4	5	6
BL1	.120	.872	.083	.323	.131	.079
BL2	.478	.702	.172	–.016	.192	.004
BCP1	.921	.111	.060	.164	.070	.011
BCP2	.856	.273	–.021	.152	.222	.099
BAs1	–.014	.039	.090	–.041	.089	.960
BAs2	.148	–.014	.633	.046	.185	.655
BAs3	–.071	.082	.126	.127	.134	.901
PBQ1	.089	.067	.538	–.031	.685	.021
PBQ2	.087	.080	.060	.039	.912	.148
BAw1	–.020	.092	–.039	.926	.037	.090
BAw2	.268	.086	.213	.776	–.021	–.148
BCGC1	–.207	.628	.631	–.016	–.073	.045
BCGC2	.039	.602	.650	–.087	–.145	–.148

Extraction method: Principal Component Analysis.

Rotation method: Varimax with Kaiser Normalization.

Rotation converged in ten iterations.

The next step of our analysis is to utilize standard regression analysis in order to test the hypothesis described in Section 4. Figure 2 shows that all of the hypotheses are significantly verified (p<0.01, where p is the level of significance). The significance of the correlations confirms the high impact of OBC dynamics on brand loyalty.

Figure 2.

The estimated model (correlation values are represented on the arrows, ** stands for significance p<0.01).

‘Brand community participation’ has a positive influence on ‘perceived brand quality’ (H1 accepted), which is positively correlated with ‘brand loyalty’ (H2 accepted). Moreover, ‘brand community participation’ has a strong influence on ‘brand loyalty’ (H3 accepted).

Indeed, OBC members sense such a strong attachment to the brand and to the OBC that they publically demonstrate this attachment on a voluntary basis. Their shared enthusiasm incites brand loyalty in people with whom they interact online through the OBC [13, 32].

Moreover, the higher the participation and interaction of OBC members (‘brand community participation’), the greater the content shared in the OBC (‘brand community's generated content’) (H4 accepted). In a virtual-social environment such as OBCs, an increase in members' interaction involves, at the same time, an increase in the production of brand-related information [5, 31–32].

Additionally, the growth of brand-related content on the OBC (‘brand community's generated content’) enhances the ‘brand loyalty’ of the OBC members (H5 accepted). Overall, the ‘brand community's generated content’ is able to increase various loyalty behaviours, such as repurchase intentions, positive word-of-mouth and constructive complaints.

In this scenario, OBCs have empowered today's fashion consumers, because brand loyalty is highly influenced (both positively or negatively) by their online shared opinions, perspectives, insights and opinions about fashion brands [50]. Customers' preferences expressed on OBCs should be considered and weighted by companies in order to increase comprehension of market needs [57].

By becoming OBC members, fashion consumers are evolving into fashion “prosumers” [58], meaning that they simultaneously: consume and produce information on the fashion brand through their interaction on the OBC [59]. Following this lead, the application to fashion OBCs of our research model shows that a greater ‘brand community participation’ determines a greater ‘brand awareness’ (H6 accepted). The relationship between ‘brand awareness’ and ‘brand loyalty’ is also positive and significant (H7 accepted).

In addition, H8 is accepted because a greater interaction between OBC members (‘brand community participation’) enforces the ‘brand associations’, like thoughts, feelings, perceptions, images, experiences, beliefs and attitudes, that become linked to the fashion brand in the minds of the OBC members, because of their shared brand experience on the web.

Finally, ‘brand associations’, that are increased by OBC members' participation, have a positive effect on ‘brand loyalty’ (H9 accepted) [47–48].

All the significance values are very high (p<0.01) indicating that OBC dynamics (participation, content production and quality perception of OBC members) have a significant positive impact on brand equity (brand loyalty, awareness and associations). However, the correlation values are different for the various hypotheses of the model (min 0.12 - max 0.66), showing that some variables are more strongly correlated than others (Figure 2). The most relevant results concern the direct influence on brand loyalty of the participation in the OBC (H3: correlation 0.54**) and of the production of shared content by OBC members (H5: correlation 0.64**). Moreover, the participation and interaction of OBC members has a considerable impact on the content shared in the OBC (H4: correlation 0.66**).

The last result is of great importance for fashion companies' marketing strategies: spontaneous OBCs are not managed or controlled by companies and, from this perspective, they represent a “wild card”. They must be considered as an unpredictable and uncontrollable factor of success or failure in terms of fashion online marketing, because a positive or a negative ‘word-of-mouse’ could cause either a competitive advantage or disadvantage for the fashion brand.

7. Conclusions

This paper examines the effects of OBC dynamics on luxury fashion brands in terms of brand equity (brand loyalty, brand awareness and brand associations).

From a marketing perspective, OBCs seem to be an innovative ground for improving business. Our findings show that OBC dynamics (brand community participation, brand community's generated content, members' perception of the brand quality) positively influence brand equity. Considering brand equity as a strategic asset for luxury fashion firms, marketing and brand managers should exploit effectively the opportunities presented by OBCs. In particular, the level of OBC members' participation and the production of shared content directly influence brand loyalty behaviours. These OBC characteristics are boosted by Web 2.0 technologies such as social networks like Facebook or Twitter. In this context, marketers could gain advantages from careful monitoring of spontaneous OBC dynamics as a whole, especially taking note of members' ideas and suggestions. In fact, OBC members represent the most involved stakeholder groups and developing their ideas might raise corporate value.

From a managerial point of view, it is important to point out that in the Web 2.0 scenario, luxury fashion firms, characterized by high-value brand assets, cannot refrain from dealing with spontaneous OBCs. Due to their unpredictable nature, together with the capability to aggregate a stunning number of consumers, allowing them to interact and share opinions, spontaneous OBCs can represent both a serious menace and an amazing opportunity for brands.

References

Capece

(2008) An e-distinctivity parameter to evaluate an e-business idea. Management Research News, 31: 311–323.

Capece

(2009) Technological and Conceptual Accessibility to Measure the Soundness of an e-Business Idea. Knowledge and Process Management, 16: 49–64.

Capece

Calabrese

Di Pillo

Costa

Crisciotti

(2013) The Impact of National Culture on E-commerce Acceptance: The Italian Case. Knowledge and Process Management. 20(2): 102–112.

Calabrese

Campisi

Capece

Costa

Di Pillo

(2013) Competiveness and innovation in high-tech companies: An application to the Italian biotech and aerospace industries. International Journal of Engineering Business Management.

Adebanjo

Michaelides

(2010) Analysis of Web 2.0 enabled e-clusters: A case study. Technovation. 30 (4): 238–248.

Capece

Campisi

(2013) User satisfaction affecting the acceptance of an e-learning platform as a mean for the development of the human capital. Behaviour & Information Technology, 32(4): 335–343.

J Y C

Dempsey

(2010) Viral marketing: Motivations to forward on line content. Journal of Business Research. 63: 1000–1006.

Füller

(2006) Why consumers engage in virtual new product developments initiated by producers. Advances in Consumer Research. 33(1): 639–646.

Füller

Bartl

Ernst

Muhlbacher

(2006) Community based innovation: How to integrate members of virtual communities into new product development. Electronic Commerce Research. 6(1): 57–73.

10.

Füller

Jawecki

Mühlbacher

(2007) Innovation creation by online basket-ball communities. Journal of Business Research. 60(1): 60–71.

11.

Muniz

A M

O'Guinn

T C

(2001) Brand community. Journal of Consumer Research. 27 (4): 412–432.

12.

S C

Fang

W C

(2010) The effect of consumer-to-consumer interactions on idea generation in virtual brand community relationships. Technovation. 30 (4): 238–248.

13.

Kim

A J

(2012) Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research. 65: 1480–1486.

14.

Ouwersloot

Odekerken-Schröder

(2008) Who's who in brand communities—And why? European Journal of Marketing. 42 (5/6): 571–585.

15.

Adjei

M T

Noble

S M

Noble

C H

(2010) The influence of C2C communications in online brand communities on customer purchase behaviour. Journal of the Academy of Marketing Science. 38 (5): 634–653.

16.

Kozinets

R V

De Valck

Wojnicki

A C

Wilner

S J

(2010) Networked narratives: Understanding word-of-mouth marketing in online communities. Journal of Marketing. 74(2): 71–89.

17.

Brogi

(2013) Online brand communities: A literature review. Proceedings of WCBEM 2013-2nd World Conference on Business, Economics and Management.

18.

Albert

Merunka

Valette-Florence

(2008) When consumers love their brands: Exploring the concept and its dimensions. Journal of Business Research. 61 (10): 1062–1075.

19.

McAlexander

J H

Schouten

J W

Koenig

H F

(2002) Building brand community. Journal of Marketing. 66 (1): 38–54.

20.

Jang

Olfman

Koh

Kim

(2008) The influence of on-line brand community characteristics on community commitment and brand loyalty. International Journal of Electronic Commerce. 12 (3): 57–80.

21.

Bender

(1978) Community and Social Change in America. New Brunswick, NJ: Rutgers University Press.

22.

Fournier

(1998) Consumers and their brands: Developing relationship theory in consumer research. Journal of Consumer Research. 24: 343–373.

23.

Bergami

Bagozzi

R P

(2000) Self categorization, affective commitment and group self esteem as distinct aspects of social identity in the organization. British Journal of Social Psychology. 39: 555–577.

24.

Bagozzi

R P

Dholakia

U M

(2006) Open source software user communities: A study of participation in Linux user groups. Management Science. 52 (7): 1099–1115.

25.

Di Pillo

Cricelli

Gastaldi

Levialdi

(2010) Asymmetry in mobile access charges: Is it an effective regulatory measure? NETNOMICS: Economic Research and Electronic Networking. 11 (3): 291–314.

26.

Casaló

L V

Flavián

Guinalíu

(2008) Promoting consumer's participation in virtual brand communities: A new paradigm in branding strategy. Journal of Marketing Communications. 14 (1): 19–36.

27.

Capece

Costa

(2013) The new neighbourhood in the internet era: Network communities serving local communities. Behaviour & Information Technology. 32 (5): 438–448.

28.

Fournier

Avery

(2011) The uninvited brand. Business Horizons. 54: 193–207.

29.

Facebook.com (2013) Newsroom. Available: http://newsroom.fb.com/Key-Facts. Accessed 2013 Jun 12.

30.

Zaglia

M E

(2013) Brand communities embedded in social networks. Journal of Business Research. 66: 216–223.

31.

Casaló

L V

Flavián

Guinalíu

(2010) Relationship quality, community promotion and brand loyalty in virtual communities: Evidence from free software communities. International Journal of Information Management 30: 357–367.

32.

Algesheimer

Dholakia

U M

Herrmann

(2005) The social influence of brand community: Evidence from European car clubs. Journal of Marketing. 69 (4): 19–34.

33.

Capece

Costa

(2009) Measuring knowledge creation in virtual teams through the social network analysis. Knowledge Management Research and Practice. 7 (4): 329–338.

34.

Costa

Evangelista

(2008) An AHP approach to assess brand intangible assets. Measuring Business Excellence. 12 (2): 68–78

35.

Costa

Menichini

(2013) A multidimensional approach for CSR assessment: The importance of the stakeholder perception. Expert Systems With Applications. 40 (1): 150–161.

36.

Calabrese

Costa

Menichini

Rosati

Sanfelice

(2013) Turning CSR-Driven Opportunities in Competitive Advantages: A Two-Dimensional Model. Knowledge and Process Management. 20 (1): 50–58.

37.

Calabrese

Costa

Menichin

Rosati

(2013) Does Corporate Social Responsibility Hit the Mark? A Stakeholder Oriented Methodology for CSR Assessment. Knowledge and Process Management. 20 (2): DOI: 10.1002/kpm.1406.

38.

Campisi

Gastaldi

(1996) Decomposing growth in a multiregional I-O framework. Annals of Regional Science 30 (4): 409–425.

39.

Campisi

Nastasi

(1993) Capital usage and output growth in multiregional multisectoral models: An application to the Italian case. Regional Studies 27 (1): 13–27.

40.

Campisi

Mancuso

Nastasi

(1997) Cost reduction, competitive pressure and firms' optimal R&D strategies in a duopolistic industry. Review of Industrial Organization. 12 (2): 259–270.

41.

Biondi

Calabrese

Capece

Costa

Di Pillo

(2013) A New Approach for Assessing Dealership Performance: An Application for the Automotive Industry. International Journal of Engineering Business Management, 5 (18): 1–8. doi: 10.5772/56662

42.

Calabrese

Costa

Menichini

(2013) Using Fuzzy AHP to manage Intellectual Capital assets: An application to the ICT service industry. Expert Systems With Applications. 40 (9): 3747–3755.

43.

Okonkwo

(2007) Luxury Fashion Branding: Trends, Tactics, Techniques. New York, NY: Palgrave Macmillan.

44.

Okonkwo

(2010) Luxury Online: Styles, Strategies, Systems. New York, NY: Palgrave Macmillan.

45.

Okonkwo

Assouline

(2011) Luxury Now: Evolution, Status, Future. New York, NY: Palgrave Macmillan.

46.

Kim

A J

(2010) Impacts of Luxury Fashion Brand's Social Media Marketing on Customer Relationship and Purchase Intention. Journal of Global Fashion Marketing. 1 (3): 164–171

47.

Aaker

D A

(1996a) Building strong brands, New York. Free Press.

48.

Aaker

D A

(1996b) Measuring Brand Equity Across Products and Markets. California Management Review. 38: 102–120.

49.

Battistoni

Colladon

Fronzetti A

Mercorelli

(2013) Prominent determinants of consumer based brand equity. International Journal of Engineering Business Management.

50.

Steenkamp

J E M

Batra

Alden

D L

(2003) How perceived brand globalness creates brand value. Journal of International Business Studies. 34 (1): 53–65.

51.

Hardey

(2011) To spin straw into gold? New lessons from consumer-generated content. International Journal of Research in Marketing. 53 (1): 13–15.

52.

Lobschat

Zinnbauer

M A

Pallas

Joachimsthaler

(2013) Why Social Currency Becomes a Key Driver of a Firm's Brand Equity–Insights from the Automotive Industry. Long Range Planning. 46: 125–148.

53.

Grzeskowiak

Sirgy

M J

(2007) Consumer Well Being (CWB): The Effects of Self Image Congruence, Brand Community Belongingness, Brand Loyalty, and Consumption Recency. Applied Research in Quality of Life. 2(4): 289–304.

54.

Fischer

(2011) Brand Community Management. markeZin, special edition. 8–15.

55.

Hair

J F

Anderson

R E

Tatham

R L

Black

W C

(1998) Multivariate Data Analysis (5th ed.). New Jersey: Prentice-Hall International.

56.

Capece

Gitto

Campisi

(2008) Beyond the Learning Frontier and the Human Capital Development: New and Old Technological Opportunities for the Competence-Based Enterprises. Knowledge and Process Management. 15 (4): 270–279.

57.

Battistoni

Colladon

Fronzetti A

Scarabotti

Schiraldi

M M

(2013) Analytic Hierarchy Process for New Product Development, dx.doi.org/10.5772/56816, International Journal of Engineering Business Management

58.

Ritzer

Jurgenson

(2010) Production, Consumption, Prosumption. Journal of Consumer Culture. 10 (1): 13–36.

59.

Sicilia

Palazón

(2008) Brand communities on the internet- A case study of Coca-Cola's Spanish virtual community. Corporate Communications: An International Journal. 13 (3): 255–270.