Customer participation in company social networks: the role of customer brand engagement and the effect on customer loyalty Gijs Rikhof

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Customer participation in company social networks:

the role of customer brand engagement and the effect

on customer loyalty

Gijs Rikhof

Double Degree Master of Science

Advanced International Business Management and Marketing

Newcastle University: Business School

Supervisor: Dr. S. Bhattacharya

Student number: B15068797

Rijksuniversiteit Groningen: Faculty of Economics and Business

Supervisor: Prof. Dr. A.R. Muller

Student number: S2381001

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Abstract

The aim of this research was to understand what motivates customers to participate in a company social network (i.e. communities on a social network that are initiated by a commercial organization). The tri-dimensional concept customer brand engagement (based on cognitive-, emotional- and intentional brand engagement) was used to understand what motivates customers to participate in a company social network. Furthermore, this research aimed to understand the relation between customer participation in a company social network and customer loyalty. Additional, the moderating role of community identification on this relation is analysed.

This research used a web-based survey which resulted in N = 272 respondents. General internet and social network as well as socio-demographic data has been collected. Of the total sample, N = 199 customers participated in a company social network. Regression analyses were used (N = 199) to test the hypotheses and understand the underlying data. Additional, a structural equation model has been created.

The key findings of this research indicate that all the individual dimensions of customer brand engagement explain customer participation in a company social network. Furthermore, this research indicated that there is a positive relation between customer participation in a company social network and customer loyalty. It has been found that community identification does not influence this relation. The findings of this research have implications for academic researchers and managers. The dimensions of customer brand engagement help in explaining why customers participate in a company social network. Furthermore, managers should be aware that investments that enhance customer participation in a company social network positively relate to customer loyalty. A limitation of this research is that respondents self-selected an organization. Therefore, respondents might have been biased in relation to their selected organization.

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Acknowledgements

This dissertation marks the end of my studies. After completion I will graduate at the Rijksuniversiteit Groningen and the Newcastle University Business School. I want to express my gratitude to some people since I would not be able to complete this dissertation without them.

First, I would like to express my gratitude to my supervisors, Dr.

Bhattacharya

from the Newcastle University Business School and Prof. Dr. Muller from the Rijksuniversiteit Groningen. My supervisors provided me with important feedback and supported me throughout my dissertation process. I would also like to express my gratitude to the people that are close to me. They motivated and facilitated me in my dissertation process. Therefore, many thanks.

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List of tables

Table 2.1 Literature on customer participation

Table 2.2 Marketing literature on engagement

Table 2.3 Literature on customer brand engagement

Table 2.4 Literature on customer loyalty

Table 3.1 Variable type

Table 3.2 Constructs and items

Table 4.1 Socio-demographic sample characteristics

Table 4.2 Internet- and social network sample characteristics

Table 4.3 Cronbach's alpha

Table 4.4 Factor analysis

Table 4.5 Correlation matrix, AVE, √AVE and CR

Table 4.6 Regression of cognitive brand engagement on customer

participation in a company social network

Table 4.7 Regression of emotional brand engagement on customer

participation in a company social network

Table 4.8 Regression of intentional brand engagement on customer

participation in a company social network Table 4.9

Multiple regression of cognitive-, emotional- and intentional brand engagement on customer participation in a company social network

Table 4.10

Regression of customer participation in a company social network on customer loyalty and the moderating effect of community identification

Table 4.11 Relations between concepts according to SEM

Table 4.12 Model fit

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List of figures

Figure 2.1 Conceptual model

Figure 4.1 Structural equation model

List of abbreviations

CSN Company social network

Participation Customer participation

CBE Customer brand engagement

Loyalty Customer loyalty

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Chapter 1 - Introduction

1.1. Introduction

This research investigates what motivates customers to participate in a company social network. The concept customer brand engagement will be introduced, as this research wants to understand how engagement in relation to a brand results in customer participation in a company social network. Furthermore, the linkage between customer participation in a company social network and customer loyalty will be investigated. Additional, the moderating role of community identification on the relation between customer participation in a CSN and customer loyalty will be investigated. This chapter addresses the research background of the topic, the research rationale and the further structure of the thesis.

1.2. Research background

Community activity “is the biggest change in business in 100 years” (Ahonen and Moore, 2005). In general, a community is defined as a group of people who have a shared interest in a subject (eg. brands and organizations) and therefore interact and establish relationships with each other resulting in a sense of belongingness to a group (Muniz and O'guinn, 2001; De Valck et al., 2009). Recent technological development shifted communities from an offline- to online context. Especially, social networks are areas in which communities are established. That social networks are of significant importance to organizations can be illustrated by numbers. Facebook, the most popular social networks, has 1.7 billion monthly active users which is expected to reach 2.95 billion by 2020 (Statista, 2016). These large numbers of users provide (marketing) managers with new business opportunities, such as customer participation (hereafter referred to as participation). When customers participate with organizations they are assigned a role in the value creation process. Assigning customers with a role in the value creation process results in a win-win situation for customer and organizations since both groups benefit from participation (Chan et al., 2010).

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al., 2013b). This research utilizes the recently developed concept customer brand engagement (CBE)

(Hollebeek, 2011b; Hollebeek, 2011a; Hollebeek et al., 2014), a tri-dimensional concept based on cognitive-, emotional- and intentional brand engagement that is psychological and motivational in nature. In line with other academics (Brodie et al., 2011; Solem and Andrine, 2016), this research approaches CBE as a precedent of participation. Consequently, CBE is appropriate for illustrating what motivates customers to participate in a CSN. To acquire insights on the specific dimensions of CBE this research will analyze the dimensions individually.

Furthermore, this research recognizes that participation is often associated with customer loyalty (hereafter referred to as loyalty). Loyalty is essential for a firm's survival (Chiu et al., 2014; Turban et

al., 2015). Yet, the direct effects of participation on loyalty, and especially in a CSN-context, remain

unclear (Royo-Vela and Casamassima, 2011). This research will argue that from a social-exchange theory participation in a CSN will result in increased loyalty, as customers with stronger and more intense customer-organization relationships will feel the intention to maintain these relationships by repurchases of products and services, which reflects loyalty (Cropanzano and Mitchell, 2005; Verma et

al., 2012). Moreover, it is argued that customers that participate feel a sense of ‘ownership’ resulting

in additional (economic) behaviour, which reflects loyalty effects (Algesheimer et al., 2005; Grissemann and Stokburger-Sauer, 2012).

Finally, from the social- and organizational identity theory it is established that customers can identify with a brand, organization or a community (Bhattacharya and Sen, 2003; Algesheimer et al., 2005). Consequently, customers that participate in a CSN can identify with the community of the organization they participate in. In academic literature, there is general consensus stating that increased community identification (hereafter referred as identification) results in stronger (economic) behavioural intentions and perceptions (Ahearne et al., 2005; Algesheimer et al., 2005; Hogg and Reid, 2006; Van Dick et al., 2006). Consequently, this research argues that higher identification moderates the relation between participation in a CSN and loyalty.

1.3. Research objectives and question

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Research question: How can aspects of customer brand engagement illustrate the motivations

customers have to participate in a company social network?

Research question: What is the effect of customer participation in a company social network

on customer loyalty?

To answer the main research question the following sub-questions will be answered.

1. To what extent do cognitive-, emotional- and intentional brand engagement influence customer participation in a company social network?

2. To what extent does customer participation in a company social network influences customer loyalty?

3. To what extent does community identification influences the relation between customer participation in a company social network and customer loyalty?

1.4. Research rationale

In the research rationale the topic of this research will be justified. Both the theoretical- and managerial relevance will be outlined.

1.4.1. Theoretical relevance

There is little academic literature on what stimulates and motivates customers to participate with an organization in a social network context (Madupu and Cooley, 2010; Coulter et al., 2012; Ho and Wang, 2015; Solem and Andrine, 2016). Brodie et al. (2013) state that central to the discussion about what motivates customers to participate with organizations can be explained by the engagement concept. This research builds on CBE (Hollebeek, 2011b), which is based on both relationship marketing and service-dominant logic (Ashley et al., 2011; Lusch and Vargo, 2014; Vivek et al., 2012). The CBE concept can enhance the field of relationship marketing and service-dominant logic because engagement literature recognizes that customer behaviour is based on interactive experiences between customers and stakeholders. Furthermore, since measures of CBE can be utilized to capture motivations for participation (Brodie et al., 2013; Hollebeek et al., 2014), the concept is appropriate as it can be used as an antecedent of participation in a CSN (Hollebeek, 2011b; Solem and Andrine, 2016).

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12 linkage between participation and loyalty in particular (Chen and Wang, 2016). Furthermore, outcomes of participation differ and rely on the context (Chen and Wang, 2016). In financial- and travel industries it has been found that participation increased loyalty (Auh et al., 2007; Grissemann and Stokburger-Sauer, 2012). The antecedents and consequences of participation in CSN context are still understudied (Madupu and Cooley, 2010; Brodie et al., 2013; Ho and Wang, 2015). This research aims to contribute to the academic field by investigating the direct relation between participation in a CSN and loyalty. From a social-exchange perspective, this research will argue that participation in a CSN positively relates to loyalty. In line with Chan et al. (2010), this research argues that mediating variables that are known to influence relations between participation and loyalty are less persistent in a CSN-context. To illustrate, in the service industry customers are often physically present when they participate with an organization (Auh et al., 2007; Grissemann and Stokburger-Sauer, 2012). Therefore, mediating variables might be more influential. In a CSN-context, participation can be considered to exist in more indirect forms diminishing the influence of mediating variables. Finally, this research will investigate if identification moderates the relation between participation in a CSN and loyalty. The reason is that there is consensus in academic literature which states that greater identification results in extra (economic) behaviour (Ahearne et al., 2005; Algesheimer et al., 2005; Hogg and Reid, 2006; Van Dick

et al., 2006).

1.4.2. Managerial relevance

From a managerial perspective CBE, participation, loyalty and identification can be considered relevant. Foremost, positive outcomes and values that derive from participation in a CSN can result in organizations creating a competitive advantage (Malinen, 2015). To sustain a competitive advantage, it is key for managers to understand what makes customers willing to participate in a CSN (Malinen, 2015). Yet, many organizations do not understand the phenomena that motivate customers to participate in a CSN (McAlexander et al., 2002; Nambisan and Baron, 2009; Shankar and Batra, 2009; Madupu and Cooley, 2010; Coulter et al., 2012; Heinonen et al., 2013b). If the underlying phenomena are understood, CSNs can be organized in such a way that maximum value potential from participation can be reached (Madupu and Cooley, 2010; Lorenzo-Romero et al., 2014). Furthermore, (marketing) managers often intend to enhance loyalty since it is crucial for firm survival (Chiu et al., 2014; Turban

et al., 2015). Despite many (marketing) managers invest extensive resources in a CSN to, the effects of

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1.5. Structure

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Chapter 2 - Literature review

2.1. Introduction

This chapter will outline existing literature on the concepts relevant for this research. Furthermore, a conceptual model will be presented and hypotheses will be formulated.

2.2. Company social networks

The rise of social networks changed business environments. Social networks provide customers with easy access to information, increased possibilities to spread information and the possibility to engage in social interactions (Cross et al., 2004; Ellison, 2007). For these reasons, organizations consider social networks as instruments which can be used to advance marketing activities (Zarrella, 2009). A definition on social networks is provided by Kaplan and Haenlein (2010), who state that a social network is an internet-based application which is facilitated by the foundations of Web 2.0 that allows for the exchange and creation of user generated content. Organizations create a company social network (CSN) on a social network to acquire the potential commercial benefits that derive from social networks.

A CSN can be explained as a group of people who are connected to a company or brand, all within the boundaries of a social network (Heinonen et al., 2013b). Muniz and O'guinn (2001) state that a CSN is a group or community that is not bound to geographical boundaries. Moreover, in a CSN customers focus on commercialized products or services. Participants in a CSN are linked by a sense of community, identify with each other and have a similar understanding of the commercial landscape the organization of the CSN is in (Muniz and O'guinn, 2001).

In general, a CSN provides information on a company brand, -product or –service (Muniz and O'guinn, 2001; McAlexander et al., 2002). Furthermore, within a CSN there is interaction between customers themselves and between customers and organizations. Interactions can relate to diverse topics, ranging from product feedback to marketing initiatives of organizations. Typically, a CSN is open to all users of a social network site. Social network sites facilitate interaction, providing a form of ‘infrastructure’ to organizations (Coulter et al., 2012; Pineda, 2015). In line with other academic literature (Zaglia, 2013), this research considers a CSN to be a community on a social network, initiated by a commercial organization, that consists of entities like brands, products and services, customers, the organization and the relations between these entities.

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15 organization is in control over the information it distributes. Customers, in their turn, have the ability to add own content. Second, CSNs are open and can be found by anybody. Third, all users of a social network site can participate in a CSN by ‘following’ or ‘liking’ a CSN (depending on the terminology of the social network). The third point provides users with an opportunity instead of an obligation, meaning that information is de-institutionalized: the recipient has control over what is received (Bechmann and Lomborg, 2013).

Whereas participation is central to this research, CSNs are highly suitable because they provide extensive opportunities for participation (Lorenzo-Romero et al., 2014). Customers already participate in a CSN by ‘following’ or ‘liking’ the CSN. The easiness by which participation exists illustrates the appropriateness of a CSN as an instrument for participation (Aksoy et al., 2013). Furthermore, the interactive nature of relations in social networks results in customers being ‘prosumers’ (Bechmann and Lomborg, 2013). Customers both create and obtain value when they participate in a CSN. Further on, this research will elaborate on the effects of participation in a CSN and how this relates to loyalty.

2.3. Customer participation

In this research, participation is of significant importance. Consequently, this research first elaborates on participation in general. After that, academic literature on participation in relation to a CSN-context will be reviewed.

2.3.1. Customer participation in general

There has been a transformation in marketing practices in the past decades. Marketers of products and services take into account emerging positive outcomes that result from participation, such as increased productivity (Lovelock and Young, 1979; Bitner et al., 1997), increased customer satisfaction (Marzocchi and Zammit, 2006) and value related to product and service innovation (Tether and Tajar, 2008). Customers benefit primary through an increase in empowerment, which results in superior value through a better fit of offering (Marzocchi and Zammit, 2006). Furthermore, networks might enhance skills from which customer derive value (Svensson and Grönroos, 2008).

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16 between groups of customers and customers and organizations (Tether and Tajar, 2008). Participation can take form in collaboration, dialogues, experiments and learning from interactions (Prahalad and Ramaswamy, 2004). Table 2.1 provides conceptualizations and definitions on participation.

SOURCE CONCEPTUALIZATION – DEFINITION

(Levitt, 1972) Customer participation is the customer’s (physical) access to the technical/production core of service activities

(Lovelock and Young, 1979; Fitzsimmons, 1985)

Customer participation is the customer's provision of productive labour or production inputs in the service process

(Bitner et al., 1997) Customer participation refers to different roles performed/behaviour exhibited by customers in creation of service outputs

(Bettencourt et al., 2002)

Customer participation may include labor, information, service specification, quality control, sharing of codified and tacit knowledge, and contribution of customer competencies

(Magnusson et al., 2003)

Customer participation refers to customer involvement in tasks related to innovation, design, and/or production of offerings of

products/services (Grönroos and Ravald, 2011; Lusch

and Vargo, 2014)

Customer participation refers to customers’ complete engagement with the creation of resources from which they create value

Table 2.1 – Literature on customer participation

This research indicates that there seems consensus related to three criteria on participation. First, customers are assigned a role in the value creation process and there are interactions between customers and organizations and between groups of customers. Second, customers are not obligated to participate in a process. Third, customers add value to the process by providing (in)tangible resources to a process. The following section outlines how participation can be transformed to a CSN-context.

2.3.2. Value creation through customer participation in a company social network

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17 From a customer perspective, the value that derives from participation in social networks is usually instrumental. To start, customers participate in social networks to find relevant information. It is known that customers rather look for information on a CSN instead of on the official company website (Heinonen et al., 2013b). Furthermore, customers are seen as more trustworthy and therefore information from customers is considered to be more credible (Bickart and Schindler, 2001). However, in relation to a CSN, information deriving directly from the organization is perceived to be more credible (Heinonen et al., 2013b). Moreover, participation in a CSN creates value for customers as it results in a sense of belongingness, primarily by feeling connected with like-minded people (Coulter et

al., 2012; Bechmann and Lomborg, 2013; Brodie et al., 2013). Additional, customers create an online

identity when they participate in a CSN, therefore participation can be motivated by exploring a person’s identity and by self-representation (Bechmann and Lomborg, 2013).

In general, there is no specific definition of participation in an online context (Malinen, 2015). However, most studies use an active-passive dichotomy, in which visibility reflects a starting point for participation. In relation to a CSN, participation is often looked at from an interactive/non-interactive lens. ‘Lurkers’ are non-interactive participants, therefore passive. Still, despite their passivism, ‘lurkers’ are considered participants of CSN. For example, ‘lurkers’ typically participate by watching which is a passive activity that results in ‘informational benefits’. On the contrary, interactive members engage in various forms of activities in the CSN. According to Madupu and Cooley (2010), participation of interactive customers exists in form like posting messages, responding to questions, participating in contents and information sharing about their experiences.

In line with Bagozzi and Dholakia (2006), this research argues that customers participate in a CSN when a CSN is ‘followed’ (depending on the terminology of social network). Reasons are that a ‘follow’ is visible. Next, a ‘follow’ is a purposeful action which implicates that customers have an intention/motive for their participation (Cullen and Morse, 2011). This research is aware that after initial participation some customers stay ‘lurkers’ whereas other customers become interactive. In general, this interactivity is measured by quantitative techniques, like the number of visits and posts (Malinen, 2015). However, this research operationalizes participation in a CSN as a customer’s

willingness to participate in a CSN. This operationalization is justified because participation in a CSN is

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2.4. Customer brand engagement

The motivations customers have to participate in a CSN remain unclear. Central to the discussion about what motivates customers to participate with organizations is the ‘engagement’ concept (Brodie et al., 2013). Yet, marketing literature only recently adopted the ‘engagement’ concept as an explanatory factor of participation (Van Doorn et al., 2010). Theoretical foundations of ‘engagement’ concepts derive from relationship marketing (Ashley et al., 2011; Vivek et al., 2012) and the service-dominant logic perspective (Lusch and Vargo, 2014). In general, these academic streams of literature recognize that organizations create value based on relationships with customers. A variety of ‘engagement’ forms have been introduced, such as ‘customer engagement’ (Patterson et al., 2006), customer engagement behaviours (Van Doorn et al., 2010) and customer brand engagement (Hollebeek, 2011b). Outcomes of engagement relate to how customers perceive experiences when they interact with organizations, its products and its services. Consequently, engagement influences customers repeat patronage, influencing loyalty and retention effects, organization profitability and stimulating interactivity resulting in co-created value (Bowden, 2009; Verhoef et al., 2010). Table 2.2 provides conceptualizations and definitions on engagement concepts in current marketing literature.

(Levitt, 1972; Vivek et al., 2012) The intensity level by which a customer feels connected to and participates with an organization and the organizational activities.

(Patterson et al., 2006) The physical, cognitive and emotional occupancy customers feel in relation to a service organization.

(Van Doorn et al., 2010) Engagement demonstrates customers behaviour to an organization or brand apart from purchasing, that derives from intrinsic motivations.

(Higgins, 2006) Engagement is being involved, interested and occupied with something.

(Algesheimer et al., 2005)

Positive feelings towards an organization or brand community resulting in intrinsic motivations to interact/co-operate with an organization and its community.

Table 2.2 – Marketing literature on engagement

Overall, the engagement concepts possess some recurring elements. Namely, there is some form of interaction between customers and organizations. Moreover, engagement can be considered as motivational which is often captured on multiple dimensions. Furthermore, engagement can be measured at the individual level.

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19 are incorporated as Hollebeek (2011b) defines CBE to be: “the level of a customer’s cognitive, emotional and behavioural investment in specific brand interactions” (p. 565). Table 2.3 below summarizes the definitions that are relevant for understanding CBE.

Concept Definitions of customer brand engagement (Hollebeek, 2011b) Customer brand

engagement

“The level of a customer’s cognitive, emotional and behavioural investment in specific brand interactions” (p. 565).

Cognitive brand engagement

“a customer’s level of brand-related concentration in particular brand interactions” (p. 566).

Emotional brand engagement

“the degree of a customer’s positive brand-related affect in particular brand interactions” (p. 567).

Intentional brand engagement

“a customer’s level of energy, effort and/or time spent on a brand in particular brand interactions” (p. 568).

Table 2.3 - Literature on customer brand engagement

This research will clarify and elaborate on the definitions provided by Hollebeek (2011b) to get a better understanding of the concepts in table 2.3. First, cognitive brand engagement can be explained by levels of ‘immersion’. In general, contemporary marketing states that immersion is fully assessing an experience, whereas this involves the ‘entire living being’ (Schmitt, 1999). Therefore, immersion exists both at the physical and mental level and relates to customers minimalizing ‘distance’ to an experience. More specific, customers that are highly immersed in a brand activity spend a considerable amount of thought processing and thought elaboration in relation to a brand. Consequently, customers feel very focused on and are absorbed by a brand when they engage in a brand activity (Patterson et al., 2006; Hollebeek, 2011b). Overall, this research recognizes the comprehensives of the definition of Carù and Cova (2006) who state that “immersion literally implies becoming one with the experience and therefore conveys the idea of a total emanation of the distance between consumer and the situation” (p.5).

Second, emotional brand engagement can be explained by levels of ‘affection’. Within affection recurring feelings are passion, obsessiveness and even love (Hollebeek, 2011b). Furthermore, affection can result in customers becoming fans of an organization or brand. An important factor within passion is pride. Pride towards a brand exists because customers that interact with a brand or organization can identify with it. Consequently, customers that feel great affection towards a brand or organization feel greater pride when they are associated with that specific brand or organization. Furthermore, Chaudhuri and Holbrook (2001) define affection as a brand’s capability to evoke positive emotional responses when customers use products/services of an organization. Moreover, their research states that affection provides customers with feelings such as joy, happiness and love.

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20 activity. According to Hoffman and Novak (2009), customers with greater ‘activation’ (intentional brand engagement) towards a brand can be categorized as goal-oriented. On the contrary, customers with low ‘activation’ are categorized as experiential-oriented. Goal-oriented customers are more interested in the value they receive for their participation and are especially interested in the content. Experiential-oriented customers want to experience fun when they participate with an organization and therefore also care about how content is designed. Moreover, activation exists in different strengths (Hollebeek, 2011b). Customers with low ‘activation’ don’t have to commit a lot of (intangible) resources. An example is watching a CSN. Customers with high ‘activation’ commit more (intangible) resources which is referred to as ‘full energy’ commitment.

There is little academic research on the outcomes of CBE. However, it appears that brand satisfaction (Van Doorn et al., 2010) and brand loyalty (Hollebeek, 2011a) are positively relate to CBE. In an exploratory research, Brodie et al. (2013) found that CBE is a core element of online brand communities and therefore is of significant importance. Yet, the exact relation between CBE and participation in a CSN remains unclear (Solem and Andrine, 2016). Some efforts have been made to understand this relation. For example, Sashi (2012) proposes an engagement cycle for social networks in which more engagement results in greater interactions and increased feeling of connectedness. Sawhney et al. (2005) state that for virtual communities higher customer engagement stimulates a customer to participate in innovative marketing initiatives. Moreover, Coulter et al. (2012) state that engagement motivates customers to interact with organizations on brand activities, like Facebook based brand communities. Despite these researchers consider CBE to be an antecedent of participation, other researchers suggests that CBE is a consequence of participation (Ramaswamy and Gouillart, 2010; Nysveen and Pedersen, 2014). In general, they argue that engagement results from the customers efforts to contribute own (intangible) resources into participation initiatives created by organizations. Nevertheless, this research follows the approach of Brodie et al. (2011) and Solem and Andrine (2016) who state that the CBE reflects intrinsic motivations for participations and therefore precedes participation. Consequently, CBE is appropriate for this research as it can be used to clarify the motivations customers have for their participation in a CSN (Brodie et al., 2011).

2.5. Customer loyalty

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21 for vital business operations (Algesheimer et al., 2005). Retaining existing customers and strengthening their loyalty is crucial to create and enhance a sustainable competitive advantage (Chan et al., 2010), viable long-term business organizations (Chen and Chen, 2010) and increased overall performance (Watson IV et al., 2015). In marketing, higher loyalty can realize a competitive advantage because it reduces cost of failure, result in greater word-of-mouth effects, increases cross-selling opportunities, decreases transaction- and marketing costs, lowers price sensitivity, lowers switching behaviour of customers and supports stable and bigger incomes (Hallowell, 1996; Knox and Denison, 2000; Lynch Jr and Ariely, 2000; Turban et al., 2015). Table 2.4 provides conceptualizations and definitions on loyalty.

(Jacoby and Kyner, 1973)

“brand loyalty is biased (i.e., non-random), behavioural response (i.e., purchase), expressed over time, by some decision-making unit, with respect to one or more alternative brand out of a set of such brands, and is a function of psychological (decision-making, evaluative) process” (p. 2).

(Dick and Basu, 1994)

“customer loyalty is viewed as the strength of relationship between an individual’s relative attitude and repeat patronage” (p. 99).

(Anderson and Srinivasan, 2003) “a preference, or psychological attachment, accompanied by

repeat behaviour” (p. 125). Table 2.4 - literature on customer loyalty

Many researchers state that loyalty is based on two aspects: attitudinal loyalty and behavioural loyalty. Attitudinal loyalty is considered to be a customer’s psychological attachment to a brand or organizations, resulting in certain preferences and therefore repurchases (Anderson and Srinivasan, 2003). On the other hand, behaviour loyalty can be defined as the behavioural intention to revisit, re-order and repurchase from the brand (Gefen, 2002). All the definitions in table 2.4 incorporate both aspects of loyalty. Furthermore, this research recognizes loyalty to be an enduring relation between customers and organizations over a period of time, in which customers are willing to maintain a stable relationship by the commitment of individual effort. This research operationalizes loyalty as the intended behaviour that customers demonstrate towards an organization. Therefore, loyalty is measured from the perspective of attitudinal loyalty.

Many antecedents of loyalty have been studied in academic literature. The factors with the most significant impact on loyalty are satisfaction, trust, and commitment (Toufaily et al., 2013; Watson IV

et al., 2015). Other factors that affect loyalty are service quality, product quality, price, information

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22 First, participation in a CSN results in more information for organizations which provides insight into unmet demands of customers. Consequently, adaptions to products and services can be made to meet customer preferences, resulting in superior value and greater loyalty (Marzocchi and Zammit, 2006; Auh et al., 2007). Second, participation in a CSN results in a ‘customer data profile’ that provides organizations with opportunities for real-time promotions (Merlo et al., 2014). A ‘customer data profile’ increases knowledge organizations have on customers. Therefore, organizations can provide customers with the correct value at the correct time at lower costs (Auh et al., 2007).

2.6. Community identification

In this research, the role of community identification is incorporated. According to the social- and organizational identification theory customers can identify with a social group or organization (Bhattacharya and Sen, 2003). Moreover, Algesheimer et al. (2005) extend this view as they argue that customers can identify with brand communities, such as a CSN. When customers participate in a CSN it can be claimed that they feel associated with the community of the organization they participate with. Therefore, the role of community identification is relevant and incorporated in this research. A community can be explained by three principal criteria: locality, social interaction and bond (Hillery, 1955). Locality has a geographical character and states that a community differentiates itself based on location. However, there are also communities that are not geographically bounded. Such as online- and organizational communities (Malinen, 2015). The second point, social interaction, states that in communities relationships are built. Third, bond refers to a communal feeling, meaning that actors within a community feel a sense of belongingness (Koh et al., 2003). A community consists of two central attributes. First, there is an affective relationship towards a common interest, ranging from specific organizations to experiences. Second, there is a sense of commitment to a common behaviour, which is based on the same sets of values, meanings, and history. A comprehensive definition of a community derives from Muniz and O'guinn (2001) and De Valck et al. (2009) who state that a community is a group of people with a shared interest towards a subject. Based on this shared interest interactions between individuals’ take place on which relationships are established and a sense of belongingness to a group is created (Muniz and O'guinn, 2001; De Valck et al., 2009).

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23 to a CSN, Carlson et al. (2008) found evidence that for online communities both passive and active members can identify with the community.

Outcomes of identification are in general behavioural since members of the community are expected to behave according to a certain role (Ahearne et al., 2005). Extra-role behaviour derives from identification and adhering to group standards and values. Furthermore, individuals in a community show greater commitment and consequently feel the desire to maintain current relationships (Hogg and Reid, 2006; Van Dick et al., 2006). Moreover, customers who identify with a community feel stronger attached to the organization and consequently want to help other community members by sharing information on the organization's products, services and experiences (Muniz and O'guinn, 2001; McAlexander et al., 2002). This research operationalizes identification as whether or not a person construes him- or herself to the community of the organization. In line with other researchers, this research incorporates both the categorical- and affective component of identification (Bergami and Bagozzi, 2000; Bhattacharya and Sen, 2003). For the categorical component this research questions if individuals are self-aware of their membership to a community. For the affective component of the community, it is questioned if individuals feel emotionally attached towards and community.

2.7. Conceptual model and development of hypotheses

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24 Figure 2.1 - Conceptual model

2.7.1. Customer brand engagement and customer participation in a CSN

As mentioned before, CBE has been found to be a core element of online brand communities (Brodie

et al., 2013). Moreover, CBE can be used as a concept which precedes participation and indicates

motivations customers have for participation (Coulter et al., 2012; Brodie et al., 2013). Furthermore, CBE is a concept that derives from relationship marketing and service-dominant logic perspective and therefore CBE is of relation nature. Gwinner et al. (1998) argue that for relationships to be created and maintained, both of the involved parties need to feel the possibility to gain something from the relationship. This is clearly the case for participation in a CSN. Finally, the interactive nature indicates the appropriateness of CSN in which relationships can be established. The CBE concepts are hypotheses at the individual level for a more fine-grained understanding of the relations between CBE and participation in a CSN.

2.7.1.1. Cognitive brand engagement and customer participation in a CSN

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25 that higher cognitive brand engagement results in higher participation in a CSN and vice versa. This research formulates the following hypothesis:

H1a: There is a positive relation between cognitive brand engagement and customer participation in a company social network.

2.7.1.2. Emotional brand engagement and customer participation in CSN

Emotional brand engagement provides a customer with a feeling of pride when associated or using a brand (Hollebeek, 2011b; Hollebeek et al., 2014; Solem and Andrine, 2016). Brands that highly engage customers are considered to provide customers with a strong felt affection in relation to a brand (Hollebeek, 2011a). Auh et al. (2007) found that emotional engagement results in the customer-brand relationship to be stronger and more intense. Consequently, customers are willing to invest own (intangible) resources to maintain this relation, for example by participating in a CSN. When there is no psychological connection between a customer and a brand, there is no form of affection (Hollebeek, 2011a). In general, brands with low emotional engagement are considered as functional. Therefore, customers are less inclined to commit (intangible) resources to the relationship. Furthermore, social benefits, like self-representation and ‘social belonging’, will especially take place in a group of like-minded people who share a common interest. Because a CSN is characterized by a communal attitude that provides feelings of friendship and intimacy, customers with similar affection to a brand will be more motivated to participate in a CSN (Dholakia et al., 2004; Lorenzo-Romero et al., 2014). Overall, this research expects that higher emotional brand engagement results in higher participation in a CSN and vice versa. This research formulates the following hypothesis:

H1b: There is a positive relation between emotional brand engagement and customer participation in a company social network.

2.7.1.3. Intentional brand engagement and customer participation in CSN

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26 is interactivity (Lorenzo-Romero et al., 2014). A CSN facilitates both ‘watching’ and ‘full energy’ interactions between customers and a brand. Furthermore, a CSN is de-institutionalized, meaning that customers do not have an obligation to participate. Especially for low intentional brand engagement, it will be hard to intrinsically motivate customers to participate in a CSN. Overall, this research expects that higher intentional brand engagement results in higher participation in a CSN and vice versa. This research formulates the following hypothesis:

H1c: There is a positive relation between intentional brand engagement and customer participation in a company social network.

2.7.2. Customer participation and customer loyalty

Previous sections described that both participation and loyalty requires customers to commit (in)tangible resources to a relation or interaction. Within CSN, participants invest (in)tangible resources as they expect to acquire a certain value for their participation. For loyalty, it can be argued that customers invest (intangible) resources to maintain a relationship with an organization. In general, social-exchange theory states that in order to maintain relationships customers feel the intention to repurchase products or services from an organization (Cropanzano and Mitchell, 2005). Consequently, customers that feel higher intentions to participate in a CSN and therefore maintain relationships will also feel higher intentions to repurchase products or services, which is considered an expression of loyalty. Moreover, increased usage intensity of an online brand page (like a CSN) results in stronger relationships between customers and organizations, which consequently increases intentions to repurchase or promote products or services from an organization (Verma et al., 2012). Furthermore, customers that participate feel a sense of ownership and consequently care for the product/service outcome (Merlo et al., 2014). Moreover, customers both take the credit and blame of the outcome of participation and adapt their behaviour as they feel responsible (Grissemann and Stokburger-Sauer (2012)). Besides, Grissemann and Stokburger-Sauer (2012) state that interactions between customers and organizations lead to social bonds which stimulate loyalty. Finally, customers that participate with an organization are more ‘sticky’ and adapt their (economic) behaviour (Merlo et al., 2014). Overall, this research formulates the following hypothesis:

H2: There is a positive relation between customer participation in a company social network and customer loyalty.

2.7.3. Customer participation and customer loyalty: community identification moderation

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27 that demonstrate customer-organization relationships. In general, there is evidence that stronger identification influences relations. For example, Tsai and Pai (2012) state that customers that to a greater extent identify with a community are more inclined to maintain a relationship, which can be accomplished by repurchases of a service or product. Furthermore, Auh et al. (2007) mention that stronger identification changes customers perceptions, also strengthening customers’ desires to maintain a relationship. Moreover, customers that strongly identify with a community can take on extra-role behaviour (Ahearne et al., 2005; Algesheimer et al., 2005; Van Dick et al., 2006). According to Selnes (2013), customers might see themselves as early adopters of products and services and thus might feel the need to inform the community. Posting reviews or recommending products and services to others are examples of how customers inform others. This extra-role behaviour stimulates loyalty and can result in repurchases but also in customers being ‘promoters’ of an organization. Next, greater identification results in a greater sense of ownership (Algesheimer et al., 2005; Grissemann and Stokburger-Sauer, 2012; Merlo et al., 2014), strengthening the relation between participation and loyalty. Finally, customers can feel obligated to adhere to a certain behaviour when this is expected by a community (Bergami and Bagozzi, 2000). Because of the above, this research formulates the following hypothesis:

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Chapter 3 - Methodology

3.1. Introduction

This chapter will outline the research paradigm. Next this research will discuss its survey structure, measurement and item specification, survey development and the data analyses. Additional, the ethical consideration will be mentioned.

3.2. Research paradigm

Holden and Lynch (2004) consider a research paradigm to be a philosophical framework that guides scientific research to be conducted properly. Philosophical frameworks are bi-polar, with on one side objectivism or positivism, and on the other side subjectivism or interpretivism (Holden and Lynch, 2004). Objectivism assumes that social reality is objective and singular, meaning that investigating it will not change it (Creswell, 2013). Subjectivism assumes that reality is in our mind and therefore subjective (Creswell, 2013). An important assumption for objectivistic research paradigm is that phenomena can be quantified. In quantitative research, hypotheses are based on conceptualizations of the object under study and will be verified or rejected based on observations in collected data (Holden & Lynch, 2004). Large samples are needed to generalize findings and translate findings to different contexts.

This research formulated hypotheses based on operationalizations of concepts. An objectivistic research approach is taken, in which quantitative data will be used to verify the concepts and test the hypotheses.

3.3. Research design

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3.3.1. Survey structure

The survey consisted of 6 parts. Before the survey started, respondents were provided with information on social networks, CSN, and participation. Consequently, respondents were informed on the topic of this study. The structure of this survey was different, depending on whether respondents participated in a CSN or not. In this survey, the independent variables were asked before the dependent variables to minimize effects of common method bias (Podsakoff et al., 2003). The first part was answered by all respondents and related to internet- and social network usage. In the first part respondents were asked if they participated in a CSN. If not, respondents were redirected to the end of the survey, where they were asked socio-demographic questions. Respondents that participate in CSN proceeded to the second part, in which they were asked the name of an organization they participated with. The third part consisted of questions on CBE in relation to the organization's respondents filled in. In the fourth part, questions related to participation with the CSN were asked. The fifth part consisted of questions related to loyalty. In the sixth part question on CI were asked. In the seventh part two control questions were asked. Lastly, also these respondents filled in socio-demographic questions. At the end of the survey, there was a word of appreciation towards the participants. The survey can be found in Appendix A.

3.3.2. Measurement and item specification

In order to answer the research question, the sub-concepts of CBE are used as well as participation, loyalty and identification. In table 3.1 an overview of the types of variables can be found

Type of variable Variable

Independent and dependent Customer participation in a company social

network (CP)

Independent Cognitive brand engagement (CBECOG)

Independent Emotional brand engagement (CBEEMO)

Independent Intentional brand engagement (CBEINT)

Dependent Customer loyalty (CL)

Moderator Community identification (CI)

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30 For the variable participation, this research used the items from Algesheimer et al. (2005), Qu and Lee (2011) and Ho and Wang (2015). For cognitive-, emotional and intentional brand engagement, this research adopted the measures from Hollebeek et al. (2014), who screened and verified 69 CBE items. In the end, 10 items were considered appropriate (significant and reliable) that could describe cognitive-, emotional and intentional brand engagement. For loyalty, the measures of Solem and Andrine (2016) were adopted. These measures are intentional and reflect future loyalty, a continued patronage, recommendation to others and repeat selection (Brakus et al., 2009; Selnes, 2013). Identification items were taken from Algesheimer et al. (2005) and reflect both the categorical- and affective component of a community. The quality of these items can be found in chapter 4. Table 3.2 provides an overview of the constructs and individual items.

Additional to these constructs, control variables were added. The variables age, gender, education and current daily occupation were added to control for socio-demographics of the sample, which is common in social- and marketing sciences (De Valck et al., 2009; Pallant, 2013). Furthermore, a control variable that measured the duration of participation was added because Madupu and Cooley (2010) propose the length of the relationship to be a moderator. Subsequently, a control variable measured if the respondents were familiar with the products or services of the organization.

Concepts Items

Customer participation

(Algesheimer et al., 2005; Qu and Lee, 2011; Ho and Wang, 2015)

 I often watch the company social network activities of (brand)

 I’m willing to participate in the company social network of (brand) because of informational benefits

 I’m willing to participate in the company social network of (brand) because of social benefits

 I intend to actively participate in the social network page of (brand)

Customer brand engagement (Hollebeek et al., 2014)

Cognitive brand engagement

 Using (brand) gets me to think about (brand)

 I Think about (brand) a lot when I’m using it

 Using (brand) stimulates my interest to learn more about brand

Emotional brand engagement

 I feel very positive when I use (brand)

 Using (brand) makes me happy

 I feel good when I use (brand)

 I’m proud to use (brand) Intentional brand engagement

 I spend a lot of time using (brand), compared to others (category) brands

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 (Brand) is one of the brands I usually use when I use (category).

Customer loyalty

(Solem and Andrine, 2016)

 I intend to stay loyal to (brand) in the future

 I intend to stay on as a customer of (brand) in the next three years

 I intend to recommend (brand) to other people

 If I had to choose again I would still choose (brand)

Community identification (Algesheimer et al., 2005)

 I am very attached to the community of (brand)

 I see myself as a part of the (brand)’s community Table 3.2 - Constructs and items

In this research a seven-point Likert scale is used. Scale questions are a common method of measuring respondents perceptions, attitudes and beliefs (Blumberg et al., 2014). The concepts that are measured in this research are based on perceptions and beliefs of respondents, justifying the use of Likert scales. The following 7 point Likert scale is used: 1 = strongly disagree, 2 = disagree, 3 = somewhat disagree, 4 = neutral, 5 = somewhat agree, 6 = agree and 7 = strongly agree. A seven-point Likert scale is useful because respondents are provided with sufficient options which can indicate perceptions, attitudes and beliefs in more detail (Blumberg et al., 2014). Furthermore, a seven-point Likert scale provides respondents with the option to answer neutral.

3.3.3 Survey development

After the survey was created a pilot test of N = 6 respondents was done. The questionnaire was discussed and respondents provided their opinion on the questions. Some questions were perceived as unclear. Therefore, some adaptions to the wording were done. Furthermore, not all of respondents in the pilot test fully understood the English questions because their primary language was Dutch. To collect as much data as possible a translation of the questionnaire to Dutch was logical. This research adopted the back-translation approach of Chidlow et al. (2014) who argue that it is still the most accepted translation form in current international (marketing) business research. The back-translation process was conducted by three bilinguals, resulting in a Dutch- and English questionnaire.

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3.3.4. Primary data collection and sample

There are two sampling techniques: non-probability and probability sampling. This research leans towards the non-probability technique. The reason is that this research used a convenience sampling scheme. In a convenience sampling schema respondents are easily accessible and quick to reach (Babin and Zikmund, 2015). The online survey of this research was distributed via social networks and people were invited to participate. It can be argued that this process of inviting respondents to participate is an easy and quick way of acquiring data, that is based on the personal network of the researcher. A disadvantage of convenience sampling is the risk that acquired data might not be representative for the whole population. Much effort was put into the random selection of respondents to overcome the disadvantages of convenience sampling (e.g. different channels of distribution of the web-based survey). Furthermore, for testing the hypotheses it was required that respondents participate in a CSN. Consequently, self-selection occurred. Self-selection can cause biased results based on part of the population. This research argues that the influence of external factors that might influence whether or not a person participates in a CSN only has limited influence on the relations between CBE, participation, loyalty and identification. The basis for this argumentation derives from Kaplan and Haenlein (2010) who recognize that there is growth in almost all generations in relation to social network participation. In other words, there are no significant differences between participants and non-participants that might cause results to be biased. However, because of the dynamic nature of social networks results should be interpreted with caution. Finally, all respondents were asked general questions. The underlying purpose is to illustrate differences between participants and non-participants, which might be interesting for future research (Field, 2009).

3.3.5. Data analysis

The data is collected via the Qualtrics survey tool and is analyzed in SPSS 23. First, the raw data set is cleaned. Next, sample characteristics and descriptive statistics will be provided. Afterwards, the hypotheses will be tested using regression analysis. Chapter 4 will discuss the analysis in greater detail.

3.3.6. Ethical considerations

When collecting data via internet some ethical considerations should be taken into account (Rhodes

et al., 2003). Ethical considerations in relation to web-based surveys relate to privacy, confidentiality,

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Chapter 4 - Findings

4.1. Introduction

In this chapter, data will be analyzed and findings will be presented. The data is collected according to the research design outlined in chapter 3. First, the data is screened and inappropriate responses are removed. Second, a preliminary analysis is conducted which provides insights on the sample characteristics and the quality of the data. Third, the hypotheses are tested by regression analysis. Additional, this research performed a structural equation model on which it will elaborate later on. Finally, the empirical findings will be presented.

4.2. Preliminary analysis

Preliminary analysis was conducted which ensures the quality of the data. First, abnormal- and missing values were removed together with outliers. Next, the sample is described based on their socio-demographics and general internet- and social network usage. Furthermore, descriptive statistics per item are presented. Finally, this research tested reliability and validity of the constructs by performing Cronbach’s alpha, factor analysis, average variance extracted and composite reliability.

4.2.1. Data screening and cleaning

The online survey was closed after one and a half week. The raw data set consisted out N = 358 respondents. The raw data set was cleaned using the Listwise technique. Incomplete and inappropriate cases were removed. Furthermore, respondents that filled in more than one organization (e.g. I participate in Zara, H&M, C&A) were excluded from the sample. The cleaned data set consisted out N

= 272 respondents from which N = 199 are participants and N = 73 are non-participants in a CSN.

4.2.2. Sample characteristics

The sample can be described based on socio-demographic and general internet- and social network usage. Table 4.1 illustrates the socio-demographic characteristics. Table 4.2 illustrates the internet- and social network characteristics. In this research, participants are respondents that participate in a CSN. Non-participants are respondents that did not.

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35 respondents had an Applied Science or University degree (70.2%), which somewhat increases for participants (78.9%) and lowers for non-participants (46.6%). Lastly, most participants study (66.3%) and most non-participants work (54.8%), which probably relates to the age of the respondents. Almost all of the respondent (98.5%) use the internet every day. More than half of the participants (66.9%) use the internet more than 3 hours a day whereas 52.1% of the non-participants use the internet only for 1 à 3 hours per day. Participants in a CSN make significantly more use of the internet each day. Furthermore, only 5.9% of the respondents do not have a social network account. Logically, these respondents fall in the non-participant group. The most popular social network is Facebook, followed by Instagram and YouTube. Almost all of the participants (98.5%) and also a significant amount of the non-participants have a Facebook account (68,5%). Table 4.1. and table 4.2 can be found on the following page.

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36 Socio-demographics Complete sample Participants Non-participants

N % N % N % Sample 272 100 199 100 73 100 Gender Male 140 51,5 102 51,3 38 52,1 Female 132 48,5 97 48,7 35 47,9 Age 18 to 25 years 180 66,2 157 78,9 23 31,5 26 to 35 years 26 9,6 18 9 8 11 36 to 45 years 18 6,6 8 4 10 13,7 46 to 55 years 34 12,5 14 7 20 27,4 56 to 65 years 11 4 2 1 9 12,3

66 years and older 3 1,1 0 0 3 4,1

Country of origin Netherlands 259 95,2 186 93,5 73 100 Germany 3 1,1 3 1,5 0 0 Italy 1 0,4 1 0,5 0 0 United Kingdom 3 1,1 3 1,5 0 0 France 1 0,4 1 0,5 0 0 Portugal 1 0,4 1 0,5 0 0 Indian 1 0,4 1 0,5 0 0 Turkey 1 0,4 1 0,5 0 0 USA 2 0,7 2 1,0 0 0

Highest level of education

Primary or high school 35 12,9 16 8,0 19 26

Vocational education 40 14,7 21 10,6 19 26 Applied Sciences 88 32,4 68 34,2 20 27,4 Bachelor degree 72 26,5 62 31,2 10 13,7 Master degree 31 11,4 27 13,6 4 5,5 Others 6 2,2 5 2,5 1 1,4 Main occupation Work 104 38,2 64 32,2 40 0,5 Study 153 56,3 132 66,3 21 0,3 Retired 4 1,5 3 1,5 4 0,1 Unemployed 4 1,5 0 0 4 0,1

Stay at home mom/dad 7 2,6 0 0 4 0,1

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37 Internet- and social network

usage Complete sample Participants Non-participants

N % N % N %

Sample 272 100 199 100 73 100

Daily use of internet

Yes 268 98,5 199 100 69 94,5

No 4 1,5 0 0 4 5,5

Hours spend on internet per day

None 1 0,4 0 0 1 1,4

Less than 1 hour 19 7 5 2,5 14 19,2

Between 1 and 3 hours 99 36,4 61 30,7 38 52,1

Between 3 and 5 hours 83 30,5 72 36,2 11 15,1

More than 5 hours 70 25,7 61 30,7 9 12,3

Social networks Instagram 155 57 130 65,3 25 34,2 Facebook 246 90,4 196 98,5 50 68,5 LinkedIn 116 42,6 101 50,8 15 20,5 Twitter 112 41,2 97 48,7 15 20,5 YouTube 131 48,2 110 55,3 21 28,8 Google+ 97 35,7 84 42,2 13 17,8 Pinterest 5 1,8 5 2,5 0 0,0 Snapchat 9 3,3 6 3 3 4,1 WhatsApp 2 0,7 0 0 2 2,7

Table 4.2 - Internet- and social network sample characteristics

4.2.3. Descriptive results

For all the individual items the descriptive results are measured. Appendix B provides an overview of the mean, the standard deviation and the Kurtosis and Skewness of the items.

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4.2.4. Reliability analysis

To test for internal consistency this research conducted a Cronbach’s alpha test and a factor analysis. According to Field (2009), a Cronbach’s alpha value of 0.7 or higher indicates internal consistency. Table 4.3 indicates the Cronbach’s alpha’s of the concepts. Only the Cronbach’s alpha for cognitive brand engagement is lower than 0.7. However, this research expects no problems related to internal consistency as there is a minimal deviation.

Internal consistency Number of items Cronbach's alpha

Customer brand engagement

Cognitive brand engagement 3 0,687

Emotional brand engagement 4 0,788

Intentional brand engagement 3 0,737

Customer participation 4 0,774

Customer loyalty 4 0,819

Community identification 2 0,923

Table 4.3 - Cronbach's alpha

In social science, factor analysis is frequently computed to understand how much of a variable is measured by specific items (Field, 2009). Consequently, factor analysis indicates the reliability of constructs. Moreover, a value of 0.7 or higher indicates no issues with reliability. Table 4.4 indicates the factor loadings of the individual items on the overall variable. There are no issues with reliability as there are no factors below 0.7.

Factor analysis Factor

Customer brand engagement

Cognitive brand engagement

CBECOG1 When I use product or services of (brand), I expect to learn about (brand) 0,803 CBECOG1 When I use product or services of (brand), I think a lot about (brand) 0,762 CBECOG1 When I use product or services of (brand), I become fascinated by (brand) 0,789

Emotional brand engagement

CBEEMO1 I feel very positive towards (brand) 0,743 CBEEMO2 I feel energetic when in contact with (brand) 0,790

CBEEMO3 (brand) makes me happy 0,791

CBEEMO4 (brand) makes me proud 0,837

Customer participation in company social networks: the role of customer brand engagement and the effect on customer loyalty Gijs Rikhof