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Article

The Effect of Brand Experience on Customers’ Engagement Behavior within the Context of Online Brand Communities: The Impact on Intention to Forward Online Company-Generated Content

by
Mahmoud Yasin
1,
Lucia Porcu
2 and
Francisco Liébana-Cabanillas
2,*
1
Department of Marketing, Arab American University, Jenin, P.O. Box 240, Palestine
2
Department of Marketing and Market Research, University of Granada, 18071 Granada, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(17), 4649; https://doi.org/10.3390/su11174649
Submission received: 30 June 2019 / Revised: 16 August 2019 / Accepted: 20 August 2019 / Published: 26 August 2019
(This article belongs to the Section Economic and Business Aspects of Sustainability)

Abstract

:
The purpose of this study is to assess the antecedent role of brand experience (BE) in the intention to forward online company-generated content (CGC) within an online Islamic banking sector. The present study analyzed 387 valid responses collected through an online survey conducted among a number of online Islamic bank customers in Palestine. The results of this study revealed that BE has a stronger influence on customers’ intention to forward online company-generated contents. This research pioneers the empirical research in Palestinian Islamic banking systems exploring the instrumental role of BE on customers’ engagement behaviors, as well as the intention to forward online CGC. In addition, this research aims to fill the existing gap in the under-researched area of the online branding of Islamic banking services.

1. Introduction

With the advent of Internet and social media, the nature of communications has drastically changed between marketers and customers from one-way to two-way communication [1]. In this sense, social media networks have become significantly developed platforms for businesses to use to perform their activities and achieve their goals [2,3]. In addition, social media platforms are also an important tool for marketers to understand customers’ motivations to express and share their needs and wants [4]. Companies approach social media platforms to gather information related to their products, services, and brands in order to satisfy customers’ needs and wants [5,6]. Statistics show that there are more than 50 million businesses using Facebook as a social media platform to conduct businesses such as offering products and services, running promotional campaigns, running advertisements, obtaining feedback on customers’ experiences, and so on. The leading organizations in the market spend 30 percent of their budget on customer engagement and interaction with brands via social media [7]. On the other hand, previous studies in this field focused on measuring and investigating customer experiences with products, services, and brands both in offline and online settings in various marketing fields for the following reasons: customers’ experiences are central to measuring organizational performance. Customers with positive experiences help companies achieve competitive results in customer attraction, retention, and positive word of mouth. Customer experience is considered as a competitive battlefield between companies [8]. Positive and negative experiences represent a vital indicator of the level of customer satisfaction [9]; in this sense, experiences are important in understanding customers’ purchases decision-making [10]. Customer experience also shapes the interaction process with regard to the different reactions between the customers and businesses [8]. In addition, customer experiences can be evaluated through the comparison between customers’ expectations and the offerings of the firms via different touch points [11]. Therefore, studying and measuring customer experiences with brands and engagement behaviors through social media represents the most important purpose for marketing professionals and marketing firms. In this light, brand experience has never been investigated within the context of Palestine, in particular in the Islamic banking sector. For that reason, this study aims to address the following question: does the brand experience of Islamic banks affect customers’ engagement behaviors through brand community pages on Facebook? The results of this study are especially valuable for marketing professionals and banks managers in Palestine to understand how brand experiences will drive engagement behaviors and should help them design, develop, and implant marketing campaigns successfully.

2. Literature Review

The literature review conducted for this study is divided into the following five themes: the Islamic banking and finance systems, brand experience, customer engagement within the social media setting, consumer intention, and finally online brand community engagement and perceived trust with regard to brand community pages.

2.1. Subject of the Study: the Islamic Banking and Finance Systems

The Islamic banking and finance market have been growing rapidly over the past few years. The swift growth has translated into a larger market with a broader area of influence and greater diversity with regard to the Islamic financial industry. Moreover, the Islamic banking and finance market has expanded geographically. In this sense, Islamic banking services and operations are mostly established in Muslim-majority countries. Also, the geographical expansion of these banks has reached non-Muslim territories such as Singapore, the United Kingdom, Hong Kong, and South Africa, which have added some forms of Islamic banking and finance activities to their financial services [12]. The Islamic banking system prohibited interest rates (riba), fixed rates on return deposit, or charging interest rates on loans. The Islamic financial systems depend on sharing profits and loss according to previous agreements between the Islamic banks and their customers [13,14]. The Islamic banking guidelines and procedures derive from the principles of Sharia. Kpodar and Imam [15] indicated that the Islamic banks are not only forbidding interest rates (riba), they also prohibit all kinds of activities and transactions restricted by Islamic law such as asymmetric information in the transaction between the bank and the client, financial uncertainty, and activities that may have a negative impact on society by leading customers to fall into forbidden activities and transactions (haram). Furthermore, Islamic finance bans the funding of haram (unlawful) products and activities such as intoxicating beverages, tobacco products, pork products, pornography, gambling, illegal drugs, and any transaction deemed unethical, immoral, and/or socially objectionable.
On the other hand, for the Islamic banking sector to be successful and competitive in the market, it must be trustworthy for their customers by satisfying their needs and wants while complying with the rules of Shari’ah. If the Islamic bank is deemed untrustworthy and customers do not feel that the source of their wealth is entirely halal (lawful) [16], the bank is likely to lose customers who will switch to a competitor. For that reason, social media plays an important role in creating the brand community pages of Islamic banks and financial institutions in order to connect with their customers, build relationships, and engage clients with the brand while identifying customers’ needs according to the Islamic rules of Shari’ ah [17].

2.2. Brand Experience

The concept of experience is not a new notion; it was introduced first by Holbrook and Hirschman [18] in marketing literature. Later, the authors of that study directly addressed the concept of brand experience. Ambler et al. [19] reported that brand experience is created by customers who interact personally with the brand when they use the brand, search and find information about the brand, talk to others about the brand and other related activities. Brakus et al. [20] posit that customer experience is especially relevant in fields such as marketing, philosophy, cognitive sciences, and management practices. In addition, previous research focused on measuring the experiences derived from the products features instead of those stemming from the brands. In that light, the study identified and conceptualized the concept of brand experience.
Brakus et al. [20] approached the concept of brand experience according to four dimensions (sensory, affective, intellectual, and behavioral) in order to shape customer experience with the brands as a part of brand design. His study further explained that the conceptual perspective on brand experience differs from other brands constructs, i.e., brand experience differs from brand attitude, brand involvement, brand attachment and brand personality. Therefore, brand experience is best approached through specific sensations, feelings, cognitions, and behavioral responses instead of a general evaluation, emotional relationship concept, or a motivational state about the brand. Nysveen et al. [21] reveals that brand experience involves both customers and non-customers, while Chase and Dasu [22] corroborates that the impression of brand experiences has a stronger effect on consumer memory when compared with the impact of the features and benefits of the products and services. BE in its simplest form can be defined as a set of variables that collectively shape the attitude of customers toward a product, a service or a company. These variables include purchasing experience, customer satisfaction, post purchase service, and the behavioral response of the customers. BE, mediated by Brand community engagement (BCE) and perceived trust of Brand Community Pages (BCP), encourages customers to develop a positive or negative stand toward the brand—considering that experiences affect attitudes, judgments, and other aspects of consumer behavior [23].
According to Schmitt [24], consumers’ expectations from brands as a means to integrate consumers’ sensations, feelings, and intelligence far exceed the functionality and utility associated with the products. On the other hand, the work of Brakus et al. [20] and Cheng and Khan [25] revealed that consumer experience with the brand “can affect certain aspects of consumer behavior such as satisfaction and loyalty”.
In this sense, previous research approached brand experience in online contexts, i.e., searching for products and services online [20]. The online brand experience resulting from the advent of online brands as a result of the rise of the internet and other information technologies has also been researched [26,27]. The interactions with online brands as a result of customers’ internal subjective responses have also been examined [28]. In addition, Helm [29] reports that online brand experience is central to improving the quality of customers’ experience while building relationships with the consumers of the banks.
With regard to previous research assessing brand experience in online and offline settings within the context of the banking sector it is worth noting both offline experiences in the banking sector [30,31,32] and online experiences in the banking sector [8,33,34].
According to previous studies and the theoretical background, the present study infers that customer experiences in the case of Islamic banks’ brands influences customers’ perceived trust with regard to the Facebook community pages while increasing customers’ level of brand community engagement with Islamic banking. In this regard, the following hypothesis is put forward:
Hypothesis 1. (H1).
Brand experience positively influences customers’ perceived trust of Facebook community pages.
Hypothesis 2. (H2).
Brand experience positively influences customers’ level of brand community engagement.

2.3. Customer Engagement within the Social Media Setting

Social media platforms have changed customers’ behavior by encouraging them to interact with each other as well as with companies and brands. Social media development has transformed customers from passive buyers into active customers. Malthouse et al. [35] revealed the role of social media in turning customers into active participants while changing their interactions and behaviors with regard to company-generated content, resulting in customers in social media platforms becoming value creators [36]. Investigating customers’ behavior in social media platforms is also relevant. Previous research reported the different factors affecting customer engagement within the context of social media platforms.
Brodie et al. [37] and Brodie et al. [38] revealed that customer engagement depends on multiple dimensions (cognitive, emotional, and behavioral) playing a significant role in relational exchange. Along these lines, Hollebeek [39,40,41] and Brodie et al. [37] identified the different dimensions (cognitive, emotional, and behavioral) mediating the concept of customer-brand engagement and brand interactions. In addition, reference [42] examined engagement as a behavior other than a simple purchase. Also, Dolan et al. [43] assessed customer behavior in social media beyond the purchase. On the other hand, Brodie et al. [37] indicated that customer engagement is more than customers’ participation and interaction and that it is actually related to the relationship and engagement with objects such as brands.
With regard to previous studies examining customer engagement within the context of brand community engagement: Algesheimer et al. [44] examined customer engagement within brand communities and found that it is affected by three dimensions (Utilitarian, Hedonic, and Social) which provide an intrinsic motivation for customers to interact with other community members. In this light, McAlexander et al. [45] assessed the process of building a brand community and defined brand communities as the fabric of the relationships between customers in the community, brand, products, and the firm. This study also tested previous results with regard to studies on brand communities through quantitative methods by expanding the definition of brand communities. In this sense, they revealed entities and relationships that previous research ignored at that time. These studies also focused on the key characteristics of brand communities, such as geotemporal concentrations, and the richness of social context. In this sense, the brand community can be strengthened by encouraging customers to share and provide feedback, which in turn improves brand loyalty. Also, Sprott et al. [46] approached the self-concept of brand engagement. In this sense, Chang et al. [47] defined the brand community as an increasingly widespread social aggregate that attracts the attention of brand fans. The importance of a brand community is especially significant for customers who appreciate their role in building and developing the online and offline brand community. In this regard, motivating customers to engage in these communities and fostering customers’ loyalty with regard to the brand of the company is absolutely instrumental. Other previous studies approached customer engagement in online and social media contexts. In this sense, Calder et al. [48] assessed online engagement with regard to websites. Thus, Baldus et al. [49] examined the key dimensions affecting online brand community engagement and their role in motivating customers to participate in online brand communities. This study also described online brand community engagement as the compelling, intrinsic motivations that result in a continuous interaction between customers and the online brand community. Wang et al. [50] and Madupu [51] revealed the role of functional, psychological, and social needs in encouraging customers to participate in the community, in addition to assessing hedonic needs as a driver to participate in online communities. Wang and Fesenmaier [52] and Dholakia et al. [53] investigated the factors that motivate customers to participate in virtual communities; these studies also assessed and outlined the structures of said communities. In addition, Gong [54] identified consumer-brand engagement behavior in online brand communities. The study assessed the antecedents of customer brand engagement behavior from a cross-cultural perspective. On the other hand, Cvijikj and Michahelles [55] posit that social networks have become additional marketing channels complementing traditional channels with regard to marketing strategies. The marketing exchange and engagement through social media between companies and customers are fundamental, non-transactional constructs [55]. On the other hand, previous studies posit that the antecedent constructs of customer engagement are the following: involvement [28,37,39], participation [28,37], flow [39], identification [56,57] and identity [42,58]. In addition, previous research identified the consequence constructs of customer engagement as follows: loyalty [59] and customer value [39]. Other studies investigated both antecedent and consequence constructs of customer engagement and found the following dimensions: interaction [39,57,60], rapport [37,39], customer satisfaction [42,57], trust [39,42,57,59,61] and commitment [39,42,59,61].
In the context of the development of social media, the open line of communication in social media platforms between financial institutions and their customers is central to establishing relationships between the financial institutions (brand) and their customers. On the other hand, previous studies and reports indicated that 46% of social media users would use a social media platform as their primary source of communication with their banks and financial institutions [62]. Financial institutions neglecting the importance of social media are basically losing the opportunity to be strategically well-positioned in their field [63]. For that reason, social media serves as a significant tool for financial institutions to attract new customers and retain their existing loyal base while improving their business performance [64].

2.4. Consumer Intention

According to Watts and Peretti [65] in the context of online environment, marketing companies create contents such as video, audio, and websites available online for their users in order to build their brand. In this sense, users will eventually consume these contents by interacting with them and will ultimately contemplate whether to forward, or share the company-generated content. In this light, previous research focused on the motivational factors to forward and share online contents [66]. Taylor et al. [67] indicated that there are differences in the motivational factors impacting on users’ decisions to forward and share company-generated content. In this sense, the more individualistic and altruistic individuals are, the more likely they are to forward online content. In addition, those individuals who reveal their self-concepts motivate others to also share online content [67]. In light of these findings, one of the main objectives of the present study is to explore and test the empirical relation between brand experience (BE) and consumer behavior beyond satisfaction, trust and loyalty. More specifically, the endeavor is to assess the impact of BE on consumers’ intentions within the online Islamic banking sector in Palestine. Does an attractive BE entice consumers to act favorably toward the brand beyond being loyal customers? Would they forward the online company-generated content (CGC) to potential consumers?

2.5. Mediating Factors

The comprehensive understanding of the relationship that links BE to customers’ intentions requires the modification of the model to account for a second order construct measuring the impact of two fundamental mediating factors, namely online BCE and perceived impact of BCP on customers’ intentions to forward online CGC (Figure 1).
The success and the continuity of any online BCP largely depends on the brand’s ability to create and maintain credible online content and on its resolve to actively engage its current and potential customers in the branding process. The quality of the website and its contents as well as the level of audience engagement exert a profound influence on shaping customers’ attitudes and consequently swaying their intentions and behavior toward online CGC.

2.5.1. Perceived Trust of Brand Community Pages

The content of BCP, among other variables, is an integral factor affecting customers’ perceived trust of a webpage. Providing updated, relevant, and informative content to guide and inspire the intended audience is fundamental for any social media platform (i.e., online BCP) to stay lively and command an abundance of traffic [68].
Companies seek to create trustworthy online brand community pages which will enable them to gain customers’ trust as a key factor to the success of the branding campaign [69]. Akkucuk and Turan [70] argued that the benefits of securing customers’ trust of the BCP include enhanced potential for purchase intention and increased market share.
Customers put greater trust in brand-generated content because companies have complete information with regard to the brand, while customers’ knowledge of the brand is limited [71]. The challenge for companies therefore is to be honest when communicating their brand identities by presenting balanced and reliable information. This is important in order to defy the claim that companies tend to manipulate information by highlighting the positive aspects of their brands while concealing their flaws, in order to attract more customers and boost sales [72,73].
In line with the above discussion, it becomes clear that the relationship between customers and brands is bounded by customers’ perceived trust of the brand community page. Thus, based on the above theoretical arguments, the present study infers that customers’ level of perceived trust in Facebook community pages influences their intentions to forward online CGC. In this sense, the following hypothesis is put forward:
Hypothesis 3. (H3).
Customers’ level of perceived trust of the Facebook community page positively influences their intention to forward online company-generated contents (CGC).

2.5.2. Online Brand Community Engagement

Muniz and O’guinn [74] describe brand communities (BC) as “specialized, non-geographically bound communities”. Unlike traditional communities, the members of a BC share the same interests, values, social relationships, and their common appreciation for a brand. Trusov et al. [75] indicated that OBCs usually become the most popular, powerful, and leading marketing tools with regard to social media networks, since OBCs members can easily invite members of the social network to the online brand community.
In this sense, online brand communities OBCs have been built and created to form strong relationships between customers [76]. Also, online brand communities serve as new channels for customers to interact with other community members and brands [77]. In addition, Brodie et al. [37] posits that customers build the relationships with the brands. Therefore, studying customer engagement behaviors, relationships, and interactions with regard to the brand is central to building successful brand relationships and interactions. This finding was corroborated by Brodie et al. [37] who reported the need to understand customers’ relationship and engagement with brands.
In this sense, Hollebeek [39] reported that customer engagement with brands is affected by cognitive, affective and behavioral dimensions. The study also revealed that customers’ interactions with the brand are considered as a complementary part of the consumer-brand engagement. On the other hand, Shao and Ross [78] indicated that entertainment and need for information are also important factors impacting customer commitment and engagement with regard to brand communities. In addition, a great level of interaction results in an improved intention to purchase and consume [79]. The social interaction of customers within social media networks and online communities depends on the value that they provide [80]. In this sense, companies have a marked interest in engaging customers on social media platforms to influence them not only to purchase their products or services, but also to mediate their intentions and fostering their intention to forward online CGC. Therefore, it can be hypothesized that the intensity of online BCE will have a proportional impact on customers’ intention to forward CGC. Thus, based on the above theoretical arguments, the present study infers that customers’ levels of BCE influences their intention to forward online CGC in the context of online Islamic banking. In this light, the following hypothesis is put forward:
Hypothesis 4. (H4).
The customer’s level of brand community engagement positively influences the customer’s intention to forward online CGC.

3. Materials and Methods

3.1. Data Collection and Sample Design

The specific criteria used to select the participants for this study dictate that respondents should have at least one registered Islamic bank account and a Facebook account, and should have joined the Facebook page of the Islamic bank brand in which the brand’s customers participate. A total of 387 questionnaires were randomly distributed via email and through the Facebook fan pages of each Islamic bank, the survey was distributed among the members of the Islamic banking brand communities in March and April in 2018.
A total of 400 questionnaires were retrieved, 387 were deemed to be valid responses, which amount to a 97% response rate. Out of the 400 received responses, 13 responses were found to be unusable for data analysis based on incomplete information. The questionnaire was prepared in English, and was translated into Arabic by professional translators to ensure uniformity and consistency. To ensure the quality of the questionnaire items, a pilot test involving 35 university professors was conducted using the same data collection instruments and procedures. Furthermore, experts in the Islamic banking sector, brand management and brand experiences were also asked to review the items of the questionnaire to ensure the consistency of each item. The questionnaire was developed to address all variables in the study (personal data, independent variables, moderating variables and dependent variables), which were measured using a 7-point Likert scale.
The survey questionnaire is organized in three sections. The first section includes various assessment questions to confirm the subject’s interest and consistency. The second section groups the items in order to organize the proposed study. The third section contains users’ sociodemographic information and other miscellaneous information in order to analyze the participants’ profiles, classification, and the relevant variables.

3.2. Measurements

The survey used for data collection includes the adaptation of some of the most recognized scales in the scientific literature. In order to check understanding and absence of error in these scales, (1) qualitative personal interviews and quantitative tests were carried out amongst professional bankers in order to guarantee the validity of the terms used, and (2) a pilot test with a sample of 35 questionnaires was tested on university professors to validate measuring elements. A back-to-back translation system was used for the validation of the scales, while keeping the original meaning. Specifically, this study adapted the Brand Experience scales used by Brakus et al. [20]. Perceived Trust of Facebook Community Page was adapted from Morgan and Hunt [81] and Kim et al. [82]. BCE was adapted from Algesheimer et al. [44]. Intention to forward online CGC was adapted from Davis [83] (see Appendix A). Furthermore, the questionnaire contained a series of questions regarding the demographic characteristics or behavior of users (e.g. gender, educational qualifications, family status, age, employment status, place of residence and standard of living, experience using electronic banking and mobile banking, etc.). Table 1 summarizes the main characteristics of the sample.

4. Data Analysis and Results

4.1. Reliability and Validity

Cronbach’s α indicator was first used to measure the reliability of the scales, with 0.7 used as the reference value [84]. All the variables obtained rather good values (α > 0.8). To test the convergent and divergent validity of the scales, a confirmatory factor analysis was performed. This procedure also deleted the items that contributed least to the explanatory power of the model (R2 > 0.5). Convergent validity was evaluated by means of the factor loadings of the indicators. The coefficients were significantly different from zero, and the loadings between latent and observed variables were high in all cases (β > 0.7). Consequently, the present study posits that the latent variables adequately explain the observed variables [85].
With regard to discriminant validity, the variances were found to be significantly different from zero. Moreover, the correlation between each pair of scales did not exceed 0.8. Given the weak relationship among the constructs, this research confirms the existence of five different constructs in each of the three models proposed.
The reliability of the scales can be evaluated again from a series of indicators drawn from the confirmatory analysis. The standard compound reliability and the average variance explained exceeded the threshold used as a reference at 0.7 and 0.5, respectively, as well as other indicators of overall fit for the measurement model [85]. Table 2 shows the main indicators of the scale validation process.

4.2. Structural Equation Model

After analyzing the reliability and validity of the initial measurement scales, the research hypotheses in the literature review were tested through a structural equation model (SEM). Considering the absence of normality of the variables, this study opted for the maximum likelihood estimation method and bootstrapping technique (or bootstrap learning samples) for 500 consecutive steps or samples, and a significance level of 95 percent. The maximum likelihood is preferable in the case of small samples, as opposed to generalized or weighted least squares [86]. In the bootstrapping technique, this research approached the Bollen-Stine’s corrected p-value, testing the null hypothesis that the model is correct. Through re-sampling, this technique permits the standard error of the constructs to be corrected.
The values of the proposed model are consistent with the values established in the literature [85]: RMSEA < 0.08 GFI > 0.90, CFI and NFI > 0.90 (see Table 3).

4.3. Hypothesis Testing

To evaluate the structural model, the statistical significance of the structural loads of the different proposed relationships was analyzed.
The results of the SEM analysis and the hypotheses testing are shown in Table 4 and Figure 2. In this research study, all the relationships hypothesized were found to be significant. H1, which proposed a positive relationship between brand experience and perceived Trust of Facebook page, was confirmed (β = 0.768; p-value < 0.001, indicating that brand experience stimulates strong trust of the Facebook page in an Islamic online banking context. H2, which proposed a positive relationship between brand experience and brand community engagement, was confirmed (β = 0.900; p-value < 0.001); this means that brand experience stimulates strong brand community engagement in an Islamic online banking context. H3, which proposed a positive relationship between perceived trust of the Facebook page and intention to forward CGC, was confirmed (β = 0.150; p-value < 0.001); this means perceived trust of the Facebook page plays an important role in affecting the customers’ intentions to forward CGC. H4, which proposed a positive relationship between brand community engagement and intention to forward CGC was confirmed (β = 0.793; p-value < 0.001). This means that the online brand community engagement has a positive influence on customers’ intentions to forward CGC.
Lastly, the mediation effect was assessed through Sobel’s [87] test and a nonparametric bootstrapping procedure [88], yielding the coefficients and the standard errors of each path for the Sobel test (see Table 5). Results from the Sobel test suggest the mediating effect of perceived trust of the Facebook community page and brand community engagement between brand experience and intention to forward online CGC.

5. Discussion and Conclusions

The main objective of this study was to examine the type of relationship that exists between the brand experience and the online BCE, and their behavioral outcomes in the online Islamic banking context. Results of the study indicate that the BE affects perceived Trust of Facebook page and online BCE and consumer behavioral outcomes, namely, intention to forward CGC.
The findings of this study contribute to the existing body of literature by providing a clear understanding of BE and its influence on the online BCE, perceived Trust of Facebook page, and intention to forward CGC in online Islamic banking research. From a theoretical viewpoint, this study extends the existing explanations of the BE and its effects on the online BCE. Moreover, Brakus et al. [20] argued that the BE has a direct and indirect effect on customers’ behaviors. Therefore, it can be taken as an important step forward in directing theories related to BE effects, and the combined effects of linking BE to consumer behavioral outcomes that, until date, have received minimal attention in the Palestinian Islamic banking context. The proposed framework suggests that the BE with an online BCE provides positive engagement, interactions, and brand intentions to customers. On the other hand, several studies on consumer-brand engagement approached BE as a consequence of consumer-brand engagement [39,40,41]. However, this study allows us to integrate the idea of viewing BCE as a consequence of BE. Importantly, this framework will serve as a platform for academics that are interested in studying the relationships between the concepts of the “experience” and “engagement”. The empirical investigation about the influence of BE on BCE and perceived trust is a significant contribution to the marketing literature. An understanding of the mediation effect of BCE offers valuable insights into BCE literature. More importantly, this study extends the previous work on the BE and BCE relationship by providing empirical evidence of the prior explanation in the banking sectors [89]. The results of this study reveal the importance of BE in creating a unique BCE in an online setting, in addition to the intention of consumers’ behaviors to forward the online company-generated contents. The result of this study also agreed with the previous research that indicated the important roles of social media platforms in increasing customer participation, interactions, customer experience, trust, brand image, positive word of mouth, and information sharing [1]. The theories of social interaction and social influence also indicated that social media is the most important marketing tool for marketers and decision makers to enhance interactive communication, consumer interaction, and engagement at lower cost in a short time [1]. On the other hand, previous studies revealed that customer engagement is more than just interactions and participation and is related to the relationship and engagement with objects such as a brand [43,90] approached customers’ behaviors in social media platforms beyond purchases. These results are in line with this study proving that customers’ engagement within the social media is more than interaction and participation, in fact it depends on the interaction with the brand following previous experiences with regard to that particular brand. Helm [29] indicated that online brand experience is an important factor to improve the quality of customers’ experience while building relationships with the customers who are consuming the brands. Therefore, this study will add new insights to BE as an antecedent to online BCE literature and the impact on intention to forward online CGC. In addition, this study assesses the interaction and participation level within the context of social media.

5.1. Practical Implications

The findings of this research provide a number of practical implications for managers in the Islamic banking industry. Results from this research confirm the positive influences of BE on intentions to forward CGC, which are mediated by the BCE. This conclusion suggests that managers should focus on engaging customers with the bank brand in an online environment, especially through the Facebook social network as a social media tool, in light of the fact that the majority of Palestinians use Facebook as their main social media tool. Empirical results indicate BE has an indirect influence on the intention to forward CGC. This important finding suggests that positive BE would increase the level of customers’ engagement with the brand community, and consequently enable banks to enhance the level of customer intention to forward CGC. Furthermore, it will aid bank managers and decision makers in improving business performance by tracking the behaviors that motivate customers through social media. The findings of this study also provide valuable guidelines for the Islamic bank managers to give proper attention to the bank’s Facebook page and the website as an important tool which can engage customers with the bank’s brand [90]. Managers should formulate their marketing strategy in order to increase the BE for customers with the bank’s brand that will ultimately motivate and help engage customers with the brand through social media, thereby increasing customers’ intention to forward online CGC. With this finding, one can argue that customer experience with regard to the brand of a bank improves customers’ intention to forward online CGC, indirectly via the BCE. Thus, it promotes the concept of the BCE as a tool which is more effective for bank managers.

5.2. Limitations and Avenues for Future Research

As with any study, some limitations need to be acknowledged. First, the characteristics of the sample limits the findings of the study from being generalized due to the fact that (1) data were gathered from customers of financial entities operating specifically in the geographical area of the Middle East, and (2) data were collected via a specific social network (Facebook). Thus, future research is needed to test the proposed model in other geographical areas and through other social networks. Second, this research was carried out within the financial sector; in this sense researchers are encouraged to conduct further studies across other industries in order to expand the scope and the domain of the proposed model in this study. Lastly, further studies need to be conducted to test the relationships in banking services through cross-cultural research comparing Islamic and non-Islamic customers, by using different social media (e.g. Twitter) to analyze, compare, and obtain a better understanding from the findings.

Author Contributions

The authors contributed equally to this work.

Funding

This research was funded by the Spanish Ministry of Science, Innovation and Universities, National R&D&I Plan and FEDER grant number B-SEJ-209-UGR18.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Brand Experience
The brand of Islamic banks induces feelings and sentiments (BEA1).
I have strong emotions for the brand of Islamic banks (BEA2).
The brand of Islamic banks is an emotional brand (BEA3).
I engage in special behaviors when I see the brand of Islamic banks (BEE1).
The brand of Islamic banks results in bodily experiences (BEE2).
The brand of Islamic banks is an action oriented (BEE3).
I engage in a lot of thinking when I encounter the brand of Islamic banks (BEI1).
The brand of Islamic banks makes me think (BEI2).
The brand of Islamic banks stimulates my curiosity and problem solving (BEI3).
The brand of Islamic banks makes a strong impression on my visual sense or other senses (BES1).
I find he brand of Islamic banks interesting in a sensory way (BES2).
The brand of Islamic banks appeal to my senses (BES3).
Brand community engagement
I benefit from the following of the Islamic banks brand community’s rules (BCE1).
I am motivated to participate in the Islamic banks brand community’s activities because I feel better afterwards (BCE2).
I am motivated to participate in the Islamic banks brand community’s activities because I am able to support other members (BCE3).
I am motivated to participate in the Islamic banks brand community’s activities because I am able to reach personal goals (BCE4).
Perceived trust
Communicating with Islamic banks brand community member to forward information has imparity (PTF1).
Communicating with Islamic banks brand community member to forward information is reliable (PTF2).
Communicating with Islamic banks brand community member to forward information will be trustworthy (PTF3).
I trust the quality of information forwarded by Islamic banks brand community member (PTF4).
Intention to forward online company-generated contents
It is probable that I will continue to forward the online content generated by the Islamic banks (IFCGC1).
I intend to begin or continue to forward the online content generated by the Islamic banks (IFCGC2).
I will frequently to forward the online content generated by the Islamic Banks in the future (IFCGC3).
I will recommend others to forward the online content generated by Islamic banks (IFCGC4).

References

  1. Naeem, M. Role of social networking platforms as tool for enhancing the service quality and purchase intention of customers in Islamic country. J. Islamic Mark. 2019. [Google Scholar] [CrossRef]
  2. Aslam, U.; Muqadas, F.; Imran, M.K. Exploring the sources and role of knowledge sharing to overcome the challenges of organizational change implementation. Int. J. Organ. Anal. 2018, 26, 567–581. [Google Scholar] [CrossRef]
  3. Aslam, U.; Muqadas, F.; Imran, M.K.; Saboor, A. Emerging organizational parameters and their roles in implementation of organizational change. J. Organ. Chang. Manag. 2018, 31, 1084–1104. [Google Scholar] [CrossRef]
  4. Kim, J.; Ko, E. Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. J. Bus. Res. 2012, 65, 1480–1486. [Google Scholar] [CrossRef]
  5. Akar, E.; Topçu, B. An examination of the factors influencing consumers’ attitudes toward social media marketing. J. Internet Commer. 2011, 10, 35–67. [Google Scholar] [CrossRef]
  6. Scott, D.M. The New Rules of Marketing and PR: How to Use Social Media, Online Video, Mobile Applications, Blogs, News Releases, and Viral Marketing to Reach Buyers Directly; John Wiley and Sons: Noboken, NY, USA, 2015. [Google Scholar]
  7. Valos, M.J.; Habibi, F.H.; Casidy, R.; Driesener, C.B.; Maplestone, V.L. Exploring the integration of social media within integrated marketing communication frameworks: Perspectives of services marketers. Mark. Intell. Plan. 2016, 34, 19–40. [Google Scholar] [CrossRef]
  8. Garg, R.; Rahman, Z.; Qureshi, M.N. Measuring customer experience in banks: Scale development and validation. J. Model. Manag. 2014, 9, 87–117. [Google Scholar] [CrossRef]
  9. Meyer, C.; Schwager, A. Understanding customer experience. Harv. Bus. Rev. 2007, 85, 116. [Google Scholar] [PubMed]
  10. Zeithmal, V.A.; Bitner, M.J.; Gremler, D.D.; Pandit, A. Service Marketing, 5th ed.; Tata Mc Graw Hill Education Pvt Ltd.: New Delhi, India, 2011. [Google Scholar]
  11. Gentile, C.; Spiller, N.; Noci, G. How to sustain the customer experience: An overview of experience components that co-create value with the customer. Eur. Manag. J. 2007, 25, 395–410. [Google Scholar] [CrossRef]
  12. Al-Salem, F. The size and scope of the Islamic finance industry: An analysis. Int. J. Manag. 2008, 25, 124. [Google Scholar]
  13. Khan, M.S.; Mirakhor, A. Islamic Banking: Experiences in the Islamic Republic of Iran and Pakistan; IMF Working Paper No. WP/89/12; International Monetary Fund: Washington, DC, USA, 1989. [Google Scholar]
  14. Iqbal, Z. Islamic financial systems. Financ. Dev. 1997, 43, 42–45. [Google Scholar]
  15. Kpodar, K.; Imam, P.A. Islamic Banking: How Has It Diffused; IMF: Washington, DC, USA, 2010; pp. 1–29. [Google Scholar]
  16. Husain, I. Islamic finance: Growth and poverty alleviation. In Proceedings of the 3rd Annual International Conference on Islamic Banking, Karachi, Pakistan, 11 September 2007. [Google Scholar]
  17. Kwak, H.; Lee, C.; Park, H.; Moon, S. What is Twitter, a social network or a news media. In Proceedings of the 19th international conference on World Wide Web, New York, NY, USA, 26–30 April 2010. [Google Scholar]
  18. Holbrook, M.B.; Hirschman, E.C. The experiential aspects of consumption: Consumer fantasies, feelings, and fun. J. Consum. Res. 1982, 9, 132–140. [Google Scholar] [CrossRef]
  19. Ambler, T.; Bhattacharya, C.B.; Edell, J.; Keller, K.L.; Lemon, K.N.; Mittal, V. Relating brand and customer perspectives on marketing management. J. Serv. Res. 2002, 5, 13–25. [Google Scholar] [CrossRef]
  20. Brakus, J.J.; Schmitt, B.H.; Zarantonello, L. Brand experience: What is it? How is it measured? Does it affect loyalty? J. Mark. 2009, 73, 52–68. [Google Scholar] [CrossRef]
  21. Nysveen, H.; Pedersen, P.E.; Skard, S. Brand experiences in service organizations: Exploring the individual effects of brand experience dimensions. J. Brand Manag. 2013, 20, 404–423. [Google Scholar] [CrossRef]
  22. Chase, R.B.; Dasu, S. Experience psychology—A proposed new subfield of service management. J. Serv. Manag. 2014, 25, 574–577. [Google Scholar] [CrossRef]
  23. Same, S. Experience marketing in country branding: Theoretical developments and an Estonian case study. Res. Econ. Bus. Cent. East. Eur. 2014, 6, 65–88. [Google Scholar]
  24. Schmitt, B. The concept of brand experience. J. Brand Manag. 2009, 16, 417–419. [Google Scholar] [CrossRef] [Green Version]
  25. Cheng, E.; Khan, N. Game of Trust: Brand-Generated Content vs Consumer-Generated Advertising: A Qualitative Study of Arla Foods; Uppsala University: Uppsala, Sweden, 2017. [Google Scholar]
  26. Ha, H.Y.; Perks, H. Effects of consumer perceptions of brand experience on the web: Brand familiarity, satisfaction and brand trust: An International Research Review. J. Consum. Behav. 2005, 4, 438–452. [Google Scholar] [CrossRef]
  27. Lee, S.A.; Jeong, M. Enhancing online brand experiences: An application of congruity theory. Int. J. Hosp. Manag. 2014, 40, 49–58. [Google Scholar] [CrossRef]
  28. Vivek, S.D.; Beatty, S.E.; Morgan, R.M. Customer engagement: Exploring customer relationships beyond purchase. J. Mark. Theory Pract. 2012, 20, 122–146. [Google Scholar] [CrossRef]
  29. Helm, C. From tech-led to brand-led—Has the internet portal business grown up? J. Brand Manag. 2007, 14, 368–379. [Google Scholar] [CrossRef]
  30. Garg, R.; Rahman, Z.; Qureshi, M.N.; Kumar, L. Identifying and ranking critical success factors of customer experience in banks: An analytic hierarchy process (AHP) approach. J. Model. Manag. 2012, 7, 201–220. [Google Scholar] [CrossRef]
  31. Chahal, H.; Dutta, K. Measurement and impact of customer experience in banking sector. Decision 2015, 42, 57–70. [Google Scholar] [CrossRef]
  32. Phan, K.N.; Ghantous, N. Managing brand associations to drive customers’ trust and loyalty in Vietnamese banking. Int. J. Bank Mark. 2013, 31, 456–480. [Google Scholar] [CrossRef]
  33. Khan, I.; Rahman, Z.; Fatma, M. The concept of online corporate brand experience: An empirical assessment. Mark. Intell. Plan. 2016, 34, 711–730. [Google Scholar] [CrossRef]
  34. Hamzah, Z.L.; Alwi, S.F.S.; Othman, M.N. Designing corporate brand experience in an online context: A qualitative insight. J. Bus. Res. 2014, 67, 2299–2310. [Google Scholar] [CrossRef]
  35. Malthouse, C.; Haenlein, M.; Skiera, B.; Wege, E. Managing customer relationships in the social media era: Introducing the social CRM house. J. Interact. Mark. 2013, 274, 270–280. [Google Scholar] [CrossRef]
  36. Bijmolt, T.H.; Leeflang, P.S.; Block, F.; Eisenbeiss, M.; Hardie, B.G.; Lemmens, A.; Saffert, P. Analytics for customer engagement. J. Serv. Res. 2010, 13, 341–356. [Google Scholar] [CrossRef]
  37. Brodie, R.J.; Hollebeek, L.D.; Juric, B.; Ilic, A. Customer engagement: Conceptual domain, fundamental propositions, and implications for research. J. Serv. Res. 2011, 14, 252–271. [Google Scholar] [CrossRef]
  38. Brodie, R.J.; Ilic, A.; Juric, B.; Hollebeek, L. Consumer engagement in a virtual brand community: An exploratory analysis. J. Bus. Res. 2013, 66, 105–114. [Google Scholar] [CrossRef]
  39. Hollebeek, L. Exploring customer brand engagement: Definition and themes. J. Strateg. Mark. 2011, 19, 555–573. [Google Scholar] [CrossRef]
  40. Hollebeek, L. Demystifying customer brand engagement: Exploring the loyalty nexus. J. Mark. Manag. 2011, 27, 785–807. [Google Scholar] [CrossRef]
  41. Hollebeek, L.; Glynn, M.; Brodie, R. Consumer brand engagement in social media: Conceptualization, scale development and validation. J. Interact. Mark. 2014, 28, 49–165. [Google Scholar] [CrossRef]
  42. Van Doorn, J.; Lemon, K.; Mittal, V.; Nass, S.; Pick, D.; Pirner, P.; Verhoef, P. Customer engagement behavior: Theoretical foundations and research directions. J. Serv. Res. 2010, 13, 253–266. [Google Scholar] [CrossRef]
  43. Dolan, R.; Conduit, J.; Fahy, J.; Goodman, S. Social media engagement behaviour: A uses and gratifications perspective. J. Strateg. Mark. 2016, 24, 261–277. [Google Scholar] [CrossRef]
  44. Algesheimer, R.; Dholakia, U.M.; Herrmann, A. The social influence of brand community: Evidence from European car clubs. J. Mark. 2005, 69, 19–34. [Google Scholar] [CrossRef]
  45. McAlexander, J.H.; Schouten, J.W.; Koenig, H.F. Building brand community. J. Mark. 2002, 66, 38–54. [Google Scholar] [CrossRef]
  46. Sprott, D.; Czellar, S.; Spangenberg, E. The importance of a general measure of brand engagement on market behavior: Development and validation of a scale. J. Mark. Res. 2009, 46, 92–104. [Google Scholar] [CrossRef]
  47. Chang, A.; Hsieh, S.H.; Tseng, T.H. Online brand community response to negative brand events: The role of group eWOM. Internet Res. 2013, 23, 486–506. [Google Scholar] [CrossRef]
  48. Calder, J.; Malthouse, E.C.; Schaedel, U. An experimental study of the relationship between online engagement and advertising effectiveness. J. Interact. Mark. 2009, 23, 321–331. [Google Scholar] [CrossRef]
  49. Baldus, J.; Voorhees, C.; Calantone, R. Online brand community engagement: Scale development and validation. J. Bus. Res. 2015, 68, 978–985. [Google Scholar] [CrossRef]
  50. Wang, Y.; Yu, Q.; Fesenmaier, D.R. Defining the virtual tourist community: Implications for tourism marketing. Tour. Manag. 2002, 23, 407–417. [Google Scholar] [CrossRef]
  51. Madupu, V. Online Brand Community Participation: Antecedents and Consequences; The University of Memphis: Memphis, TN, USA, 2006. [Google Scholar]
  52. Wang, Y.; Fesenmaier, D.R. Modeling participation in an online travel community. J. Travel Res. 2004, 42, 261–270. [Google Scholar] [CrossRef]
  53. Dholakia, U.M.; Bagozzi, R.P.; Pearo, L.K. A social influence model of consumer participation in network- and small-group-based virtual communities. Int. J. Res. Mark. 2004, 21, 241–263. [Google Scholar] [CrossRef]
  54. Gong, T. Customer brand engagement behavior in online brand communities. J. Serv. Mark. 2018, 23, 286–299. [Google Scholar] [CrossRef]
  55. Cvijikj, P.; Michahelles, F. Online engagement factors on Facebook brand pages. Soc. Netw. Anal. Min. 2013, 3, 843–861. [Google Scholar] [CrossRef]
  56. Nambisan, S.; Baron, R.A. Interactions in virtual customer environments: Implications for product support and customer relationship management. J. Interact. Mark. 2007, 21, 42–62. [Google Scholar] [CrossRef]
  57. Tsai, H.T.; Huang, H.C.; Chiu, Y.L. Brand community participation in Taiwan: Examining the roles of individual-, group-, and relationship-level antecedents. J. Bus. Res. 2012, 65, 676–684. [Google Scholar] [CrossRef]
  58. Eisenbeiss, M.; Blechschmidt, B.; Backhaus, K.; Freund, P.A. The (real) world is not enough: Motivational drivers and user behavior in virtual worlds. J. Interact. Mark. 2012, 26, 4–20. [Google Scholar] [CrossRef]
  59. Bowden, J.L.H. The process of customer engagement: A conceptual framework. J. Mark. Theory Pract. 2009, 17, 63–74. [Google Scholar] [CrossRef]
  60. De Vries, N.J.; Carlson, J. Examining the drivers and brand performance implications of customer engagement with brands in the social media environment. J. Brand Manag. 2014, 21, 495–515. [Google Scholar] [CrossRef]
  61. Gambetti, R.; Graffigna, G. The concept of engagement: A systematic analysis of the ongoing marketing debate. Int. J. Mark. Res. 2010, 52, 801–826. [Google Scholar] [CrossRef]
  62. American Bankers Association. The State of Social Media in Banking; American Bankers Association: Washington, DC, USA, 2017. [Google Scholar]
  63. Macknight, J. Banks-Say-Social-Media-is-Important-But-How-Many. 2017. Available online: https://www.thebanker.com/.../Banks-say-social-media-is-important-but-how-many- (accessed on 15 May 2018).
  64. Ray, A. Four Studies on the Adoption of Social Media by Financial Advisors and Investors. 2013. Available online: https://www.socialmediatoday.com/.../four-studies-adoption-social-media-financial-ad (accessed on 22 May 2018).
  65. Watts, D.J.; Peretti, J.; Frumin, M. Viral Marketing for the Real World; Harvard Business School Publishing: Brighton, MA, USA, 2007. [Google Scholar]
  66. Weman, E. Consumer Motivations to Join a Brand Community on Facebook; Hanken School of Economics: Helsinki, Finland, 2011. [Google Scholar]
  67. Taylor, D.G.; Strutton, D.; Thompson, K. Self-enhancement as a mmotivation for sharing online advertising. J. Interact. Advert. 2012, 12, 213–228. [Google Scholar] [CrossRef]
  68. TRW Consultant, Why Your Social Media is Not Working, Nairland Forum. 2016. Available online: www.nairaland.com/2862827/why-social-media-not-working (accessed on 17 June 2018).
  69. Tang, J.; Liu, H. Trust in Social Media; Morgan & Claypool Publishers: San Rafael, CA, USA, 2015. [Google Scholar]
  70. Akkucuk, U.; Turan, C. Mobile use and online preferences of the millenials: A study in Yalova. J. Internet Bank. Commer. 2016, 21, 1–11. [Google Scholar]
  71. Kivetz, R.; Simonson, I. The effects of incomplete information on consumer choice. J. Mark. Res. 2000, 37, 427–448. [Google Scholar] [CrossRef]
  72. Choi, B.; Lee, I. Trust in open versus closed social media: The relative influence of user- and marketer-generated content in social network services on customer trust. Telemat. Inform. 2017, 34, 550–559. [Google Scholar] [CrossRef]
  73. Goh, K.-Y.; Heng, C.-S.; Lin, Z. Social media brand community and consumer behavior: Quantifying the relative impact of user- and marketer-generated content. Inf. Syst. Res. 2013, 24, 88–107. [Google Scholar] [CrossRef]
  74. Muniz, M.; O’guinn, T.C. Brand community. J. Consum. Res. 2001, 27, 412–432. [Google Scholar] [CrossRef]
  75. Trusov, M.; Bucklin, R.E.; Pauwels, K. Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site. J. Mark. 2009, 73, 90–102. [Google Scholar] [CrossRef]
  76. Habibi, M.R.; Laroche, M.; Richard, M.O. Brand communities based in social media: How unique are they? Evidence from two exemplary brand communities. Int. J. Inf. Manag. 2014, 34, 123–132. [Google Scholar] [CrossRef]
  77. Blazevic, V.; Wiertz, C.; Cotte, J.; de Ruyter, K.; Keeling, D.I. GOSIP in cyberspace: Conceptualization and scale development for general online social interaction propensity. J. Interact. Mark. 2014, 28, 87–100. [Google Scholar] [CrossRef]
  78. Shao, W.; Jones, R.G.; Grace, D. Brandscapes: Contrasting corporate-generated versus consumer-generated media in the creation of brand meaning. Mark. Intell. Plan. 2015, 33, 414–443. [Google Scholar] [CrossRef]
  79. Phang, C.W.; Zhang, C.; Sutanto, J. The influence of user interaction and participation in social media on the consumption intention of niche products. Inf. Manag. 2013, 50, 661–672. [Google Scholar] [CrossRef]
  80. Hajli, M.; Hajli, M. Organisational development in sport: Co-creation of value through social capital. Ind. Commer. Train. 2013, 45, 283–288. [Google Scholar] [CrossRef]
  81. Morgan, R.M.; Hunt, S.D. The commitment-trust theory of relationship marketing. J. Mark. 1994, 58, 20–38. [Google Scholar] [CrossRef]
  82. Kim, M.; Chung, N.; Lee, C. The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea. Tour. Manag. 2011, 32, 256–265. [Google Scholar] [CrossRef]
  83. Davis, D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
  84. Nunnally, J.C. Psychometric Theory, 2nd ed.; McGraw-Hill: New York, NY, USA, 1978. [Google Scholar]
  85. Hair, J.; Anderson, R.; Tatham, R.; William, C. Multivariate Data Analysis with Readings; Prentice-Hall, Inc.: Upper Saddle River, NJ, USA, 1995. [Google Scholar]
  86. West, S.G.; Finch, J.F.; Curran, P.J. Structural Equation Models with Nonnormal Variables: Problems and Remedies; Sage publications Inc.: Thousand Oaks, CA, USA, 1995. [Google Scholar]
  87. Sobel, M.E. Asymptotic confidence intervals for indirect effects in structural equation models. Sociol. Methodol. 1982, 13, 290–312. [Google Scholar] [CrossRef]
  88. Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef]
  89. Khan, M.N.; Aabdean, Z.; Salman, M.; Nadeem, B. The impact of product and service quality on brand loyalty: Evidence from quick service restaurants. Am. J. Mark. Res. 2016, 2, 84–94. [Google Scholar]
  90. Sekhon, H.; Yap, K.B.; Wong, D.H.; Loh, C.; Bak, R. Offline and online banking—Where to draw the line when building trust in e-banking? Int. J. Bank Mark. 2010, 28, 27–46. [Google Scholar]
Figure 1. Conceptual model that summarizes the research hypotheses.
Figure 1. Conceptual model that summarizes the research hypotheses.
Sustainability 11 04649 g001
Figure 2. Results of the structural model analysis.
Figure 2. Results of the structural model analysis.
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Table 1. Descriptive statistics of participant characteristics.
Table 1. Descriptive statistics of participant characteristics.
ItemFrequencyPercentage (%)
Gender
Male24864.1
Female13935.9
Marital Status
Married25866.7
Unmarried12933.3
Education level
High school164.1
Professional training9123.5
Diploma (2 years)4411.4
1st university degree (4 years)12131.3
Post-graduate studies11529.7
Age
Under 1892.3
18–258622.2
26–306216.0
31–358923.0
36–406617.1
41–45246.2
46–50164.1
51–55338.5
56–6020.5
61–6500
Over 65 00
Activity
Unemployed4912.7
Student14136.4
Retired11028.4
Employed 8722.5
Monthly income (US$)
Less than 500112.8
500–89913334.4
900–1299112.8
1300 and above23259.9
Facebook profile
Yes387100.0
No00.0
Comment on FB
Yes387100.0
No00.0
Comments for the bank page on the social media
Yes387100.0
No00.0
Experience in FB
Same or Less than 1 years82.1
Between 2 and 3 years6015.5
Between 3 and 5 years14537.5
More than 5 years17445.0
Bank Name
Arab Islamic Bank15640.3
Palestine Islamic Bank12732.8
Safa Bank10426.9
Table 2. Convergent validity and internal consistency reliability.
Table 2. Convergent validity and internal consistency reliability.
VariableItemStandard CoefficientCronbach’s AlphaCRAVE
BE (Affective)BEA10.8240.9040.9060.762
BEA20.897
BEA30.896
BE (Behavioral)BEE10.8910.8840.8900.731
BEE20.899
BEE30.769
BE (Intellectual)BEI10.8430.8780.8790.707
BEI20.857
BEI30.823
BE (Sensory)BES10.8740.8900.8900.730
BES20.844
BES30.844
BCEBCE10.8380.8780.8880.666
BCE20.789
BCE30.806
BCE40.830
PTFPTF10.8170.9210.9230.749
PTF20.884
PTF30.901
PTF40.858
IFCGCIFCGC10.8430.9120.9130.724
IFCGC20.882
IFCGC30.832
IFCGC40.846
Table 3. Goodness-of-fit indicators in the structural model.
Table 3. Goodness-of-fit indicators in the structural model.
Fit IndicesRecommended ValueValue in the Model
CMIN/DF2 < CMIN/DF < 53.208
GFI>0.900.890
RFI>0.900.903
NFI>0.900.915
CFI>0.900.939
TLI>0.900.931
IFI>0.900.940
RMSEA<0.080.076
* Notes: CMIN/DF—normal chi-square/degrees of freedom; GFI—goodness-of-fit index; RFI—relative fix index; NFI—normed fit index; CFI—comparative goodness of fit; TLI—Tucker-Lewis Index; IFI—incremental fit index; RMSEA—root mean square error of approximation.
Table 4. Results of the hypotheses test.
Table 4. Results of the hypotheses test.
HypothesisEffectCoefficientsS.E.Sig.Support
H1BEPTF0.7680.051<0.001Yes
H2BEBCE0.9000.048<0.001Yes
H3PTFIFCGC0.1500.054<0.001Yes
H4BCEIFCGC0.7930.066<0.001Yes
Table 5. SOBEL test results.
Table 5. SOBEL test results.
Mediator (Path)CoefficientStandard ErrorSobel Testp-Value
BE→ PTF0.7680.0512.7310.006
PTF→ IFCGC0.1500.054
BE→ BCE0.9000.0482.8730.004
BCE→ IFCGC0.7930.066

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MDPI and ACS Style

Yasin, M.; Porcu, L.; Liébana-Cabanillas, F. The Effect of Brand Experience on Customers’ Engagement Behavior within the Context of Online Brand Communities: The Impact on Intention to Forward Online Company-Generated Content. Sustainability 2019, 11, 4649. https://doi.org/10.3390/su11174649

AMA Style

Yasin M, Porcu L, Liébana-Cabanillas F. The Effect of Brand Experience on Customers’ Engagement Behavior within the Context of Online Brand Communities: The Impact on Intention to Forward Online Company-Generated Content. Sustainability. 2019; 11(17):4649. https://doi.org/10.3390/su11174649

Chicago/Turabian Style

Yasin, Mahmoud, Lucia Porcu, and Francisco Liébana-Cabanillas. 2019. "The Effect of Brand Experience on Customers’ Engagement Behavior within the Context of Online Brand Communities: The Impact on Intention to Forward Online Company-Generated Content" Sustainability 11, no. 17: 4649. https://doi.org/10.3390/su11174649

APA Style

Yasin, M., Porcu, L., & Liébana-Cabanillas, F. (2019). The Effect of Brand Experience on Customers’ Engagement Behavior within the Context of Online Brand Communities: The Impact on Intention to Forward Online Company-Generated Content. Sustainability, 11(17), 4649. https://doi.org/10.3390/su11174649

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