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Article

No One Is Leaving This Time: Social Media Fashion Brand Communities

by
Albert Chukwunonso Diachi
1,*,
Ayşe Tansu
2 and
Oseyenbhin Sunday Osemeahon
1
1
Management Information Systems Department, School of Applied Sciences, Cyprus International University, Nicosia 99258, Turkey
2
Industrial Engineering Department, Faculty of Engineer, Cyprus International University, Nicosia 99258, Turkey
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(23), 12957; https://doi.org/10.3390/su132312957
Submission received: 9 September 2021 / Revised: 18 October 2021 / Accepted: 18 October 2021 / Published: 23 November 2021
(This article belongs to the Special Issue Social Media and Sustainability in the Digital Era)
Browse Figure
Review Reports Versions Notes

Abstract

:
In an attempt to enrich existing literature on online fashion brand communities in the digital era, this research aimed at exploring the relationship between peer influence and self-disclosure on sustaining consumer engagement in generating loyalty to social media fashion brand communities (SMFBCs). The survey included a sample of 365 members who follow local Nigerian SMFBCs and was analyzed using SmartPLS v3.2.9. Findings from the study show that peer influence and self-disclosure have a positive impact on sustaining consumer engagement in social media fashion brand communities. Furthermore, the findings show that self-disclosure mediated the relationship between peer influence and sustaining consumer engagement. Finally, consumer engagement fosters loyalty to social media brand communities.

1. Introduction

Over the years, social media has attained commendable relevance, as it has become a ubiquitous part of daily living [1]. It is estimated that over 65 million brands regard social media as a means of interacting with consumers and achieving their brand marketing objectives through social media brand communities [2]. Social media brand community (SMBC), an online brand community consisting of a brand and its admirers on a social media platform [3,4], is gaining more attention as a potential means in the digital era to involve consumers in online branding activities [1,5,6]. This community provides brands with the facilities to build brand awareness, have community involvement, obtain insight for better decision making, and engage in open and honest dialog [7].
With over 33.0 million employees [8], the fashion industry is among the biggest segments of the world economy, with an estimate of 3 trillion dollars, representing 2% of the global gross domestic product [8,9]. This industry is one of the prominent industries that have affected every aspect of social life, causing visible changes in social [10], economic [11], political [12], climate [12], and cultural landscapes [13]. The fashion industry has benefited from social media, as it has transformed the way fashion is presented, reported, and consumed [14]. Top fashion events such as the London Fashion Week recorded massive success in generating “clout” on their 2014 show in which they had over half a million mentions on social media [15]. In addition, fashion bloggers are given special invitations and front seats in Dolce & Gabbana fashion shows so as to enable them to upload real-time content of the show on social media [16].
The fashion industry is also among the industries that have integrated the SMBC concept into their business strategies [17,18]. This can be attributed to the ability of SMBCs to enable brands to direct offline activities [19] and online traffic to their online milieu [20] so they can effectively monitor consumers’ digital footprints and obtain more insight into customer journeys [21]. More importantly, SMBCs provide necessary tools in sustaining consumer engagement (SCE) that generates enhanced firm performance [22]. Although SMBCs are easy to create and consumers easy to recruit as community members, many brands face a lot of challenges in SCE in their communities [23].
Prior research considered consumer engagement (CE) as a vital indicator of brand marketing performance in the aspect of maintaining consumers’ loyalty to the community [24,25], which is essential for the sustenance of the community. Social cognitive theory upholds this view as it posits that engagement motivates a long-term relationship that secures the loyalty of consumers to an online community [26]. It costs less to maintain loyal consumers as they tend to give lesser consideration to alternatives [27,28,29]. The research by [30], showed that despite the rise in popularity of online communities, there have been just a few reports of success in enhancing engagement and retaining members of the community. This report is in sync with [31], asserting that the major challenge in sustaining any online brand community is sustaining engagement and [32] highlighting that the CE phenomenon is a vital academic research agenda that has picked up the interest of brands worldwide. It is important to have loyal SMBC members as many active online brand communities have transformed into “online ghost towns” due to the inability to retain their members [33]. Thus, investigating concepts of SCE in SMBCs, which subsequently enhances the community’s loyalty is a critical issue in understanding the sustainability of SMBCs especially in fashion brands as there is no report to date on how to retain members of fashion brand SMBCs (SMFBCs).
Other SMBC literature exhibited that CE in these communities leads to a profitable relationship between brands and consumers [4,34,35]. Some reported that the beneficial outcomes prompted CE to be enlisted amongst primacy research topics by the Marketing Science Institute in 2010 [36,37], alongside more authors calling for more insights into the dynamics of consumer engagement in online brand communities [5,32,38,39,40,41]. Despite the acceleration in the research of sustaining this concept in online brand communities, the context of SMBCs has so far been under-explored, and especially studies in the SMFBC domain are still sparse. This is an issue of concern especially for ignored African regions with emerging fashion markets such as Nigeria, ranked among the top five countries in the world experiencing the most growth in economic development, consumer spending [42], and a unique passion for keeping up with trends in the fashion business [43]. Authors have suggested the need for more research on SCE in the fashion context [44,45,46], with Maria et al. (2018) highlighting that it is of importance to have more understanding on the drivers that motivate fashion consumers to keep engaging in SMFBCs and the consequences of such engagement.
In this respect, existing literature has hardly considered the effect of peer influence on generating engagement in SMBCs or SMFBCs. This is surprising as peer influence has a renowned reputation of fostering behaviors in both online and offline settings [47,48,49], coupled with shaping attitudes of individuals in the fashion realm [50,51,52,53]. Peer influence applies when an individual’s attitude and behavior are influenced by other members of the peer group [54]. This influence can be studied using social influence theory, which shows how peers influence the behaviors of an individual in a social environment [55]. Sherman et al., 2016, highlighted peer influence as a major influencer of engagement behaviors on social media. An SMFBC consists of a fashion brand and its peer consumers, and the influence of peers is of importance to online brand marketers as it encourages self-disclosure behaviors in consumers [56], which is needed for a better understanding of target consumers [57]. Ref. [58], outlined that more is yet to be known on the dynamics of consumer peers on social media especially their self-disclosure behavior.
In an attempt to address the aforementioned concerns, the present research used social influence theory and social cognitive theory to enhance the current understanding of antecedents and outcomes of SCE in SMFBCs. More specifically, the study examined:
  • The impact of peer influence and self-disclosure as antecedents of SCE in SMFBCs;
  • The effect of SCE on loyalty to SMFBCs;
  • Self-disclosure as a mediator between peer influence and SCE in SMFBCs.

2. Literature Review

The concept of engagement is one that originated from a multidisciplinary theoretical perspective such as psychology, sociology, marketing, and information systems [59,60]. Various literature has provided diverse understanding of the engagement concept in relation to diverse contexts. However, it has led to a more general consensus that engagement is in three basic dimensions: cognitive, affective, and behavioral. Cognitive engagement deals with mental activities centered on something that involves attention and absorption. Affective engagement deals with the enjoyment and enthusiasm and as regards to an engagement object. Behavioral engagement comprises the active manifestations of engagement, which include sharing, learning, and endorsing behaviors [61].
Online engagement is a major factor in assessing the effectiveness of a social media platform [62]. Engagement in social media is a concept exhibited by both creating and posting content [63]. Ref. [64], showed engagement in SMFBCs as consumers’ interactions with each other in which they share interests or reveal their perceptions on content posted by anyone with the social plugins on the platform. Ref. [65], described engagement on social media as participation and communication methods that rely on remixed texts, collaborations, and posting on social media. Ref. [66], showed that engagement on social media is functional as it involves online users’ real-time interaction in the environment.
In relation to the online setting, sustaining engagement deals with constant or regular shares, comments, and the number of likes and clicks on a certain post [67,68,69,70]. SMFBC platforms have the facilities to enable members to send their comments, post reviews, share experiences, like posts and comments, and interact with other community members. In other words, SMFBC platforms enable interactivity that provides many engagement opportunities.

3. Theories and Hypothesis Development

The current study underlined two main theories, namely social influence theory (SIT) and social cognitive theory. Social influence theory (SIT) provides a well-established foundation for understanding the behaviors of individuals in a community [71]. It focuses on how an individual exhibits changes in behaviors, attitudes, and beliefs with the presence of others in the social network [72]. This type of influence can be informational and normative. Informational influence occurs when one accepts information received from another as evidence about reality, while normative influence occurs when one is influenced to conform to the expectations of a group [73]. Normative social influence is prevalent in communities or groups due to the desire to maintain harmony in the community or to gain positive evaluations from others [74]. This is the case of self-disclosure as it plays a dominating role in maintaining harmony in relationships and influencing engagement behaviors on social media [56,75]. This theory is expected to be prevalent in this study as peer influence is a type of social influence [76], which is expected to facilitate SMFBC members’ compliance to keep on engaging in community activities so as to achieve a favorable reaction from community members.
Persuading consumers to stay loyal to an SMFBC is a daunting challenge due to the intense competition and reduced financial implications [77]. SCT is a widely verified theory that explains the relationship existing between personal cognition, environmental influences, and behavioral outcomes [78]. SCT is of the view that people have a self-belief mindset that drives them to interact and also develop loyalty to an online community [79]. With SCT, consumers’ loyalty to an online community is a function of their cognitive judgment on their capabilities to keep engaging in the community activities [26], which was expected to be the case in this current study.

3.1. Peer Influence

People tend to be peers with individuals that have similar features or possibly operate in the same environment [80]. There is burgeoning evidence supporting that peers have a pervasive impact when it comes to engagement [81,82], with others affirming that individuals are influenced by their peers into undertaking certain actions [83,84]. This was likely to be the case in this context as SIT suggests that peers in a group can influence individuals to adopt an induced behavior (engagement) as the individuals seek to get a sense of approval from the group [85]. The role of peer influence has a great deal in online brand communities as consumers prefer sharing their brand-related experiences with other consumers [84]. Peer actions (such as feedback) toward a member’s online message play a vital role in sustaining continuous interactions [86]. Online communities that exhibit peer-like relationships tend to have more engagement as peer-like relationships have stronger interactions [87]. Thus, this study was of the view that:
Hypothesis 1 (H1).
Peer influence has a positive effect on SCE in SMFBCs.
An online brand community is a platform where one can affiliate with his or her peers. A vital aspect of affiliating with peers is self-disclosure [88]. People can read personal comments or posts shared by their peers and be motivated to respond in accordance with the message [58]. Self-disclosure is one of the interactive strategies that social media users adopt in interacting with their peers online [89]. Individuals are usually inspired to engage in behaviors supported by their peers [90], which is a process in SIT, so as not to be seen as being out of place [74]. The same goes for online brand communities as community members influence the behavioral intentions of other members by supporting them to express themselves [91,92]. The trust individuals have for their peers in an online community makes them disclose information about their personal experiences [4]. Therefore, this study was of the view that:
Hypothesis 2 (H2).
Peer influence has a positive effect on self-disclosure.

3.2. Self-Disclosure

Self-disclosure deals with individuals voluntarily and intentionally sharing their personal thoughts, feelings, and experiences [93]. The nature of most SMBCs allows the creation and exchange of user-generated content, thereby facilitating highly interactive communication in the community, with opportunities for members to act as self-advocates in matters regarding their personal experience with the brand [94,95]. Brands use their social media community in engaging brand-mediated intimacy in which community members disclose factual and emotional information relating to themselves [96]. Some individuals also like to disclose information about themselves, as they seek to provide value to other members of the community [97,98], especially in online communities [98]. Self-disclosure is prevalent in a socially interactive setting [99], and online brand communities are relational communities that enhance social interaction among their members [100]. This is similar to normative social influence when individuals tend to conform to engaging in discussion especially where discussion content presents positions favored by other community members [74]. Thus this study posited that:
Hypothesis 3 (H3).
Self-disclosure has a positive effect on SCE in SMFBCs.
A mediating variable is an intermediate in the causal sequence between an independent and dependent variable. It transmits the effect of its antecedent variable on the outcome variable [101]. The same case was with self-disclosure in this study as shown earlier with peer influence being its antecedent and CE being the outcome variable. This shows that when an online community behaves in a peer-related manner, it generates cues that signal the extent of closeness possessed by the current community encouraging its members to keep on expressing themselves and engaging more in the community [87]. This resulted in the study positing that:
Hypothesis 4 (H4).
Self-disclosure mediates the relationship between peer influence and SCE in SMFBCs.

3.3. Sustaining Consumer Engagement and Loyalty in SMFBCs

Studies on consumer loyalty differ, but most scholars [102,103] adopt the concept of [104], who declared that loyalty is observed when one is strongly committed to a particular product or service at the expense of alternatives. The concept of loyalty can be applied in virtual environments [70]. A customer’s intent of sticking with a particular SMBC as its first choice is a display of loyalty to the community. It is a positive attitude toward an online realm that involves integrating, retaining, and engaging in the virtual realm activities consistently over time [104,105]. Online brand communities are platforms where community members interact and exchange brand-related information [106,107], which results in customers’ loyalty to the community [108,109]. Interaction on social media entails posting, liking, sharing, and commenting [110] and is an important resource of brands that drives the devotion of the community members [111]. The more an individual continuously engages in an online brand community, the more the individual integrates and becomes more loyal to the community [112,113]. Thus, this study hypothesized that:
Hypothesis 5 (H5).
SCE in SMFBCs is positively associated with loyalty to SMFBCs.

4. Methodology

4.1. Profile of the Respondents

The study investigated key questions about associations among peer influence, self-disclosure, consumer engagement, and loyalty. This necessitated a quantitative approach in line with similar CE studies [5,24]. The study surveyed 365 members who follow local Nigerian fashion brands on Facebook. Facebook was used for this research due to its overwhelming popularity and diverse examples of active SMBCs [4,17,114].
In line with prior SMBC literature and using purposive sampling technique, the authors made sure the respondents fit into the following criteria: (1) they were members of one or more local Nigerian SMFBC [64,115]. (2) The SMFBC was brand-initiated [115]. (3) SMFBC page allows comments [4,116]. (4) Community members were allowed to share brand-related experience on the platform [4,70]. (5) There is regular release of updated brand-related information [4,116].
From the data retrieved, 45.8% (167) of respondents were male and 54.2% (198) were female. In terms of the age of participants, 49 (13.4%) were in the range of 16–20, 171 (46.8%) were within the range of 22–25, and finally, 145 (39.7%) were above 25 years.

4.2. Measurement Scales

Items were adopted and modified from existing studies to measure the variables in the model, coupled with a five-point Likert scale containing endpoints of 1 as “strongly agree” to 5 as “strongly disagree” as shown in Appendix A.

5. Measurement Model

5.1. Data Analysis and Results

To analyze the collected data, the study used partial least squares structural equation modeling (PLS–SEM), specifically SmartPLS v3.3.3. PLS–SEM is gaining vast popularity among researchers and was best suited for this study as it provides robust estimation in conceptual frameworks explaining the relationships between the variables [117] and is effective for analyzing data with a small sample size (e.g., ≤500) [118]. Moreover, in line with prior SMBC and SCE literature that confirmed the applicability of the PLS-based SEM approach in predicting key target constructs in their conceptual framework [4,119,120], this study used the PLS-based approach in testing and validating the proposed hypotheses.
In determining the reliability of the survey instrument, values of the composite reliability (CR) and Cronbach’s alpha (α) were used. Table 1 shows that all the CR values exceeded 0.8, which exceeds the commonly acceptable score of 0.7 [121]. Therefore, the data in this study demonstrated good reliability and stability.
The reliability and validity analysis conducted on the survey involved internal consistency, convergent validity, and discriminant validity tests. An array of parameters consisting of α, CR, and average variance extracted (AVE) was used in deriving the internal consistency.
As depicted in Table 1, the α of the values exceeded 0.8, which exceeds the commonly accepted score of 0.7 [121], meaning sufficient reliability. Furthermore, the analysis of the convergent validity was carried out using factor loadings (λ), AVE, and CR. As displayed in Table 1, all the AVE results were above the 0.5 threshold while CR values surpassed 0.7 and the λ exceeded 0.60, showing convergent validity and a significant level of acceptance [121,122].
The Fornell–Larcker criterion and heterotrait–monotrait ratio (HTMT) were used in evaluating the discriminant validity. The Fornell–Larcker criterion principle states that the AVE square root for each variable has to be higher than the inter-construct correlation of the research model [123]. The results shown in Table 2 depict that the AVE square roots (in bold) surpass the correlation values of the variables. Based on the criteria proposed by [124], the HTMT values have to be below 1. Table 3 shows that the HTMT values are in line with the required threshold.

5.2. Common Method Bias

In order to ensure that there was no common method bias, the study employed Harman’s one-factor test. Academics are of the opinion that common method bias exists if a single factor represents the bulk of covariance among the measures [4]. It was observed from the results that several factors emerged and that 44.14% was the highest level of covariance explained by one factor. This shows that all the indicators could not be accounted for by a single latent variable.

5.3. Structural Model

In testing the tendered hypotheses, the path coefficient coupled with their statistical significance was analyzed using the bootstrap re-sampling function (5000 re-samples) in the Smart-PLS software. As shown in Table 4 and Figure 1, the path analysis outcome denotes that the hypothesized paths from peer influence to SCE (β = 0.210, p < 0.000) and self-disclosure (β = 0.545, p < 0.000) were significant and positive, thus endorsing H1 and H2, respectively, inferring that peer influence significantly impacts SCE and self-disclosure. Furthermore, as hypothesized, self-disclosure (β = 0.595, p < 0.000) not only showed a positive and significant effect on SCE but also positively mediated the relationship between peer influence and SCE in SMFBCs (β = 0.324, p < 0.000), thus endorsing H3 and H4 accordingly. Finally, SCE (β = 0.493, p < 0.000) showed a significantly positive effect on consumer loyalty to SMFBC.

6. Discussion and Conclusions

6.1. Theoretical Contributions

This research advances knowledge in the theoretical realm of SCE and SMFBCs in particular. From the lens of SIT and SCT, the current study extends the body of knowledge on SCE by conceptualizing peer influence and self-disclosure as antecedents of SCE which leads to loyalty in SMFBC. This study also offers a pioneering investigation into the role of self-disclosure as a mediator between peer influence and SCE in SMFBCs. This answers the call for more research on SCE and SMFBCs [5,38,39,40,41]. Specifically, the following contributions were made toward the SCE, SMBC, and fashion literature:
The first contribution lies in investigating the role of peer influence and self-disclosure as antecedents of SCE. This result extends the work of [51,98] by showing that peer influence and self-disclosure are influencers of consumer behavior as they drive consumers to engage in SMFBCs.
The second contribution of this study is in showing that self-disclosure mediates the relationship between peer influence and SCE. To the best of our knowledge, this study is the first to investigate this relationship thus extending consumer self-disclosure literature [58] and the importance of self-disclosure for organizational benefit.
The third contribution of this study lies in showing the effect of SCE in securing the loyalty of consumers to an SMFBC. Prior literature has investigated this relationship in various contexts [113,116], but none has streamlined the effect of this relationship to the SMFBC realm.
Lastly, this study was the first to investigate the relationships that exist among various variables in the Nigerian SMFBC context, thereby extending the SMFBC and SCE literature [18,116].

6.2. Practical Implications

The findings from this study have a number of managerial implications for managers. First, in line with H1 revealing that peer influence positively correlates with SCE in SMFBC, managers of local SMFBCs in Nigeria should pay attention to their SMFBC environment making sure that it operates in a peer-like manner where all the members (both new and old) feel equal and comfortable to make the members feel confident and interested in engaging in the community. As a result of ensuring this type of convenient setting, the community members will be more interested in engaging in the community. This can be achieved by welcoming brand-related topics, relating with all community members equally, and moderating discussions between community members in a neutral and subtle manner.
Second, H2 and H3 showed the pervasive effect of self-disclosure as it serves as both an SCE driver and a mediator between peer influence and SCE in SMFBCs. Marketers and managers of local SMFBCs in Nigeria should be keen on making sure their community members feel comfortable in disclosing their brand-related personal experiences because this will strengthen engagement in the community providing more insight to fashion brands on their consumers.
Finally, H3 showed that sustained engagement in the community leads to the loyalty of the members. This implies that managers of local SMFBCs in Nigeria should keep their social media platforms active to make sure their community members are constantly engaged. This will not only make the members focus on the community but also ensure that the fashion brand will have a sustained and reliable fan base where their products can be marketed.

7. Limitations and Further Research Directions

This study had a few limitations that open up avenues for further research. First, this research adopted composite measurements for the behavioral aspect of SCE variables; thus future studies can measure other aspects (cognitive and emotional). Future studies can measure other activities of the SCE aspect separately by adopting (for instance) the dimensions in [61]. Secondly, results obtained from this research cover local fashion brands in Nigeria. Future research can focus on other countries and specific fashion sections, e.g., clothes, shoes, hair, etc.

Author Contributions

Conceptualization O.S.O.; writing—original draft preparation, A.C.D.; supervision, A.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Cyprus International University.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
ConstructsItemsSources
Peer InfluenceSome members on this fashion brand’s fan page could push me into continuing to engage in this fashion brand’s fan page[125,126]
At times, I keep on interacting on this fashion brand’s fan page because some members have encouraged me to
At times, I’ve felt pressured to keep on engaging on this fashion brand’s fan page, because some members have urged me too.
When I see members of this fashion brand’s fan page participating in activities on this page, I feel pressured to also participate.
Self-DisclosureI usually talk about my personal experiences on this fashion brand’s fan page[93]
I feel sincere when I reveal my own feelingsand experiences on this fashion brand’s fan page
I often disclose intimate, personal things about myself on this fashion brand’s fan page
My conversations last long when I amDiscussing about myself on this fashion brand’s fan page
SCE in SMFBCWhen online on Facebook, I constantly participate in activities on this fashion brand’s fan page.[4,127]
When I engage in this fashion brand’s fan page, I keep on reading other peoples comment and conversations
I continuously like, share and comment on post from this fashion brand’s fan page
I spend a lot of time participating in activities on this fashion brand’s fan page, compared to other brand pages.
Loyalty to SMFBCI will frequently re-participate in activities of this fashion brand’s fan page in the future[113,128]
I intend to revisit this fashion brand’s fan page
I would recommend this fashion brand’s fan page to my friends/relatives.
I will hardly consider switching to another fashion brand’s fan page

References

  1. Tajvidi, R.; Karami, A. The effect of social media on firm performance. Comput. Human Behav. 2021, 115, 105174. [Google Scholar] [CrossRef]
  2. Sanz-Blas, S.; Bigné, E.; Buzova, D. Facebook brand community bonding: The direct and moderating effect of value creation behaviour. Electron. Commer. Res. Appl. 2019, 35. [Google Scholar] [CrossRef]
  3. Barger, V.; Peltier, J.W.; Schultz, D.E. Social media and consumer engagement: A review and research agenda. J. Res. Interact. Mark. 2016, 10, 268–287. [Google Scholar] [CrossRef]
  4. Liu, L.; Lee, M.K.O.; Liu, R.; Chen, J. International Journal of Information Management Trust transfer in social media brand communities: The role of consumer engagement. Int. J. Inf. Manag. 2018, 41, 1–13. [Google Scholar] [CrossRef]
  5. Gómez, M.; Lopez, C.; Molina, A. Computers in Human Behavior An integrated model of social media brand engagement. Comput. Human Behav. 2019, 96, 196–206. [Google Scholar] [CrossRef]
  6. Won, S.; Ha, S.; Lee, K. How to measure social capital in an online brand community? A comparison of three social capital scales. J. Bus. Res. 2021, 131, 652–663. [Google Scholar] [CrossRef]
  7. Teixeira, A. Data extraction and preparation to perform a The example of a Facebook fashion brand page. In Proceedings of the 12th Iberian Conference on Information Systems and Technologies (CISTI), Lisbon, Portugal, 14–17 June 2017. [Google Scholar]
  8. Wang, H.; Liu, H.; Kim, S.J.; Kim, K.H. Sustainable fashion index model and its implication. J. Bus. Res. 2019, 99, 430–437. [Google Scholar] [CrossRef]
  9. Gu, X.; Gao, F.; Tan, M.; Peng, P. Fashion analysis and understanding with artificial intelligence. Inf. Process. Manag. 2020, 57, 102276. [Google Scholar] [CrossRef]
  10. Wiedmann, K.; Hennigs, N.; Langner, S. Spreading the Word of Fashion: Identifying Social Influencers in Fashion Marketing Spreading the Word of Fashion: Identifying Social Influencers in Fashion Marketing. J. Glob. Fash. Mark. 2012, 2685, 142–153. [Google Scholar] [CrossRef]
  11. Jain, S.; Mishra, S. Luxury fashion consumption in sharing economy: A study of Indian millennials Luxury fashion consumption in sharing economy: A study of Indian millennials. J. Glob. Fash. Mark. 2020, 11, 171–189. [Google Scholar] [CrossRef]
  12. Sandvik, I.M.; Stubbs, W. Circular fashion supply chain through textile-to-textile recycling. J. Fash. Mark. Manag. 2017. [Google Scholar] [CrossRef]
  13. Godart, F.C. Poetics Culture, structure, and the market interface: Exploring the networks of stylistic elements and houses in fashion. Poetics 2018, 68, 72–88. [Google Scholar] [CrossRef]
  14. Hsiao, S.; Wang, Y.; Wang, T.; Daniel, T.K. How social media shapes the fashion industry: The spillover e ff ects between private labels and national brands. Ind. Mark. Manag. 2020, 86, 40–51. [Google Scholar] [CrossRef]
  15. Helal, G.; Lancaster, G. Social media brand perceptions of millennials. Int. J. Retail Distrib. Manag. 2018, 46, 977–998. [Google Scholar] [CrossRef] [Green Version]
  16. Martín-Consuegra, D.; Faraoni, M.; Díaz, E.; Ranfagni, S.; Faraoni, M.; Díaz, E.; Ranfagni, S. Exploring relationships among brand credibility, purchase intention and social media for fashion brands: A conditional mediation model. J. Glob. Fash. Mark. 2018, 9, 237–251. [Google Scholar] [CrossRef]
  17. Kim, J.; Lee, K.H. Influence of integration on interactivity in social media luxury brand communities. J. Bus. Res. 2019, 99, 422–429. [Google Scholar] [CrossRef]
  18. Maria, S.; Loureiro, C.; Maximiano, M.; Panchapakesan, P. Engaging fashion consumers in social media: The case of luxury brands. Int. J. Fash. Des. Technol. Educ. 2018, 11, 310–321. [Google Scholar] [CrossRef] [Green Version]
  19. Ho, C.W.; Wang, Y.B. Re-purchase intentions and virtual customer relationships on social media brand community. Human-centric Comput. Inf. Sci. 2015. [Google Scholar] [CrossRef] [Green Version]
  20. Yi, D.; Phang, C.W.; Lu, X.; Tan, C.-H.; Sutanto, J. The Role of Marketer- and User-generated Content in Sustaining the Growth of a Social Media Brand Community. In Proceedings of the 47th Hawaii International Conference on System Sciences; Waikoloa, HI, USA, 6–9 January 2014; IEEE: New York, NY, USA, 2014; pp. 1785–1792. [Google Scholar] [CrossRef]
  21. Wang, T.; Lee, F. Journal of Retailing and Consumer Services Examining customer engagement and brand intimacy in social media context. J. Retail. Consum. Serv. 2020, 54, 102035. [Google Scholar] [CrossRef]
  22. Kaur, P.; Dhir, A.; Rajala, R.; Dwivedi, Y. Why people use online social media brand communities:A consumption value theory perspective. Online Inf. Rev. 2018, 42, 205–221. [Google Scholar] [CrossRef]
  23. Ray, S.; Kim, S.S.; Morris, J.G.; Ray, S.; Kim, S.S.; Morris, J.G. The Central Role of Engagement in Online Communities The Central Role of Engagement in Online Communities. Inf. Syst. Res. 2014, 25, 528–546. [Google Scholar] [CrossRef]
  24. Islam, J.; Rahman, Z. The impact of online brand community characteristics on customer engagement: An application of Stimulus-Organism-Response paradigm. Telemat. Inform. 2017, 34, 96–109. [Google Scholar] [CrossRef]
  25. Alwreikat, A.A.; Rjoub, H. Impact of Mobile Ad Wearout on Consumer Irritation, Perceived Intrusiveness, Engagement, and Loyalty: A PLS-SEM Analysis. J. Organ. End User Comput. (JOEUC) 2021, 33, 69–84. [Google Scholar] [CrossRef]
  26. Perera, C.H.; Nayak, R.; Long, N.V.T. The Impact of Electronic-Word-of Mouth on e-Loyalty and C onsumers’ e-Purchase Decision Making Process: A Social Media Perspective. Int. J. Trade Econ. Financ. 2019, 10, 86–91. [Google Scholar] [CrossRef] [Green Version]
  27. Zeithaml, V.A.; Berry, L.L.; Parasuraman, A. The behavioral consequences of service quality. J. Mark. 1996. [Google Scholar] [CrossRef]
  28. Popp, B.; Wilson, B. Computers in Human Behavior Investigating the role of identi fi cation for social networking Facebook brand pages. Comput. Human Behav. 2018, 84, 141–152. [Google Scholar] [CrossRef]
  29. Asperen, M. Van; Rooij, P. De; Dijkmans, C. Engagement-Based Loyalty: The Effects of Social Media Engagement on Customer Loyalty in the Travel Industry Engagement-Based Loyalty: The Effects of Social Media. Int. J. Hosp. Tour. Adm. 2018, 19, 78–94. [Google Scholar] [CrossRef]
  30. Lee, J.Y.; Yang, C.; Hsu, C.; Wang, J. Longitudinal study of leader influence in sustaining an online community. Inf. Manag. 2019, 56, 306–316. [Google Scholar] [CrossRef]
  31. Kamboj, S.; Rahman, Z. Understanding customer participation in online brand communities: Literature review and future research agenda. Qual. Mark. Res. 2017, 20, 306–334. [Google Scholar] [CrossRef]
  32. Hamzah, Z.L.; Wahab, H.A.; Waqas, M. Unveiling drivers and brand relationship implications of consumer engagement with social media brand posts. J. Res. Interact. Mark. 2021. [Google Scholar] [CrossRef]
  33. Bock, G.W.; Ahuja, M.K.; Suh, A.; Yap, L.X. Sustainability of a virtual community: Integrating individual and structural dynamics. J. Assoc. Inf. Syst. 2015, 13. [Google Scholar] [CrossRef] [Green Version]
  34. Chahal, H.; Rani, A. How trust moderates social media engagement and brand equity. J. Res. Interact. Mark. 2017, 11, 312–335. [Google Scholar] [CrossRef]
  35. Harrigan, P.; Evers, U.; Miles, M.; Daly, T. Customer engagement with tourism social media brands. Tour. Manag. 2017, 59, 597–609. [Google Scholar] [CrossRef]
  36. Brodie, R.J.; Ilic, A.; Juric, B.; Hollebeek, L. Consumer engagement in a virtual brand community: An exploratory analysis. J. Bus. Res. 2013. [Google Scholar] [CrossRef]
  37. MSI. Research Priorities. 2018. Available online: https://www.msi.org/research/2016-2018-research-priorities/ (accessed on 18 October 2021).
  38. Fletcher-Brown, J.; Turnbull, S.; Viglia, G.; Chen, T.; Pereira, V. Vulnerable consumer engagement: How corporate social media can facilitate the replenishment of depleted resources. Int. J. Res. Mark. 2021, 38, 518–529. [Google Scholar] [CrossRef]
  39. Hollebeek, L.D.; Andreassen, T.W. The S-D logic-informed “hamburger” model of service innovation and its implications for engagement and value. J. Serv. Mark. 2018. [Google Scholar] [CrossRef]
  40. Islam, J.U.; Rahman, Z.; Hollebeek, L.D. Consumer engagement in online brand communities: A solicitation of congruity theory. Internet Res. 2018, 28, 23–45. [Google Scholar] [CrossRef]
  41. Kaur, H.; Paruthi, M.; Islam, J.; Hollebeek, L.D. Telematics and Informatics The role of brand community identification and reward on consumer brand engagement and brand loyalty in virtual brand communities. Telemat. Inform. 2020, 46, 101321. [Google Scholar] [CrossRef]
  42. Aksoy, H. Exploring the impact of religiousness and culture on luxury fashion goods purchasing intention A behavioural study on Nigerian. J. Islam. Mark. 2019, 768–789. [Google Scholar] [CrossRef]
  43. Falade, T. Globalization and the Cultural/Creative Industries: An Assessment of Nigeria’ s Position in the Global Space. J. Adv. Res. Soc. Sci. 2020, 2, 10–19. [Google Scholar]
  44. Islam, J.U.; Rahman, Z. Examining the effects of brand love and brand image on customer engagement: An empirical study of fashion apparel brands. J. Glob. Fash. Mark. 2016, 7, 45–59. [Google Scholar] [CrossRef]
  45. Geissinger, A.; Laurell, C. User engagement in social media—An explorative study of Swedish fashion brands. J. Fash. Mark. Manag. 2016, 20, 177–190. [Google Scholar] [CrossRef]
  46. Pentina, I.; Guilloux, V.; Micu, A.C.; Pentina, I. Exploring Social Media Engagement Behaviors in the Context of Luxury Brands Exploring Social Media Engagement Behaviors in the Context of Luxury Brands. J. Advert. 2018, 47, 55–69. [Google Scholar] [CrossRef]
  47. Brunner, M.; Ostermaier, A. Peer Influence on Managerial Honesty: The Role of Transparency and Expectations. J. Bus. Ethics 2019, 154, 127–145. [Google Scholar] [CrossRef]
  48. Liou, Y.H.; Daly, A.J. The networked leader: Understanding peer influence in a system wide leadership team. Sch. Leadersh. Manag. 2020, 40, 163–182. [Google Scholar] [CrossRef]
  49. Sherman, L.E.; Greenfield, P.M.; Hernandez, L.M.; Dapretto, M. Peer Influence Via Instagram: Effects on Brain and Behavior in Adolescence and Young Adulthood. Child Dev. 2018, 89, 37–47. [Google Scholar] [CrossRef]
  50. Zhao, L.; Lee, S.H.; Copeland, L.R. Social media and Chinese consumers’ environmentally sustainable apparel purchase intentions. Asia Pacific J. Mark. Logist. 2019, 31, 855–874. [Google Scholar] [CrossRef]
  51. Ünal, S.; Deniz, E.; Akin, N. Determining the Factors That Influence the Intention To Purchase Luxury Fashion Brands of Young Consumers. Ege Acad. Rev. 2019, 19, 221–236. [Google Scholar] [CrossRef]
  52. Kong, H.M.; Ko, E.; Chae, H.; Mattila, P. Understanding fashion consumers’ attitude and behavioral intention toward sustainable fashion products: Focus on sustainable knowledge sources and knowledge types. J. Glob. Fash. Mark. 2016, 7, 103–119. [Google Scholar] [CrossRef]
  53. Kobia, C.; Liu, C. Teen girls’ adoption of a virtual fashion world. Young Consum. 2016, 17, 419–432. [Google Scholar] [CrossRef]
  54. Wolske, K.S.; Gillingham, K.T.; Schultz, P.W. Peer influence on household energy behaviours. Nat. Energy 2020, 5. [Google Scholar] [CrossRef]
  55. Hu, X.; Chen, X.; Davison, R.M. Social Support, Source Credibility, Social Influence, and Impulsive Purchase Behavior in Social Commerce. Int. J. Electron. Commer. 2019, 23, 297–327. [Google Scholar] [CrossRef]
  56. Cheung, C.; Lee, Z.W.Y.; Chan, T.K.H. Self-disclosure in social networking sites benefits and social influence. Internet Res. 2013, 25, 279–299. [Google Scholar] [CrossRef]
  57. Gabisch, J.A.; Milne, G.R. Self-disclosure on the web role of regulatory focus. J. Res. Interact. Mark. 2013, 11, 140–158. [Google Scholar] [CrossRef]
  58. Ardiansyah, Y.; Harrigan, P.; Soutar, G.N.; Daly, T.M.; Ardiansyah, Y.; Harrigan, P.; Soutar, G.N.; Daly, T.M. Antecedents to Consumer Peer Communication through Social Advertising: A Self-Disclosure Theory Perspective Antecedents to Consumer Peer Communication through Social Advertising. J. Interact. Advert. 2019, 18, 51–71. [Google Scholar] [CrossRef]
  59. Yang, S.; Lin, S.; Carlson, J.R.; Ross, W.T. Brand engagement on social media: Will firms’ social media efforts influence search engine advertising effectiveness? J. Mark. Manag. 2016, 32, 526–557. [Google Scholar] [CrossRef]
  60. Anthony, A.; Bonifield, C.M.; Elhai, J.D. Modeling consumer engagement on social networking sites: Roles of attitudinal and motivational factors. J. Retail. Consum. Serv. 2021, 59, 102348. [Google Scholar] [CrossRef]
  61. Dessart, L.; Veloutsou, C.; Morgan-Thomas, A. Consumer engagement in online brand communities: A social media perspective. J. Prod. Brand Manag. 2015. [Google Scholar] [CrossRef]
  62. Pezzuti, T.; Leonhardt, J.M.; Warren, C. Certainty in Language Increases Consumer Engagement on Social Media. J. Interact. Mark. 2021, 53, 32–46. [Google Scholar] [CrossRef]
  63. Claesson, A.; Tägt Ljungberg, N. Consumer Engagement on Instagram: Viewed through the Perspectives of Social Influence and Influencer Marketing; Lund University: Lund, Sweden, 2018. [Google Scholar]
  64. Ananda, A.S.; Hernández-García, Á.; Acquila-Natale, E.; Lamberti, L. What makes fashion consumers “click”? Generation of eWoM engagement in social media. Asia Pacific J. Mark. Logist. 2019, 31, 398–418. [Google Scholar] [CrossRef]
  65. Alt, D. College students’ academic motivation, media engagement and fear of missing out. Comput. Human Behav. 2015, 49, 111–119. [Google Scholar] [CrossRef]
  66. Lim, J.S.; Hwang, Y.; Kim, S.; Biocca, F.A. How social media engagement leads to sports channel loyalty: Mediating roles of social presence and channel commitment. Comput. Human Behav. 2015, 46, 158–167. [Google Scholar] [CrossRef]
  67. Pletikosa Cvijikj, I.; Michahelles, F. Online engagement factors on Facebook brand pages. Soc. Netw. Anal. Min. 2013, 3, 843–861. [Google Scholar] [CrossRef]
  68. Lee, D.; Hosanagar, K.; Nair, H.S. Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook. Management Science Published online in Articles in Advance. Manage. Sci. 2018. [Google Scholar] [CrossRef] [Green Version]
  69. Luarn, P.; Lin, Y.F.; Chiu, Y.P. Influence of Facebook brand-page posts on online engagement. Online Inf. Rev. 2015, 39, 505–519. [Google Scholar] [CrossRef]
  70. Osemeahon, O.S. Linking FOMO and Smartphone Use to Social Media Brand Communities. Sustainability 2020, 12, 2166. [Google Scholar] [CrossRef] [Green Version]
  71. Hsu, L.; Wang, K. Investigating virtual community participation and promotion from a social influence perspective. Ind. Manag. Data Syst. 2018, 118, 1229–1250. [Google Scholar] [CrossRef]
  72. Leenders, R.T.A.J. Modeling social influence through network autocorrelation: Constructing the weight matrix. Soc. Netw. 2002, 24, 21–47. [Google Scholar] [CrossRef]
  73. Li, C. Computers in Human Behavior Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Comput. Human Behav. 2013, 29, 264–275. [Google Scholar] [CrossRef]
  74. Kaplan, M.F.; Miller, C.E. Group Decision Making and Normative Versus Informational Influence: Effects of Type of Issue and Assigned Decision Rule. J. Personal. Soc. Psychol. 1987, 53, 306–313. [Google Scholar] [CrossRef]
  75. Farías, P. Identifying the factors that influence eWOM in SNSs: The case of Chile. Int. J. Advert. 2017, 0487, 852–869. [Google Scholar] [CrossRef]
  76. Montgomery, M.R.; Casterline, J.B. Social learning, social influence, and new models of fertility. Popul. Dev. Rev. 1996, 22, 151–175. [Google Scholar] [CrossRef]
  77. Potgieter, L.M.; Naidoo, R. Factors explaining user loyalty in a social media-based brand community. SA J. Inf. Manag. 2017. [Google Scholar] [CrossRef]
  78. Chang, I.; Chen, K. The effects of hedonic/utilitarian expectations and social influence on continuance intention to play online games. Internet Res. 2014, 24, 21–45. [Google Scholar] [CrossRef]
  79. Lin, C.P. Learning virtual community loyalty behavior from a perspective of social cognitive theory. Int. J. Hum. Comput. Interact. 2010, 26, 345–360. [Google Scholar] [CrossRef]
  80. Bapna, R.; Umyarov, A.; Bapna, R.; Umyarov, A. Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks. Manage. Sci. 2015, 61, 1–19. [Google Scholar]
  81. Ryan, A.M.; North, E.A.; Ferguson, S. Chapter 6. Peers and Engagement; Elsevier Inc.: Amsterdam, The Netherlands, 2019; ISBN 9780128134139. [Google Scholar]
  82. Wentzel, K.; Ramani, G.B. Handbook of Social Influences in School Contexts: Social-Emotional, Motivation, and Cognitive Outcomes; Routledge: London, UK, 2016. [Google Scholar]
  83. Van De Weijer, S.G.A.; Beaver, K.M. An Exploration of Mate Similarity for Criminal Offending Behaviors: Results from a Multi-Generation Sample of Dutch Spouses. Psychiatr. Q. 2017, 88, 523–533. [Google Scholar] [CrossRef] [PubMed]
  84. Liao, J.; Huang, M.; Xiao, B. Promoting continual member participation in fi rm-hosted online brand communities: An organizational socialization approach. J. Bus. Res. 2017, 71, 92–101. [Google Scholar] [CrossRef]
  85. Liu, X.; Min, Q.; Han, S. Understanding users’ continuous content contribution behaviours on microblogs: An integrated perspective of uses and gratification theory and social influence theory. Behav. Inf. Technol. 2020, 39, 525–543. [Google Scholar] [CrossRef]
  86. Haiyi, Z.; Amy, Z.; Jiping, H.; Robert, E.K.; Kittur, A. Effects of peer feedback on contribution: A field experiment in Wikipedia. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, 27 April–2 May 2013. [Google Scholar]
  87. Sungwook, L.; Do-hyung, P.; Han, I. Computers in Human Behavior New members’ online socialization in online communities: The effects of content quality and feedback on new members’ content-sharing intentions. Comput. Human Behav. 2014, 30, 344–354. [Google Scholar] [CrossRef]
  88. Irwin, A. Reciprocity of Interpersonal Exchange. J. Theory Soc. Behav. 1973, 3, 249–261. [Google Scholar]
  89. Kashian, N.; Jang, J.; Yun, S.; Dai, Y.; Walther, J.B. Computers in Human Behavior Self-disclosure and liking in computer-mediated communication. Comput. Human Behav. 2017, 71, 275–283. [Google Scholar] [CrossRef]
  90. Kreager, D.A.; Schaefer, D.R.; Davidson, K.M.; Zajac, G.; Haynie, D.L.; De Leon, G. Evaluating peer-influence processes in a prison-based therapeutic community: A dynamic network approach. Drug Alcohol Depend. 2019, 203, 13–18. [Google Scholar] [CrossRef] [PubMed]
  91. Aihwa, C.; Sara, H.H.; Timmy, H.T. Online brand community response to negative brand events: The role of group eWOM. Internet Res. 2013, 23, 486–506. [Google Scholar]
  92. Hsu, L.C.; Chih, W.H.; Liou, D.K. Investigating community members’ eWOM effects in Facebook fan page. Ind. Manag. Data Syst. 2016, 116, 978–1004. [Google Scholar] [CrossRef]
  93. Zhang, S.; Kwok, R.C.; Benjamin, P.; Liu, Z.; Wu, J. Information & Management The influence of role stress on self-disclosure on social networking sites: A conservation of resources perspective. Inf. Manag. 2019, 56. [Google Scholar] [CrossRef]
  94. Rialti, R.; Scuola, F. Co-creation experiences in social media brand communities Analyzing the main types of Comunidades de marca de medios n de sociales y co-creaci o experiencias n sobre los principales tipos. Spanish J. Mark. 2018, 22, 122–141. [Google Scholar] [CrossRef] [Green Version]
  95. Reza, M.; Laroche, M.; Richard, M. Computers in Human Behavior Testing an extended model of consumer behavior in the context of social media-based brand communities. Comput. Human Behav. 2016, 62, 292–302. [Google Scholar] [CrossRef]
  96. Simões, P.; Rita, P.; Raposo, Z. On the relationship between consumer-brand identi fi cation, brand community, and brand loyalty. J. Retail. Consum. Serv. 2018, 43, 101–110. [Google Scholar] [CrossRef]
  97. Maria, S.; Elena, D.-B.; Mariola, P. The need to belong and self-disclosure in positive word-of-mouth behaviours:The moderating effect of self–brand connection. J. Consum. Behav. 2016, 15, 60–71. [Google Scholar]
  98. Hassan, M.; Iii, S.M.; Pervan, S.J.; Kortt, M. Facebook, self-disclosure, and brand-mediated intimacy: Identifying value creating behaviors. J. Consum. Behav. 2016, 502, 493–502. [Google Scholar] [CrossRef]
  99. Town, J.P.; Harvey, J.H. Self-Disclosure, Attribution, and Social Interaction. Soc. Psychol. Q. 1981, 44, 291–300. Available online: https://www.jstor.org/stable/3033898 (accessed on 18 October 2021). [CrossRef]
  100. Preece, J.; Preece, J. Sociability and usability in online communities: Determining and measuring success Sociability and usability in online communities: Determining and measuring success. Behav. Inf. Technol. 2010, 20, 347–356. [Google Scholar] [CrossRef]
  101. Mackinnon, D.P. Mediating Variable, 2nd ed.; Elsevier: Amsterdam, The Netherlands, 2015; Volume 15, ISBN 9780080970868. [Google Scholar]
  102. Chang, Y.; Yeh, C. Corporate social responsibility and customer loyalty in intercity bus services. Transp. Policy 2017, 59, 38–45. [Google Scholar] [CrossRef]
  103. Wu, Y.; Li, E.Y. Marketing mix, customer value, and customer loyalty in social commerce. Internet Res. 2018, 1066–2243. [Google Scholar] [CrossRef] [Green Version]
  104. Oliver, R.L. Whence consumer loyalty? J. Mark. 1999, 63, 33–44. [Google Scholar] [CrossRef]
  105. Kim, D.J.; Zhang, D. The effects of sense of presence, sense of belonging, and cognitive absorption on satisfaction and user loyalty toward an immersive 3D virtual world. In Lecture Notes in Business Information Processing; Springer: Berlin, Germary, 2010. [Google Scholar]
  106. Liu, S.; Perry, P.; Gadzinski, G. The implications of digital marketing on WeChat for luxury fashion brands in China. J. Brand Manag. 2019, 26, 395–409. [Google Scholar] [CrossRef]
  107. Xu, X.; Wang, X.; Li, Y.; Haghighi, M. Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors. Int. J. Inf. Manag. 2017, 37, 673–683. [Google Scholar] [CrossRef]
  108. Bruhn, M.; Schnebelen, S.; Schäfer, D. Antecedents and consequences of the quality of e-customer-to-customer interactions in B2B brand communities. Ind. Mark. Manag. 2014. [Google Scholar] [CrossRef]
  109. Han, J.; Jun, M.; Kim, M. Impact of online community engagement on community loyalty and social well-being. Soc. Behav. Pers. 2019, 47, 1–8. [Google Scholar] [CrossRef]
  110. Huang, F.H. Motivations of facebook users for responding to posts on a community page. In International Conference on Online Communities and Social Computing; Springer: Berlin/Heidelberg, Germany, 2013; pp. 33–39. [Google Scholar] [CrossRef]
  111. Kang, M.; Shin, D.H. The effect of customers’ perceived benefits on virtual brand community loyalty. Online Inf. Rev. 2016, 40, 298–315. [Google Scholar] [CrossRef]
  112. Woisetschläger, D.M.; Hartleb, V.; Blut, M.; Woisetschl, D.M.; Hartleb, V. How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation How to Make Brand Communities Work: Antecedents and Consequences of Consumer Participation. J. Relatsh. Mark. 2008, 2667. [Google Scholar] [CrossRef]
  113. Wu, H.; Xiao, T.; Wu, X.; Wu, H. More is better ? The influencing of user involvement on user loyalty in online travel community in online travel community. Asia Pacific J. Tour. Res. 2017, 1665, 357–369. [Google Scholar] [CrossRef]
  114. Pasternak, O.; Veloutsou, C.; Morgan-Thomas, A. Self-presentation, privacy and electronic word-of-mouth in social media. J. Prod. Brand Manag. 2017, 26, 415–428. [Google Scholar] [CrossRef]
  115. Wiese, M.; Akareem, H.S. Friends with benefits: Can firms benefit from consumers’ sense of community in brand Facebook pages? Eur. Bus. Rev. 2019, 31, 947–969. [Google Scholar] [CrossRef]
  116. Odunaiya, O.; Agoyi, M.; Osemeahon, O.S. Social TV Engagement for Increasing and Sustaining Social TV Viewers. Sustainability 2020, 12, 4906. [Google Scholar] [CrossRef]
  117. Hair, J.F.; Hopkins, L.; Georgia, M.; College, S. Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. Eur. Bus. Rev. 2014, 26, 106–121. [Google Scholar] [CrossRef]
  118. Hair, J.F.; Hult, G.T.M.; Ringle, C.M.; Sarstedt, M.; Thiele, K.O. Mirror, mirror on the wall: A comparative evaluation of composite-based structural equation modeling methods. J. Acad. Mark. Sci. 2017, 45, 616–632. [Google Scholar] [CrossRef]
  119. Singh, R. Extending the experience construct: An examination of online grocery shopping construct. Eur. J. Mark. 2019. [Google Scholar] [CrossRef]
  120. Cheung, M.L.; Rosenberger, P.J. The influence of perceived social media marketing elements on consumer—Brand engagement and brand knowledge. Asia Pacific J. Mark. Logist. 2020, 32, 695–720. [Google Scholar] [CrossRef]
  121. Hair, J.F., Jr.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 7th ed.; Pearson Education Inc.: Cranbury, NY, USA, 2010. [Google Scholar]
  122. Chen, C.F.; Phou, S. A closer look at destination: Image, personality, relationship and loyalty. Tour. Manag. 2013. [Google Scholar] [CrossRef]
  123. Fornell, C.; Larcker, D.F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981. [Google Scholar] [CrossRef]
  124. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2014, 43, 115–135. [Google Scholar] [CrossRef] [Green Version]
  125. Santor, D.A.; Deanna, M.; Kusumakar, V. Measuring peer pressure, popularity, and conformity in adolescent boys and girls: Predicting school performance, sexual attitudes, and substance abuse. J. Youth Adolesc. 2000, 22, 163–182. [Google Scholar] [CrossRef]
  126. Zhou, M.; Cai, X.; Liu, Q.; Fan, W. International Journal of Information Management Examining continuance use on social network and micro-blogging sites: Different roles of self-image and peer influence. Int. J. Inf. Manag. 2019, 47, 215–232. [Google Scholar] [CrossRef]
  127. Hollebeek, L. Exploring customer brand engagement: Definition and themes. J. Strateg. Mark. 2011. [CrossRef]
  128. Hsu, C.; Lu, H. Consumer behavior in online game communities: A motivational factor perspective. Comput. Hum. Behav. 2007, 23, 1642–1659. [Google Scholar] [CrossRef]
Sustainability 13 12957 g001 550
Figure 1. Hypothesis testing.
Figure 1. Hypothesis testing.
Sustainability 13 12957 g001
Table
Table 1. Measures and factor loadings.
Table 1. Measures and factor loadings.
ConstructFactor LoadingCronbach’s Alpha (α)Composite Reliability (CR)Average Variance Extracted (AVE)
SCE0.8030.8440.9060.762
0.797
0.818
0.763
Loyalty to SMFBC0.8190.8370.9020.754
0.854
0.879
0.835
Peer Influence0.7900.8310.8980.746
0.745
0.878
0.822
Self-Disclosure0.8390.8330.9000.749
0.874
0.842
0.774
Table
Table 2. Discriminant validity (Fornell–Larcker).
Table 2. Discriminant validity (Fornell–Larcker).
SCELoyalty to SMFBCPeer InfluenceSelf-Disclosure
SCE0.873
Loyalty to SMFBC0.4930.869
Peer Influence0.5350.4270.864
Self-Disclosure0.7100.5100.5450.866
Table
Table 3. Discriminant validity (HTMT).
Table 3. Discriminant validity (HTMT).
SCELoyalty to SMFBCPeer InfluenceSelf-Disclosure
SCE
Loyalty to SMFBC0.581
Peer Influence0.6350.509
Self-Disclosure0.8470.6070.648
Table
Table 4. Summary of hypotheses test results.
Table 4. Summary of hypotheses test results.
Coefficient (β)T Statistics p Values
SCE -> Loyalty to SMFBC0.4938.8180.000
Peer Influence -> SCE0.2104.2520.000
Peer Influence -> Self-Disclosure0.5459.1340.000
Self-Disclosure -> SCE0.59510.9570.000
Indirect Effect
Peer Influence -> Self-Disclosure -> SCE0.3246.8610.000
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Diachi, A.C.; Tansu, A.; Osemeahon, O.S. No One Is Leaving This Time: Social Media Fashion Brand Communities. Sustainability 2021, 13, 12957. https://doi.org/10.3390/su132312957

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Diachi AC, Tansu A, Osemeahon OS. No One Is Leaving This Time: Social Media Fashion Brand Communities. Sustainability. 2021; 13(23):12957. https://doi.org/10.3390/su132312957

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Diachi, Albert Chukwunonso, Ayşe Tansu, and Oseyenbhin Sunday Osemeahon. 2021. "No One Is Leaving This Time: Social Media Fashion Brand Communities" Sustainability 13, no. 23: 12957. https://doi.org/10.3390/su132312957

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