Abstract
Introduction
The widespread application of information technology and the development of social media have eliminated the boundaries between time and space in the purchase scene, allowing consumers to find brand information, view other consumers’ purchase experience at any time and place, and communicate and interact with other users. Trudeau H and Shobeiri (2016) showed that strengthening consumer’s social interaction is an effective way for companies to create an excellent brand experience. Excellent brands are helping people find confidantes who share common aspirations and passions, further promoting to unite people as a group, and make them more successful through interactions between members (Fisk, 2015). More and more brands have gradually realized the importance of social interaction these days, and have begun to build their own social platforms to serve the interactive needs between brands and consumers, and among consumers. For example, aided by Instagram, Nike Run Club Community, offline brand store activities and other online and offline methods, Nike build its own social network, encourage consumers to participate in offline activities to form a common experience, promote story sharing, and closely associate more and more people with the brand.
Compared with traditional brand retailing which tends to focus on product innovation, service enhancement and brand communication, BSI is more conducive to motivate consumers’ interactive engagement because BSI can not only help consumers access to their own information of products, brands and services, but also act as the publisher and disseminator of information to help consumers interact with a lot more other consumers. For example, Facebook emphasizes “social interaction design,” focusing on shifting thinking from user content production to social interaction between users inspired by content, which indirectly promotes the interaction frequency between the brand and its consumers, and helps the brand build a lasting social relations with consumers. In addition, meaningful and valuable social interaction itself brings more to the brand, becoming the third product besides the practical products and services provided to users because BSI build a closer relationship between the brand and its consumers, and help brands provide prompt, attentive and personalized service to attract and retain consumers via social media, increasing user stickiness and purchase intention.
Purchase intention, a personal behavior that can be manipulated through information and emotional processes, will be affected by information and knowledge sharing, and one of the core factors affecting the latter is social interaction (Ghahtarani et al., 2020). Majority of consumers are affected by social interaction when making purchase decisions (Godes et al., 2005), and the closer the social interaction between consumers, the stronger consumers’ awareness of relevant information and their willingness to buy (N. Kim & Kim, 2018; J. Yang et al., 2019; Yin et al., 2019). Social interaction between brands and their consumers via social media has an impact on consumers’ perceptions, behaviors and purchase intentions (Dwivedi et al., 2021; Onofrei et al., 2022; Popp & Wilson, 2018; Qin, 2020). In fact, social interaction has long become an important way for companies to increase their brand’s future earnings, continue to inspire consumers to pay premium for product, create the combination and sharing of information and knowledge (Razak et al., 2016), and enhance their willingness to repurchase. However, most brands haven’t realized that they can create more sustainable benefits from the social interaction of their design and planning (Chang & Zhu, 2012; Ghahtarani et al., 2020). The main reasons pointed out in this paper are: (a) it remains to be seen the key factors of BSI that affect consumers’ purchase intention; (b) It still needs further research to clarify the media via which BSI exerts influence on consumers’ purchase intention.
Some scholars believed that social interaction is closely related to social capital, whose establishment and maintenance rely on continuous social interaction (Chiu et al., 2006; Nahapiet & Ghoshal, 1998). Ghahtarani et al. (2020) showed that social interaction is a method for consumers to jointly obtain information resources. Regularly increasing social interaction can deepen familiarity, build social capital between the two parties, and significantly affect customers’ purchase intention. Social interaction is essentially defined as resource exchange of value, from which both parties can benefit; social capital is the total source of all value creation. Nahapiet and Ghoshal (1998) previously divided social capital into structural, cognitive and relational dimensions. Structural capital represents the mode of general communication between individuals and forms network connections between actors (Castro & Roldán, 2013). Cognitive social capital is a resource that promotes the perception among people, and between people and systems, building a system where users can share common meanings. Relational social capital is an interpersonal relationship developed by individuals through a series of interactions (X. Zhao et al., 2016). Though extensive research on the concept and dimensions of social capital has been conducted, fewer studies have explored the variables that might influence the closeness between social capital and BSI, which can be pursued further.
In addition, the social interaction between brands and their consumers can often be divided into two types: online interactions via social media, and offline events or activities organized by brands, both of which serve as important foundations for the formation of social capital (Guo et al., 2017; Li & Chen, 2022). Therefore, the factors affecting sustainable BSI should include both online and offline aspect. It should be noted that, first, brands discussed here are self-operated, like Apple and Xiaomi, rather than comprehensive brands like Amazon, selling a wide range of commodities either directly or as the middleman. Self-operated brands own self-established and self-hosted online brand communities, one of the key features of which is social interaction among consumers, and the sharing of information and knowledge in the interaction (Alden et al., 2016; Chiu et al., 2006; Tajvidi et al., 2020; Yahia et al., 2018). Second, online brand community will serve as the core social media for brand-consumer interaction in this paper to analyze the common factors of online social interaction, and conduct empirical research, because a large number of Chinese brands are striving to build online brand communities as their own social media to promote communication and build relationship between consumers and brands, showing the practical significance of the paper to take the online brand community as the research object; while at the same time, social capital and online brand communities have become major network research issues. Chiu et al. (2006) believed that a virtual community is an online social network where people with common interests, goals or practices share information and knowledge, and participate in exchanges and interactions. Frequent online social interaction promotes the forming of social capital, and social capital further affects consumers’ purchase intention.
Our research attempts to study the role of BSI factors in the formation of social capital from the perspective of social capital, and to dig deeper into the influence of social capital on consumers’ purchase intentions. In this research, we take (Guo et al., 2017) social capital framework as the overall theoretical framework to establish the relationship between BSI, social capital and purchase intention. The aim of this paper is to (a) explore online and offline factors that affect the social interaction between brands and their consumers; (b) identify social capital variables strongly associated with BSI; and (c) study the influence of BSI on consumers’ purchase intention combing these social capital variables.
Related Work
Brand Social Interaction and Social Capital
BSI is inseparable from the development of social media. Social media tools support social interaction and user contribution, focusing on content production, sharing and information exchange. It promotes buying and selling brand products (C. Wang & Zhang, 2012). Although the basic need of brands on social media is to deliver valuable and attracting information to consumers, some scholars believe that the social interaction between brands and their consumers via social media is more important (Hudson et al., 2016; Oncioiu et al., 2021). This paper defines BSI as a flexible and varied interactive form between brands and consumers based on social media, mainly divided as online and offline social interaction, for the purpose of consolidating the relationship between brands and consumers, and increasing consumers’ continued purchase intention. The literature research shows that social media involved in previous studies on BSI mainly related to non-enterprise operational social platforms such as Facebook, Youtube and Instagram (Castillo-Abdul et al., 2021; Khan, 2017; Qin, 2020), as well as online brand communities directly operated by brands (Choi et al., 2017; Rossolatos, 2021). Much work has been done to explore the relationship between the intensity of social interactions on Facebook and types of social capital (Chu & Kim, 2011; Ellison et al., 2007). Kim et al. (2020) have confirmed the influence of parasocial interaction on social capital and of social capital on consumers’ purchase intention by surveying users on YouTube. X. Yang (2021) discussed social interaction and the effect of different dimensions of social capital on purchase intention by the method of SEM and fsQCA. Research on BSI also focuses on online brand communities. Chiu et al. (2006) believed that a virtual community is an online social network where people with common interests, goals or practices share information and knowledge, and participate in exchanges and interactions. Through frequent online social interactions, brand communities increase communication among consumers, which strengthens the emotional connection between members and further establish identity, thus increase the possibility of members’ participation in virtual communities (Dholakia et al., 2004). Meanwhile, online BSI helps quickly form a community and breed a social relationship network, based on which a social bond will be gradually established among consumers (X. Wang & Feng, 2017). Therefore, the online brand community is an information system and also plays the role of social media. As many brands have integrated the online community into their profit model, the study of social interaction in the online brand community will provide more positive suggest for the sustainable development of enterprises. Obviously, based on non-enterprise operational and enterprise operational social media, the existing work has demonstrated the impact of social interaction between brands and their consumers on purchase intention. However, further excavation of the key factors supporting BSI will yield more clues. Therefore, this paper takes the online brand community as a media to further explore the online and offline factors that affect sustainable BSI.
Guo et al. (2017) took online brand communities as social media to explore the antecedents of social capital, summarized the social interaction factors related to brands into firm’s reaction, interaction support and offline activities, and explained the effect of these three factors on social capital. Online brand social interaction requires brand’s personnel to continuously exist in social media and provide consumers with prompt feedback from online interactions (Castillo-Abdul et al., 2021). Efficient online interaction reaction can exert a significant impact on consumers’ emotional tendencies, and positive emotions can improve consumers’ satisfaction with brands and even promote to create the popular identity of brands (Boenigk & Helmig, 2013). Meanwhile, some scholars believed that social presence is conducive to shaping immersion, and consumers with mobile immersion (flow experience) may participate in socialized business activities and further increase their purchase intentions (Huang, 2016). Compared with the extensive use of mobile immersion in studying online interactions (M. C. Lee & Tsai, 2010), studies about flow experience and social capital are relatively few (Chang & Zhu, 2012). Note that the perceptual elements such as facial expressions, postures, and gestures that can promote the formation of immersion rely on online interactive support. Users can truly perceive these social cues only in the interaction process, and Online interaction support plays a positive role in social capital (Liu et al., 2014). In fact, online interaction support is a necessary condition to promote the production of social capital, and is also the cornerstone of online social interaction between brands and consumers. Online interaction support can not only meet users’ own social interaction needs, but also accelerate the widespread of brand products, contents and hot topics, and drive to build word-of-mouth referrals for brands, which undoubtedly contributes to the formation of social capital.
In addition, offline activities may significantly affect the formation of social capital (Guo et al., 2017; Rui et al., 2015). As a supplement to the interaction of online brand communities, offline activities can not only effectively promote the familiarity among consumers participating in, but also empower users to participate in in-depth discussions and collaboration tasks, thus, to make up for the lack of reaction from online social interaction (Liu et al., 2014). In addition, the interaction of users in offline activities will produce an in-depth emotional response, which is not just a simple personal emotion, but also involves more advanced emotional connections. Collins (2014) pointed out in his book “Interaction Ritual Chain” that higher-level interactive situations (active participation activities with a common focus) are more likely to increase emotional connection, develop collective excitement, then enhance unity and identity, and ultimately strike a chord. In fact, international brands like Red Bull and Nike have always insisted on offline activities to enhance the stickiness between users and brands. Similarly, offline social interaction has also been diversified in China. Pop-up retails, art exhibitions, theme exhibitions and other offline social interactions attract a plenty of consumers to participate. Obviously, BSI can promote the relationship between brands and consumers as well as among consumers via the online community operated by the brand, and help brands maintain their social capital (Phua & Ahn, 2016). Therefore, previous work (Castillo-Abdul et al., 2021; Liu et al., 2014) has demonstrated that online social support, online interactive feedback, the sense of immersion, and offline activities can strongly support the realization of BSI and have an effect on social capital.
Social Capital and Purchase Intention
Purchase intention describes the psychological extent to which consumers form behavioral intentions to buy a product or brand, which is considered to be one of the main goals of brand interaction via social media. Social capital theory has been studied as a unique concept that affects purchase intention (Han & Lee, 2016; N. Kim & Kim, 2018; J. Kim et al., 2020; Y. C. Lee, 2017), and is considered as one of the important resources to increase consumers’ purchase intention (Tajvidi et al., 2020; X. Yang, 2021). For example, Yin et al. (2019) represented the dimensions of social capital as shared version, social interaction tie and trust, and the study showed that frequent interactions helped consumers integrate into the online community and form trust, which in turn reduced their suspicion of purchasing risks and increased websites members’ purchase intention In virtual communities, the familiarity of the structural dimension, the perceived similarity of the cognitive dimension and the trust of the relational dimension can all promote consumers’ online sense of belonging and further influence their purchasing decisions (Lu et al., 2016). Chiu et al. (2006) believed that identity refers to an individual’s sense of belonging and positive emotions toward a virtual community. Emotional identity promotes loyalty in a group environment and helps mirror the willingness of individuals to maintain firm relationships with online communities. Ciadini (2016) indicated that when people observe others’ behavior similar to theirs, the principle of social identity exerts the greatest influence. In fact, the identification of both the online brand community and the members of the community will have an impact on consumers’ purchase intentions. Meanwhile, structural social capital constitutes a valuable source of information benefits. Social tie involves intra-organizational relationships formed by members’ interactions (Guo et al., 2017; K. Y. Lin & Lu, 2011), which is a reason why consumers continue to engage in social interaction in online brand communities (Zhang et al., 2019). Once consumers obtain social capital in the relationship dimension in the online brand community, they will recognize the brand community more and hope to maintain a long-term relationship with the brand, which will greatly increase the possibility of consumers repurchasing. Previous studies have also demonstrated that good social interaction ties can affect consumers’ purchase intentions. Also, the cognitive dimension of social capital can be realized through a shared vocabulary and language, and a shared narrative. Individual narratives can describe and interpret personal experiences, and when shared with others, these narratives often turn to be co-created as shared narratives. Brands are more likely to exert a strong influence on Generation Z’s purchase intentions through narratives (Tabassum et al., 2020). Shared narratives enable social groups to construct shared understandings, such as shared values, attitudes, and beliefs, as well as shared goals, purposes, and visions. Narrative is a reconstruction of past experience, and sharing content with common experiences makes it easier for people to gather together. Shared narratives in a community can create, deliver, and develop new interpretations of events, thereby realizing a combination of multiple knowledge including a large amount of the consumer’s tacit knowledge (Nahapiet & Ghoshal, 1998). Dove (2015) indicated that by sharing participants’ experiences and stories, people can explore the surrounding environment from a new perspective. From the current point of view, brands should pay attention to the following points when forming a shared narrative: First, whether the narrative produces an emotional response to the wishes and preferences of consumers via attraction rather than compulsion; second, whether the brand’s narration is related to audiences’ life story, which will help stimulate resonance. Research suggests that although the concept of shared narratives has been proposed long ago, studies on BSI, shared narratives, and purchase intention is relatively few. As researchers have acknowledged the impact of social capital on consumers’ purchase intention, it is reasonable to explain consumers’ purchase intention from the perspective of social capital. However, opinion remains divided on this issue. For example, trust and social interaction shape each other, but they haven’t produced residuals in the form of social capital (Uslaner, 2004). Research (Chen & Chou, 2012; Guo et al., 2017) showed that trust can’t increase consumers’ continued intention to use a brand’s shopping site or their willingness to engage in online brand communities. In other words, unsustainable intention will lead to a reduction in the frequency of social interaction between consumers and brands, which in turn reduces the possibility of consumers shopping online. Therefore, this paper doesn’t take trust as the relational dimension of social capital.
Previous work (Chiu et al., 2006; Ciadini, 2016; Guo et al., 2017; K. Y. Lin & Lu, 2011), inspired this paper to adopt identity, social ties, and shared narratives as social capital which closely related to BSI and discuss their impact on purchase intention. In addition, identification is a long-term emotional response and commitment, which can better describe the relationship between users and companies (brands) in a business environment (H. Lin et al., 2014). Moreover, shared narratives can gather a lot more people with same interests and same values on social platforms built by brands, and form a strong resonance by sharing consumers’ own experiences and stories, thereby consolidating the relationship between consumers and the brand. Therefore, this paper declares that identification and shared narratives are more suitable as factors to explore the influence of BSI on purchase intention.
Hypothetical Model Construction
Relations Between Brand Social Interaction and Social Capital
Offline Activities and Social Capital
Face-to-face communication and interaction make it easier for consumers to establish good relationships with more flexible forms of communication and more true feelings, and it also makes them more inclined to deep communication and collaboration, which means that in offline social activities, users can better understand the brand and other users through interactions with each other, and also find people with similar interests or values, and enhance their sense of identity with the group. At the same time, users who participate in offline activities on the same theme will form a common experience and gradually derive emotional resonance, facilitating subsequent sharing of stories co-created with the brand. In addition, face-to-face offline social activities and environments can not only consolidate users’ existing relationships and expand new interpersonal relationships (Rui et al., 2015; Trudeau H & Shobeiri, 2016), but also enhance the stickiness and cohesion among community members and increase the social ties. Hypotheses are thereby proposed as follows:
H1 offline activities have a positive effect on identification
H2 offline activities have a positive impact on social ties
H3 offline activities have a positive impact on shared narratives
Online Interaction Reaction and Social Capital
Brand’s efficiency and attitude of online response will significantly affect the user’s emotional tendency (J. H. Kim et al., 2010). Positive online interaction reactions can not only improve user satisfaction, but also encourage consumers to form a sense of identity and belonging to the brand (Boenigk & Helmig, 2013; Li & Chen, 2022). Online interaction reaction ensures that online interactions focus on the brand’s own theme. In fact, users are more inclined to identify with the online brand community with clear themes (X. Wang & Feng, 2017). At the same time, timely interaction reaction facilitates the sharing and dissemination of common experiences and triggers emotional resonance among consumers. In addition, members of the enterprise often join in the online brand community as visitors. These members play an important role in solving users’ questions, adjusting their conflicts, and promoting interaction. Therefore, online interaction reaction from users and brand’s internal members is reasonable regarded as a positive role in building the bond between consumers and the brand. Hypotheses are thereby proposed as follows:
H4 online interaction reaction has a positive effect on identification
H5 online interaction reaction has a positive impact on social ties
H6 online interaction reaction has a positive effect on shared narratives
Online Interaction Support and Social Capital
It is through Online interaction support that consumers can collaborate to complete tasks, enjoy convenient online communication, and share their own experiences and stories, which triggers resonance, enhances emotions, and strengthens the social relationship between users. Meanwhile, we believe that good Online interaction support will play a positive role in promoting consumers to share brand stories and disseminate information. In addition, the interactive support of brand managers for online communities can also benefit the formation of social bonds (Guo et al., 2017; Liu et al., 2014; Tiwana & Bush, 2005). Hypotheses are thereby proposed as follows:
H7 Online interaction support has a positive impact on social ties
H8 Online interaction support has a positive impact on shared narratives
Immersion and Social Capital
Immersion is a flow experience that occurs when people are fully involved in a certain situation and ignore the surroundings. Hoffman and Novak (1996) believed that immersion can stimulate people to repeatedly participate in a certain activity, and people who are immersed will have a higher sense of satisfaction and loyalty than those who are not. In fact, immersion in online communities can make consumers increasingly exhibite swarm behavior in virtual communities (Lifang, 2018). It is believed that consumers immersing themselves in will fully participate in online social interaction and may trigger additional purchase intentions (Koufaris, 2002; Liu et al., 2016). Therefore, we believe that consumers will immerse themselves in online social interaction or offline activities organized by brands due to their interest of online brand communities’ information and other participants. In this process, deep immersion can not only make consumers happy and deepen their sense of identity, but also stimulate the formation of common experiences and subsequent stories, and encourage information sharing. Hypotheses are thereby proposed as follows:
H9 Immersion has a positive effect on identity
H10 Immersion has a positive effect on shared narratives
Relations Between Social Capital and Purchase Intention
The Impact of Identification on Purchase Intention
Chiu et al. (2006) believe that identification refers to people’s recognition of the knowledge of a social group or an organization to which they belong, along with some important values and emotional meanings among members. Ciadini (2016) indicated that when people are not sure about something, it is easier to decide based on the behavior of their kind. Identification can effectively influence people’s intentions and usage behaviors. Their recognition of other users in the online brand community can obviously affect their attitude toward the brand and their purchase intentions (Ho & Wang, 2015). Hypothesis is thereby proposed as follows:
H11 identification has a positive effect on purchase intention
The Impact of Social Tie on Purchase Intention
Social tie is a kind of community relationship within an organization, a relatively stable relationship established between individuals and individuals. It is formed through effective interaction between consumers (K. Y. Lin & Lu, 2011; Wasko & Faraj, 2005). The social interaction between members of the online brand community allows a more cost-effective way to acquire a wider range of knowledge sources, and recommendations from community members or acquaintances increase users’ purchase intention (T. Wang et al., 2021). Hypothesis is thereby proposed as follows:
H12 social tie has a positive effect on purchase intention
The Impact of Shared Narratives on Purchase Intention
Shared narrative can effectively gather people with the same experience in a group. Narratives connects people with each other in an interrelated and memorable way. Scenarios can help the audience accept new ideas, allow consumers to integrate into the role, and generate emotional connections. Consumers are glad to post moments on brand social media and share with friends or other consumers (Onofrei et al., 2022). Narratives can not only stimulate consumers to discuss similar experiences on social media and trigger their positive emotional responses, but also promote the sharing of content and influence consumers’ purchase intention (Tabassum et al., 2020; T. Wang et al., 2021). Hypothesis is thereby proposed as follows:
H13 shared narrative has a positive effect on purchase intention
Based on the above theoretical analysis, we believe that social capital is key between brand social interaction and consumer purchase intention. We categorize social capital into three dimensions: relational, structural and cognitive, which are represented by identification, social tie and shared narratives, respectively. Meanwhile, this paper proposes a set of hypotheses to explore the impact of online and offline brand social interaction factors on social capital. Figure 1 depicts the hypothetical model and 13 hypotheses proposed in this study.
Research hypothesis model.
Research Methods
Survey Design
A total of eight constructs have been tested in this study. Most measurement items on the questionnaire mainly referred to previous studies. The measurement items of online interaction support in the questionnaire mainly refer to the research results of Porter and Donthu (2008) and of online interaction reaction refer to that of Guo et al. (2017); of offline activities refer to the research design of Koh et al. (2007) and Ma and Agarwal (2007); of immersion the research of Liu et al. (2016) with appropriate modifications. Three measurement items of social capital mainly come from the research results of Chiu et al. (2006) and Guo et al. (2017), among which that of shared narratives are self-developed. The measurement items of purchase intention mainly refer to the research designs of Zhou (2019).
Since this research targets Chinese consumers while most items were originally created in English, we asked professional translators to translate them into Chinese and made necessary changes to make them easier to understand. The questionnaire adopts the 5-point Likert scale for scoring. Answers to the items contain five criteria, namely strongly agree, agree, neutral, disagree, and strongly disagree, coded as “5, 4, 3, 2, 1.”
Data Collection
The research hypothesis model collects samples from the online brand community (Meiju App) managed by Midea and carries out tests. Midea pays attention to the social interaction between users, and has built its own community on platforms such as Weibo earlier. Now the number of Midea’s followers on Weibo is close to 1.5 million. Midea Smart, one of Midea’s online communities, mainly includes several functions: support for online shopping; enable brand managers to share and advertise new products by post; promote social interaction, creation and collaboration among fans; reply to users’ ask about use and purchase; attract online users to offline activities; carry out brand social events. Thus, Meiju App is an ideal setting for our research.
To start with, before conducting a large sample survey, we have contacted the managers of Midea’s online brand community and obtained the contact information of 28 consumers who participated in both online and offline BSI. We conducted pilot surveys with them via email and offline interviews, and optimized the formal questionnaire. Then, we used the questionnaire-making software “Wenjuanxing” (literally “Questionnaire Star”) to formulate the interview questionnaire, and generate the web link and WeChat QR code of the official questionnaire. Afterward, with the authorization and help of the managers of Midea’s online brand community, the questionnaire launched in the Midea brand community in early January 2022, and was completely collected in mid-February 2022. A total of 460 questionnaires were distributed and 437 were returned, of which 395 were valid. Among the participants in the survey, males accounted for 45.7% and females 54.3%. In terms of geographical distribution, Guangdong (11.65%) and Jiangsu (11.23%) accounted for a major proportion, followed by Hunan (7.84%). The proportion of Shanxi are relatively close to that of Shanghai, namely 5.51% and 5.3% respectively, and followed by Henan (4.66%), Hubei (4.45%), Zhejiang (4.45%), Shandong (4.45%), Guangxi (4.24%) and Hebei (4.03%). Compared with provinces have mentioned above, respondents from Liaoning (2.97%), Fujian (2.75%), Jiangxi (2.54%) and Tianjin (2.33%) were relatively few. According to the overall geographical distribution, the questionnaire has basically covered East China, South China, and North China, as shown in Figure 2.
Geographical distribution of questionnaire participants.
Data Analysis and Results
Reliability Analysis and Model Matching Test
To verify the reliability of the questionnaire, a reliability test is required. This study adopts Cronbach’s α to test the reliability of the measurement. According to the rules, if the value of Cronbach’s α is above .7, it indicates that the questionnaire has good reliability. The scale reliability test results show that: Cronbach’s α value for offline activities is .763; online interaction support .761; online interaction reaction .732; immersion .764; identification is .758; social tie .733, shared narratives .754; and purchase intension .781. The reliability coefficients of the eight latent variables are all above .7, all passing the reliability test. In addition, the value of KMO (Kaiser-Meyer-Olkin) is .766, which is suitable for factor analysis. According to the results of exploratory factor analysis, factors OA1 to OA3, OIS1 to OIS3, OIR1 to OIR3, IM1 to IM3, ID1 to ID3, ST1 to ST3, SN1 to SN3 are all divided into their own principal components, and the research results are consistent with the theoretical structure of this scale.
AMOS24.0 software is used for structural equation model testing and validity testing. The values are all normalized estimates. The fitting path results of each variable in the model are shown in Figure 3. The path coefficients among the latent variables in the figure represent the degree of influence of one variable on another. For example, among the three social capital variables, the standardized path coefficient of identification on purchase intention is 0.14, of shared narratives on purchase intention is 0.45, and of social tie on purchase intention is −0.07. It shows that compared with identification, shared narratives make a deeper, positive impact on purchase intention, and the hypothesis that social tie positively affect consumers’ purchase intention is not supported. Regarding whether the research hypotheses are valid, and whether the loading coefficient and path relationship between variables are supported, a more detailed description is given below in conjunction with the significance level of path relationships. Based on the structural equation model, we conduct a model fit analysis. The index matching values are as follows: CMIN/df is 1.730 (Ideal range is 1–3), RMSEA is 0.043 (Ideal range <0.05), IFI is 0.937 (Ideal range <0.05). range> 0.9), TLI is 0.925 (Ideal range> 0.9), CFI is 0.936 (Ideal range> 0.9), PNFI is 0.740 (Ideal range> 0.5), PCFI is 0.803 (Ideal range> 0.5), all up to standard. In addition, the remaining statistical data of the remaining models are all within the ideal range, indicating that the structural model matches the scale well, as shown in Table 1.
Structural equation model and path analysis results.
Overall Fitting Coefficient.
Convergent Validity Test
The convergent validity test index refers to the average variance extracted (AVE). The larger the AVE value is, the more explanatory the corresponding items to the variable will be. The ideal range of AVE needs to be greater than 0.5. The specific results are shown in Table 2. The factor loads of the 24 test items are all greater than 0.63, indicating that the 24 test items can effectively reflect the content of the measured dimensions. The composite reliability can reflect the intrinsic quality of each factor. The test results show that the combined reliability of the scale is greater than 0.7, indicating that the intrinsic quality of the scale is good. Also, the AVE value is above 0.5, indicating that the scale has good convergence validity and effectively verifies that the scale is of good quality.
Convergent Validity Results.
Path Analysis and Hypothesis Testing
In addition, we use AMOS24. software and the maximum likelihood method to verify the hypothesis model, calculates the path coefficient and various fitting indicators, and the path relationship is at the 0.05 (
Path Analysis and Hypothesis Test Result.
Analysis result.
Discussion
This study has empirically tested the hypothetical model of brand social interaction on consumers’ purchase intention, excavated the key factors that affect brand social interaction and its relationship to social capital, and explored the impact of social capital on purchase intention. The findings provide strong support for the proposed model. The most obvious findings to emerge from this study are as follows:
First, we can see from Table 3 that, except H6 and H12 that failed the significance test, the other 11 hypothetical paths have all been supported by empirical data, and the positive correlation is significant. In terms of the influence of social capital on purchase intention, the research results showed that identification and shared narratives have significant effects on users’ purchase intention at the 0.05 and 0.001 levels respectively, which doesn’t support the argue that social ties has impact on purchase intention. The results demonstrate a positive relationship between identification and purchase intention, which is consistent with previous studies (Chiu et al., 2006; Ho & Wang, 2015; Kim et al., 2014), and reclarify that the role of relational social capital (Identity) in influencing consumers’ purchase intention. Additionally, the results emphasize the key role of shared narratives on users’ purchase intention, and provide more supports to the existing assertion that narratives positively affect purchase intention (Tabassum et al., 2020), and also enrich the existing theory that cognitive social capital affects purchase intention. Moreover, unlike previous findings (Wang & Zhang 2012; Zhu et al., 2016), the argue that social ties have impact on purchase intention doesn’t get supported in this study. Reasonable explanation should be that real interpersonal relationships among consumers may be more stable and firmer than virtual relationships among members of an online community (Dholakia et al., 2004), and information gained from stronger relationships often exert more influence on consumers’ purchasing decisions, while weak ties among members of online brand communities increase consumers’ perception of purchasing risk, which in turn affects purchase intentions. Meanwhile, this result may come from the selection of online brand community as the research vehicle. Compared with online communities, consumers have more acquaintances on social media such as Facebook, so the following research can further work on how social ties on social media such as Facebook, Twitter, YouTube affect purchase intention.
Second, regarding the effect of BSI on relational social capital, the results show that offline activities, online interactive feedback and immersion have a significant impact on identification, clarifying that offline social interaction activities organized by brands greatly contribute to the sense of belonging in the online community, which is consistent with previous findings (H. Lin, 2007; Rui et al., 2015). Meanwhile, online interaction reaction has a significant impact on identification at the level of 0.05, consistent with previous findings that online interactive feedback positively affects identification (Guo et al., 2017). That is to say, consumers are more likely to identify with the online community if they are satisfied with the help or feedback provided by the brand. Moreover, at the level of 0.001, immersion has a positive effect on identification, indicating that once users gain a sense of immersion, they will be more active and willing to share their purchase experience, product experience, and brand activities under the influence of pleasant emotions, which is of great help in enhancing their identity.
Third, regarding the effect of BSI on structural social capital, the study shows that offline activities, online interactive feedback, and online interactive support all significantly affect social bonds, which confirms the key role of offline activities organized by brands in promoting the formation of social ties. Specifically, brand offline activities allow face-to-face communication and interaction between users. Real contact and interaction can consolidate the interpersonal relationship between them, enhance mutual trust, and form a positive impact on social ties. This result once again validates the previous research (Tiwana & Bush, 2005; Trudeau H & Shobeiri, 2016). In addition, online interactive feedback has a significant impact on social relations, which is contrary to the previous assertion (Guo et al., 2017) that employees have to communicate with multiple consumers and answer their questions in a very limited time, making it difficult for brands to build close and long-term relationships with users. One possible explanation should be the popularity of online intelligent customer service, which can solve general problems of consumers in a short time through keywords; as for relatively complex problems, smart terminals will deliver to the brand employees, and let real personnel to communicate with consumers online, thereby improving the efficiency of the brand’s online interactive feedback. Moreover, online interaction support also has a positive impact on social ties, which is consistent with previous research results (Guo et al., 2017; Liu et al., 2014). Good interaction support promotes users to have a deeper understanding of other users and consumers of the brand, which may expand their social networks and consolidate existing social relationships.
Finally, regarding the role of brand social interaction on cognitive social capital, the results show that offline activity, online interactive support and immersion have a significant impact on shared narratives, suggesting that offline activities increase interactions between consumers and the brand, as well as among other consumers, which shapes a shared brand-related experience and even a shared brand story, an integral part to fostering shared narratives. Consumers who co-participate in the same brand activity are more likely to discuss and share their experience about the activity as a story in an online community. Meanwhile, online interaction support has been confirmed to have a significant impact on shared narratives, which means the diversification of online interaction technologies and interaction methods has increased users the frequency and the length of time spent on online communication, and made it easier for consumers to describe their own experiences or stories related to brands in online communities, arousing common discussions and sharing. Also, a good sense of immersion helps users spend more time browsing brand products, services, and related brand activities. Obviously, immersion in an online brand community increases the chances of consumers discovering similar interests or experiences, which benefits consumers in expanding, discussing and sharing resonant narratives and to create shared narratives. However, the hypothesis that online interactive feedback has an impact on shared narratives was not supported in the study. A reasonable explanation is that, to users, since narrative is a reconstruction of past experiences, interaction reaction may be affected by personal habits, cognition, and memory. Thus, each one’s description of the same experience may appear different, which causes contradictions and hinders shared narratives. In addition, not all users own shared experiences under the brand’s organization, and some of them may not understand others’ sharing, and may even give negative reaction, which hinders users from sharing common experiences or affairs created by the brand. Therefore, future work should be encouraged to checkout which online interaction reaction or management mode can promote the formation of shared narratives, thereby enhancing users’ purchase intentions.
Conclusion and Implication
This study adopts hypothetical model proposed by Guo et al. (2017) to study the determinants of online and offline BSI on users’ purchase intention from the perspective of social capital. Our results enrich existing studies referring to the influence of BSI on users’ purchase intention, increase the understanding of the influencing factors that support brands and consumers to have social interaction, and provide practical suggestions for brand managers to carry out more targeted and efficient brand social interaction.
Theoretical significance
It contributes to the relevant research on BSI, social capital and purchase intention in several aspects. First, although how social interaction between brands and consumers affects consumers’ purchase intention has become the focus of social commerce research, research on the factors that specifically affect BSI in social media hasn’t obtained enough attention. Therefore, this paper clarifies the factors that affect the social interaction between brands and consumers, and divides them into two types: online factors (online interaction reaction, online interaction support, and immersion) and offline factors (offline activities). At the same time, this study has explored social capital variables (identification, social tie, and shared narratives) that are closely related to BSI, and build a research model combining the above two. The results show that except that online interactive feedback has no effect on shared narratives, other online and offline BSI factors can significantly affect the formation of social capital, which lays the foundation for more extensive exploration of key factors affecting BSI in the following research.
Second, the empirical findings show that identification and shared narratives positively affects purchase intention, and shared narratives have a stronger influence on purchase intention than other variables, which emphasizes the dominant role of cognitive social capital on users’ purchase intention. It suggests that vivid narratives tend to stimulate users’ resonance, and resonance increases purchase intentions. Besides, shared narratives are more likely to gather people of like mind and even form a culture circle. Therefore, shared narratives are not only conducive to the spread and development of brand’s culture, values, stories, etc., but also can highly awaken users’ emotions with a continuous positive impact. There’s a reasonable prospect that shared narratives will attract uses to continuedly pay attention to the brand and its products and/or services in a richer form, especially when new members join the brand online community.
Third, offline activities, online interactive support, and immersion contribute to shared narratives, while offline activities and the shaping of immersion exert the most powerful impact on shared narratives. Shared narratives are co-created through social interaction in the pursuit of meaning. On the one hand, offline activities enable consumers to communicate face-to-face and participate in the same brand activities, which not only helps consumers to form a common experience, but also helps them interpret and understand their experience in a common way. On the other hand, the shaping of immersion prompts consumers to continuously read and browse in online brand communities, discovering content related to their own experiences, and triggering wider discussions and sharing. Therefore, following work may further explore which specific types of offline activities (e.g., parent-child activities, visiting activities) organized by brands that are more likely to stimulate consumers’ to create narratives on brand social media, as well as dig deeper the factors that contribute to immersion in online social media.
In conclusion, contrary to expectations, the study found that social ties had no effect on purchase intention, which is inconsistent with previous studies (K. Y. Lin & Lu, 2011; Wasko & Faraj, 2005) that claimed that social ties play a positive role in increasing purchase intention. The study argues that the instability of social relationships on social media provides an insight for future research. Future work should be done to further investigate the impact of different types of social relationships on brand social media on purchase intentions under BSI.
Practical Significance
Our research also provides practical implications on how to improve consumers’ purchase intention via brand social interaction. First, due to the significant impact of offline activities on the structure, cognition and relation of social capital, brand managers should formulate a reasonable plan, regularly carry out offline activities closely related to the brand, and even expansion sports. They can publish theme activities through channels like online communities and Weibo, to attract and encourage users’ participation. Meanwhile, with open and creative mind, managers can recruit high-quality users to participate in the design and planning of offline activities. Listen to get to know their actual needs and inner thoughts to make activities customized, and form a set of targeted design principles for the enterprise and provide corresponding guidance for the subsequent activities. Second, data analysis results indicate that immersion significantly affects identification and shared narratives. This requires managers to be user-centric in the preliminary research and planning, paying special attention to the sensory stimulation (style, color, graphics, icons of website) personalized needs (DIY customization), interaction methods, emotions, and other factors that can promote users to immerse themselves. Finally, because brand social interaction factors have positive impact on the development of social capital, online brand managers need to improve the efficiency and service quality of online interactive feedback. In case that consumers’ narratives on a brand’s social media may not be endorsed or shared by other consumers, managers need to weigh the content of narratives, actively communicate with consumers and optimize, enhance the connection between narratives and reality, make up for important details, and ensure the fidelity and coherence of narratives.
Research Limitations
However, this study has several limitations. First, the study has selected a social interaction carried out by one brand to test our model, and further study are needed to test whether the social interaction of other brands meets the research results, due to different types of brands show differences and diversity in the way they organize and carry out social interactions, as well as the behavior and motivation of members participating in social interactions vary. Second, in the selection of social media, this paper chose the online community operated by brands as the object. Further proof needs to be done whether these BSI factors are also effective in the social media operated by the non-brand. Moreover, this article hasn’t discussed the internal relationship between online interaction support, online interaction reaction, immersion, offline activities and other influencing factors, and whose direct impact on users’ purchase intention. This provides a certain entry point for follow-up research. Besides, this article only discusses the influence of part factors of online and offline BSI (offline activities, online interaction support, online interaction reaction, immersion) on social capital, failing to cover all determining factors of social capital. Therefore, future work is expected to make a supplement in other BSI factors that promote the development of social capital. Therefore, future work is expected to complement other BSI factors that promote the development of social capital, as well as increase consumers’ purchase intention.
Footnotes
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