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Article

Emotional Attachment in Social E-Commerce: The Role of Social Capital and Peer Influence

by
Jianwen Yan
,
Siwei Zhang
* and
Siqi Zhang
School of Management, Hefei University of Technology, Hefei 230009, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 4792; https://doi.org/10.3390/su15064792
Submission received: 1 February 2023 / Revised: 2 March 2023 / Accepted: 6 March 2023 / Published: 8 March 2023
(This article belongs to the Special Issue Consumer Behavior in the Mobile Commerce and Social Media Sphere: Limits and Challenges for Companies)
Browse Figures
Versions Notes

Abstract

:
As competition in the social e-commerce industry intensifies, building high-quality relationships with users to increase customer loyalty and gain sustainable competitive advantage is important for platforms. Based on the perspective of social capital, this paper constructs a relationship model of “social capital-peer influence-emotional attachment” based on Red Booklet and Poizon users and explores the influence and mechanism of social capital on emotional attachment in the context of social e-commerce. Social capital has a significant positive effect on peer influence and emotional attachment, while peer influence has a significant positive effect on emotional attachment and partially mediates the relationship between social capital and emotional attachment. This study provides practical insights from the perspective of “social capital” for enterprises to improve the users’ emotional attachment to the platform and further develop themselves in the social e-commerce environment.

1. Introduction

As a new type of e-commerce derived from social relationship networks, social e-commerce mainly refers to “social + e-commerce” [1], which was proposed by Yahoo in 2005. In recent years, social e-commerce has been rising rapidly around the world, such as on Instagram, Facebook, YouTube, etc., which sellers can use to facilitate transaction closing. Especially in China, which has a huge consumer market and development potential, the social e-commerce industry is diversifying. Its main types and typical platforms can be seen in Table 1. However, with fierce competition and low user conversion costs in the social e-commerce industry, companies face serious challenges in building lasting and strong relationships with their users. Emotional attachment is the main antecedent variable that leads to sustained user usage [2]. Thus, an in-depth understanding of the formation mechanism of emotional attachment in the social e-commerce environment and the promotion of emotional connection between users and the platform has become an important issue that platforms urgently need to, and must, address.
The current research on emotional attachment focuses on the person-to-person and person-to-subject levels. In terms of person-to-person, emotional attachment is derived from attachment theory, which was first used to study the relationship between infants and their mothers [3]. Since the field of attachment research expanded from parent–child attachment to adult attachment in 1987, research has focused on the types, functions, and roles of adult attachment. In terms of people and specific objects, Schults et al. introduced attachment theory to the field of marketing to explore the intimate relationship between people and brands. Some scholars later applied attachment theory to study the antecedents and outcomes of brand community attachment [4], celebrity attachment [5,6], and place attachment [7]; some scholars also divided attachment into shared identity and shared connection [8].
Research on specific objects has not yet formed a consensus, most research on specific objects focuses on places, brands, etc. However, research on e-commerce platforms is very scarce. Secondly, the studies mainly focus on behaviors arising from emotional attachment. Some scholars have proven that brand attachment has a positive impact on users’ behaviors such as participating in brand communities [9], receiving brand extensions [10], and investing additional resources [2]. Again, in the small number of studies on the antecedents of emotional attachment, the generation of emotional attachment has been studied mainly from a technological perspective. For example, Namjoo Cho considers the characteristics of information systems: relative visual aesthetics, personalization, and relative performance as antecedents of emotional attachment [11]. However, the influence of non-technical factors, such as social capital, on the production of emotional attachment is neglected.
Further, social e-commerce is developed based on social relationship networks [12]. Compared with traditional e-commerce, the users’ shopping mode is transformed from active search to passive discovery, and users are both consumers and promoters. Users interact socially and recommend products through social networks to support other users’ decisions and assist in online shopping [13,14], a process that is essentially peer-to-peer influencing. Not only does peer influence become more prominent and pervasive in social network contexts [15], but it is also related to the particular network structure and resources in which it is embedded, i.e., to the social capital that users possess on the platform. Social e-commerce platforms are highly interactive [16] and users form intricate networks of relationships through interactions that fulfill their needs and facilitate the creation of emotional attachments. Once formed, the users’ attachments to the platform are difficult to break and promote continued use of the social e-commerce platform [17]. It is crucial for e-commerce platforms to build relationships with users in order to form emotional attachments. Therefore, an in-depth analysis of the social capital and peer influence in social networks and their impact on emotional attachment is a key issue to be addressed.
In summary, based on theoretical and practical needs, we try to ask and answer the following questions: How does social capital enhance users’ emotional attachment to the platform in the social e-commerce environment? What is the role of peer influence in the relationship between social capital and emotional attachment? How can users’ emotional attachment to the platform be enhanced in management practices? The responses to these questions aid in directing the present study. Based on social capital theory, this paper explores the influence of social capital on emotional attachment in the social e-commerce context and its mechanisms of action by constructing a structural equation model, taking the users of Red Booklet and Poizon social e-commerce platforms in China as research objects. The results of the study showed that social capital and peer influence all had a significant positive effect on emotional attachment. This broadens the scope of attachment theory and introduces peer influence theory into the field of marketing. Moreover, it indicates effective strategies for companies to enhance the users’ emotional attachment to platforms and further their development in the social e-commerce environment.

2. Literature Review

2.1. Social Capital Theory

Since 1980, when sociologist Pierre Bourdieu first defined “social capital” systematically, more scholars have been exploring and defining the definition of “social capital” from various perspectives. From the perspective of networks, social capital is inseparable from the possession of social networks; from the perspective of functions, social capital can bring convenience to individuals in social structures and improve social efficiency through trust, norms, and networks [18]; from the perspective of resources, social capital is a resource that can be rewarded by being embedded in social structures [19]. Thus, this paper argues that social capital is a resource that can be rewarded through mutual trust and norms based on social relationship networks.
The most influential divisions of social capital dimensions are the two-dimensional theory [20] and the three-dimensional theory [21]. Granovetter (1985) divides social capital into structural and relational dimensions [20], and Nahapiet and Ghoshal (1998) add a cognitive dimension to it [21]. The structural dimension is based on the structure of connections formed by social interactions and the closeness of the connections [22]; the relational dimension refers to the mutual relationships formed between members, measured by trust and reciprocity [23]; the cognitive dimension is the joint depiction, understanding, and significance among actors [24], mainly consisting of a common language and a shared vision. Cultural capital, on the other hand, refers to the capital constituted by culture (values, beliefs, behavioral norms, and patterns), as well as the material carriers of culture. Combined with the concept of cultural capital, this paper argues that the cognitive dimension should fall under the category of cultural capital. Additionally, by joining social e-commerce platforms, we discover that most users on the platforms do not share common goals, visions, etc. Therefore, the cognitive dimension is not the focus of this paper. This paper will continue Granovetter’s research by dividing social capital into structural and relational dimensions.
With the development of information technology, people started to pay attention to social capital in social media. Although some scholarly studies conclude that social media use leads to a decline in social capital [25], most scholars believe that the use of social media promotes the accumulation of social capital [26]. Social capital influences a person’s behavior. Molly McLure Wasko et al. found that personal motivation and social capital promote knowledge contribution [27]. Social capital also affects users’ emotions. Asha Thomas and Vikas Gupta argue that social capital affects a person’s financial well-being [24].

2.2. Emotional Attachment

Attachment first originated from the study of mother–infant relationships and can prompt infants to seek the care and closeness of their mothers in order to feel secure [3]. Into the growth period, this attachment will evolve into a relationship with friends, lovers. With the deepening research, the study of attachment has developed from between people to the relationship between people and specific objects, which is the emotional bond between individuals and specific objects, such as brand attachment in marketing as the emotional bond between individual consumers and brands [4]. Referring to previous studies, this paper defines the emotional attachment of social e-commerce platforms as the special emotional connection of users to social e-commerce platforms [2,4].
Based on Self-Determination Theory (SDT), attachment emerges because the continuous satisfaction of a specific object to an individual’s needs motivates the individual to regard the specific object gradually as part of their self-concept. For example, Faheem Gul Gilal and Jian Zhang’s study proved that satisfying consumers’ needs through product design can promote emotional attachment to the brand [28]. On the one hand, the satisfaction of consumer needs makes consumers willing to pay extra money, time, energy, and other tangible and intangible personal resources for it [29], resulting in premium purchases, positive word-of-mouth communication, persistence, and other behaviors [2,9,30,31]. On the other hand, being attached to an object that satisfies the needs of the attached person can also provide the attached person with a sense of emotional security [32] and promote positive user behaviors such as user stickiness and continued use of the information system [33]. Thus, the satisfaction of users’ needs by social e-commerce platforms will cause users to incorporate the platform into the self-concept, leading to the creation of emotional attachment, which will promote the continued use of the platform.

2.3. Peer Influence

American educator Coleman (1961) first studied peer groups, and he found that adolescents are more likely to influence each other, and this influence is greater than the influence of teachers and schools on adolescents. With the development of the Internet and social networks, the scope of peers has expanded further, while consumers who use the same social media, individuals with common interests, or similar preferences are peers [34,35]. Therefore, users who use the same social e-commerce platform due to similar interests, preferences, and so on are peers. The interaction of users on the platform is essentially the process of peer influence [36], wherein peer influence in the context of social networks is a social psychological process in which users with similar interests and preferences interact with the same social relationship network, thereby changing each other’s views, attitudes, or behaviors [37,38].
Peer influence arises when individuals select peers to build social networks, interact with each other, and are socialized, which influences their choice of social objects, thus evolving in a continuous cycle and synergistic evolution, resulting in individual and peer convergence. Peer influence is divided into informational influence and normative influence, drawing on social influence theory: informational influence refers to changes in individuals’ perceptions and understanding of things as a result of information provided by peers; normative influence refers to individuals’ convergence with peers in attitudes and behaviors to avoid punishment and conform to peer expectations. Unlike general interpersonal influence, peer influence is more profound because of the similarity between peers.
In social networking contexts, peer influence is prevalent [39] and significantly stronger [34], and even plays a decisive role in consumers’ purchase intentions [35]. Previous studies have focused on exploring peer influence on user purchase behavior. For instance, Arpita Khare examines peer influence impacts on green apparel purchase behavior [40]. Jaemin Jung et al. expanded the study to demonstrate that peer influence impacts attitudes and behavioral intention toward social networking advertising [41]. Zhiguo Zhu et al. went further and explored the key factors of peer influence on users’ purchases [42]. However, previous studies have neglected the study of peer influence on users’ behavior in using the platform.

3. Research Hypothesis and Model

3.1. Social Capital and Emotional Attachment

An increase in the two dimensions of social capital can promote the users’ emotional attachment to the platform. The higher the social capital structure dimension, the stronger the social connection between members, who can establish and maintain connections with other people, gain social and informational support, dispel loneliness, and satisfy their own needs [43]. The relationship dimension mainly comprises norms of trust and reciprocity. The presence of relational capital on the platform affirms users’ own value, which leads to a sense of belonging to the community and further spending more energy and time on it [44]. The satisfaction of consumer needs by the platform makes users feel positively emotionally connected, causing them to see the platform as an integral part of themselves, thus facilitating the creation of emotional attachment [17,45]. Thus, the following hypotheses are proposed.
Hypothesis H1a.
The social capital structure dimension has a significant and positive effect on emotional attachment.
Hypothesis H1b.
The social capital relationship dimension has a significant and positive effect on emotional attachment.

3.2. Social Capital and Peer Influence

The higher the structural capital in a social e-commerce platform, the stronger the social interaction links between platform users. Additionally, the more interaction and the more frequent the information exchange [46], the greater the influence of peer-to-peer information. The higher the structural capital, the closer the relationship between users, and the easier their behavior is to be observed by surrounding users [47], generating greater peer pressure. Thus, users may choose to be accepted and approved by their peers to reduce pressure and be more susceptible to normative influences. Trust is a prerequisite and necessary condition for peer influence to occur [15] and is one of the most important factors influencing consumers’ willingness to shop online [48]. The higher the relational capital in social e-commerce platforms, the higher the mutual trust of users and the more frequent the interactions. Therefore, the more conducive the social relationship network composed of consumers is to the function of information collection and transmission, and the more capable it is of exerting inter-peer informational influence [49]. The presence of reciprocity rules can lead consumers to believe that active participation can lead to feedback and rewards. It will also lead to changes in individuals’ attitudes and behaviors, thus contributing to the generation of normative influence. Therefore, the following hypotheses are proposed.
Hypothesis H2a.
The social capital structure dimension has a significant and positive effect on peer influence.
Hypothesis H2b.
The social capital relationship dimension has a significant and positive effect on peer influence.

3.3. Peer Influence and Emotional Attachment

Peer influence and emotional attachment are significantly related. Based on uncertainty reduction theory, individuals actively seek out information to reduce uncertainty. The higher the individual’s uncertainty, the greater the degree of influence by others [50]. However, based on social identity theory, individuals will produce convergent outcomes with their peers to reduce peer pressure and gain peer acceptance and approval. Therefore, consumers spend more time and energy actively interacting on social e-commerce platforms to obtain information, eliminate uncertainty, reduce purchase risk, and gain peer acceptance, among other things. According to self-determination theory, peer influence to satisfy the users’ needs for information and relationships drives the formation of emotional attachments to social e-commerce platforms. Thus, the following hypothesis is proposed.
Hypothesis H3.
Peer influence has a significant and positive effect on affective attachment.

3.4. The Mediating Role of Peer Influence

The occurrence of peer influence requires a specific social network and is prevalent [15,49]. In social e-commerce platforms, with the accumulation of users’ structural capital and relational capital, the more closely connected the platform users are, the higher the mutual trust [51], and thus the relatively greater the force generated [15]. While users spend more time and effort browsing information and interacting on the platform, and building trust in the process, to obtain the information they want, reduce the risk of decision-making, and obtain group approval, the more they can exert peer-to-peer influence. The more information and social support peer-to-peer interaction brings to users, the more positive the emotional connections such as warmth and a sense of belonging that are created, which leads to the creation of emotional attachments to the platform. Thus, the following hypotheses are proposed.
Hypothesis H4a.
Peer influence mediates between the structural dimension of social capital and affective attachment.
Hypothesis H4b.
Peer influence mediates the relationship dimension of social capital and affective attachment.
Thus, the research model for this paper is shown in Figure 1.

4. Methodology of the Study

4.1. Questionnaire Design

The variables examined in this paper include: social capital, peer influence, and emotional attachment. Social capital is divided into two dimensions: structural and relational; peer influence is divided into two dimensions: informational influence and normative influence. The measures of the variables in this paper are based on established scales and adapted to the characteristics of social e-commerce platforms to make them easy to understand. Once the scales were designed, renowned professors in the field were invited to revise any issues that were not clearly expressed to determine the final scales.
Social capital is divided into a structural dimension and a relational dimension, with the structural dimension measured through social interaction linkages and reflected in the frequency, density, and breadth of communication between individuals and other members of the platform [52]. Drawing on the scale designed by Chiu et al., three questions were designed, which include “I spend more time interacting with some members of the community” [52]. The relationship dimension is mainly measured by trust and reciprocity, which refers to the user’s belief that the information in the social commerce platform is trustworthy and that helping others will receive feedback and rewards. The scale designed by Wasko and Faraj [27] and Chiu and Hsu [52] has four questions, which include “I believe that the information posted or shared by members of this community is true”, etc.
Based on Deutsch [53], Kaplan [54], and Bearden [55] et al., this paper divides peer influence into informational and normative influence. According to the scale designed by Bearden [55] et al., the informational influence scale consists of three questions, which include “To ensure that I can buy the right items, I often ask or observe the purchases of community members” and the normative influence scale consists of three questions, which include “When purchasing items, I usually choose those items that are approved by community members”. Based on the scale designed by Park [29], the emotional attachment scale was designed with five questions, which include “I feel very good when I use the community”. All items on the scale were rated on a five-point Likert scale and respondents rated each item honestly according to their experiences and circumstances.

4.2. Sample Selection and Data Collection

This paper mainly focuses on the generation of emotional attachment through the influence arising from users in social networks. Therefore, this paper tends to focus on social content e-commerce platforms and Red Booklet and Poizon as typical social content e-commerce platforms in China which has the largest social e-commerce scale: Red Booklet was selected as the seventh in the list of “China’s Top Ten Unicorns” in December 2021, with over 200 million monthly active users; Poizon App, through the dual business model of “community + e-commerce”, uses “socialization” to rapidly attract a large number of young people, with one in three young people using Poizon App. Therefore, this paper investigates the relationship between social capital and users’ emotional attachment in the social e-commerce environment by selecting users of Red Booklet and Poizon as the respondents.
The questionnaires were distributed in two main stages: the first stage was a pre-test of the questionnaire. After the questionnaire was designed, 42 users were selected for a small-scale survey, and the results show that the questionnaire had good reliability and validity. The second stage was the formal distribution of the questionnaire. The survey was released on two platforms, Red Booklet and Poizon, then the link to the questionnaire was distributed to Red Booklet and Poizon users through social networking sites and instant messaging tools such as WeChat’s circle of friends and Weibo. The main targets for distribution were university students and white-collar workers, which matched the profile of the main users of Red Booklet and Poizon. The questionnaire was officially distributed over a 12-day period from 23 April 2022 to 4 May 2022. A total of 251 questionnaires were collected, 49 invalid questionnaires with less than 60 s of answer time and the same answer were excluded. A total of 202 valid questionnaires were collected, with a valid return rate of 80.48%. The basic information of the survey sample is shown in Table 2.
Table 2 presents the demographic information of the sample. The percentage of female respondents was 63.37%, and the respondents who had experiences using social e-commerce within 6 months comprised 30.69%; 6 months–1 year, 25.25%; 1 year–3 years, 29.70%; and more than 3 years, 14.36%.

5. Analysis of Data

5.1. Measurement Model Testing

Model fit is a prerequisite for model testing, and if the fit is not up to standard, the significance of the path coefficients will be meaningless. Therefore, we used MPLUS version 8.3 for confirmatory factor analysis and obtained the following values: χ2/df = 305.88/121 = 2.53, CFI = 0.919, SRMR = 0.073. These values are within the acceptable limits and demonstrated the satisfactory fit of the hypothesized model with the data [56].
We further analyzed the reliability and validity of the scales in this paper by using SmartPLS software, as shown in Table 3. The reliability of the scale was measured by the Cronbach’s alpha coefficient and the combined reliability (CR), both of which were greater than 0.7, indicating that the internal consistency of the scale was good. The validity of the scale was measured mainly through convergent validity and discriminant validity. The standardized factor loadings and the average variance extracted (AVE) for the scale were greater than 0.5, indicating that the scale has good convergent validity. Table 4 shows that the square root of each latent variable AVE is greater than 0.5 and is greater than the standardized correlation coefficient between each latent variable, indicating that further analysis can be conducted on the measurement model of this study.
R2 (Coefficient of Determination) can be used to illustrate the explanatory power of a model, with larger R2 values indicating that the measured variables have greater explanatory power for the latent variables. According to the rule of thumb for marketing research, when the R2 values of the endogenous latent variables are greater than 0.67, 0.33, and 0.19, respectively, the explanatory power of the model is substantial, moderate, and deficient, respectively. The R2 values for peer influence and emotional attachment in this study were 0.527 and 0.576, respectively, both greater than 0.33, which are moderate levels, thus indicating that the model has good explanatory power. Stone-Geisser’s Q2 indicates the predictive relevance of the model, while the Q2 for peer influence and emotional attachment in this study were 0.312 and 0.387, respectively, both of which were greater than 0, indicating that the theoretical model in this study had good predictive power. Therefore, this study’s structural model is robust.

5.2. Common Method Bias and Variance Inflation Factor

Common method bias is a systematic bias caused by the same data source or rater, the same measurement environment, etc. However, we tested model fitness by concatenating all observed variables to a latent variable. The results showed that: χ2/df = 719.069/135 = 5.33, CFI = 0.745, SRMR = 0.083. All indicators were lower than the fitness indicators and normal indicators of the measurement model in this paper, indicating that the common method bias in this study was not significant. We also tested the overall variance inflation factor (VIF) to detect multicollinearity among the hypotheses, which was 1.506–2.841, lower than the suggested value of 5 [57]. Therefore, multicollinearity is not a concern in this work.

5.3. Hypothesis Testing

The path relationships of the conceptual model were estimated using the bootstrap resampling method (N = 5000) in the SmartPLS software, while the results are shown in Figure 2 and Table 5. The path coefficients of the structural and relational dimensions of social capital on emotional attachment were 0.278 (t = 3.738 > 1.96) and 0.225 (t = 2.598 > 1.96), respectively, indicating that hypotheses H1a and H1b held. It shows that the structural dimension of social capital and the relational dimension have a significant and positive effect on emotional attachment. The path coefficients of the structural dimension of social capital and the relational dimension on peer influence are 0.334 (t = 4.782 > 1.96) and 0.471 (t = 7.618 > 1.96), respectively, indicating that Hypotheses H2a and H2b are valid. It shows that the social capital of the social e-commerce platform, including the structural dimension and relationship dimension, has a significant and positive effect on users being influenced by peers. The path coefficient of peer influence on emotional attachment was 0.366 (t = 3.686 > 1.96), indicating that hypothesis H3 holds, and peer influence has a significant positive effect on emotional attachment.

5.4. Testing for Mediating Effects

To explain the role of peer influence between social capital and emotional attachment further, the bootstrap method in smartPLS software was used to test and analyze the mediating effect of peer influence. The bootstrap sample size was set at 5000 and the results of the analysis were shown in Table 6, using percentile confidence intervals (PC) with bias-corrected confidence intervals (BC) at 95% confidence intervals for the structural dimension → peer influence → emotional attachment and the VAFs of [0.054, 0.193] and [0.072, 0.282] at 95% confidence level for PC and BC, respectively, both excluding 0, which indicates that the indirect effect of peer influence exists, while hypotheses H4a and H4b are valid, thus partially mediating the structural dimension–emotional attachment and relational dimension–emotional attachment pathways.

6. Discussion and Conclusions

6.1. Research Findings

We used Red Booklet and Poizon users as research objects to explore the influence of social capital on emotional attachment and the role of the mechanism of peer influence among e-commerce platform users between the two. We used structural equation modeling the and bootstrap method to analyze the relationship between social capital–peer influence–emotional attachment. The results showed that:
(1)
The structural dimension of social capital and the relationship dimension have a significant positive effect on emotional attachment. This finding confirms the claim of previous studies that the higher the social capital in a social e-commerce platform, the higher the degree to which users develop emotional attachments to the platform [30,33]. Based on this, we further subdivided the social capital dimensions and determined that structural capital promotes users’ emotional attachment to the platform more than relational capital. This is due to users building social circles on the platform, forming interpersonal attachments with other users in their interactions, as well as investing more resources before forming attachments to the platform.
(2)
Social capital on social e-commerce platforms comprises structural and relational dimensions, which have a significant and positive effect on users being influenced by their peers. This expands on previous literature in the area of peer influence [36,38,40]. Bogdan Anastasiei et al.’s study found that people who used social media to stay connected were more receptive to their peers’ recommendations and endorsements [39]. Further, this paper finds that the relational capital of social e-commerce platforms has a greater impact on the peer effect on users compared with structural capital. This is due to the fact that the nature of peer influence is a social psychological process of interaction between individuals [2] and that connection is a prerequisite for good interaction patterns, but it is trust and reciprocity that are important factors in facilitating users to interact [48].
(3)
Peer influence has a significant and positive effect on emotional attachment and plays a partially mediating role in social capital and emotional attachment. Structural capital and relational capital may have a significant positive effect on emotional attachment through peer influence. Peer influence mediates more between structural dimensions and affective attachment than between relational dimensions and affective attachment. This indicates that in social commerce platforms, structural capital is more likely to increase the users’ affective attachment to the platform through peer influence.

6.2. Theoretical Contributions

This paper reveals the mechanism of action that generates emotional attachment between users and social e-commerce platforms. It deepens the study of attachment theory in the context of human–object attachment and complements and develops attachment theory. It provides ideas on how to enhance the users’ emotional attachment to the platform and thus promote the development of social e-commerce platforms. Using social e-commerce as a research context, the social capital perspective is used to study users’ attachment to the platform, promoting the integration of theory and practice, while providing a new entry point for future research on social e-commerce platforms and emotional attachment. This paper attempts to introduce peer influence as a mediating variable to confirm the social capital–peer influence–emotional attachment relationship. While research on peer influence has been multi-disciplinary, it is less so in the field of marketing. This paper explores peer influence in a social networking context to inform the development of peer influence theory in the marketing field.

6.3. Practical Recommendations

Combined with these results, relevant recommendations are made for the development of social e-commerce enterprises.
First, the structural capital of social e-commerce platforms should be improved. On the one hand, platforms should promote social interaction connection between users. Connection is the premise of good interaction mode, social e-commerce can be directly logged in through other social accounts to pull in the users’ social relationship chain, combined with big data pushing nearby people or people you may know, as well as to enhance the number of users’ friends; on the other hand, stimulating users to interact can increase the interaction between users through likes, comments, and so on, through platform updates. Platforms should promote user and enterprise interaction.
Second, it is important to improve the relationship capital of social e-commerce platforms. To enhance trust among users and between users and the platform, the platform should improve the auditing and gate-keeping mechanism, strictly prohibit the violation of users’ personal privacy, strictly control false and undesirable information, and create a clear cyberspace; they should promote the integration of online social networks and offline interaction by holding online and offline activities to enhance trust among users. A sound reward system should be established to provide spiritual rewards, such as medals, as well as material rewards, such as the distribution of platform peripherals, to users who are more active and well-known on the platform and who have contributed to the platform.
Third, companies can use peer influence to promote the users’ emotional attachment to the platform. By organizing operational activities, establishing reward mechanisms, and providing timely feedback, companies can stimulate users to produce content; they can optimize search and sorting functions to classify user-produced content and help users quickly retrieve the information they need and pay attention to the quality control of information to enhance peer influence. Establishing platform norms is necessary to enhance the users’ awareness of helping each other and forming an atmosphere conducive to the platform.
Although this paper makes some theoretical and practical contributions to the emotional attachment of social commerce platforms, there are still some limitations. First, only users of two social commerce platforms, namely, Red Booklet and Poizon, were selected for the survey. The study can be extended to more social commerce platforms in the future to enhance the generalizability of the results. Second, to simplify the model, this paper only considers peer influence as an overall variable. Peer influence can be further subdivided into informational influence and normative influence in future studies to investigate the differences in their effects on emotional attachment.

Author Contributions

Conceptualization, J.Y.; formal analysis and methodology, S.Z. (Siwei Zhang); investigation, S.Z. (Siwei Zhang) and S.Z. (Siqi Zhang); resources, J.Y.; data curation, S.Z. (Siwei Zhang) and S.Z. (Siqi Zhang); writing—original draft preparation, S.Z. (Siwei Zhang); writing—review and editing, S.Z. (Siwei Zhang). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions.

Acknowledgments

The authors want to extend their gratitude toward the editor and the anonymous reviewers for their indispensable and valuable suggestions and comments that improved the quality of the paper significantly.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 04792 g001 550
Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Sustainability 15 04792 g002 550
Figure 2. Path coefficient test results.
Figure 2. Path coefficient test results.
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Table
Table 1. The main types of social e-commerce and typical platforms in China.
Table 1. The main types of social e-commerce and typical platforms in China.
TypeSocial Content E-CommerceSocial Sharing E-CommerceSocial Retail E-Commerce
Typical representativesSustainability 15 04792 i001Red Booklet Sustainability 15 04792 i002PinduoduoSustainability 15 04792 i003Yunji
http://www.xiaohongshu.com, accessed on 1 March 2023.https://www.pinduoduo.com, accessed on 1 March 2023.https://www.yunjiglobal.com, accessed on 1 March 2023.
Sustainability 15 04792 i004PoizonSustainability 15 04792 i005EtaoSustainability 15 04792 i006Aikucun
https://www.poizon.com, accessed on 1 March 2023.https://etao.com, accessed on 1 March 2023.https://aikucun.com, accessed on 1 March 2023.
ImplicationAssist in the purchase and sale of goods or services through social interaction between users, user-generated content, etc.Attract users through group purchase actively through lower prices, and achieve fission based on social sharingBecome a distributor by adopting the S2B2C model and membership model, and use the distribution mechanism to promote user sharing to achieve fission
FeatureUser-generated content as the coreLow price as an attractionS2B2C as the core model
AdvantagesGather a large number of users through content, and can facilitate user transactionsTo achieve rapid accumulation of users by groupRetail decentralization model enables massive growth in retail channels
DisadvantagesCustomer trust crisis due to the proliferation of false informationProduct quality and after-sales service are difficult to guaranteeProduct categories are not complete and the price advantage is not enough
Main sources of usersContent produced by opinion leadersRely on users’ own social networksRely on users’ own social networks
Note: S2B2C is a new e-commerce marketing model that centralizes suppliers to empower distributors and serve customers together.
Table
Table 2. Sample distribution characteristics.
Table 2. Sample distribution characteristics.
FeaturesQuantity (N = 202)Percentage (%)
GenderMan7436.63
Woman12863.37
Level of educationBelow bachelor’s degree209.9
Bachelor’s degree4622.77
Graduate and above13667.33
Monthly income/living expensesBelow 1500 yuan3617.82
1500–3000 yuan10652.48
3001–5000 yuan3014.85
5001–8000 yuan146.93
More than 8000 yuan167.92
Time of useWithin 6 months6230.69
6 months–1 year5125.25
1 year–3 years6029.7
More than 3 years2914.36
Frequency of useFeel free to browse7336.14
1 time per day3416.83
2–3 times a week3718.32
1 time a week62.97
Before shopping or only when needed5225.74
Table
Table 3. Reliability and validity analysis for each variable.
Table 3. Reliability and validity analysis for each variable.
VariableQuestion ItemFactor LoadingCronbach’s AlphaCRAVE
Structural dimensions
JG		JG10.9260.8480.9090.771
JG20.92
JG30.78
Relational dimensions
GX		GX10.8320.7990.8690.625
GX20.791
GX30.772
GX40.765
Peer influence
TC		XX10.7680.8750.9050.613
XX20.84
XX30.734
GF10.792
GF20.772
GF30.788
Emotional attachment
YL		YL10.7950.8860.9170.688
YL20.852
YL30.86
YL40.871
YL50.763
Table
Table 4. Correlation matrix of latent variables and square root of AVE.
Table 4. Correlation matrix of latent variables and square root of AVE.
Relational DimensionsPeer InfluenceEmotional AttachmentStructural Dimensions
Relational dimensions0.79
Peer influence0.6760.783
Emotional attachment0.6430.6910.829
Structural dimensions0.6150.6240.6440.878
Note: The square root of AVE is marked in bold.
Table
Table 5. Hypothesis testing results.
Table 5. Hypothesis testing results.
HypothesisPath FactorSample MeanStandard DeviationT ValueTest Results
H1a: The social capital structure dimension has a significant and positive effect on emotional attachment0.2780.280.0743.738 ***establish
H1b: The social capital relationship dimension has a significant and positive effect on emotional attachment0.2250.2270.0872.598 **establish
H2a: The social capital structure dimension has a significant and positive effect on peer influence0.3340.3330.074.782 ***establish
H2b: The social capital relationship dimension has a significant and positive effect on peer influence.0.4710.4750.0627.618 ***establish
H3: Peer influence has a significant and positive effect on affective attachment0.3660.3640.0993.686 ***establish
Note: ** p < 0.01, *** p < 0.001.
Table
Table 6. Results of mediating effects tests.
Table 6. Results of mediating effects tests.
PathDirect EffectsIndirect EffectsTotal EffectVAF
(%)		Believe
Interval
Structural dimension–peer influence–emotional attachment0.278 (3.687 ***)0.122 (3.343 ***)0.469.50[0.054, 0.193]
Relational dimension–peer influence–emotional attachment0.225 (2.619 **)0.172 (3.169 **)0.39756.68[0.072, 0.282]
Note: ** p < 0.01, *** p < 0.001.
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Yan, J.; Zhang, S.; Zhang, S. Emotional Attachment in Social E-Commerce: The Role of Social Capital and Peer Influence. Sustainability 2023, 15, 4792. https://doi.org/10.3390/su15064792

AMA Style

Yan J, Zhang S, Zhang S. Emotional Attachment in Social E-Commerce: The Role of Social Capital and Peer Influence. Sustainability. 2023; 15(6):4792. https://doi.org/10.3390/su15064792

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Yan, Jianwen, Siwei Zhang, and Siqi Zhang. 2023. "Emotional Attachment in Social E-Commerce: The Role of Social Capital and Peer Influence" Sustainability 15, no. 6: 4792. https://doi.org/10.3390/su15064792

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