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Article

Acquisition and Utilization of Chinese Peasant e-Entrepreneurs’ Online Social Capital: The Moderating Effect of Offline Social Capital

by
Yan Li
and
Weiping Chen
*
School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(7), 6154; https://doi.org/10.3390/su15076154
Submission received: 23 February 2023 / Revised: 29 March 2023 / Accepted: 29 March 2023 / Published: 3 April 2023
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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Abstract

:
Online social capital (OSC) is of great significance to the sustainable development of peasant e-entrepreneurs in the era of social media. The objective of this research was to explore how peasant e-entrepreneurs acquire and utilize OSC through the use of social media. This study proposes an analytical framework of “social media behaviors–OSC–resource acquisition” including the moderating effect of offline social capital. An empirical test was conducted using data from 306 surveys from China and the partial least squares method (PLS). The results show that (1) self-presentation and browsing behaviors have significant positive effects on both bridging and bonding OSC; communication behaviors only have a significant positive effect on bonding OSC; and self-presentation behaviors have the greatest effect on both types of OSC. (2) Both bridging and bonding OSC have significant positive effects on resource acquisition, and bonding OSC has a greater effect. (3) Offline social capital has a negative moderating effect on the relationship between bonding OSC and resource acquisition but does not have that effect on bridging OSC. These findings contribute to the extant social capital literature and provide references for peasant e-entrepreneurs to better acquire and utilize OSC by exploring the antecedents and impacts of OSC in the context of peasant e-entrepreneur in China.

1. Introduction

Entrepreneurship is a sustainable engine for economic growth and social development. The Sustainable Development Goals (SDGs) proposed by the United Nations highlight poverty alleviation as a priority, along with decent work and economic growth, among others. Entrepreneurship has been identified as one of the key drivers of economic prosperity [1,2]. For individuals, it is a means to overcome financial insecurity and improve the lives of individual entrepreneurs [3]. For society, it is seen as a useful tool to support the growth of emerging economies and overcome the major challenges of poverty among rural populations in developing countries [4]. Therefore, promoting entrepreneurship is in line with the SDGs and important for sustainable development, both for individuals and society [5].
Due to relatively poor conditions, peasant entrepreneurship often faces greater challenges. Rural areas are usually located in a remote and closed geographic environment that is difficult to reach. Therefore, peasant entrepreneurs often face problems such as long distances to consumers and capital markets, lack of labor and imperfect labor markets, information blockage, and insufficient communication in a timely manner [6]. As a result, it is difficult for them to obtain the necessary resources and appropriate support, which hinders their entrepreneurship.
The emergence of social media platforms has opened up new opportunities for peasant e-entrepreneurs. Through online interactions, e-entrepreneurs can adopt various social media strategies to maintain and expand their social reach [7]. This will help them obtain more industry information, business opportunities, and consumer support and provide more opportunities to overcome time and space constraints in acquiring resources. In this context, it is of noteworthy importance to explore how peasant e-entrepreneurs successfully start their own businesses through the Internet to promote rural employment and economic development.
Online social capital (OSC) is a critical success factor for e-entrepreneurs as it provides them with essential support. Social capital is considered a fundamental theoretical perspective in entrepreneurship and is well suited for studying the essential elements that make e-entrepreneurs successful [8]. Regarding the sources of OSC, most research has focused on the impact of Internet or social media usage and usage intensity [9,10,11,12]. In addition, there have been initial attempts to explore specific social media behaviors in the context of online social capital [6]; for example, browsing behaviors were found to have a greater facilitative effect on OSC than participation behaviors. Regarding the impact of OSC, previous research has shown that OSC, as a key outcome of online networking, can promote consumer purchase intentions, loyalty, mental health, and other subjective emotional factors [10,13].
Existing studies on OSC focus mainly on enterprises in urban areas, but there is a lack of research on how to obtain and leverage OSC in the context of peasant e-entrepreneurs. In addition, a few empirical studies have examined how social media use can help build and sustain OSC in rural communities, but none of these studies have examined this issue for specific social media behaviors. Moreover, these few studies have rarely attempted to analyze the role of offline social capital in the process of using OSC.
To address these gaps, the overall goal of this study is to construct an analytical framework of “social media behaviors–OSC–resource acquisition” with offline social capital as a moderating variable and test the model empirically. Considering that rural e-commerce started early and developed rapidly, China is a typical representative place for studying peasant e-entrepreneurs. This paper uses data from 306 surveyed peasant e-entrepreneurs in China. Based on the theoretical analysis, partial least squares (PLS) techniques are used to investigate the main model and the moderating effect of offline social capital. This study not only contributes to the enrichment and extension of social capital theory but also provides useful guidance for peasant e-entrepreneurs. In addition, this work is significant for formulating relevant policies, promoting industrial revitalization, and achieving shared prosperity for China.
The paper is organized as follows. The theoretical background and development of the hypothesis are discussed in Section 2. Section 3 formulates arguments for the hypotheses and presents data, variables, and methods. Section 4 reports the results of the statistical analysis. Section 5 discusses the results of the study and Section 6 provides conclusions.

2. Theoretical Background and Hypotheses Development

2.1. Online Social Capital

Social capital is an important concept widely used in sociology, economics, management, and other disciplines. It provides a new theoretical perspective to explain how individuals and organizations achieve development and promotion. The academic community has yet to form a unified understanding of the concept. Coleman [14] argues that, as with other forms of capital, social capital is productive and can make certain goals possible. As with physical and human capital, social capital is not completely fungible, but it may be specific to certain activities. Nahapiet and Ghoshal [15] believe that social capital is the sum of actual and potential resources contained in the network of relationships owned by individuals or social units. Adler and Kwon [16] argue that social capital comes from goodwill (sympathy, trust, understanding, etc.) in interpersonal relationships and thus has the opportunity to obtain valuable resources. Although different scholars have different definitions of social capital, they all contain two core elements. Therefore, according to its function, social capital is a relational resource, which also provides more possibilities for the transformation and acquisition of other forms of resources.
Previous studies on social capital have mostly been based on realistic scenarios (i.e., offline social capital). With the wide application of social media technology, online communication has gradually become a norm in people’s work and life. Thus, OSC has derived from traditional offline social capital and become an important research topic. OSC mainly refers to social capital obtained through the use of information and communication technology (ICT) to establish and maintain connections with others online [17]. Compared with traditional offline social capital, OSC expands the scope of resource acquisition and improves the convenience, diversity, reliability, and matching of resource acquisition. It is an effective way for peasant e-entrepreneurs to obtain resources in the era of social media.
According to the strength of social relations, OSC can be divided into bridging and bonding types [17,18]. Bridging OSC is related to “weak relationships”. Weak relationships in networks are mainly characterized by loose connections, wide coverage, and a large number of nodes [19]. The relationship between network members is loose, and the background is very different. It includes not only the members who know but are not familiar with each other in the social organization but also the ordinary friends who are widely contacted and made through various channels. Thus, its coverage is relatively wide, and more information from different perspectives and sources can be provided. Bridging OSC exists in this kind of relatively distant network relationship, which provides little emotional support. However, due to common interests, members can exchange information with each other through reciprocity.
Bonding OSC is related to “strong relationships” and exists in a close relationship network. A “strong relationship” is a relationship depth mechanism that provides emotional or substantive support to the actors. It is formed through frequent interaction and input between the actors and strengthened in the continuous accumulation. Williams [18] developed a measurement scale of OSC based on the traditional social capital theory. The measurement of bridging OSC includes four aspects: expanding beyond the familiar relationship circle, contacting a wider range of people, seeing oneself as part of a wider group, and establishing a reciprocal relationship with it. The bonding OSC scale is composed of emotional support, access to scarce resources, the ability to unite and mobilize, and out-of-group confrontation. Therefore, this paper refers to Williams’ measurement approach.

2.2. Social Media Behavior and OSC

Social media provides social interactions and network functions such as information release, information exchange, and contact management. Starting from the basic activities of one-way output, one-way input, and two-way interaction involved in social media, this paper focuses on three kinds of behaviors, including self-presentation, browsing, and communication.

2.2.1. Self-Presentation Behaviors and OSC

Self-presentation refers to the behavior of peasant e-entrepreneurs in building personal and brand images to the outside world through the release of personal information. For example, to establish a personalized homepage; update personal life messages; share personal views and attitudes; and release commodity-related knowledge and production, sales, and service-related information. This behavior contributes to the formation of bridging OSC. On the one hand, rich information provided by self-presentation behaviors can form personal background information and digital identity, which can help release active social signals. Updating messages can create potential interaction opportunities and increase the possibility of contact. On the other hand, the disclosure of personal information helps enhance authenticity and trustworthiness in the online environment and improves the attractiveness of peasant e-entrepreneurs [20]. Complete personal information, such as gender, age, region, personal experience, and one’s main business, can provide homogeneity assessment (background similarity) and social judgment assessment (social reputation, status, legitimacy, etc.) clues. This promotes the generation of a sense of belonging and identity and builds broader trust and connection [11,21].
This behavior is also an important prerequisite for the formation and accumulation of bonding OSC. On the one hand, it forms a personal information set through long-term iteration. The breadth and depth of the information set keep growing as time goes by, which helps deepen the degree of trust and intimacy between people [22]. On the other hand, this information set is helpful for other users in evaluating commonalities with peasant e-entrepreneurs (conveying similar concepts, attitudes, lifestyles, ideas, etc.). It can provide a basis for interaction, facilitate the generation and strengthening of a common vision, and enhance users’ recognition and trust. For example, the cognition of green production, healthy diets, and other issues will attract users with similar views to exchange experiences, promote knowledge sharing and emotional interactions, further narrow the relationship between them, and strengthen the original connection. Therefore, self-presentation behaviors can reduce the uncertainty of a relationship, lay a solid foundation for the development of a strong relationship, and thus improve the bonding OSC of peasant e-entrepreneurs. Accordingly, the following hypothesis is proposed:
Hypothesis 1a (H1a).
The self-presentation behaviors of peasant e-entrepreneurs will have a positive impact on bridging OSC.
Hypothesis 1b (H1b).
The self-presentation behaviors of peasant e-entrepreneurs will have a positive impact on bonding OSC.

2.2.2. Browsing Behaviors and OSC

Browsing refers to the behavior of peasant e-entrepreneurs in observing, consulting, and browsing information published by other users on social media platforms, which is a one-way passive consumption behavior [23]. Through browsing, they can conveniently view and collect the effective information of other users, contact and recognize more users, and expand the scale of their potential relationship network. At the same time, it is possible to add more friends by sending friend requests, turn unfamiliar relationships into weak ones, and expand new social networks to increase their bridging OSC.
Browsing behaviors can help peasant e-entrepreneurs track the latest news of friends in real-time, such as personal life statuses, moods, business statuses, updated personal information, etc. Rich information presented in various forms, such as video, audio, pictures, texts, or links, can enhance the in-depth understanding of existing friends in a vivid and multi-dimensional way. When browsing and visiting friends’ homepages and posting content, the data and information obtained are beneficial to building potential interactions. Therefore, we propose Hypothesis 2:
Hypothesis 2a (H2a).
The browsing behaviors of peasant e-entrepreneurs will have a positive impact on bridging OSC.
Hypothesis 2b (H2b).
The browsing behaviors of peasant e-entrepreneurs will have a positive impact on bonding OSC.

2.2.3. Communication Behaviors and OSC

Communication refers to interactions between peasant e-entrepreneurs and other users on social media, including comments, forwarding, liking, and chatting. This behavior can effectively maintain the weak relationship network of peasant e-entrepreneurs. In the real environment, contact between individuals may be interrupted, and the accumulated social capital may also be lost. Social media increases interest in and the possibility of interactions through likes, comments, and forwarding [24] or communication in various forms such as texts, pictures, and videos [13] so as to avoid the decay or even severing of relationships [25]. Therefore, weak relationships can be maintained for a long time. In addition, communication through social media has relatively low requirements for social skills, which can effectively weaken social boundaries [23] and realize broader connections, thus increasing bridging OSC.
This behavior can also effectively deepen the development of strong relationship networks. The diversified communication forms and low cost of social media can increase interaction opportunities and improve efficiency, thus enhancing the sense of presence among individuals [26]. Through the chat function, peasant e-entrepreneurs can easily initiate chat and activate dormant strong relationships. Meanwhile, communication behaviors encourage interactions between peasant e-entrepreneurs and other users to be targeted and direct, and they will comment on common topics. As a result, the spatial and psychological distance between peasant e-entrepreneurs and their online friends is narrowed, thus increasing bonding OSC. Therefore, Hypothesis 3 is proposed:
Hypothesis 3a (H3a).
The communication behaviors of peasant e-entrepreneurs will have a positive impact on bridging OSC.
Hypothesis 3b (H3b).
The communication behaviors of peasant e-entrepreneurs will have a positive impact on bonding OSC.

2.3. OSC and Resource Acquisition

According to the resource-based theory, resource acquisition refers to the ability to acquire all resources (different from relational resources) in an external network, such as human resources, information resources, and material wealth, and the process of integrating internal and external resources [27]. Although there is no inevitable connection between the possession of social capital and the actual acquisition of various relevant resources, OSC provides an effective way for peasant e-entrepreneurs to obtain resources. Peasant e-entrepreneurs can seek and acquire necessary instrumental and non-instrumental resources in the established online relationship network [28,29] to meet their multiple resource needs for entrepreneurship and future development.
Bridging OSC is often linked to a broader network of relationships and can lead to a variety of new resources. According to the structural hole theory [30], the nodes at the intersection position in relational networks are usually the gathering points of information, bringing together rich heterogeneous resources [31]. Existing studies have shown that the larger the scale of the personal network, the larger the scale of funds available, the richer experience and knowledge, and the wider source of information for entrepreneurs [32]. Peasant e-entrepreneurs are located in remote rural areas with limited information. Their demands for experience, knowledge, industry and policy information, and other resources [33] can be met to a large extent via social media. Therefore, bridging OSC contributes to creating more opportunities to obtain resources.
Bonding OSC has strong relational attributes, and members in the network have a strong willingness and ability to provide the resources they have. Bonding OSC exists among subjects with close relationships and is more likely to provide strong emotional support or scarce substantive resources [18,34]. Firstly, bonding OSC is usually accompanied by high social trust and commitment, and the transaction cost of acquiring resources is low [35,36,37]. Secondly, it can provide more reliable and relevant resources. The information quality generally decreases with the increase in the length of the relationship path, so a direct connection is the most suitable for delivering reliable information [38]. By establishing and maintaining a close network, peasant e-entrepreneurs can reduce the mixing of redundant resources or false resources so as to focus on the key resources needed for development [33]. For example, when in the bottleneck stage of development, peasant e-entrepreneurs need spiritual support from friends, a sense of belonging to peer groups feasible suggestions and guidance, etc. These resources are more likely to be obtained from bonding OSC. Therefore, Hypothesis 4 is proposed:
Hypothesis 4a (H4a).
The bridging OSC of peasant e-entrepreneurs will have a positive impact on resource acquisition.
Hypothesis 4b (H4b).
The bonding OSC of peasant e-entrepreneurs will have a positive impact on resource acquisition.

2.4. The Moderating Effect of Offline Social Capital

Offline social capital arises from social networks in real life and plays a moderating role in the relationship between OSC and resource acquisition. Entrepreneurs can obtain resources by activating online or offline social networks. However, which type of social network they activate depends on the practical needs of the entrepreneurs [39]. In the entrepreneurial process, peasant e-entrepreneurs face resource difficulties of varying degrees [40,41]. The stock of offline social capital directly affects the quantity and quality of resource acquisition [42].
The familiarity, trust, relationships, and local complexities among people in real life have a profound impact on people’s lives and work [43]. From the perspective of reliability, the social network in real space is stable and authentic, formed by long-term repeated interactions. From the perspective of effectiveness, unique regional characteristics and social networks constitute the basic entrepreneurial environment. Peasant e-entrepreneurs must make full use of the role of offline social capital to obtain unique resources, such as local policy support, agricultural production conditions, natural environmental laws, and production technologies adapted to the local environment. Therefore, obtaining necessary resources from familiar real communities usually becomes the primary option for peasant e-entrepreneurs.
However, it is difficult to meet all resource demands only with offline social capital. Resources related to industry prospects, judgments of economic market trends, and experiences exchanged between peers still need to be obtained with OSC. Therefore, due to the effect of resource acquisition, offline social capital has formed a certain degree of substitution for OSC. When offline social capital is sufficient, the number of resources obtained by invoking OSC decreases accordingly. Otherwise, OSC is more likely to be activated and utilized to acquire the resources needed. Therefore, Hypothesis 5 is proposed:
Hypothesis 5a (H5a).
The offline social capital of peasant e-entrepreneurs will have a negative moderating effect on the relationship between bridging OSC and resource acquisition.
Hypothesis 5b (H5b).
The offline social capital of peasant e-entrepreneurs will have a negative moderating effect on the relationship between bonding OSC and resource acquisition.
Figure 1 depicts an analytical framework of how Chinese peasant e-entrepreneurs acquire and utilize online social capital.

3. Methodology

3.1. Data Resources

The data in this paper come from a questionnaire survey of peasant e-entrepreneurs. As there is no official statistical data specifically, it is difficult to identify peasant e-entrepreneurs in the research process. In order to establish a representative sample set, two criteria are used in this paper. One is the type of business. The samples must involve agricultural operating entities engaged in the production or sale of agricultural products, including family farms, cooperatives, large farming and breeding households, or e-commerce on professional platforms. The other is the proportion of online sales of agricultural products. Online sales of agricultural products must account for at least 10 percent of total sales (national online retail sales of agricultural products account for 9.8% of the total transaction volume of agricultural products).
This study adopts a questionnaire survey scheme combining field and online that can be conducted in the following three ways. The first is to establish cooperation with the Rural Social Undertakings Development Center, Ministry of Agriculture and Rural Affairs of China. A total of 531 questionnaires are obtained. Given the standard that online sales must account for 10%, 182 valid questionnaires are left. The second way is to use the snowball method. On the basis of regional sampling, questionnaires are sent out via snowball sampling through the recommendation of familiar industry personnel. A total of 128 questionnaires are collected, of which 80 are valid. Third, the survey is issued at a meeting site. Relying on the onsite registration office of the 11th National Eco-Agriculture Conference, questionnaires are distributed to the participants in charge of new agricultural business entities; 100 questionnaires are collected one by one during the conference, and 44 are valid.
As is shown in Table 1, a total of 306 effective peasant e-entrepreneur samples are included in this study, including 146 family farms, 100 cooperatives, 21 large farming households, and 39 platform e-entrepreneurs. In total, 83, 90, and 133 came from eastern, central, and western China, respectively. The proportion of males is 77.78%, and the average age is about 39 years old. Those with college degrees account for the highest proportion, 32.68%, while those with high school or above account for 83.98%. On the whole, the samples are generally relatively young and highly educated, which is consistent with the previous survey results on new agricultural business entities that use Internet thinking [44].

3.2. Variable Selection

The variable measurement in this paper mainly adopts a scale that has proven effective in relevant studies and adjusts the scale by referring to the peasant e-entrepreneur situation. In order to improve the reliability and validity of the measurement, this paper refers to the research by Hinkin [45] and adopts multiple steps to determine the scale. In order to ensure the validity of the scale, this study first adopts the maximum variance rotation method in principal component analysis to conduct exploratory factor analysis and verify that each variable meets the construct’s requirements.

3.2.1. Social Media Behaviors

Social media behaviors in this paper include self-presentation (SE), browsing (BR), and communication (CO) behaviors. As shown in Table 2, SE refers to the measurement scale developed by Chen and Li [13]. BR is mainly derived from Burke et al.’s measurement scale of content consumption behavior and Horng and Wu’s scales [6] for measuring browsing. CO refers to Burke et al. [23]’s measurement scales related to directed communication behaviors.

3.2.2. Online Social Capital

Williams’ measurement scale is adopted, which is the method commonly used to measure OSC. Thus, a total of 9 items are set to measure social capital from both bridging OSC (BRSC) and bonding OSC (BOSC).

3.2.3. Resource Acquisition

Considering the large differences in the types of resources that peasant e-entrepreneurs may acquire, this paper draws on the resource acquisition (RS) variable measurement method from the studies by Lee et al. [37]. A single multidimensional structure is adopted to determine the overall degree of resource acquisition.

3.2.4. Offline Social Capital

In the context of rural China, offline social capital, especially government-related resources, has a direct and far-reaching impact on the success of entrepreneurs [46]. Government capital is an important part of traditional offline social capital, and it affects the long-term development of enterprises. Richer political and social capital means more opportunities to obtain preferential policies and supports and, thus, more practical resources, such as convenient loans, taxes, and subsidies [47,48].
Therefore, this paper draws on the measurement method of corporate political capital from the study by Luo et al. [47] and combines it with the actual demands of peasant e-entrepreneurs. We set three measurement items: “Whether there have been government department leaders visiting to investigate or research (OffSC1)”, “Whether it is in a local government development plan (OffSC2)”, and “Whether it is a cooperative unit of a university or research institute (such as an internship base or research base) (OffSC3)”. To test the comprehensive effect of offline social capital, the values of the three items are summed to obtain the offline social capital comprehensive index (OffSC), which is 0, 1, 2, or 3. The larger the value is, the higher the level of offline social capital.

3.2.5. Control Variable

Based on the variables that may have an impact on OSC [31] and resource access [49,50] in previous studies, this paper controls the model from three perspectives: the individual characteristics of operators, business types, and the characteristics of social media use.

3.3. Data Analysis

The partial least squares structural equation method (PLS-SEM) is used to analyze the path and test the significance of the model. The PLS method is good at testing complex structural models, theoretical development, and exploratory research, and it is more suitable for small-sample analyses than the traditional structural equation model (SEM) method, in line with the research needs of this paper. Therefore, this paper uses one of the mainstream programs, Smart PLS 3.0, for data analysis.

4. Results

4.1. Reliability and Validity Analysis

In terms of reliability, the internal consistency coefficient (Cronbach’s α) and composite reliability (CR) are used for evaluation. As shown in Table 3, the values of Cronbach’s α for all the latent variables are greater than the ideal value of 0.7. The CR values range from 0.855 to 0.952, all higher than 0.8, indicating the high composite reliability of data.
In terms of validity, this paper mainly tests convergent validity and discriminant validity. As for convergence validity, first of all, according to the calculation results of the factor loading coefficient after data standardization (see Table 3), most of the values are above the recommended value of 0.7. Secondly, the average variance extracted (AVE) values range from 0.600 to 0.798, all of which are higher than the threshold of 0.5. Thus, it can be seen that the data have good convergence validity. The discriminant validity is evaluated from three perspectives. First, the loadings normalized by the underlying variable and its corresponding items are much larger than the cross-loadings with the other factors. Second, it is found that the AVE square root of the latent variable is greater than the correlation coefficient between the latent variable and other latent variables. Third, the maximum value of the latent variable heterotrait–monotrait ratio (HTMT) is 0.696, which is less than the threshold value of 0.85. Consequently, the latent variables have good discriminative validity.

4.2. Common Method Bias

The common method bias (CMB) was calculated using common method variance (CMV). During the questionnaire survey, all items of each questionnaire were filled out by one person, so there may be filling inertia, which is CMV. To ensure the scientific rationality of the research data, this paper uses three methods to test possible CMV before data processing, and the results all show that there is no CMB. The first test is Harman’s single-factor evaluation. The result shows that the explained percentage of variance in the first factor is 34.08%, which is significantly less than 50%, indicating that the model is not affected by CMB. The second is the correlation coefficient of the latent variables test method. The maximum value of the correlation coefficient among the latent variables is 0.632, far lower than the threshold value of 0.9. The third test is to introduce a CMV latent variable that contains all the major observed variables into the model. Calculating the new model, the average value of the real factor loading square is 0.703, and the average value of the method factor loading square is 0.004; the former is 175 times the latter, which indicates that there is no CMB in the data.

4.3. Results of Hypothesis Test

4.3.1. Results of Main Effect Test

Figure 2 shows the model test results. The R2 value shows that the model can explain the variation in the endogenous variables of bridging OSC, bonding OSC, and resource acquisition by 46.0%, 29.7%, and 35.4%, respectively, which are all greater than or close to the acceptance level of 0.3, indicating that the model has a good explanatory ability.
H1~H3 are hypotheses of the influence of different types of social media behaviors on peasant e-entrepreneurs’ OSC. According to the empirical results of the model, both self-presentation and browsing behaviors have significant positive effects on bridging OSC, and the path coefficients are 0.562 (p < 0.001) and 0.246 (p < 0.001). However, communication behaviors have no significant effect on bridging OSC. Therefore, H1a and H2a are confirmed, while H3a is not. Self-presentation, browsing, and communication behaviors have significant positive effects on bonding OSC, and the path coefficient values are 0.292 (p < 0.001), 0.127 (p < 0.005), and 0.264 (p < 0.001), so it is assumed that H1b, H2b, and H3b are confirmed.
H4a and H4b are about the relationship between OSC and peasant e-entrepreneur resource acquisition. The results show that both bridging and bonding OSC have significant positive effects on resource acquisition, with path coefficients of 0.273 (p < 0.001) and 0.284 (p < 0.001). Therefore, both H4a and H4b are confirmed.
In addition, among the control variables, education (b = −0.147, p < 0.01) and family farm, cooperative, and platform e-entrepreneurs (b = −0.089, p < 0.05) have significant effects on bonding OSC. The influence of all the control variables on bridging OSC or resource acquisition is not significant.

4.3.2. Results of Moderating Effect Test

The moderating effect of offline social capital is further analyzed. As shown in Table 4, offline social capital has no significant moderating effect on the relationship between bridging OSC and resource acquisition. However, it has a significant negative moderating effect on the relationship between bonding OSC and resource acquisition, and its path coefficient is −0.207 (p < 0.001). Therefore, H5b is supported and H5a is not.
In order to show the moderating effect more intuitively, this paper draws an interactive relationship diagram between the variables (see Figure 3). It can be seen from Figure 3a that there is no significant difference between the slopes of the two lines in the graph of bridging OSC, showing an approximately parallel relationship. Offline social capital has no moderating effect on the relationship between bridging OSC and resource acquisition. In Figure 3b, the slope of the solid line (low offline social capital) is significantly greater than that of the dotted line (high offline social capital). This confirms the negative moderating effect of offline social capital on the relationship between bonding OSC and resource acquisition.

5. Discussion

This paper constructs a theoretical analysis framework of acquisition and utilization for Chinese peasant e-entrepreneurs’ OSC, including the moderating effect of offline social capital, and uses 306 sample data for empirical testing. Some meaningful conclusions have been drawn.
As to the source of OSC, it is found that social media behaviors have differentiated impacts on OSC. On the one hand, self-presentation and browsing behaviors have significant positive effects on both bridging and bonding OSC, which is similar to the findings of Horng and Wu [6] and Rykov [21]. Self-presentation behaviors provide social contextual cues that are missing in the online environment, helping to establish common ground and further form connections between parties.
On the other hand, self-presentation behaviors have the greatest effect on bridging and bonding OSC. It can be seen that the self-presentation of peasant e-entrepreneurs is the basic premise for the formation of OSC, whether consolidating the existing social relationship network or expanding the new social relationship network. This differs from the results of previous studies, which concluded that browsing behaviors have stronger effects on social capital accumulation online [21]. Additionally, most previous studies focus on self-presentation and browsing behaviors and do not discuss communication behaviors. These studies looked at general users on Facebook, who are mostly from urban contexts.
In contrast to previous studies, this paper adds a communication behavior dimension, using peasant e-entrepreneurs as the research context. The findings show that communication behaviors only have positive effects on bonding OCS, while there is no significant effect on bridging OSC. This may be due to the fact that the online activities of e-entrepreneurs through social media generally have a strong commercial purpose. The one-way, active self-presentation of information about themselves practiced by peasant e-entrepreneurs is not too intrusive to others, and it has a more positive effect. Therefore, self-presentation behaviors help broaden and enhance the outside world’s understanding of peasant e-entrepreneurs and make significant contributions to their online social capital. However, if peasant e-entrepreneurs actively open two-way connections or chats, the effect depends on the situation. For close online relationships, communication can lead to better retention. For loose or unfamiliar relationships, communication is often perceived as an act with a sales purpose. These findings have important practical implications for peasant entrepreneurs who want to succeed in business.
As for the impact of OSC, bridging and bonding OSC both have significant positive effects on resource acquisition. This is consistent with the conclusions of Meurer et al. [14]. This finding suggests that, with the use of social media and digital affordances, peasant e-entrepreneurs have built an online space and active community that can serve as an important access channel to accumulate OSC. OSC provides peasant e-entrepreneurs with a wealth of resources that they can immediately use, which is especially important taking into account that fast responses to crises are critical for the survival of new ventures.
The above findings differ from those of Smith [29]. Smith concludes that entrepreneurs are able to access information resources from online social networks based on a case analysis in North America. However, their willingness to access resources from online social networks is low due to perceived social risk.
Our view is consistent with the conclusions of Meurer et al. [14]. Using the COVID-19 pandemic as a research context, Meurer conducted a textual analysis of entrepreneurial website postings on Reddit. It is concluded that, through the use of digital affordance, e-entrepreneurs build an online space and activity community, which provides important access to accumulate social capital. OSC helps peasant e-entrepreneurs gain access to wealth resources that they can use immediately, which is especially important taking into account that fast responses to crises are critical for the survival of new ventures.
Therefore, to some extent, this illustrates the importance of OSC for e-entrepreneurs in accessing resources in regions or periods of high resource constraints. At the same time, the role of online social capital continues to grow as the degree of digital technology development and application increases. In addition, compared with existing qualitative studies, this paper empirically uses a large quantitative analysis sample to provide Chinese evidence for resource acquisition facilitated by OSC.
In terms of the moderating effect, this study finds that the impact of bonding OSC on resource acquisition will be negatively moderated by offline social capital, but bridging OSC is not affected. Although both provide important access to resources for rural entrepreneurs, online and offline social capital may be different constructs with different consequences [51]. Especially in rural societies characterized by acquaintance relationships, entrepreneurs are strongly influenced by offline social networks. Thus, it is necessary to further explore whether the application of OSC is influenced by offline social capital, which is rarely mentioned in the existing literature.
The offline social capital embedded in offline social networks is more authentic and credible, allowing for access to dedicated resources applicable to the local area as well as more substantial resources. For reasons of perceived risk and conversion costs, peasant e-entrepreneurs primarily choose to obtain required resources from offline social capital, the extent of obtaining resources from OSC will be reduced.
Bonding OSC has a greater impact on resource acquisition compared with bridging OSC. Due to the reality of time and space inflexibility and a lack of personal energy, it is difficult for peasant e-entrepreneurs to obtain diversified and heterogeneous resources from offline social capital, but they can obtain them from online social capital, specifically from bridging OSC. This study provides insightful guidelines for peasant e-entrepreneurs and has practical implications for optimizing access to resources through the use of online and offline social capital.

6. Conclusions, Implications, and Limitations

6.1. Conclusions

This study aims to explore how peasant e-entrepreneurs acquire and utilize OSC. Based on the data from 306 peasant e-entrepreneurs in rural China, this paper uses PLS techniques to empirically study the effect of social media behavior on OSC, as well as the impact of OSC on resource acquisition. The results of the study show that, first, there are differences in the effects of different social media behaviors on different OSC types. Self-presentation and browsing behaviors have significant positive effects on both bridging and bonding OSC. Communication behaviors have a significant positive effect on bonding OSC but not on bridging OSC. Additionally, self-presentation behaviors have the greatest effect on both bridging and bonding OSC. Second, bridging and bonding OSC both have significant positive effects on resource acquisition. Third, it is found that the impact of bonding OSC on resource acquisition will be negatively moderated by offline social capital while bridging OSC is not affected by the moderating effect.

6.2. Theoretical and Practical Implications

This paper takes peasant e-entrepreneurs as the research object, expands the research context of online social capital, and enriches the social capital theory. First, by constructing the research framework of “social media behavior–OSC–resource acquisition”, this paper provides a new analytical idea for research on OSC. Second, from the perspective of driving factors, this paper analyzes and tests the differences in the degree of effect of different social media behaviors (self-presentation, browsing, and communication) on OSC, which enriches research on the driving factors. Third, from the perspective of effect results, this paper verifies the influence of OSC on resource acquisition and introduces offline social capital as an important moderating variable. The study finds that offline social capital plays a negative moderating role in the relationship between bonding OSC and resource acquisition, which provides a useful reference for the further exploration of the influence mechanism of OSC.
This paper has the following two guiding meanings for the practical activities of peasant e-entrepreneurs. First, OSC is an important way for peasant e-entrepreneurs to achieve resource acquisition, so they should pay full attention to it and use it. For peasant e-entrepreneurs with poor resource endowments and entrepreneurship environments, OSC is an important and feasible channel to obtain necessary resources. It is necessary to cultivate the awareness of accumulation and utilization of OSC and improve the ability to utilize OSC. Furthermore, it should be noted that offline social capital will reduce peasant e-entrepreneurs’ access to resources from bonding OSC, but it does not affect their access to resources from bridging OSC. Therefore, peasant e-entrepreneurs with abundant offline social capital can focus on expanding their bridging OSC, while for those with insufficient offline social capital, it is necessary to develop both bridging and bonding OSC. Second, in terms of social media behavior, peasant e-entrepreneurs should give full play to the role of self-presentation behaviors, establish complete and dynamic digital information archives, and improve the corresponding social media skills. Studies have confirmed that self-presentation behaviors have the greatest effect on peasant e-entrepreneurs’ online social capital with respect to social media behaviors. Therefore, positive effects brought on by self-presentation behaviors should be made good use of, such as releasing and updating dynamic information (transferring personal interests, hobbies, values, emotional attitudes, etc.) and appropriately displaying relevant information such as products and services. At the same time, peasant e-entrepreneurs should also focus on cultivating and improving skills related to the use of social media, such as paying attention to the influence of information release times, content design, and other factors on the effect of information display and dissemination. In addition, peasant e-entrepreneurs should also pay attention to the timely acquisition of information published by other users through browsing and maintain communication and interaction with friends through “like”, “comment”, “forward”, and “chat” functions so as to consolidate and develop social network relations.

6.3. Limitations and Future Research

This study has certain limitations, which also provide the opportunity for further research. Firstly, the driving factors of OSC are relatively complex, and social media behaviors may only be one of the important factors. Furthermore, with the development of social media platforms, new social media behaviors may be generated. Therefore, future research can consider adding other influencing factors to make the model more consistent with the actual background. Secondly, due to the limitations of time, resources, and other objective conditions, the study adopts the principle of convenience to obtain samples, which may cause problems such as small sample sizes and insufficient representation. Future studies can further carry out random sampling in a wider range and make improvements in the representativeness and size of the samples. Finally, this paper focuses on the positive effects of social media use and OSC; the possible risks are not taken into account, which can be further discussed in future studies.

Author Contributions

Writing—original draft, Y.L.; writing—review and editing, W.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Social Science Foundation of China (Grant No.: 72073136, 71773138).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank the constructive comments and engagement with the paper from our reviewers regarding its significance in a global context.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. The fitting coefficients of each path in the model. Note: * and *** are significant at the 5% and 0.1% levels, respectively; NS means not significant. To keep the model backbone clear, the control variable significance results are omitted here.
Figure 2. The fitting coefficients of each path in the model. Note: * and *** are significant at the 5% and 0.1% levels, respectively; NS means not significant. To keep the model backbone clear, the control variable significance results are omitted here.
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Figure 3. The moderating effect of offline social capital. (a) Bridging OSC. (b) Bonding OSC.
Figure 3. The moderating effect of offline social capital. (a) Bridging OSC. (b) Bonding OSC.
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Table
Table 1. Basic statistical characteristics of samples.
Table 1. Basic statistical characteristics of samples.
VariablesCategoryCountPercentageVariablesCategoryCountPercentage
GenderFemale6822.22%EducationUnder high school309.8%
Male23877.78%High school7424.18%
Age<306922.55%College10032.68%
31~4011035.95%Graduate8327.12%
41~509430.72%Master or above196.21%
>503310.78%Peasant e-entrepreneursFamily farms14647.71%
RegionEastern China8327.12%Cooperatives10032.68%
Central China9029.41%Platform 3912.75%
Western China13343.46%Large farming households216.86%
Table
Table 2. Measurement items of social media behaviors.
Table 2. Measurement items of social media behaviors.
ConstructsItemQuestionsSource
Browsing (BR)BR1I use WeChat to get information about the status of my peers.[6,23]
BR2I use WeChat to get information about industry development.
BR3I use WeChat to get information about suppliers.
BR4I use WeChat to get information about inputs, such as agricultural materials and production technology.
BR5I use WeChat to get information about consumers.
BR6I use WeChat to get information about policies and regulations.
Self-presentation (SE)SE1From my above profile, people can easily understand my characteristics[13]
SE2I like to share my location on WeChat.
SE3I like to share my feelings on WeChat.
SE4I like to share my work process on WeChat.
SE5I like to share my life status on WeChat.
SE6I have clear personal information (age, occupation, contact, real name) on WeChat.
Communication (CO)CO1I often comment on posts on WeChat.[23]
CO2I often forward posts on WeChat.
CO3I often like posts on WeChat.
CO4I often chat with friends alone.
Table
Table 3. Model fitting indexes without control variables.
Table 3. Model fitting indexes without control variables.
Latent VariablesItemsLoadingCronbach’s αCRAVE
Self-presentationSE10.7700.8740.9050.614
SE20.811
SE30.808
SE40.804
SE50.804
SE60.700
BrowsingBR10.8850.9100.9300.690
BR20.851
BR30.866
BR40.828
BR50.825
BR60.719
CommunicationCO10.8750.7710.8550.600
CO20.834
CO30.840
CO40.580
Bridging OSCBRSC10.9080.9370.9520.798
BRSC20.892
BRSC30.899
BRSC40.868
BRSC50.899
Bonding OSCBOSC10.8440.8580.9040.704
BOSC20.891
BOSC30.876
BOSC40.736
Resource acquisitionRE10.7290.8980.9250.711
RE20.877
RE30.862
RE40.868
RE50.873
Table
Table 4. Results of moderating effect test.
Table 4. Results of moderating effect test.
Path CoefficientStd. ErrorT-Valuep-Value
Offline SC -> resource acquisition0.236 ***0.0484.8960.000
Offline SC × bridging online SC -> resource acquisition0.0780.0551.4150.157
Offline SC × bonding online SC -> resource acquisition−0.207 ***0.0523.9850.000
*** are significant at the 0.1% levels.
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Li, Y.; Chen, W. Acquisition and Utilization of Chinese Peasant e-Entrepreneurs’ Online Social Capital: The Moderating Effect of Offline Social Capital. Sustainability 2023, 15, 6154. https://doi.org/10.3390/su15076154

AMA Style

Li Y, Chen W. Acquisition and Utilization of Chinese Peasant e-Entrepreneurs’ Online Social Capital: The Moderating Effect of Offline Social Capital. Sustainability. 2023; 15(7):6154. https://doi.org/10.3390/su15076154

Chicago/Turabian Style

Li, Yan, and Weiping Chen. 2023. "Acquisition and Utilization of Chinese Peasant e-Entrepreneurs’ Online Social Capital: The Moderating Effect of Offline Social Capital" Sustainability 15, no. 7: 6154. https://doi.org/10.3390/su15076154

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