Building a Cross-Sectoral Interorganizational Network to Advance Nonprofits: NGO Incubators as Relationship Brokers in China

Abstract

In light of the recent rise of Chinese nongovernmental organizations (NGO) and the significant roles that they are playing to advance nonprofit and voluntary activities, this article explores the network dynamics of emerging NGOs in China, known as NGO incubators. NGO incubators were birthed to provide services to civil society actors, including capacity-building training, fundraising, information support, and network formation guidance. This study examines the evolution of the organizational network of the largest Chinese NGO incubator over its 6-year formative period and provides fresh empirical evidence to illustrate how NGO incubators can powerfully bridge structural holes and build cross-sectoral alliance networks in a nascent civil society. Theoretical and practical implications for NGO development are discussed.

Keywords

network cross-sectoral alliance structural hole theory NGO incubators

To shed light on an important dimension of Chinese and global civil society, this article explores the network dynamics of one type of emerging nongovernmental organization (NGO) known as an NGO incubator. Economic restructuring since the late 1980s in China has brought about widespread changes in the Chinese social fabric, including shifting relationships among such institutional players as the government, business, and civil sectors. In tandem with the rising prominence of civil society in China, the population of Chinese NGOs has risen rapidly in recent decades (Hsu & Hasmath, 2017; G. Yang, 2005). In 2004, there were 289,000 registered Chinese NGOs. By 2007, the number increased to an estimated 3 million while only 1.5% were registered with the government (Brown & Hu, 2012).

Among Chinese NGOs, some are officially organized NGOs initiated by the government while some are grassroots, citizen-run NGOs. In addition to these aforementioned types of NGOs, there is a critically new and distinctive group of NGOs emerging in China. This small but growing group of NGOs was birthed to provide services to civil actors, including capacity-building training, fundraising, information support, and network formation guidance. Because this type of NGO provides a nurturing environment for the development of new NGOs and the expansion of existing NGO services in China, they refer to themselves as “NGO Incubators.” Brown and Hu (2012) noted that this group of influential NGOs helps to connect a wide range of NGOs, private foundations, corporations, and government agencies. As such, they potentially play a very delicate and crucial role in assisting the growth of the burgeoning Chinese civil society.

Building cross-sectoral networks is increasingly important for NGOs’ operation and development (Guo & Acar, 2005; Selsky & Parker, 2005). A cross-sectoral network is a constellation of organizations from different sectors connected in a fashion that facilitates the achievement of a common goal (Provan, Fish, & Sydow, 2007). Although cross-sectoral alliance networks could allow different parties to bring their strengths in resolving pressing social issues, such networks are often plagued by collaborative inertia, distrust, and difficulties in the building and management of complex networks (Lee et al., 2012). Around the world, there are different models to approach cross-sectoral networks (Chin, 2018; Doerfel & Taylor, 2004; Lee et al., 2012), but few models involve devoted organizations specializing in bringing multisectoral organizations together. As such, little is known about how effective such organizations are in terms of maintaining cross-sectoral networks over time.

In this article, we closely examine how the network-building functions of NGO incubators influence network dynamics in the Chinese NGO community. We proposed a few research questions to examine (a) if organizations’ network positions in an NGO incubator’s network improve over time, and (b) if a community of organizations’ network structure in an NGO incubator’s network improves over time.

The example we chose in the current study is the largest NGO incubator in China, Enpai. According to Enpai’s founder, Lv Chao, the goal of Enpai is to set up a “spider architecture” around Chinese NGOs, as many small and grassroots organizations were merely fledgling due to their lack of administrative and decision-making experience, high transaction costs, poor knowledge, diminished credibility, and low capacity for fundraising (Xiamen Jianan Charity Foundation, 2015). Since 2006, Enpai has used its extensive network (with media, corporate, government, and other NGOs) to help new NGOs build crucial connections with diverse social actors. To date, Enpai has successfully incubated more than 200 NGOs including high-profile groups such as Ciwawa (a children’s rights NGO) and 1 KG More (a disaster relief NGO).

To our best knowledge, Chinese NGO incubators such as Enpai have rarely been examined in academic research. However, research of this type of NGO may hold considerable implications. In fact, China as a transitioning society is challenged by many social issues that could not be single-handedly solved by the government. The participation of a functioning civil sector is crucial for the alleviation or cure for many social ills (Lu, 2008). Nonetheless, the development of the burgeoning Chinese civil society is constrained by a range of problems such as the lack of access to political and financial resources. Chinese NGO incubators may provide a critical solution to this problem. Research that reveals the function and dynamic of NGO incubators may help domestic and international policy makers and potential donors better understand NGO incubators’ social significance, and could also provide insights to improve NGO incubators’ operation and strategic development and facilitate the building of future cross-sectoral alliance networks. Moreover, because cross-sectoral network building is a global trend, lessons learned in the Chinese incubator case may offer implications for NGOs around the world.

Moreover, the delicate role played by NGO incubators can be conceptualized as network brokers, a concept derived from Burt’s (1992) structural hole theory. Brokers do not necessarily have high centrality (degree centrality refers to the number of relationships an actor has in a social network) but they control a bridging relationship to otherwise disconnected contacts (Everett & Valente, 2016). Whereas Burt’s original work focuses on intraorganizational communication and how organizational actors (e.g., managers) can bridge structure holes to benefit their self-interests, our study explores how Enpai’s bridging-network practices benefit a Chinese NGO community. Our approach does not deny the potential benefits of strategic relationship building to individual organizations, but rather highlights the fact that individual organizations’ relationship-building patterns could create structural change at the organizational ecology level. Our study, thus, provides an alternative perspective that extends the application of structural hole theory in interorganizational communication research (Ahuja, 2000).

In addition, in recent years, a number of studies have applied structural hole theory to examine interorganizational communication networks among NGOs (González-Bailón & Wang, 2016; Stohl & Stohl, 2005; Taylor & Doerfel, 2003; A. Yang, 2012). Many of these studies tend to treat networks as external givens that either constrain or facilitate NGOs’ performance, whereas the agency of NGOs or how NGOs can alter their networks are rarely explored (Steen, Coopmans, & Whyte, 2006). Through a longitudinal research design, our study shows that the stability of network structure is a relative term, it can be renegotiated and reshaped by organizations’ strategic network-building efforts, and is constantly adjusted in social interactions (Burt, 2002).

In the reminder of this article, we first introduce the landscape of civil actors in China and explain the potentially significant role performed by NGO incubators. We then review the interorganizational communication network literature and structural hole theory. Our case study on Enpai is presented, and findings as well as implications are discussed.

The Emergence of NGO Incubators in China

Since the 1990s, Chinese NGOs have grown rapidly both in their number and activity scope as the country’s rulers retreat from socialist principles and tolerate, even encourage, the growth of new NGOs attempting to meet middle-class aspirations for civic engagement and society’s need for crucial social services (A. Yang & Taylor, 2014; G. Yang, 2005). Consequently, the NGO scene is evolving alongside changing social climates, government collaboration, and more relaxed regulations.

To understand the growing significance of Chinese NGO incubators as relationship brokers to other NGOs in China, it is first necessary to briefly survey the role and function of other civil players and the social environment in which they operate. The vast array of Chinese NGOs can be historically categorized into three broad types by the type of organizers or founders.

The first type is top-down or officially organized NGOs, which are initiated by the government (also known as GONGOs). As noted by Hasmath, Hildebrandt, and Hsu (2016), GONGOs are different from their grassroots counterparts in terms of their source of financial resources, level of legitimacy as viewed by the public, political standpoints, and geographic influence. Although there are societal needs that call for an NGO sector, in the context of China, the government hesitates to embrace a fully independent civil society. Therefore, GONGOs represent a compromise that allows the government to address some social problems, insolates the government from potential negative consequences, and makes sure of these organizations’ state-led orientation (Wu, 2003). GONGOs normally receive government subsidies, and personnel in the leadership positions are appointed by the government. Their organizational values are often consistent with those of the government. Recently, under President Xi’s leadership, the GONGO community has experienced a significant growth (Hasmath et al., 2016). Research has found GONGOs play significant roles in domestic as well as international affairs (A. Yang & Taylor, 2014).

The second type of Chinese NGO refers to grassroots or citizen-run NGOs, which are initiated by private citizens. In many ways, these grassroots NGOs are similar to their Western counterparts. Many of them are organized around marginalized interests and social issues, such as promoting labor rights, women’s rights, environmental protection, and geriatric care. The third, much smaller, type known as student NGOs is mostly initiated by college students who participate in their NGO work after school hours (G. Yang, 2005).

Struggles and Opportunities of Chinese Civil Actors

As a relatively new social sector, Chinese NGOs face the challenges of tight state regulation, unstable financial resources, and a low level of professionalization (Hsu & Hasmath, 2016). In terms of the state-NGO relationship, the constraint placed on Chinese NGOs by the Chinese government is well documented (Lu, 2008; Tam & Hasmath, 2015). Over the years, while the government has acknowledged the social benefits that NGOs offer, it has kept a watchful eye on NGOs’ civil initiatives. Many grassroots NGOs intend to avoid unnecessary entanglements with party-state actors. According to the institutional world view of many NGO founders, the source of obstacles and difficulties for their organizations is often perceived to be the Chinese state (Yang, 2003). However, it is necessary to note that the lack of cooperation between NGOs and the Chinese government has serious implications for NGOs’ access to resources (Hasmath & Hsu, 2014). In many countries, the state offers considerable resources, grants, and support for NGOs (Gazley & Brudney, 2007). In China, with the exception of GONGOs, most grassroots NGOs have a difficult time qualifying for government funding, which leaves many grassroots NGOs struggling for financial stability (Hasmath & Hsu, 2014). To survive, Chinese NGOs have developed some survival strategies such as cooperating with local agents, fostering trust with the Chinese government agencies, and maintaining a low profile to avoid state suppression (Tam & Hasmath, 2015). Ho (2008) also found that Chinese environmental NGOs adopted depoliticized and nonconfrontational strategies to survive.

In the recent decade, some studies suggest that there are signs of gradual improvement for NGOs’ operational environment. Despite harsher regulations regarding foreign funding (e.g., the 2015 “Overseas NGOs Management Law”), for NGOs, domestically, the central government and many local governments have encouraged greater societal involvement in the delivery of social welfare, and some grassroots NGOs have even obtained contracts to deliver welfare services (Hsu & Hasmath, 2014). G. Yang (2005) found that as the government recognized the importance of environmental protection, the need for environmental watchdogs and other services has prompted the development of Chinese NGOs’ development. Overall, for Chinese NGOs, simply avoiding the government may not be the best option. Cooperation and cultivation of trust may provide opportunities for NGOs to expand their activity scope and exert greater social influence. The need to foster state-NGO relationships is important for NGO incubators.

In addition to a state-NGO relationship, alliances with corporations may present an alternative financial resource for NGOs. An important trend in China is the fast accumulation of new wealth and how new fortunes change the dynamic of funding opportunities for Chinese NGOs (Saich, 2015). Domestic funding opportunities used to be difficult to come by for NGOs. In a developing country with a high level of social inequality, seeking donations to fund and sustain NGO operations was an uphill task. Chinese NGOs, thus, tended to depend on and compete for scarce sources such as government funding and foreign funding. Nowadays, as Chinese business and business leaders emerge as resourceful funding agents, they appear to be much more attractive to Chinese NGOs than foreign or state counterparts for two reasons: (a) Chinese businesses are more accessible than other funding sources due to their sheer number, and (b) the Chinese government holds suspicions about foreign funding/NGOs. Receiving donations from domestic sources, therefore, is perceived to be less controversial than receiving donations from overseas. However, to build connections with the growing Chinese business sector, many Chinese NGOs find themselves in need of introductions and training to navigate the new territory of relationship networks.

Low professionalization level is another problem that limits the future of Chinese civil actors. Many Chinese NGOs lack adequate institutional capacity and motivated, well-trained staff (Lu, 2008). The reality is echoed by Hsu and Hasmath (2016), whose interview of more than 100 NGO representatives found that the majority of Chinese NGOs consider the NGO sector immature. In recent years, more capacity-building agencies, and information and research think tanks, have emerged in China, and more local governments have set up special agencies to serve NGOs, some of which may perform functions similar to NGO incubators, but the demand for cross-sectoral networks and intermediary organizations is still largely unmet.

In short, opportunities and challenges are both rife in Chinese NGOs’ operational environment. One feasible way to help NGOs address these problems and capitalize on opportunities is to establish connections and foster trust and mutual respect between Chinese NGOs, local and central governments, and businesses. Cross-sectoral alliance networks may help to channel resources to the Chinese civil sector, increase NGOs’ financial stability, and improve professionalization.

Chinese NGO Incubators: Brokers in Delicate Relationships

The NGO communities can be considered as communities of practice, in which organizations sharing similar concerns interact frequently to learn how to improve their practice (Wenger, McDermott, & Snyder, 2002). Learning and organizational development is crucial for communities of practice. As the Chinese NGO communities continue to grow, the need for organizational training and development has also increased. Responding to the demand, NGO incubators have emerged to nurture small and innovative NGOs (Yu, 2016). As defined by Etzkowitz, de Mello, and Almeida (2005), “Incubation is fundamentally an educational process to train organizations in adequate functioning” (p. 412). Incubators are not unique to the civil sector and often play critical roles in facilitating resource and knowledge transformation among social sectors. For example, Etzkowitz et al. (2005) studied the Brazilian incubator movement. The study found that, in this movement, under governmental support, Brazilian industry associations utilized incubators to expand clusters of low-tech firms with the knowledge generated by universities. Incubators helped to build a new development model to create innovative organizations.

Although a few studies have recognized the existence of NGO incubators (Brown & Hu, 2012; Yu, 2016), little research has been dedicated to examine NGO incubators’ roles in the NGO community. NGO incubators are a unique type of NGO. In contrast with other types of Chinese NGOs, NGO incubators do not necessarily advocate for any particular social issues. Instead, NGO incubators provide training to a wide variety of NGOs working on a range of issues and cultivate different relationships with the state and private partners to help support the development of new and fledgling NGOs in the incipient Chinese civil society.

To yield a heuristic understanding on this emerging model of Chinese NGO incubators, its operations, and social significance, this study focuses on the case of a leading NGO incubator, Enpai, and the network of organizations that have connected to this NGO over its formative years. Enpai was founded in 2006 and is supported by sponsorship from the Chinese government, the Narada Foundation (a Chinese business-based foundation), and the Ford Foundation (a U.S.-based private foundation), among others. The founding of this organization is already an example of cross-sectoral collaboration. The organization’s core services include training programs that provide NGOs with registration guidance, capacity building courses, public relations courses, and financial support. Enpai has also used its extensive networks to help new NGOs build crucial connections with diverse social actors. To date, Enpai has successfully incubated more than 200 NGOs. In addition to their Shanghai headquarters, Enpai has branches in other large Chinese cities such as Beijing, Chengdu, and Shenzhen (China Philanthropist, 2015).

The potentially significant role that Enpai performs in the Chinese civil society has been studied in the social network literature as a relationship broker that bridges structural holes (Burt, 1992). The next section discusses in detail the structural hole theory and how the theory could guide our understanding of the network impact of NGO incubators such as Enpai.

Interorganizational Cross-Sectoral Networks and Structural Hole Theory

NGOs and Interorganizational Cross-Sectoral Networks

NGOs often address social issues through leveraging their influence in collaboration networks, which are chains of interactions connecting governments, intergovernmental organizations (IGO), corporations, and NGOs, through information exchange, project collaboration, and joint membership in advocacy coalitions (e.g., United Nations Global Compact; Guo & Acar, 2005). NGOs’ collaboration networks represent a powerful approach to solving pressing issues, holding powerful social actors accountable, and strengthening civil society (Varda, 2011).

Research has found that cross-sectoral networks are often associated with more effective service delivery, resource mobilization, innovation, and enhanced civic engagement (Varda, 2011). Specifically, interorganizational networks allow NGOs to pool staff, skills, knowledge, expertise, and other resources across organizations. Such networks may help NGOs to bring down operational costs, reduce risk associated with new operations, enhance organizational capacity, and provide effective problem solving and public service (Guo & Saxton, 2018; Paarlberg & Varda, 2009).

Despite these benefits, the formation and maintenance of interorganizational networks can be costly and difficult (Burt, 2015). For example, the lack of trust among partnering organizations could create tension and conflict (Lee et al., 2012). In the case of China, the lack of trust between civil actors and governments may hinder relationship building. Moreover, relationship maintenance is time consuming and requires considerable resources. When actors have too many connections, they may have difficulty effectively participating in network interactions. On the contrary, when actors have too few connections, they may be overwhelmed by the task of navigating networks (Paarlberg & Varda, 2009). As discussed earlier, the Chinese NGO incubator, Enpai, has been specifically developed to address some of the challenges associated with cross-sectoral networks. To further understanding in the value of Enpai’s role, we discuss structural hole theory below as it offers a valuable theoretical framework.

Structural Hole Theory

Burt’s (1992) structural hole theory (SHT hereafter) defines the benefits of social relationships in terms of information advantages deriving from linkages among otherwise disconnected individuals. SHT is developed from Granovetter’s (1973) strength of weak ties, betweenness centrality (Freeman, 1977), network exchange theory (Cook & Emerson, 1978), Burt’s (1976) own observation of the autonomy among conflicting affiliations, and Coleman’s (1988) topological view of social capital. According to Burt (1992), if organizations can fill structural holes in a network, they serve as tertius gaudens (the third who benefits). As the third who benefits, organizations could efficiently reap informational benefits and exercise a greater control over information flows.

Burt’s (1992) original work focuses on intraorganizational communication and how organizational actors (e.g., managers, CEOs, etc.) bridging structural holes (also known as relationship brokers) could advance their career and performance. Brokers are a type of important key player. The network literature on key players has long explored which individual actors are important in a social network (Borgatti, 2006; Herzog & Yang, 2018). One approach defines key players as the most well-connected actors, in other words, actors with the highest degree centralities (Freeman, 1979). Another approach identifies key players based on their closeness centrality, which measures the extent to which actors can independently access other members of a network (Freeman, 1979). According to this approach, key players can reach other actors through a minimum number of intermediary connections.

Burt’s approach identifies key players based on the degree to which actors have the potential to act as go-betweens between two or clusters of disconnected actors. Brokers can potentially control interactions between disconnected actors, playing one against another. Brokerage is an important theoretical concept, and it reveals aspects of key players that cannot be captured by centrality alone. For example, research showed that actors who have only high centrality but lack brokerage may suffer because they do not have access to information from distant parts of the network, which makes them vulnerable to a rapidly changing environment (Uzzi, 1996).

SHT has gained considerable attention, and empirical studies have generally supported the value of bridging structural holes for individuals’ ability to adapt to and achieve personal goals in social networks (Susskind, Odom-Reed, & Viccari, 2011). An important assumption of SHT is that actors strategically exploit network structure for their own benefit (Burt, 1992). Network structure refers to the patterns of connections within a social network (Provan et al., 2007). The existence of structural holes can be understood as opportunities because they provide unique advantages to actors who can bridge structural holes. Actors may be motivated to maintain an exclusive control of structural holes, or others may resist brokers’ bridging efforts (Burt, 2015). Nonetheless, despite the intention of individuals, cumulatively, nodal-level individual actions may create network-level structural changes that have broader implications. As noted by Walker, Kogut, and Shan (1997), on one hand, networks are maintained by the powerful forces of reproduction of dense regions of prevailing relationships. On the other hand, “it is exactly this principle of conservation that generates the opportunities for entrepreneurial actors to bridge these regions and alter the structure of the network” (p. 109).

The application of SHT in the context of interorganizational communication and global civil society research (Stohl & Stohl, 2005; Taylor & Doerfel, 2003; A. Yang, 2012), thus, shifts attention from individual actors to organizations and relationship dynamics at the organizational ecology level (Walker et al., 1997; A. Yang & Taylor, 2015). At the organizational ecology level, brokers are often the necessary forces that connect subgroups of organizations (González-Bailón & Wang, 2016) and facilitate communication and resource flows. For instance, Shumate, Fulk, and Monge (2005) studied a network of HIV/AIDS NGOs and found that because there are thousands of NGOs operating across the world in the fight against HIV/AIDs, no one donor could possibly know all of them. However, some organizations may be able to link donors to many local NGOs, thus, bridging different networks. In this way, organizations that bridge the networks play important roles that benefit the international NGO community.

As noted by González-Bailón and Wang (2016), broker organizations that span structural holes are necessary for subgroups of a social movement network to connect and expand its influence. For the incipient Chinese civil society, as previously discussed, the Chinese NGOs’ community may, thus, benefit tremendously from bridges that span holes between civil actors, businesses, and government agencies.

This study applies the SHT to the context of China to examine Enpai’s role as a relationship broker. Instead of solely examining individual organizational-level (nodal-level) network positions (an actor’s location in a network, which describes its access to various types of resources and affects its capacity to adapt to and influence change; Ahuja, 2000), we also draw insights from the recent interorganizational communication research on structural holes to examine the network-level effect of this prominent NGO incubator’s operations over time.

Specifically, at the nodal level, we are interested in the changes in the distribution of degree centrality and structural holes among Chinese organizations connected by the NGO incubator’s network. Network ties are critical to organizations’ performance. Organizations benefit from having many ties, diverse contacts, and a mix of strong and weak ties (A. Yang & Taylor, 2015). In social networks, favorable tie formation patterns not only refer to organizations’ capacity to build many ties (high-degree centrality), but also imply organizations build ties with desirable contacts that complement one another (high-brokerage score; Hallen & Eisenhardt, 2012). Organizations with high network-degree centrality tend to enjoy favorable conditions when it comes to information and resource flow (Newman, 2010). To examine NGO incubators’ contribution to the NGO community, it is important to assess network position changes experienced by other NGOs. Therefore, it is interesting to examine which organizations, in addition to Enpai the NGO incubator, emerged as critical players in the network woven by Enpai. Therefore, we propose the following question:

Research Question 1a (RQ1a): How did organizations’ degree centrality in Enpai, the NGO incubator’s network, change over time?

Moreover, as SHT suggested, organizations occupying brokerage positions have better control over the exchange of communication and resource flows (Burt, 1992). It is, thus, important to examine which organizations bridge structural holes over time. These questions direct attention to the consequence of NGO incubator’s network engineering efforts, and examine which organizations actually benefit from Enpai’s work over the years. There are different measures to assess if organizations bridge structural holes. Gould and Fernandez (1989) proposed using betweenness centrality to indicate brokerage. Betweenness centrality counts the number of connections between other actors that a given actor relies on and could indicate an actor’s ability to control others (Everett & Valente, 2016). However, Burt (1992) argues that structural hole measures need to consider redundancy, and the way in which actors are connected may affect their constraints and opportunities. Burt further proposed several structural hole measures (i.e., efficiency and constraint; see details in the Method section) to capture these nuances of structural hole opportunities. Thus, we propose a related question:

Research Question 1b (RQ1b): How did organizations’ structural hole measures (effect size, efficiency, and constraint) in Enpai, the NGO incubator’s network, change over time?

Moreover, at the network level, prior research suggests that networks with many separate areas of densely connected clusters (also known as network communities) experience difficulties in terms of integration and maintaining communication and resource flow (Newman, 2010). González-Bailón and Wang (2016) found that in a network populated with many communities of higher internal density (which means members of a community mainly connect with each other instead of members of other communities), information flows may be locally bounded and generate little value for the overall network. Therefore, the second research question examines if the presence of separate communities is a significant feature in Enpai’s network, and if these conditions have changed over time. This question is important because it examines the network ecology level consequence of NGO incubator’s structural hole bridging efforts.

Research Question 2 (RQ2): How did the number and connection patterns of network communities in the NGO incubator’s network change over time?

Method

Data

With access granted from the organization, the network data are collected from the online archive of Enpai (http://www.npi.org.cn/) with 280 records of its organization’s activities over a 7-year period. Each entry clearly records when Enpai worked with what organization on what project. Among these events, 95.239% were initiated by Enpai (e.g., Enpai initiated the “China Community Building Program”). For specific event types and descriptions, see Table 1.

Table 1.

Types of Events Coded.

Event type	Description	Numbers (percentage)
Collaboration with government agencies	Events only involve NGOs and government agencies. Many of these events aim at explaining government policies or help NGOs to build connections with governmental officials. For example, NPI undertook a research project on “The Procedure for Government Purchasing NGO Services” entrusted by the Pudong Government	28 (13.084)
Collaboration with businesses	Events only involve NGOs and businesses. Many of these events aim at fundraising or building connections with business leaders. For example, NPI set up the Lenovo Venture Philanthropy Fund in cooperation with Lenovo Group	6 (2.804)
Collaborations with multiple sectors	Events involve organizations from all three sectors. For example, NPI and Coca-Cola joined efforts to develop new capacity building models and workshop. The workshop was attended by NGOs and local government agencies.	70 (32.710)
Educational events	Events involve only NGOs. These events aim at providing capacity training or academic seminar/expert conferences on social issues. For example, NPI and Hong Kong Council of Social Service jointly organized a seminar on community building	48 (22.430)
Civic engagement events	Events involve only NGOs. These events aim at engaging the general public with NGOs or raise public awareness about social issues. For example, NPI assisted World Bank to promote “China Development Marketplace” Project	46 (21.495)
Others	Other types of events unrelated to any of the aforementioned categories. For example, Lv was appointed director of Enpai	16 (7.477)

Note. NGO = nongovernmental organization; NPI = nonprofit incubator.

In Enpai’s online database, there were records of events from 2006 to 2012. To reflect time changes, we organized the records into three periods: Period 1 (2006-2007), Period 2 (2008-2009), and Period 3 (2010-2011). The last year (2012) was dropped from the sample for unequal length of the period in comparison with previous periods and incomplete records at the time of data collection.

Next, we coded the records from each time period to construct three networks. Extracting social network data from archival sources is a commonly used data collection method in social network studies (see Crossley et al., 2015 for an extensive review). In the data coding process, the researchers first read the records to identify the names of involved organizations. Specifically, 83 organizations were identified from Period 1, 187 from Period 2, and 216 from Period 3. Second, researchers coded all the events listed in the records. Those events include capacity training programs, fundraising events, networking events, corporate social responsibility (CSR) projects, and conferences (see Table 1). Third, because the records show which organization attended which event, we constructed an affiliation network for each period. The affiliation network consists of relationships between two sets of items, in this case, organizations and events (Borgatti & Halgin, 2011). The binary relationship that connects them is the “attended” relationship. In an affiliation network matrix, the rows correspond to the organizations, and the columns are the events they attended. The coding of the matrix is based on the following scheme:

a_{i j} = {\begin{matrix} 1 & if actor i is affiliated with event j \\ 0 & otherwise \end{matrix} .

Moreover, as the study is interested in how organizations were connected to one another, the three affiliation networks were transformed into one-mode, organization-by-organization networks. The process works by selecting one set of nodes (in this case, organizations), and linking two nodes if they are connected to the same event. In other words, the relationship between organizations was established when they shared co-participants in an event. The assumption here is that co-participation in an event provides opportunities for social ties to develop (Borgatti & Halgin, 2011). The procedure of transforming affiliation network to one-mode network is performed using the UCINET. These one-mode, organization-to-organization networks, which allow us to examine the patterns of connections among organizations, were used for data analysis.

Measures

Organization type

This actor-level variable describes features of networked organizations. We coded for nine types of organizations, namely, Chinese National Governmental Organization/Agency; Chinese Local Governmental Organization/Agency (including provincial, city level, etc.); Chinese For Profit Organization; Chinese Nonprofit Organization; Foreign/International Governmental Organizations; Foreign/International For Profit Organizations; Foreign/International Nonprofit Organizations; Media Institutions, Others (Unidentified Organizations).

Structural hole measures

To examine individual organizational-level structural hole changes as well as the network-level structural hole changes, we utilized two structural hole measures: efficiency and structural constraint (Burt, 1992) and community detection algorithms (González-Bailón & Wang, 2016).

Specifically, efficiency and structural constraint focus on individual organizations’ network characteristics. These two measures were originally developed by Burt (1992). Efficiency relates to the concept of redundancy (Burt, 1992), which refers to the extent to which an organization’s contacts are connected to each other as well. Efficiency is based on the nonredundant aspect of a node’s network. An organization with a high efficiency score tends to have nonredundant contacts. Finally, constraint refers to the extent to which an organization’s access to the network is concentrated on a handful of interconnected actors. A high constraint value means an actor has a limited ability to bridge structural holes (Burt, 1992). Constraint helps to identify organizations that are in a position to span structural holes. In the context of the current study, if an organization has high constraint, it may have few connections, or its contacts are mutually connected. In contrast, an organization with low constraint indicates that it has higher brokerage opportunities.

Moreover, if we take a bird’s-eye view and examine the entire network, structural holes may exist between network communities. Organizations in a network community have more internal links to others in the same community (Newman, 2012). Therefore, a community detection method may help to detect the existence of structural holes between network communities. This study applied a community detection method to partition networks into subgroups according to patterns in the density of connections. In this study, we adopted the Louvain algorithm community detection method (Blondel, Guillaume, Lambiotte, & Lefebvre, 2008). This method has been widely used by network scholars, and research showed that it provides a reliable assessment of the significance of fragmentation in symmetric social networks. Once network communities were identified, the E-I index was also calculated for each identified community. The E-I index is the number of ties external (E) to the group minus the number of ties that are internal (I) to the group divided by the total number of ties. The E-I index describes the degree to which members of a community mainly associate with others inside or outside the same community (Wasserman & Faust, 1994). In the current study, the E-I index helps us to understand if organizations belonging to different communities connect with each other.

Centrality

In addition to structural hole measures, we calculated normalized centrality measures to identify the most well-connected organizations in the Enpai network. Specifically, we employed Freeman’s general centrality measure, which assesses actors’ centrality while accounting for the overall centralization of a network (Wasserman & Faust, 1994). The formula is listed below:

C_{D} = \frac{\sum_{i = 1}^{g} C_{D} (n^{*}) - C_{D} (i)}{(N - 1) (N - 2)} .

Because these networks have symmetrical relationships (i.e., when organization A participates in an event with B, B also participates in the event with A), there is no need to differentiate between in-degree or out-degree centrality.

Analytic Procedures

First, the above-listed network measures are calculated and reported. Second, Exponential Random Graph Modeling (ERGM) analyses were performed on each network to explore the potential effect of organization types on tie formation. The ERGM estimation process estimates the probability that a tie exists, and this probability is a function of structural network parameters and actor attributes (see Snijders, Pattison, Robins, & Handcock, 2006). The basis of the analysis is to determine if the structural signatures occur more often than by chance alone by simulating a distribution of random networks of the same size as the observed network. The prevalence of the observed network structure can then be compared with that of the simulated network. The benefit of ERGMs over other network analytic measures is that they take into consideration the interdependency of network observations and have been shown to produce reliable estimates (Contractor, Wasserman, & Faust, 2006). We used the social network analysis (SNA) package in the software R for model estimations. Models are estimated using Markov Chain Monte Carlo (MCMC) simulation methods. Organizations labeled as “media” and “others” are eliminated from the analysis due to their low presence in the sample and consequentially insignificant effect. The goodness-of-fit (GOF) diagnostics for the models from each year showed that the statistics for the estimated parameters closely matched the distribution of parameters in the observed graphs. The convergence t ratios were less than or close to 0.1 in absolute value, suggesting that the models show a good fit to these data (Snijders et al., 2006).

Results

The 6-year period was divided into three networks to allow for a comparison between networks over time and the observation of incremental changes. Specifically, at Period 1 (2006-2007), the network contained 83 organizations connected by 499 connections (density = .004). At Period 2 (2008-2009), the network size was 187, and these organizations were connected by 1,218 connections (density = .01). Finally, at Period 3 (2010-2011), this network consisted of 216 organizations with 1,187 connections (density = .009). Overall, it seems Enpai has steadily grown its network size over the 6 years. A close examination revealed that, through organizing different events and projects, Enpai has brought together a diverse group of organizations, including 282 Chinese NGOs, 106 Chinese government agencies (90 local and 16 national governmental agencies), 33 Chinese businesses, 31 other types of organizations (including foundations, universities, etc.), and 22 international businesses. It is interesting to note that besides Chinese NGOs, the second largest type of actors in these networks is Chinese government agencies. In other words, Enpai’s network was most efficient in terms of connecting Chinese NGOs with government agencies. This can be a necessary resource for Chinese NGOs’ survival in the Chinese social, political context. In the following section, we present the findings for each research question.

Central Actors and Structural Brokers

RQ1a explores in what ways the organizations’ centrality in Enpai’s network changed over time. Table 2 reports the top 10 organizations with the highest total centrality across three periods of time. For Period 1, among these 10 most central organizations, eight were Chinese NGOs, one international NGO, and one Chinese university. For Period 2, eight of the most central organizations were Chinese NGOs, one international NGO, and one Chinese private foundation. At Period 3, three Chinese NGOs, three Chinese foundations, two Chinese university/research institutions, and one Chinese business were among the most well-connected organizations. Over time, it appears that not only Chinese NGOs, but a diverse group of organizations (e.g., businesses, foundations, and university and research institutions) have become well-connected organizations.

Table 2.

Degree Centrality Measures of Top 10 Organizations Over Three Periods of Time.

	Period 1		Period 2		Period 3
	Organization	Degree centrality	Organization	Degree centrality	Organization	Degree centrality
1	NPI	.036	NPI	.095	NPI	.041
2	Chinese NGO	.024	Chinese NGO	.021	Chinese NGO	.017
3	Chinese NGO	.018	Chinese NGO	.020	Chinese Corporation (Foundation)	.015
4	Chinese NGO	.012	Chinese NGO	.018	Media	.014
5	Chinese NGO	.011	International NGO	.017	Chinese NGO	.013
6	Chinese NGO	.010	Chinese NGO	.016	Chinese Corporation	.013
7	Chinese Corporation	.010	Chinese NGO	.016	Others (University)	.012
8	Chinese NGO	.009	Chinese Government Agency	.016	Chinese NGO	.012
9	Chinese NGO	.009	Chinese Corporation (Foundation)	.014	Chinese NGO	.010
10	Others (University)	.009	Chinese NGO	.014	Others (Chinese Academy of Social Sciences)	.010
M	—	.001	—	.002	—	.001
SD	—	.003	—	.005	—	.003

Note. NGO = nongovernmental organization.

Based on the previously discussed results, it seems that centralities are unevenly distributed among organizations, which means that some organizations are favored more than others in relationship-building choices. What are the factors that drive some organizations to be more popular than others? To reveal the mechanism behind the observed differences in centralities, we fitted ERGM models. Table 3 provides estimates, standard errors, and statistical tests of the structural parameters of the baseline model as well as advanced models with both structural and nodal attribute parameters. Parameter estimates were obtained from converged models in three time periods, respectively. The results showed that the edge parameters were negative and significant across all converged models, which implies that there is a low baseline propensity to form ties net of other effects (Snijders et al., 2006).

Table 3.

Parameter Values for Converged Models.

	Edge	Chinese government	Chinese NGO	Chinese business	International business	International NGOs
Endogenous tie structure
Period 1	−1.76 *** (0.05)	—	—	—	—	—
Period 2	−2.59*** (0.03)	—	—	—	—	—
Period 3	−2.92*** (0.03)	—	—	—	—	—
Exogenous nodal attributes
Period 1	−2.45*** (0.05)	4.00 (0.02)	5.28* (0.02)	1.13*** (0.03)	−7.41* (0.03)	−3.78 (0.02)
Period 2	−2.00*** (0.21)	−0.53*** (0.12)	−0.21 (0.11)	−0.29 (0.18)	−1.37*** (0.29)	−0.80*** (0.16)
Period 3	−3.59*** (0.21)	0.03 (0.12)	0.49*** (0.11)	0.32* (0.13)	0.45*** (0.13)	−0.18 (0.16)

Note. NGO = nongovernmental organization.

p < .05. **p < .01. ***p < .001.

Findings from the models showed that organizational type significantly affected Enpai’s structural formation over time. At Period 1, there were significant and positive effects on the probability of tie formation when the network included Chinese NGOs and Chinese businesses. In contrast, there was a significant and negative effect on the probability of tie formation when the network included international businesses. At Period 2, there were significant and negative effects on the probability of tie formation when the network included Chinese government, International businesses, and International NGOs. At Period 3, there were significant and positive effects on the chance of tie formation when the network included Chinese NGOs, Chinese businesses, and International businesses. The effects of Chinese government and International NGOs were insignificant.

Not surprisingly, across the three periods of time, Chinese NGOs actively contributed to tie formation. After all, the basic purpose of Enpai’s network is to create a favorable platform for NGOs to expand their social networks, and the models showed that this goal has been accomplished to a degree. In addition, the role of Chinese business was relatively consistent. That is, it appears that the inclusion of Chinese business led to more active tie formation in these networks. This finding may suggest that many Chinese NGOs have been actively seeking financial support from Chinese business entities. In contrast, the inclusion of international NGOs had almost always inevitably led to less participation in these networks, which is likely due to the government’s suspicion of foreign NGOs. The role of Chinese government agencies in these networks tends to either be insignificant or negatively affecting tie formation, suggesting that government agencies may not actively seek relationship building in this network.

RQ1b examines if the organizations’ structural hole measures in Enpai’s network changed over time. Organizations’ chances to bridge structural holes were assessed with two measures: efficiency and constraint (Burt, 1992). When examining organizations’ efficiency, a close examination of Table 4 suggests that at first (Periods 1 and 2), organizations that can efficiently bridge structural holes are NGOs, foundations, and Chinese government agencies. Later, in Period 3, media institutions and research institutions also played important roles of bridging structural holes. In terms of constraint values (the inability to bridge structural holes), as listed in Table 5, international foundations, foreign government agencies (e.g., British Council), and regional government agencies faced the highest constraint levels.

Table 4.

Efficiency of Top 10 Organizations.

	Period 1		Period 2		Period 3
	Organization	Efficiency	Organization	Efficiency	Organization	Efficiency
1	Chinese NGO	1.000	Jiangxi Red Cross Society	1.000	Chinese Government Agency	1.000
2	NPI	1.000	Chinese Corporation Family Foundation	1.000	Chinese Government Agency	1.000
3	Chinese NGO	1.000	NPI	0.936	Chinese Corporation (Foundation)	1.000
4	Chinese Corporation (Foundation)	1.000	Chinese NGO	0.660	Media	1.000
5	Chinese NGO	1.000	Chinese Corporation Foundation	0.654	Chinese Government Agency	1.000
6	International Corporation (Foundation)	1.000	Chinese Government Agency	0.634	International Corporation (Foundation)	1.000
7	Chinese NGO	1.000	Chinese Government Agency	0.606	NPI	0.888
8	Chinese NGO	0.894	Chinese Corporation Foundation	0.601	Chinese Government Agency	0.667
9	Chinese NGO	0.658	Chinese Government Agency	0.600	Chinese Government Agency	0.619
10	Others (University)	0.650	Chinese NGO	0.592	Chinese Government Agency	0.588
M	—	.001	—	.002	—	.001
SD	—	.003	—	.005	—	.003

Note. NGO = nongovernmental organization.

Table 5.

Constraint of Top 10 Organizations Over Three Periods of Time.

	Period 1		Period 2		Period 3
	Organization	Constraint	Organization	Constraint	Organization	Constraint
1	International Corporation (Foundation)	1.000	Chinese NGO	1.125	Chinese Government Agency	1.000
2	Chinese NGO	1.000	Chinese Corporation	1.125	Chinese Government Agency	1.000
3	Chinese NGO	1.000	Chinese NGO	1.125	Chinese Corporation (Foundation)	1.000
4	Chinese NGO	1.000	Chinese NGO	1.000	Media	1.000
5	Chinese NGO	1.000	Chinese Corporation (Foundation)	1.000	Chinese Government Agency	1.000
6	Others (Oxford University)	1.000	Foreign government agency	0.730	International Corporation	1.000
7	International Corporation	1.000	Foreign government agency	0.730	Chinese NGO	0.898
8	Chinese Government Agency	0.956	Chinese NGO	0.730	Chinese Government Agency	0.733
9	International NGO	0.894	Chinese Corporation	0.579	Chinese Government Agency	0.731
10	Chinese Corporation	0.646	Chinese Government Agency	0.579	International NGO	0.731
M	—	.068	—	.127	—	.101
SD	—	.184	—	.196	—	.205

Note. NGO = nongovernmental organization.

Overall, the analysis suggests that three trends emerged from Enpai’s networks. First, there is a tendency for an increasingly diversified group of organizations to bridge structural holes. The diversity of organization(s) is reflected by their different sectors and social functions. Second, despite their relatively small number in this sample, organizations such as government agencies, foundations, and research institutions are especially efficient in terms of bridging otherwise unconnected groups. Third, some international actors such as foreign government agencies and international NGOs (both are suspicious to the Chinese government) were especially unlikely to bridge structural holes.

Community-Level Structural Holes

RQ2 examines if the number of network communities in the NGO incubator’s network changed over time. We applied the Louvain algorithm to identify network communities. At Period 1, the analysis identified four communities and the Newman modularity = .484 (a high modularity value indicates a better clustering pattern). The first community had 32 organizations (E/I index = –.421), the second one had 25 organizations (E/I index = –.261), the third one had 21 (E/I index = –.641) organizations, and the fourth one had five organizations (E/I index = –.333). Because a negative E/I index value indicates that most group members build connections with members outside of the community, this result suggests all four communities actively engaged in activities that help to bridge structural holes. In addition, a close examination suggests that all communities featured a mix of different types of organizations.

At Period 2, the analysis identified nine major communities and the Newman modularity = .615 (indicating a strong tendency toward fragmentation). The first one had 38 organizations (E/I index = .093), the second one had 25 organizations (E/I index = –.181), the third one had 23 organizations (E/I index = –.523), the fourth one had 19 organizations (E/I index = –.239), the fifth one had 18 organizations (E/I index = –.636), the sixth one had 17 organizations (E/I index = –.639), the seventh one had 12 organizations (E/I index = –.585), the eighth one had 10 organizations (E/I index = –.033), and the ninth one had nine organizations (E/I index = –.171). Again, except for the first community, all other communities demonstrated the tendency to bridge structural holes. A close examination reveals that the first communities mainly consisted of relatively small Chinese NGOs, while other more outward-going communities consisted of diverse types of organizations. This finding suggests that small NGOs tended to cluster together in Enpai’s network whereas larger NGOs socialized more with other diverse types of organizations.

Finally, at Period 3, the analysis identified seven major communities and the Newman modularity = .409. The first one had 47 organizations that are mainly small Chinese NGOs (E/I index = .004), the second one had 36 organizations (E/I index = –.477), the third one had 15 organizations that are mainly universities and research institutions (E/I index = .015), the fourth one had 15 organizations (E/I index = –.655), the fifth one had 12 organizations (E/I index = –.175), the sixth one had nine organizations (E/I index = –.639), and the seventh one had two organizations that are government agencies (E/I index = .200). Interestingly, among the seven communities, three demonstrated the tendency to focus on interactions within communities. Similarly, the three communities with predominantly inward-going connections were populated by organizations of the same type whereas communities that tended to build outward connections included a diverse group of organizations. At this stage, the analysis also suggested that some communities demonstrated the tendency to mainly connect with others in the same community.

Overall, the analysis revealed that Enpai did provide opportunities for different types of organizations to mix, and brokerage opportunities were widely available. Some types of organizations performed better than others in terms of emerging as central organizations or bridging structural holes. Furthermore, the modularity scores suggested that the community structure was an enduring characteristic of this network—that is, the observed levels of fragmentation are quite substantial and consistent over time. Implications are discussed below.

Discussion

The growth of China’s civil society is an important development for China, and for the larger global civil society writ large. As voluntary organizations surface and thrive in China, it is critical that these organizations are connected to key social ties and economic resources to navigate China’s incipient and complex voluntary community. Accordingly, the recent rise of NGO incubators in China is significant for its support and capacity-building contributions to other NGOs in China and worldwide. As research on NGO incubators is relatively scarce, this article provides fresh empirical evidence to illustrate the unique role NGO incubators play and thereby highlight their distinctive contributions to the Chinese civil society. Moreover, because cross-sectoral networks represent an important trend in how societies respond to challenging issues, these types of NGOs dedicated to network management can have implications for nonprofits operating in other countries.

Structural Holes and Civil Society Relationship Brokers

Around the world, studies have reported an emerging trend of using cross-sectoral interorganizational networks to achieve a range of public purposes (Eng, Liu, & Sekhon, 2012; Paarlberg & Varda, 2009; Varda, 2011). Research also suggests that the collaboration between NGOs and government can improve authoritarian responsiveness to social demands (Zhang, 2018). Cross-sectoral alliance networks require considerable strategic efforts to bridge structural holes and bring together organizations from multiple sectors (Selsky & Parker, 2005). As nonprofit sectors reaching out to build connection with cross-sectoral partners, many have experienced challenges and difficulties managing and navigating increasingly complex social networks (Lee et al., 2012). The situation may be especially challenging in authoritarian regimes, where weak legal frameworks and restrictive political environments can constrain NGOs’ networking behaviors (Li, Tang, & Lo, 2018). As such, findings from the study suggest that it is beneficial to have NGOs dedicated to manage relationship networks, especially bridging structural holes for other NGOs.

Drawing upon the case of the largest Chinese NGO incubator, the results showed how Enpai functioned as an important relationship broker to other Chinese NGOs, the government, and Chinese businesses over 6 years. Enpai initiated many events and invited organizations with a diverse background to participate in these events. The process of connecting with diverse organizations allowed Enpai to bridge structural holes. Moreover, other organizations were not excluded from the opportunities to bridge structural holes.

It should also be noted that the observed societal effect of Enpai may reflect its nature as a civil society organization. Compared with structural brokers in the business sector that primarily serve one industry (Walker et al., 1997), alliance networks built by civil actors are favorably disposed to bringing together diverse organizations and promoting cross-sectoral alliances. This is because the mission of civil society organizations often requires them to pursue the public good, which is by definition not for the exclusive enjoyment of the insiders of closed social circles. Furthermore, as noted by Eng et al. (2012), the social mission of NGOs may enhance their trustworthiness in networks and, thus, make them desired network partners. In addition, the solutions for many thorny social problems often require the cooperation of multiple sectors. Civil organizations are often motivated by their missions to seek broad societal support and in the process bridge structural holes (Doerfel & Taylor, 2004). In light of the above, our findings highlight that when applying SHT to the civil society context, a self-interest driven model as outlined in the original SHT may be insufficient (Burt, 1992). Some assumptions of the original theory, such as what motivates actors’ network building and to what effect actors’ actions reflect a commitment solely to efficiency, should be reconsidered. For example, in Burt’s (1992) original research, he identified organizations/individuals’ intentionally concealing relationships with others within social networks to gain advantages and control. Such practices are clearly different from Enpai’s work in China.

The finding of the study suggests that the application of SHT in the civil society context requires researchers to examine both the individual organizational-level and the community-level structural changes. Theoretically, concepts such as organizations’ motivation for network building and power need to be explicitly reconsidered. Methodologically, new community-level indicators that assess community connectedness need to be added to Burt’s (1992) original measures. The multilevel measures used in the current study can be applied to other organizational studies to see if the community-level effects of bridging structural holes are consistent across contexts.

The Unique Value of NGO Incubators

Consistent with previous studies (Doerfel & Taylor, 2004), Enpai as the foundational or creator organization in this network was able to reap considerable network benefits, and emerged as one of the top central organizations that bridged structural holes. More important, Enpai also provided a valuable platform for Chinese NGOs and other social actors to collaborate and bridge structural holes. Over the 6 years, Enpai wove a network in which government agencies, Chinese NGOs, and Chinese and international businesses could collaborate on a range of projects, and allow different types of organizations to emerge as the most central organizations or to bridge structural holes.

These data on how Enpai has filled structural holes are significant as the bulk of research on communication networks has so far focused on factors such as resources or structural constraints (González-Bailón & Wang, 2016; Granovetter, 1973; Shumate et al., 2005), which are assumed to predict NGO growth. Less attention has been paid to the role of agency, including how NGOs can strategically alter the network structure of their ego and immediate network ecology to serve their missions.

Our findings also highlight the unique network-building value of NGO incubators. As a type of NGO specifically designed to function as relationship broker, this group of NGOs may be a product of Chinese societies where organizational operations often heavily depend on social connections (also known as guanxi in China, e.g., Eng et al., 2012). For newly formed grassroots NGOs, they need guidance to navigate the vast web of Chinese social relationships and social hierarchy.

In addition, previous network research suggests that NGO incubators may represent an important NGO type that is valuable in other countries and societies as well. This is because cross-sectoral ties often bridge disconnected organizational communities (Lee et al., 2012). However, as noted by Burt (2002), these types of bridging relationships are especially subject to decay. This is because bridging relationships are nonredundant, which means the cost of maintaining each bridge is shared by fewer others, and each bridging relationship requires higher efforts to maintain. Given this tendency for bridging relationships to break apart, creating and supporting organizations that are dedicated to bridging structural holes can be crucial for the long-term development of cross-sectoral alliances. As such, NGO incubators as a type of brokerage organization offer a new model to facilitate civil society development around the world, including civic actors in authoritarian countries, emerging democracies, and developing countries where cross-sectoral alliance networks are still at an incipient stage. Future studies may further examine how NGO incubators affect the longevity of cross-sectoral alliance networks and compare how NGO incubators function in different social contexts.

It should also be noted that Enpai’s agency is not assumed to be instinctive nor unconstrained. It is, in fact, rooted within the larger social and political context of China. Our analysis demonstrates the complex interplay between Enpai’s strategic network-building initiative and what is possible within the authoritarian Chinese context. Findings from our network analyses aptly illustrate that unlike the relatively more independent development of government and civic groups in contexts with a longer history of democracy, government agencies play a considerable role in Chinese civil networks. For instance, Enpai involved a large number of Chinese government agencies throughout its formative 6-year period, despite the fact that government agencies do not necessarily contribute to new tie formations. This seemingly inefficient network-building choice is likely to reflect pragmatic choices, particularly the necessity to help Chinese NGOs obtain legal status or to signal to a positive, compliant attitude to government agencies, which in turn may allow Chinese NGOs a wider berth in their activities. Also, our analysis showed that international organizations, especially foreign government agencies and international NGOs, faced considerable constraint in Enpai’s network. It is likely that despite NGO incubators’ relationship-building efforts, other Chinese NGOs conservatively steer away from politically sensitive associations.

Moreover, our results highlight the importance of Chinese businesses in the development of Chinese NGOs. For a complex issue such as developmental opportunity for NGOs in a large country such as China, the solution cannot come from any one sector alone. The solution requires collaboration among multiple sectors. Analyses on how organization types affect Enpai’s structural patterns over time showed that the inclusion of Chinese businesses led to more active tie formation in Enpai’s networks. This finding illustrates the close relationships between Chinese NGOs and corporate funding (e.g., the initiation of the Shanghai Public Development Foundation, which helps in the raising of private and public funds) as well as Enpai’s efficiency in acting as a consultant for corporately sponsored programs to further philanthropic fundraising activities (e.g., a 7-year collaboration with Lenovo, a multinational Chinese computer technology company founded in Beijing with operations in more than 60 countries, including the United States, Japan, and Singapore; China Philanthropist, 2015). The situation may be due to fundraising challenges experienced by Chinese NGOs as discussed earlier in the article, and the growing wealth and abundant resource the Chinese business sector has amassed in recent decades. While it is exciting to note that the Chinese business sector may provide valuable resources to fund civil society programs, we should also be cautioned against the degree of direct influence of these corporate partners upon the development trajectory of NGOs in China, which remains highly contested and an area for future research.

Structural Holes and Community-Level Disjuncture

In addition, at the community level, our analysis did reveal a structural tendency of disjuncture. Over the 6-year period, the analysis consistently identified tightly connected communities. The presence of these communities may be due to the diverse backgrounds of these organizations and may also be due to the wide range of projects (e.g., women’s rights, environmental protection, children’s rights, etc.) that has brought them together. The presence of these distinctive communities further highlights the importance of network brokers such as Enpai and other Chinese NGO incubators, as they perform delicate and crucial functions to hold fragmented networks together (González-Bailón & Wang, 2016).

In addition, we found that when a community consisted of diverse organizations, members of this community were more likely to be open for external connections. In contrast, when a community is formed mainly by organizations with similar backgrounds, they tend to reinforce internal connections and form clusters that resist the inclusion of new organizations. This finding suggests that for NGO incubators to facilitate network building, they may want to strategically introduce new actors with different backgrounds to closely connected communities (e.g., introducing a new NGO to work with a group of businesses). The increase of diversity may help to create and sustain communication and expansion of diverse relationships.

The analysis also revealed a potentially worrisome finding, which is the tendency for organizations to socialize with previous alliances and form stabilized clusters over time. When comparing Enpai’s network over the 6-year period, we observed that although, at first, all communities seemed eager to develop external connections, over time, some communities tended to favor internal connections over external ones. Similar results have been reported in other longitudinal network studies (Shumate et al., 2005), and this finding may signal that organizations prefer to work with partners they are already familiar with. Such a pattern may cause persistent fragmentation in the long run and diminish the efforts of structural hole brokers such as Enpai, impairing the advancement of nonprofit organizations and the future of cross-sectoral alliances in China.

Limitations and Suggestions for Future Research

In this exploratory case study, our analysis focused on the largest NGO incubator in China. This methodological choice was made partly due to the factor that other NGO incubators are still relatively small with obscure information or offer limited data access. Although findings of our study provide in-depth insights into Enpai’s unique properties and structural hole bridging capacity, researchers should be cautioned against generalizing our findings to other NGO incubators. For example, publicly available data do not explain why Enpai was able to attract international and domestic government support from its incipient stage. As Hsu and Hasmath (2017) found in their study, NGOs operating in different regions of China may encounter different operational environments. As social conditions and the Chinese NGO sector continues to evolve in China, future studies may examine different samples of NGO incubators and examine their network-building functions. In addition, a relevant question to further explore is that if other NGO incubators wish to replicate Enpai’s success, is it possible to do so without involving the Chinese government or international foundations? Findings for this question may reveal new opportunities for more NGOs. Furthermore, the current study mainly focused on the NGO aspect of network-building, yet barely examined the motivations that drive business and government agencies’ participation. Future studies may specifically explore what factors motivate business and government agencies to collaborate with NGOs in China, and ensure such cross-sectoral alliances properly aid Chinese NGOs’ development. In addition, in terms of the role of businesses in cross-sectoral networks, it is unclear how much resources were transferred from which businesses to what types of NGOs. Future studies may further track the flow of resources to examine patterns of influence. Furthermore, the study is based on secondary records. Although this method allows for an objective extraction of the network formed around Enpai over time, it offers limited insights on Enpai’s intuition about why they organize certain events and why they chose some organizations over others. Future research may utilize interviews or ethnography to explore the rationales in decision-making processes.

Finally, another issue associated with using secondary records is that the data archive may not reflect current conditions. To track how the NGO incubator has evolved over the recent years, studies may use survey or interview to gain access to current data.

Conclusion

Our study set out to examine how the emerging organizational model of an NGO incubator bridges structural holes and facilitates interactions among a diverse group of organizations. Our findings provided evidence that especially for civil society actors in China, their efforts of bridging structural holes not only benefit themselves and the NGOs’ community, but also offer valuable opportunities for cross-sectoral alliances in the incipient Chinese civil sphere. Findings of this study hold important values for foundations, donors, and policy makers who are looking for effective ways to facilitate the development of civil societies around the world. Our study is also valuable to scholars interested in cross-sectoral alliances and social networks. The study suggests that civil society is a fertile ground for the application and development of structural hole theory. Furthermore, much more research needs to be done to advance our understanding of how NGOs strategically build alliances with powerful social actors in search of sustained development while contributing to social good.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Aimei Yang, PhD, is an assistant professor in the Annenberg School for Communication and Journalism at the University of Southern California with a research interest in nonprofit networks.

Pauline Hope Cheong, PhD, is a professor of organizational communication in the Hugh Downs School of Human Communication Arizona State University.

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